Microbial Electrolysis Cells for H₂ Generation by Treating Acid Mine Drainage: Recent Advances and Emerging Trends

Abstract

Microbial electrolysis cells (MECs) are receiving increasing scholarly recognition for their capacity to simultaneously remediate contaminated streams and generate renewable hydrogen. Within the realm of acid mine drainage (AMD) treatment, MECs demonstrate pronounced advantages by merging pollutant mitigation with hydrogen production, thereby attracting intensified research interest. Drawing on 1321 pertinent publications extracted from the Web of Science Core Collection (2004–2024), this bibliometric assessment systematically elucidates the current research landscape and prospective directions in MEC-based AMD remediation and H₂ synthesis. Key thematic areas encompass (1) a detailed appraisal of distinctive publication dynamics within this specialized domain; (2) insights into the principal contributing nations, institutions, journals, and academic fields; and (3) a synthesized overview of technological milestones, emerging investigative foci, and prospective developmental pathways. By critically reviewing extant knowledge, this evaluation offers meaningful guidance to researchers newly engaging with MEC-driven AMD treatment while illuminating the technological trajectories poised to shape the future of this evolving field.

1. Introduction

With the continuous growth in global energy demand and the worsening environmental pollution, the search for clean and sustainable energy solutions has become an urgent global task. Prolonged reliance on fossil fuels not only exacerbates geopolitical tensions in energy supply but also intensifies environmental issues such as air pollution, greenhouse gas emissions, and climate change [1,2]. Consequently, hydrogen, as an ideal clean energy source, has attracted widespread attention. Hydrogen possesses high energy density, zero-emission combustion properties, and diverse application scenarios [3], making it a crucial component of future energy systems. However, traditional hydrogen production methods, such as high-temperature steam reforming and water electrolysis, often require substantial energy input and still produce significant carbon emissions in some processes, making it difficult to achieve true sustainability. Therefore, the development of low-energy, low-carbon hydrogen production technologies is of paramount importance.

Meanwhile, acid mine drainage (AMD), a common pollutant generated during mining activities, has become a significant challenge in the environmental management of mining areas worldwide. AMD is primarily composed of sulfuric acid, heavy metals, and other harmful substances resulting from the reaction between exposed minerals, water, and air during the mining process. It is characterized by strong acidity and severe metal contamination, posing a serious threat to ecosystems and aquatic environments [4]. Traditional AMD treatment methods typically rely on chemical precipitation or neutralization reactions, which, while capable of removing some pollutants, are often associated with high costs and secondary pollution issues [5]. Therefore, the search for low-cost, environmentally friendly, and innovative treatment technologies has become a key research focus in the fields of mining and environmental protection.

In recent years, Microbial Electrolysis Cells (MECs), an emerging bioelectrochemical technology, have gradually attracted widespread attention from researchers. MECs utilize microbial catalysis to degrade organic matter and generate hydrogen through electrochemical reactions, offering lower energy demands and higher energy conversion efficiency [6,7]. MEC technology, when applied to the treatment of acid mine drainage (AMD), not only effectively degrades organic pollutants but also demonstrates significant potential for the removal of heavy metals. At the cathode of MECs, metal ions are electrochemically reduced to their elemental forms, exhibiting remarkable efficiency, particularly in the removal of metals such as copper, iron, and zinc. Furthermore, MECs maintain high treatment performance under strongly acidic conditions, primarily attributed to the activity of acid-tolerant microorganisms and optimized electrode materials. Specific electroactive microorganisms can efficiently transfer electrons in low-pH environments, while modifications to anode surfaces and the use of corrosion-resistant electrodes further enhance the system’s stability in acidic conditions. To enhance the effectiveness of MECs in AMD remediation, integrating them with other water treatment technologies, such as chemical precipitation, membrane separation, and adsorption, has proven beneficial. These multifunctional integrated approaches enable the simultaneous removal of organic matter, heavy metals, and acidic pollutants while significantly improving treatment efficiency and reducing overall operational costs, providing a more efficient and economically viable solution. The working principle of MECs involves utilizing microorganisms to carry out metabolic reactions at the electrode surface. In the anode region, microorganisms degrade organic matter, releasing electrons and protons. The electrons are transmitted through an external circuit to the cathode, while the protons move through a proton exchange membrane (PEM). At the cathode, these electrons and protons combine to produce hydrogen gas. This process reduces energy consumption compared to traditional water electrolysis, as part of the required energy is supplied by the metabolic activity of the microorganisms [8]. Compared to electrochemical water splitting, MECs offer distinct advantages in hydrogen production due to their lower energy requirements, broader feedstock adaptability, and additional environmental benefits. While electrochemical water splitting typically requires a high voltage (above 1.23 V) and relies on purified or pre-treated water, MECs operate at a much lower voltage (0.2–0.8 V) by utilizing organic matter in wastewater as an electron donor, effectively reducing energy consumption. Additionally, unlike water splitting, which focuses solely on clean energy production, MECs simultaneously remove pollutants such as COD and heavy metals, achieving dual goals of hydrogen production and wastewater treatment. Economically, although MECs face challenges in microbial stability, reactor design, and electrode optimization, their lower operational costs and potential for resource recovery provide a promising alternative. In contrast, water splitting systems, despite their simplicity, are constrained by high energy consumption and water quality requirements, limiting their feasibility for large-scale sustainable hydrogen production. Integrating the strengths of both technologies may further enhance hydrogen production and sustainability in the future.

In the application of MECs, researchers have conducted extensive investigations into several key issues, including the selection and optimization of anode materials, electrode design, microbial community construction, and reactor configuration. For example, Sharma et al. (2024) conducted a comprehensive review of microbial electrolysis cells for hydrogen production, focusing on operational parameters, optimization strategies, and solutions to technical challenges to enhance hydrogen generation efficiency [9]. Catal et al. (2020) studied the role of extracellular polymeric substances (EPS) in microbial electrolysis cells, revealing EPS composition and its impact on electroactive biofilms. Their findings emphasized EPS formation as crucial for improving hydrogen production efficiency in MECs [10]. Arun et al. (2024) reviewed biohydrogen production from microbial fuel cells (MFCs) and microbial electrolysis cells (MECs), focusing on mechanisms, influencing factors, reactor design, and catalyst performance. They highlighted the challenges in energy harvesting, economic feasibility, and scalability of MFC and MEC integration for sustainable hydrogen production and achieving SDGs. These studies aim to enhance the energy conversion efficiency, hydrogen production rate, and long-term operational stability of MEC systems [11]. In recent years, with the advancement of nanotechnology and novel materials, nanomaterials, electrocatalysts, and co-cultivation techniques have been widely applied in MEC systems to further improve their performance [12]. For example, nanometal oxides and carbon-based materials, due to their high conductivity and excellent electrocatalytic activity, have become preferred choices for anode materials, while co-cultivation techniques can optimize microbial community structures to enhance the degradation efficiency of organic matter and promote hydrogen production. Despite these advances, MECs still face several challenges in practical applications, such as energy efficiency issues, the cost and stability of electrode materials, and optimization of operational conditions [13]. Therefore, improving the performance of MECs, reducing operational costs, and enhancing their stability in real-world applications remain key research priorities.

Bibliometric analysis, as an important tool for revealing the development trends of a discipline, has been widely applied in numerous academic fields. By conducting a quantitative analysis of the academic literature, researchers can identify research hotspots, technological advancements, and academic collaboration networks within a specific domain [14]. For instance, Donthu et al. (2021) offered an overview and detailed guidelines on performing bibliometric analysis, while Passas (2024) outlined the main steps involved in the process, from data collection to visualization [15,16]. CiteSpace (https://citespace.podia.com/, accessed on 1 December 2024), a Java-based text mining and scientometric visualization tool developed by C. Chen et al. (2009) have been widely used in scientific research. Through co-occurrence and co-citation analysis, CiteSpace can visually reveal important information such as research topics, discipline focus, technological evolution, and collaboration networks. For example, Geng et al. (2023) employed CiteSpace to visualize the research progress of sustainable smart grids (SG), uncovering the research hotspots, cross-regional collaborations, and the integration of different disciplines in this field. The study also pointed out that future research trends may include the integration of information technology and social sciences [17]. Additionally, HistCite, a bibliometric analysis software developed by Eugene Garfield, has also been widely applied across various disciplines. HistCite analyzes core literature datasets (CLD) to calculate key metrics such as the h-index, total local citation score (TLCS), average TLCS (ATLCS), total global citation score (TGCS), and average TGCS (ATGCS), providing strong support for the assessment of journal impact [18].

Although there has been some accumulation of research on the application of MEC technology in acid mine drainage treatment and hydrogen generation, systematic quantitative analysis of the overall research dynamics, technological advancements, and future development directions in this field is still insufficient. Therefore, this study conducts a systematic analysis of the research literature on MEC technology for AMD treatment and hydrogen production over the past 20 years, based on the Web of Science database (https://www.webofscience.com/, accessed on 30 November 2024), combined with bibliometric tools such as CiteSpace and HistCite. Through bibliometric analysis of aspects such as publication volume, disciplinary distribution, research countries and institutional collaboration networks, keyword clustering, and the evolution of research hotspots, this study aims to comprehensively reveal the research trends and future directions in this field. This analysis provides a deeper understanding of the current status and challenges of MEC technology in AMD treatment and hydrogen production while also offering theoretical support and data-driven insights for future research in related fields. This study aims to advance the application of MEC technology in both energy and environmental domains, offering new technological pathways and solutions to address global energy shortages and environmental pollution in mining regions.

2. Methods

2.1. Data Collection

This study primarily relied on the Web of Science Core Collection (WOSCC) database, developed by the Institute for Scientific Information (ISI), for data retrieval. Known for its extensive coverage and powerful functionality, this database is widely used for bibliometric analyses and includes academic resources from diverse fields such as natural sciences, biomedicine, and engineering, providing high-quality data support for this research. The data retrieval process followed the search strategy outlined as (TS = (“microbial electrolysis cell” OR “MEC” OR “bioelectrochemical system” OR “microbial fuel cell” OR “MFC”) AND TS = (“hydrogen production” OR “hydrogen generation” OR “H2 production”) AND TS = (“mine drainage” OR “acid mine drainage” OR “acid mine water” OR “mining waste” OR “wastewater treatment”)). The search time range was set from 2005 to 2024, with the final retrieval date being 1 December 2025. A total of 213 relevant publications were retrieved based on this search strategy.

2.2. Analytical Methods

For bibliometric analysis, this study utilized CiteSpace software (version 6.2.R7), focusing on identifying key research trends and hotspots within the field (Figure 1). CiteSpace offers analytical tools that examine the co-occurrence and co-citation of the literature, providing a deeper understanding of the knowledge structure and evolutionary trends through clustering analysis and burst detection. In constructing the knowledge map, the network is represented by nodes and edges. Each node corresponds to a specific entity, such as cited papers, institutions, or countries, while the edges reflect relationships like collaboration, co-occurrence, or co-citation. The strength of these relationships is indicated by the thickness of the edges, while their color coding represents different time periods, illustrating the dynamic evolution of the field. Notably, nodes with high betweenness centrality (BC) are of particular interest, as they often represent pivotal research milestones or interdisciplinary connections within the network [19]. The BC value, calculated using Equation (1), allows for the identification of core nodes, thereby helping to uncover primary research themes and the pathways of knowledge dissemination within the domain.

$$B{C}_i={\sum }_{i\ne s\ne t}{\displaystyle \frac{n_{st}^i}{g_{st}}}$$

(1)

In the formula, $g_{st}$ represents the total number of shortest paths connecting nodes s and t while $n_{st}^i$ indicates the number of such paths that pass through node i. The BC index is used to assess the importance of a particular node within the broader network structure. A higher BC value signifies that the node plays a more crucial role in mediating connections, reflecting its influence on information flow and network cohesion. Nodes with a BC value greater than 0.1 are highlighted with a purple ring in CiteSpace, typically denoting them as key research milestones or significant events within the field [20].

In CiteSpace analysis, a “burst” refers to a sudden, significant rise in a node’s metric value over a short period, often indicating dynamic shifts within its research domain. For example, a paper that receives a surge in citations within a brief period causes a citation burst. When multiple nodes within the same cluster show such citation bursts, it suggests the emergence of new research hotspots or evolving trends in the field. In this study, cluster analysis and burst detection are applied to capture significant changes and emerging patterns in the research on microbial electrolysis cells for hydrogen generation by treating acid mine drainage [21]. To assess the quality of clustering, two key metrics are employed: Modularity Q and the Mean Silhouette. Modularity Q measures the overall strength of the clustering structure, and a Q-value greater than 0.3 is considered indicative of a well-defined structure. The Mean Silhouette evaluates the homogeneity within clusters, with higher values signifying greater internal similarity. Typically, a Mean Silhouette coefficient above 0.7 is taken as a sign of reliable clustering results [22]. In the keyword clustering map, each module represents a cluster, and those with more keywords are typically displayed as larger clusters. CiteSpace uses the Log-Likelihood Ratio (LLR) algorithm to label clusters, with labels formatted as “# + number + label”. In the timeline view, the size of a node corresponds to the co-citation frequency of the referenced paper, while the color represents the temporal distribution of the research. The timeline on the left provides the year range, with clusters arranged sequentially from left to right to show their evolution. The color of the cluster labels indicates the average publication year: warm colors (e.g., red, orange, yellow) represent more recent research clusters, while cooler colors (e.g., cyan, blue, green) reflect earlier research developments.

In academic evaluations, the impact factor (IF) is a widely used metric to assess the scholarly quality and ranking of academic journals. This indicator, derived from citation index data [23], is typically obtained from the Journal Citation Reports (JCRs) by ISI. In this study, the IF values of relevant journals were evaluated together with key parameters from Histcite software (version 12.03.17), such as TLCS and TGCS, to identify influential journals and evaluate their impact on the research field. In Hiscite, TGCS represents the total number of citations a paper has received within the WOSCC, reflecting its global academic significance. On the other hand, TLCS represents the number of citations a paper has accumulated within a specific dataset, usually papers filtered by keyword searches. While TGCS measures global influence, TLCS is more suited for evaluating a paper’s centrality within a specific research domain. Papers with high TLCS scores are often regarded as crucial contributions with considerable influence in their respective fields [24]. Moreover, by examining the frequency of node appearances in different categories, the productivity of the literature in each category can be preliminarily assessed. Nodes with high frequency and centrality often correspond to key research topics or emerging trends in the field. By integrating impact factors with citation metrics, this study systematically analyzed academic resources in the area of microbial electrolysis cells for hydrogen generation from acid mine drainage, offering valuable insights for future research.

A paper indexed in the Web of Science (WOS) is typically categorized into one or more subject areas. Analyzing the co-occurrence of these categories helps identify the key disciplines that drive scientific advancements and reveals the interdisciplinary nature of a specific field. CiteSpace’s burst detection tool not only captures fluctuations in publication frequency but also uncovers trends in the growth of subject categories. A rapid increase in a particular subject category often indicates a shift in research focus or a transformation in research direction. Thus, investigating burst patterns of subject categories is essential for pinpointing emerging and active areas of research. In this study, CiteSpace was utilized for co-occurrence and burst detection analyses to comprehensively investigate the subject categories related to microbial electrolysis cells for hydrogen generation by treating acid mine drainage. By examining these categories and their burst patterns, the study reveals the core disciplines driving research in this field, highlights the interconnections between them, and identifies key research areas within microbial electrolysis cell technology applied to acid mine drainage treatment and hydrogen production. The findings also emphasize the interdisciplinary aspects of the field and suggest potential future directions for research development.

3. Results

3.1. Publication Output Characteristics

From 2005 to 2024, a total of 213 publications related to MEC for hydrogen generation from AMD were recorded. These publications were categorized into three types: journal articles, conference papers, and review articles. Among these, journal articles accounted for the highest proportion, at 71.83%, followed by review articles at 27.23%, and conference papers at 4.4%. As shown in Figure 2, although the annual publication output fluctuated across different years, the overall research output in this field exhibited a general upward trend from 2005 to 2024. Specifically, in 2005, there were only two relevant publications, but by 2024, this number had risen to 24, an increase of exactly 12 times compared to 2005. However, this growth was not consistent. Before 2019, the annual publication volume remained relatively low, with an average of fewer than 20 papers per year, and exhibited considerable fluctuations. In addition, the number of publications in 2020 dropped to 12, failing to maintain the upward trajectory of over 20 papers. However, since 2021, the annual output has steadily increased, and in 2021, 2023, and 2024, the number of publications remained stable at 24, indicating a more stable and efficient growth trend in the field’s research activities. Overall, despite fluctuations in the annual publication volume, research activities in this field have shown a significant upward trend since 2019, particularly after 2021, with multiple years of over 20 publications, highlighting the continued interest and research activity in this area.

To examine the trend in publication output, the fitted curve model presented in Equation (2) was utilized. This model allows for a description of the fluctuations in the frequency of publications related to microbial electrolysis cells for hydrogen generation by treating acid mine drainage, as illustrated in Figure 3.

$$y=1.38x-2778.75$$

(2)

In this equation, y represents the total number of publications, while x corresponds to the year. The goodness of fit, represented by R², reaches 0.86, demonstrating a good alignment between the model and the data. It should be noted that the current linear trend reflects the historical data well. However, if the number of publications stabilizes around 24 in the coming years, the fitting model would need to be adjusted from a linear relationship to one that accounts for a plateau. The continuation of the linear trend will depend on whether the number of publications continues to grow.

3.2. Journal Performance

Based on HistCite analysis, the top 20 most prolific journals accounted for more than 54.46% of the total publications in the field (see

Table 1. Top 20 journals ranked by the number of publications on microbial electrolysis cells for hydrogen generation by treating acid mine drainage from 2005 to 2024.

Ranking	Journal Title	Category	IF	Country	H-Index	Records	% of 1321	TLCS	TGCS	ATLCS	ATGCS
1	INTERNATIONAL JOURNAL OF HYDROGEN ENERGY	ELECTROCHEMISTRY	8.1	ENGLAND	16	24	11.27%	110	1026	4.58	42.75
2	BIORESOURCE TECHNOLOGY	BIOTECHNOLOGY and APPLIED MICROBIOLOGY	9.7	NETHERLANDS	13	15	7.04%	32	1026	2.13	68.40
3	WATER RESEARCH	ENVIRONMENTAL SCIENCES	11.5	ENGLAND	8	9	4.23%	69	1608	7.67	178.67
4	JOURNAL OF CHEMICAL TECHNOLOGY AND BIOTECHNOLOGY	ENGINEERING, CHEMICAL	2.8	ENGLAND	5	6	2.82%	23	311	3.83	51.83
5	CHEMOSPHERE	ENVIRONMENTAL SCIENCES	8.1	ENGLAND	5	5	2.35%	0	348	0.00	69.60
6	ENERGIES	ENERGY and FUELS	3.0	SWITZERLAND	2	5	2.35%	0	24	0.00	4.80
7	JOURNAL OF POWER SOURCES	ELECTROCHEMISTRY	8.1	NETHERLANDS	5	5	2.35%	12	213	2.40	42.60
8	SCIENCE OF THE TOTAL ENVIRONMENT	ENVIRONMENTAL SCIENCES	8.2	NETHERLANDS	5	5	2.35%	1	156	0.20	31.20
9	ELECTROCHIMICA ACTA	ELECTROCHEMISTRY	5.5	ENGLAND	4	4	1.88%	19	276	4.75	69.00
10	ENVIRONMENTAL SCIENCE AND POLLUTION RESEARCH	ENVIRONMENTAL SCIENCES	1.0	GERMANY	4	4	1.88%	4	59	1.00	14.75
11	JOURNAL OF ENVIRONMENTAL CHEMICAL ENGINEERING	ENGINEERING, CHEMICAL	7.4	ENGLAND	3	4	1.88%	0	59	0.00	14.75
12	JOURNAL OF ENVIRONMENTAL MANAGEMENT	ENVIRONMENTAL SCIENCES	8.0	ENGLAND	3	4	1.88%	0	89	0.00	22.25
13	PROCESS BIOCHEMISTRY	ENGINEERING, CHEMICAL	3.7	ENGLAND	4	4	1.88%	19	98	4.75	24.50
14	RSC ADVANCES	CHEMISTRY, MULTIDISCIPLINARY	3.9	ENGLAND	4	4	1.88%	7	68	1.75	17.00
15	ENERGY CONVERSION AND MANAGEMENT-X	MECHANICS	7.1	ENGLAND	1	3	1.41%	0	42	0.00	14.00
16	ENVIRONMENTAL RESEARCH	ENVIRONMENTAL SCIENCES	7.7	USA	3	3	1.41%	0	32	0.00	10.67
17	INTERNATIONAL JOURNAL OF ENERGY RESEARCH	ENERGY and FUELS	4.3	ENGLAND	3	3	1.41%	8	165	2.67	55.00
18	JOURNAL OF CLEANER PRODUCTION	ENVIRONMENTAL SCIENCES	9.8	USA	2	3	1.41%	0	277	0.00	92.33
19	JOURNAL OF HAZARDOUS MATERIALS	ENVIRONMENTAL SCIENCES	12.2	NETHERLANDS	3	3	1.41%	5	159	1.67	53.00
20	JOURNAL OF WATER PROCESS ENGINEERING	ENGINEERING, CHEMICAL	6.3	NETHERLANDS	2	3	1.41%	0	62	0.00	20.67

). A significant portion of the literature on microbial electrolysis cells for hydrogen generation by treating acid mine drainage has been published in journals such as the INTERNATIONAL JOURNAL OF HYDROGEN ENERGY, BIORESOURCE TECHNOLOGY, and WATER RESEARCH, contributing 11.27%, 7.04%, and 4.23%, respectively. These publications are primarily concentrated in leading journals from the fields of biotechnology and applied microbiology, chemical engineering, and electrochemistry. To assess journal performance comprehensively, both impact factors and H-index values were examined. In 2024, journals with the highest impact factors included JOURNAL OF HAZARDOUS MATERIALS (12.2), WATER RESEARCH (11.5), and JOURNAL OF CLEANER PRODUCTION (9.8). Regarding H-index scores, the top three journals were INTERNATIONAL JOURNAL OF HYDROGEN ENERGY (16), BIORESOURCE TECHNOLOGY (13), and WATER RESEARCH (8). Furthermore, the average citation per journal was calculated by dividing the total citations of articles related to microbial electrolysis cells for H2 generation by treating acid mine drainage by the number of articles in each journal. The findings revealed that WATER RESEARCH, ELECTROCHIMICA ACTA, and the INTERNATIONAL JOURNAL OF HYDROGEN ENERGY emerged as the most influential journals in this field, demonstrating the highest ATLCS or ATGCS values.

3.3. International Collaboration

The analysis of publication contributions by different countries offers insights into their involvement in the research on MEC for hydrogen generation through acid mine drainage treatment. Between 2005 and 2024, authors from 52 different countries or regions published works in this field. To better understand the collaborative dynamics among countries, an international collaboration network was constructed using CiteSpace based on co-authorship patterns. In the network visualization, node and link colors reflect temporal shifts from 2005 to 2024. The color gradient from purple to blue corresponds to the period of 2004–2010, cyan to green represents 2011–2016, yellow to orange marks 2017–2020, and red signifies the years 2021–2024 (as indicated in the legend on the left of Figure 4). The same color coding for nodes and links applies consistently in Figure 5, Figure 6, Figure 7, Figure 8 and Figure 9. In the network diagram, the size of each node corresponds to the total number of publications from the respective country. Nodes with purple circles highlight countries with high betweenness centrality, indicating their significant influence and central role in the network. The thickness of the connecting links between nodes reflects the frequency and strength of the collaborative efforts between these countries.

Figure 4 shows that China, India, the United States, Vietnam, and Saudi Arabia are the leading contributors to research on MECs for hydrogen generation through the treatment of acid mine drainage, as reflected by their top rankings in

Table 2. Top 10 countries/regions in the cooperation network (ranked by count or centrality).

Ranking	Countries	Count	Centrality	Ranking	Countries	Count	Centrality
1	PEOPLES R CHINA	66	0	1	VIETNAM	9	0.41
2	INDIA	47	0.38	2	INDIA	47	0.38
3	USA	38	0.19	3	SAUDI ARABIA	12	0.31
4	SOUTH KOREA	21	0.26	4	ENGLAND	8	0.31
5	CANADA	18	0.11	5	MALAYSIA	8	0.27
6	SPAIN	15	0.14	6	SOUTH KOREA	21	0.26
7	SAUDI ARABIA	12	0.31	7	AUSTRALIA	6	0.23
8	VIETNAM	9	0.41	8	USA	38	0.19
9	ENGLAND	8	0.31	9	THAILAND	5	0.16
10	MALAYSIA	8	0.27	10	SPAIN	15	0.14

based on count and centrality (India appearing in both). These countries are represented by prominent nodes in the international collaboration network and maintain strong research ties. As early as 2014, Chinese researchers developed a dual-chamber MEC for metal removal from AMD and hydrogen production. The study showed selective metal recovery, with Cu²⁺ removed first, followed by Ni²⁺ and Fe²⁺. The highest hydrogen production rate reached 1.1 m³ m⁻³ d⁻¹, and the energy recovery efficiency was up to 100%. The MEC successfully recovered metals and produced hydrogen from AMD [25]. Meanwhile, researchers from Vietnam developed a MEC for hydrogen production from wastewater. The system achieved a maximum hydrogen efficiency of 21.2% at 1.0 V, with a production rate of 0.095 m³ H₂/m³ reactor/day using acetate and 0.061 m³ H₂/m³ reactor/day with piggery wastewater, along with a 45–52% COD removal rate [26]. Early research in this field, particularly on the use of MECs for treating acid mine drainage, was primarily conducted in the United States, India, and Vietnam. These countries are represented by purple nodes in the collaboration network (Figure 4), highlighting their significant roles in this area of research. As shown in Table 2, the top ten countries in terms of publication volume and centrality from 2005 to 2024 were identified. Among these, India and the United States not only published a large number of studies but also played key roles in fostering international cooperation. For instance, researchers from India and Vietnam explore bio-hydrogen production using MFC and MEC from wastewater. They discuss the mechanisms, influencing factors, reactor designs, and catalysts for hydrogen evolution, as well as the challenges and economic aspects of energy harvesting. The review highlights the need for scaling up MFC and MEC systems to improve hydrogen production and contribute to sustainable development goals (SDGs) [11]. Additionally, researchers from the United States and China investigated MECs for treating complex wastewater and producing hydrogen. They analyzed MEC performance in organic removal, hydrogen production, and energy efficiency. Key challenges, such as wastewater complexity, hydrogen production instability, and the integration with other treatment processes, were discussed. The study highlights the environmental and economic feasibility of MECs for future commercial applications in wastewater treatment [27]. Although countries such as Australia and Thailand have made relatively smaller contributions to large-scale applications of MECs for acid mine drainage treatment, they remain key players in the international research network, significantly advancing the practical application of this technology.

3.4. Institutional Collaboration

From 2005 to 2024, a total of 322 institutions have contributed significantly to research on MECs for hydrogen generation from AMD. Figure 5, generated using CiteSpace software, provides a visual representation of the distribution of these research institutions. In the figure, each node corresponds to an institution, with the node size indicating the volume of published papers from that institution.

Table 3. Top 10 institutions in the collaboration network (ranked by publication volume or centrality).

Ranking	Institutions	Country	Count	Centrality	Ranking	Institutions	Country	Count	Centrality
1	Council of Scientific & Industrial Research (CSIR)—India	India	12	0.18	1	University of Chinese Academy of Sciences	China	3	0.33
2	Harbin Institute of Technology	China	10	0	2	Yonsei University	South Korea	4	0.25
3	Pennsylvania State University—University Park	United States	9	0.04	3	Chinese Academy of Sciences	China	8	0.24
4	Pennsylvania State University	United States	9	0.04	4	Saveetha Dental College & Hospital	India	2	0.23
5	Pennsylvania Commonwealth System of Higher Education (PCSHE)	United States	9	0.04	5	Virginia Polytechnic Institute & State University	United States	4	0.22
6	CSIR—Indian Institute of Chemical Technology (IICT)	India	9	0	6	TERI University	India	3	0.19
7	Chinese Academy of Sciences	China	8	0.24	7	United States Department of Energy (DOE)	United States	3	0.19
8	Egyptian Knowledge Bank (EKB)	Egypt	6	0.11	8	Council of Scientific & Industrial Research (CSIR)—India	India	12	0.18
9	Dalian University of Technology	China	6	0.17	9	Dalian University of Technology	China	6	0.17
10	Indian Institute of Technology System (IIT System)	India	6	0.07	10	National Institute of Agricultural Sciences	South Korea	2	0.15

presents the top ten institutions, ranked by the number of publications and centrality scores, in the field of MECs for hydrogen production from AMD. A majority of the leading institutions are located in Asia, particularly in China and India, with additional contributions from the United States, Egypt, and South Korea. For example, researchers from the Indian Institute of Technology System (IIT System) combined dark fermentation with MECs to enhance energy recovery from cellulosic substrates. They achieved a hydrogen yield of 2.92 mol/mol hexose, with 28% energy recovery. The MECs produced 85.05 mW/m² power density. Overall, the system demonstrated 30.49% energy recovery, highlighting its environmental and economic sustainability [28]. The research from the University of Chinese Academy of Sciences explores the challenges and opportunities of MECs for wastewater treatment. The study emphasizes the need to integrate MECs with other treatment technologies to form a more effective MEC-centered treatment strategy. By critically analyzing existing issues, the work provides valuable insights to guide the development of MEC technology for sustainable wastewater treatment [29]. Harbin Institute of Technology developed a combined system of MEC and aluminum–air batteries (Al–air batteries) for hydrogen generation and wastewater treatment. The Al–air battery powered the MEC, enabling hydrogen production at a rate of 0.19 m³ H₂/m³/d and achieving 85% COD removal. The system operated in an energy-self-sufficient mode, with high-efficiency effluent treatment and significant microorganism removal. This work highlights the potential of integrating MECs with Al–air batteries for sustainable energy recovery and wastewater management [30].

Between 2004 and 2024, the Council of Scientific & Industrial Research (CSIR)—India, Harbin Institute of Technology, and Pennsylvania State University—University Park published 12, 10, and 9 papers, respectively, on the use of MECs for hydrogen generation by treating AMD. These contributions underline India’s leading role in this field and demonstrate the growing global interest in sustainable energy production through this technology. In terms of international collaboration, the Chinese Academy of Sciences plays a central role in the institutional network, maintaining strong partnerships with CSIR and the Indian Institute of Technology System (IIT System). Likewise, Yonsei University, Saveetha Dental College & Hospital, and Virginia Polytechnic Institute & State University have forged extensive research networks, with centrality scores of 0.25, 0.23, and 0.22, respectively. This international cooperation fosters research advancements in the application of MECs for H₂ production from AMD while enhancing global synergies and contributing to a more interdisciplinary approach to clean energy and wastewater treatment.

Figure 5. Institutional collaboration network of key organizations (2005–2024).

Figure 5. Institutional collaboration network of key organizations (2005–2024).

3.5. Co-Occurrence Analysis of Subject Categories

A co-occurrence network of subject categories covering the period from 2005 to 2024 was created using the path network scaling simplification method (Figure 6). A total of 35 distinct subject categories were identified from 213 search results. Research on MECs for hydrogen generation from acid mine drainage spans a wide range of interdisciplinary fields, encompassing areas such as “Energy & Fuels”, “Environmental Sciences”, “Chemical Engineering”, “Biotechnology; Applied Microbiology”, “Electrochemistry”, “Water Resources”, “Environmental Engineering”, “Physical Chemistry”, “Agricultural Engineering”, “Biophysics”, “Nanoscience & Nanotechnology”, and “Chemistry, Multidisciplinary”. The co-occurrence analysis indicates that categories like “Energy & Fuels”, “Environmental Sciences”, and “Engineering, Environmental” are particularly prominent, reflecting the primary research focus in this area. Further examination of the evolution of research hotspots reveals a shift over time. Early studies primarily focused on fields such as “Engineering, Environmental”, “Environmental Sciences”, and “Water Resources”, which are foundational to the research area and are marked with purple circles in the network. In more recent years, new research topics have emerged, including “Environmental Studies”, “Public, Environmental; Occupational Health”, “Toxicology”, and “Physics”, denoted by circles in different colors to show their growing relevance. Additionally, categories like “Biotechnology; Applied Microbiology”, “Engineering, Chemical”, and “Engineering, Environmental” are surrounded by dense purple circles, emphasizing their central role in bridging various academic disciplines. These categories are key in linking distinct fields and preventing the network from becoming fragmented by isolated nodes, thereby fostering greater interdisciplinary collaboration.

Figure 6. A co-occurrence network of subject areas from 2005 to 2024.

Figure 6. A co-occurrence network of subject areas from 2005 to 2024.

Table 4. Top 10 subject categories in the co-occurrence network (ranked by frequency or centrality score).

Ranking	Subject Categories	Count	Centrality	Ranking	Subject Categories	Count	Centrality
1	ENERGY and FUELS	77	0.41	1	BIOTECHNOLOGY; APPLIED MICROBIOLOGY	42	0.69
2	ENVIRONMENTAL SCIENCES	64	0.49	2	ENGINEERING, CHEMICAL	42	0.6
3	ENGINEERING, ENVIRONMENTAL	46	0.55	3	ENGINEERING, ENVIRONMENTAL	46	0.55
4	BIOTECHNOLOGY; APPLIED MICROBIOLOGY	42	0.69	4	BIOPHYSICS	3	0.52
5	ENGINEERING, CHEMICAL	42	0.6	5	ENVIRONMENTAL SCIENCES	64	0.49
6	ELECTROCHEMISTRY	38	0.18	6	BIOCHEMISTRY; MOLECULAR BIOLOGY	6	0.49
7	CHEMISTRY, PHYSICAL	36	0	7	ENERGY and FUELS	77	0.41
8	CHEMISTRY, MULTIDISCIPLINARY	21	0.29	8	NANOSCIENCE and NANOTECHNOLOGY	5	0.35
9	WATER RESOURCES	20	0.21	9	CHEMISTRY, MULTIDISCIPLINARY	21	0.29
10	AGRICULTURAL ENGINEERING	17	0	10	PHYSICS, APPLIED	3	0.22

presents the top ten subject categories identified through co-occurrence analysis, ranked by frequency and centrality. The key research areas related to the application of MECs for hydrogen generation by treating AMD include fundamental fields such as “Energy & Fuels”, “Environmental Sciences”, and “Biotechnology; Applied Microbiology”. Additionally, interdisciplinary topics such as “Agricultural Engineering”, “Nanoscience & Nanotechnology”, and “Physics, Applied” also hold significant research value in this context. In the field of Energy and Fuels, key aspects such as microbial culture, electrodes, and operational parameters impacting hydrogen generation are explored. The study highlights challenges like high costs, internal resistance, and biofouling while suggesting strategies for optimization and future advancements in MEC technology [9]. This research in Environmental Sciences presents a dual-cathode bioelectrochemical system (BES) for simultaneous hydrogen production and electricity generation in MECs. It demonstrates that the Power-cathode can supply sufficient voltage for hydrogen production at the H₂-cathode, with a hydrogen rate of 0.19 m³/m³/d. The study also highlights bacterial distribution patterns in the anodic biofilm, improving MEC performance for wastewater treatment and resource recovery [31]. In Agricultural Engineering, this study investigates a bioelectrochemical reactor that simultaneously produces hydrogen and recovers ammonium from rejected water. Microbial activity at the anode generates electricity, driving hydrogen production at the cathode. The process also converts ammonium into ammonia, with recovery efficiencies of 94% for synthetic and 79% for real rejected water. This method could improve resource efficiency in wastewater treatment [32]. These findings underscore the interdisciplinary nature of MEC research, with promising advancements in both fundamental understanding and practical applications.

The results indicate that all 35 identified subject categories exhibit citation bursts, reflecting significant attention during specific periods.

Table 5. Detailed information on the top 30 subject categories with the strongest citation bursts in the co-occurrence network.

Subject Categories	Strength	Duration	Begin	End	2004–2024	Count	Centrality
CHEMISTRY, PHYSICAL+A3:H32	2.23	4	2010	2013	▂ ▂ ▂ ▂ ▂ ▃ ▃ ▃ ▃ ▂ ▂ ▂ ▂ ▂ ▂ ▂ ▂ ▂ ▂ ▂	36	0
ELECTROCHEMISTRY	1.77	5	2008	2012	▂ ▂ ▂ ▃ ▃ ▃ ▃ ▃ ▂ ▂ ▂ ▂ ▂ ▂ ▂ ▂ ▂ ▂ ▂ ▂	38	0.18
MATERIALS SCIENCE, MULTIDISCIPLINARY	1.56	2	2013	2014	▂ ▂ ▂ ▂ ▂ ▂ ▂ ▂ ▃ ▃ ▂ ▂ ▂ ▂ ▂ ▂ ▂ ▂ ▂ ▂	11	0.06
NANOSCIENCE and NANOTECHNOLOGY	1.53	2	2013	2014	▂ ▂ ▂ ▂ ▂ ▂ ▂ ▂ ▃ ▃ ▂ ▂ ▂ ▂ ▂ ▂ ▂ ▂ ▂ ▂	5	0.35
GREEN; SUSTAINABLE SCIENCE; TECHNOLOGY	1.39	2	2023	2024	▂ ▂ ▂ ▂ ▂ ▂ ▂ ▂ ▂ ▂ ▂ ▂ ▂ ▂ ▂ ▂ ▂ ▂ ▃ ▃	13	0.18
BIOCHEMISTRY; MOLECULAR BIOLOGY	1.14	2	2020	2021	▂ ▂ ▂ ▂ ▂ ▂ ▂ ▂ ▂ ▂ ▂ ▂ ▂ ▂ ▂ ▃ ▃ ▂ ▂ ▂	6	0.49
ENVIRONMENTAL SCIENCES	1.10	2	2023	2024	▂ ▂ ▂ ▂ ▂ ▂ ▂ ▂ ▂ ▂ ▂ ▂ ▂ ▂ ▂ ▂ ▂ ▂ ▃ ▃	64	0.49
THERMODYNAMICS	1.04	1	2015	2015	▂ ▂ ▂ ▂ ▂ ▂ ▂ ▂ ▂ ▂ ▃ ▂ ▂ ▂ ▂ ▂ ▂ ▂ ▂ ▂	6	0.11
BIOTECHNOLOGY; APPLIED MICROBIOLOGY	1.00	1	2015	2015	▂ ▂ ▂ ▂ ▂ ▂ ▂ ▂ ▂ ▂ ▃ ▂ ▂ ▂ ▂ ▂ ▂ ▂ ▂ ▂	42	0.69
MICROBIOLOGY	0.97	3	2022	2024	▂ ▂ ▂ ▂ ▂ ▂ ▂ ▂ ▂ ▂ ▂ ▂ ▂ ▂ ▂ ▂ ▂ ▃ ▃ ▃	6	0
WATER RESOURCES	0.90	1	2017	2017	▂ ▂ ▂ ▂ ▂ ▂ ▂ ▂ ▂ ▂ ▂ ▂ ▃ ▂ ▂ ▂ ▂ ▂ ▂ ▂	20	0.21
PUBLIC, ENVIRONMENTAL, OCCUPATIONAL HEALTH	0.83	3	2022	2024	▂ ▂ ▂ ▂ ▂ ▂ ▂ ▂ ▂ ▂ ▂ ▂ ▂ ▂ ▂ ▂ ▂ ▃ ▃ ▃	3	0
NUCLEAR SCIENCE and TECHNOLOGY	0.80	2	2021	2022	▂ ▂ ▂ ▂ ▂ ▂ ▂ ▂ ▂ ▂ ▂ ▂ ▂ ▂ ▂ ▂ ▃ ▃ ▂ ▂	3	0
ENGINEERING, MECHANICAL	0.69	1	2011	2011	▂ ▂ ▂ ▂ ▂ ▂ ▃ ▂ ▂ ▂ ▂ ▂ ▂ ▂ ▂ ▂ ▂ ▂ ▂ ▂	1	0
BIOLOGY	0.67	1	2009	2009	▂ ▂ ▂ ▂ ▃ ▂ ▂ ▂ ▂ ▂ ▂ ▂ ▂ ▂ ▂ ▂ ▂ ▂ ▂ ▂	1	0
MARINE/FRESHWATER BIOLOGY	0.67	1	2010	2010	▂ ▂ ▂ ▂ ▂ ▃ ▂ ▂ ▂ ▂ ▂ ▂ ▂ ▂ ▂ ▂ ▂ ▂ ▂ ▂	1	0
CHEMISTRY, APPLIED	0.65	1	2016	2016	▂ ▂ ▂ ▂ ▂ ▂ ▂ ▂ ▂ ▂ ▂ ▃ ▂ ▂ ▂ ▂ ▂ ▂ ▂ ▂	1	0
ENGINEERING, ELECTRICAL and ELECTRONIC	0.65	1	2016	2016	▂ ▂ ▂ ▂ ▂ ▂ ▂ ▂ ▂ ▂ ▂ ▃ ▂ ▂ ▂ ▂ ▂ ▂ ▂ ▂	1	0
TOXICOLOGY	0.65	1	2020	2020	▂ ▂ ▂ ▂ ▂ ▂ ▂ ▂ ▂ ▂ ▂ ▂ ▂ ▂ ▂ ▃ ▂ ▂ ▂ ▂	1	0
PHYSICS, ATOMIC, MOLECULAR and CHEMICAL	0.65	1	2020	2020	▂ ▂ ▂ ▂ ▂ ▂ ▂ ▂ ▂ ▂ ▂ ▂ ▂ ▂ ▂ ▃ ▂ ▂ ▂ ▂	1	0
METEOROLOGY; ATMOSPHERIC SCIENCES	0.63	1	2017	2017	▂ ▂ ▂ ▂ ▂ ▂ ▂ ▂ ▂ ▂ ▂ ▂ ▃ ▂ ▂ ▂ ▂ ▂ ▂ ▂	1	0
BIOCHEMICAL RESEARCH METHODS	0.59	1	2019	2019	▂ ▂ ▂ ▂ ▂ ▂ ▂ ▂ ▂ ▂ ▂ ▂ ▂ ▂ ▃ ▂ ▂ ▂ ▂ ▂	1	0
MULTIDISCIPLINARY SCIENCES	0.53	1	2022	2022	▂ ▂ ▂ ▂ ▂ ▂ ▂ ▂ ▂ ▂ ▂ ▂ ▂ ▂ ▂ ▂ ▂ ▃ ▂ ▂	2	0
ENGINEERING, MULTIDISCIPLINARY	0.47	1	2021	2021	▂ ▂ ▂ ▂ ▂ ▂ ▂ ▂ ▂ ▂ ▂ ▂ ▂ ▂ ▂ ▂ ▃ ▂ ▂ ▂	2	0.02
LIMNOLOGY	0.47	1	2021	2021	▂ ▂ ▂ ▂ ▂ ▂ ▂ ▂ ▂ ▂ ▂ ▂ ▂ ▂ ▂ ▂ ▃ ▂ ▂ ▂	2	0
ENGINEERING, ENVIRONMENTAL	0.42	2	2023	2024	▂ ▂ ▂ ▂ ▂ ▂ ▂ ▂ ▂ ▂ ▂ ▂ ▂ ▂ ▂ ▂ ▂ ▂ ▃ ▃	46	0.55
AGRICULTURAL ENGINEERING	0.40	1	2018	2018	▂ ▂ ▂ ▂ ▂ ▂ ▂ ▂ ▂ ▂ ▂ ▂ ▂ ▃ ▂ ▂ ▂ ▂ ▂ ▂	17	0
CHEMISTRY, ANALYTICAL	0.40	1	2019	2019	▂ ▂ ▂ ▂ ▂ ▂ ▂ ▂ ▂ ▂ ▂ ▂ ▂ ▂ ▃ ▂ ▂ ▂ ▂ ▂	3	0.02
BIOPHYSICS	0.40	1	2019	2019	▂ ▂ ▂ ▂ ▂ ▂ ▂ ▂ ▂ ▂ ▂ ▂ ▂ ▂ ▃ ▂ ▂ ▂ ▂ ▂	3	0.52
ENERGY and FUELS	0.36	1	2016	2016	▂ ▂ ▂ ▂ ▂ ▂ ▂ ▂ ▂ ▂ ▂ ▃ ▂ ▂ ▂ ▂ ▂ ▂ ▂ ▂	77	0.41

highlights the top 30 categories with the most prominent citation bursts. According to the burst detection tool in CiteSpace, the five categories with the highest citation burst intensity are “Chemistry, Physical” (2.23), “Electrochemistry” (1.77), “Materials Science, Multidisciplinary” (1.56), “Nanoscience & Nanotechnology” (1.53), and “Green; Sustainable Science; Technology” (1.39). These categories experienced notable surges in research activity, emphasizing their importance in the corresponding fields. The colored bars in Table 5 illustrate the time intervals of citation bursts for each category, with red sections marking the onset and duration of these bursts. For instance, the category “Chemistry, Physical” experienced a burst intensity of 2.23 from 2010 to 2013, indicating a substantial increase in research output during that period, emphasizing its key role in the development of MECs for hydrogen generation from acid mine drainage. “Electrochemistry” shows the longest burst period, lasting 5 years, highlighting its sustained significance in the field. In the early phases of research, the focus of MEC technology was primarily on areas such as “Environmental Sciences”, “Engineering, Environmental”, “Energy & Fuels”, “Water Resources”, “Biotechnology; Applied Microbiology”, and “Nanoscience & Nanotechnology”. This multidisciplinary approach reflects the complexity of applying MEC technology to acid mine drainage treatment, involving knowledge of environmental remediation techniques, electrochemical processes, microbial metabolism, resource recovery, water treatment technologies, and materials science. Over the past two years, advancements in “Environmental Studies”, “Public, Environmental; Occupational Health”, “Toxicology”, and “Physics” have become increasingly critical to the development of MECs for hydrogen production. This shift toward a broader multidisciplinary perspective highlights the increasing acknowledgment of MEC technology’s potential, not only in achieving efficient pollutant removal and hydrogen production but also in enhancing energy conversion, optimizing microbe–electrode interactions, and developing novel multifunctional materials. As the field continues to advance, contributions from additional disciplines are expected to provide new insights and strategies, further expanding the application of MECs. This will accelerate the ongoing evolution of MEC technology while addressing emerging challenges and unlocking new opportunities for its implementation.

3.6. Keyword Cluster Analysis

Keywords play a crucial role in summarizing and highlighting key research areas. In this study, keyword cluster analysis is used to provide an organized view of significant themes in the research on MECs for hydrogen production from AMD.

Table 6. Analysis of document co-citation clusters and their features.

Cluster ID	Cluster Name	Size	Silhouette	Mean (Year)	Main Keywords
0	Energy Efficiency	41	0.948	2016	microbial electrolysis cell; wastewater treatment; bioenergy production; electrode materials; anaerobic digestion|microbial fuel cell; anaerobic baffled reactor; fecal wastewater; organic wet waste; hydrothermal liquefaction
1	Anaerobic Fermentation	31	0.865	2014	microbial fuel cell; mixed culture; anaerobic wastewater treatment; sustainable power; single chamber|wastewater treatment; medatiorless anode; h-2 producing mixed microflora; anaerobic fermentation; microbial electrochemical system
2	Biofilm Formation	30	0.819	2015	wastewater treatment; bioelectrochemical systems; volatile fatty acids; acetic acid; exoelectrogenic bacteria|domestic wastewater; microbial electrolysis cell; costs estimation; extracellular electron; bioelectrochemical systems
3	Optimization	29	0.931	2011	hydrogen production; organic removal; green syntheses; microbial electrodialysis cells; techno-economic analysis|microbial electrolysis cell; spiral wound electrode; energy efficiency; methane production; green syntheses
4	Exoelectrogenic Bacteria	28	0.950	2020	microbial electrolysis cell; microbial fuel cell; microbial electrochemical technology; petrochemical wastewater; recalcitrant organic pollutants|bioelectrochemical systems; exoelectrogenic bacteria; acetoclastic methanogenesis; mesophilic anaerobic digesters; anaerobic digestion models
5	Concentrate from EDR	26	0.946	2013	microbial electrolysis cell; simultaneous removal; bacterial community; mixed culture; anaerobic wastewater treatment|microbial fuel cell; anaerobic wastewater treatment; sustainable power; single chamber; mixed culture
6	Dark Fermentation	25	0.909	2016	microbial electrolysis cell; dark fermentation; toxicity assessment; carbon nanotubes; electrochemical characterization|wastewater treatment; microbial fuel cell; bioelectrochemical system; organic load; cattle manure
7	Photoelectrocatalysis	23	0.909	2019	wastewater treatment; power generation; solar energy; advanced oxidation process; environmental remediation|microbial electrolysis cell; light irradiation; molybdenum deposition; environmental remediation; solar energy
8	Microbial Electrolysis Cell	21	0.922	2018	microbial electrolysis cell; wastewater treatment; electrode materials; bioenergy production; microbial community|hydrogen production; organic removal; electro-catalytic activity; high-strength wastewater; hydrogen evolution reaction
9	Syntrophic Interaction	20	0.943	2017	microbial electrolysis cell; wastewater treatment; microbial fuel cell; conduction-based mechanism; extracellular electron|key performance indicators; microbial electrosynthesis; microbial electrocatalysis; electrochemically active surface area; extracellular electron
10	Reuse	20	0.913	2014	energy recovery; bioelectrochemical systems; acetoclastic methanogenesis; mesophilic anaerobic digesters; anaerobic digestion models|bioelectrochemical system; microbial fuel cell; wastewater treatment; organic loading rate; bioelectrochemical systems
11	Reactor Design	19	0.908	2019	microbial electrolysis cell; distillery wastewater; current density; reactor design; bifunctional electrochemistry|bifunctional electrochemistry; biohydrogen upgradation; electrochemical analyses; microbial fuel cells; bes integration
12	Circular Economy	19	0.842	2018	wastewater treatment; hydrogen production; nife layered double hydroxide; nickel foam; microbial electrolysis cell|resource recovery; circular economy; sewage sludge; nife layered double hydroxide; wastewater treatment
13	Fermentative Hydrogen Production	19	0.915	2015	wastewater treatment; microbial fuel cell; bioelectrochemical systems; carbon dioxide reduction; based materials|microbial electrolysis cell; hydrogen production; life cycle assessment; electron transfer pathways; power density
14	Bioenergy	16	0.884	2013	wastewater treatment; microbial electrolysis cell; microbial fuel cells; electron transfer; key performance indicators|microbial fuel cell; key performance indicators; electrochemically active surface area; microbial electrocatalysis; microbial electrosynthesis
15	Refractory Pollutant	4	1	2008	wastewater treatment; microbial electrolysis cell; microbial fuel cell; nafion membrane; bipolar membrane|hydrogen production; organic wet waste; hydrothermal liquefaction; process maturity; oil palm waste

and Figure 7 display 16 keyword clusters and their characteristics, with each term arranged according to cluster size. The largest and most prominent cluster, labeled “#0”, is titled “Energy Efficiency”, which reflects a key focus in the field. The clustering quality metrics, including Q-value (0.7617) and S-value (0.9111), suggest strong reliability of the research results. Research on hydrogen production from AMD using MECs primarily focuses on three core areas. First, the application of MECs in power generation and energy recovery aims to enhance power density and energy recovery efficiency, with an emphasis on scaling from laboratory to industrial applications. Key research topics include electricity production, proton exchange membrane optimization, redox reactions, reactor design, and system scalability. Relevant research clusters include Energy Efficiency (#0), Optimization (#3), Exoelectrogenic Bacteria (#4), and Reactor Design (#11). Second, MECs demonstrate significant potential in wastewater treatment, particularly in the removal of nitrogen and phosphorus, constructed wetland development, and Chemical Oxygen Demand (COD) reduction. Studies explore MEC integration with eco-innovative technologies for enhanced wastewater purification and resource recovery. Relevant clusters include Biofilm Formation (#2), Dark Fermentation (#6), Microbial Electrolysis Cell (#8), Circular Economy (#12), and Refractory Pollutant Removal (#15). Lastly, the structural optimization of MEC systems and their integrated use in AMD resource recovery focuses on forward osmosis technology, microbial community control, and bioelectrochemical systems to improve overall treatment capacity and resource recovery efficiency. Relevant clusters include Photoelectrocatalysis (#7), Syntrophic Interaction (#9), Reuse (#10), and Fermentative Hydrogen Production (#13). These studies advance MEC applications in hydrogen production, wastewater treatment, and resource recovery by optimizing system structures and incorporating cutting-edge technologies for microbial community regulation. The three largest clusters are “Energy Efficiency”, “Anaerobic Fermentation”, and “Biofilm Formation”. On the other hand, “Optimization”, “Concentrate from EDR”, and “Bioenergy” are among the earliest clusters identified in the research. In contrast, the most recent research trends are represented by clusters such as “Photoelectrocatalysis” and “Reactor Design”. These shifts illustrate the progression of MEC research, with earlier studies concentrating on foundational areas such as optimization, concentrate recovery, and bioenergy production. More recent trends focus on advanced topics like photoelectrocatalysis and reactor design, reflecting an increasing emphasis on improving the efficiency and scalability of MEC systems for sustainable applications.

Cluster #0, focused on “Energy Efficiency”, encompasses essential technologies such as “microbial electrolysis cells”, “wastewater treatment”, “bioenergy production”, “electrode materials”, and “anaerobic digestion”. The primary emphasis is on optimizing MEC systems to improve energy efficiency, particularly for hydrogen generation from AMD. MECs, as an innovative bioelectrochemical system, convert organic pollutants into electrical energy through the interaction between microorganisms and electrodes while simultaneously generating hydrogen, offering a sustainable approach for both AMD treatment and resource recovery. The research underscores the pivotal role of electrode material selection and optimization in enhancing MEC performance. Conductive materials, such as carbon-based and metal alloy electrodes, significantly boost electrode surface activity, facilitating efficient electron transfer and increasing hydrogen production rates [33]. Moreover, integrating anaerobic digestion with MECs enhances the degradation of organic wastewater, where microorganisms work in tandem to generate electricity and drive hydrogen production [34]. The cluster also investigates synergies between MECs and other wastewater treatment technologies, such as the use of anaerobic baffled reactors, to improve organic degradation efficiency and support electricity generation [35]. Green synthesis methods, including hydrothermal liquefaction, are explored to further enhance resource recovery and energy efficiency. Additionally, optimizing proton exchange membranes (PEMs) plays a crucial role in improving current efficiency, energy utilization, and hydrogen production, particularly under the acidic conditions of AMD. The acid resistance and electrochemical stability of PEMs are vital for ensuring the long-term operation of MECs in such harsh environments [36].

Cluster #1, centered on “Anaerobic Fermentation”, includes key technologies and concepts such as “microbial fuel cells”, “mixed culture”, “anaerobic wastewater treatment”, “sustainable power”, “single chamber structure”, “mediatorless anode”, “H₂-producing mixed microflora”, “anaerobic fermentation”, and “microbial electrochemical systems”. This cluster primarily focuses on optimizing microbial fuel cell systems for energy recovery from AMD, with a particular emphasis on enhancing hydrogen production. Studies show that the use of mixed cultures improves system stability and increases the efficiency of organic matter degradation, which, in turn, boosts the generation of electrical energy and hydrogen [9,37]. Anaerobic wastewater treatment is central to MFC performance, where anaerobic fermentation processes degrade complex organic pollutants into simpler molecules, releasing electrons and producing hydrogen. This process not only facilitates wastewater treatment but also contributes to the generation of sustainable power [38]. The single-chamber design of MFCs simplifies system construction, reduces costs, and improves efficiency. The application of mediatorless anodes further reduces system complexity while enhancing electron transfer efficiency. Research into H₂-producing mixed microflora highlights the synergistic roles of various microorganisms in electrochemical reactions, optimizing pathways for hydrogen production [39]. The optimization of microbial electrochemical systems, including electrode material selection and the fine-tuning of operational parameters, plays a crucial role in enhancing both energy recovery and hydrogen yield [40].

Cluster #2, centered on “Biofilm Formation”, encompasses key technologies and concepts such as “bioelectrochemical systems”, “volatile fatty acids”, “acetic acid”, “exoelectrogenic bacteria”, “domestic wastewater”, “microbial electrolysis cells”, “costs estimation”, and “extracellular electron transfer”. This cluster primarily focuses on optimizing wastewater treatment processes through the integration of MECs within BES. The research highlights the pivotal role of exoelectrogenic bacteria in facilitating extracellular electron transfer, which is essential for the efficient degradation of organic pollutants and the subsequent generation of hydrogen [41]. Volatile fatty acids (VFAs), particularly acetic acid, are identified as key intermediates in the anaerobic digestion process, serving as primary substrates for exoelectrogenic bacteria to produce electrical current and hydrogen [42]. Studies within this cluster emphasize the treatment of domestic wastewater, demonstrating how MECs can effectively reduce COD while simultaneously generating valuable bioenergy [43]. Additionally, cost estimation analyses are integral to this research, providing insights into the economic feasibility and scalability of implementing MEC-based wastewater treatment systems in real-world applications [44]. The optimization of extracellular electron transfer mechanisms is also a critical area of investigation, aiming to enhance the overall efficiency and sustainability of bioelectrochemical wastewater treatment [45].

Cluster #3, centered on “Optimization”, encompasses key technologies and concepts such as “hydrogen production”, “organic removal”, “green syntheses”, “microbial electrodialysis cells”, “techno-economic analysis”, “microbial electrolysis cells”, “spiral wound electrodes”, “energy efficiency”, “methane production”, and “green syntheses”. This cluster primarily focuses on optimizing hydrogen production and organic pollutant removal efficiency by enhancing the power density of MECs while also emphasizing the application of green synthesis methods and system energy efficiency. Research indicates that power density is a critical performance metric for MECs, directly impacting the rate of hydrogen generation and the efficiency of organic pollutant degradation. Advanced electrode designs, such as spiral wound electrodes, contribute to increasing electrode surface area and enhancing electron transfer capabilities, thereby significantly improving system power density [46]. Additionally, the incorporation of green synthesis methods, such as hydrothermal liquefaction, further enhances the efficient utilization of resources and the sustainable production of energy [47]. The techno-economic analysis also plays a crucial role within this cluster, with studies evaluating the cost-effectiveness of MEC systems to determine their economic feasibility in practical applications. Enhancing energy efficiency not only helps reduce operational costs but also promotes the generation of byproducts like methane, providing possibilities for diversified energy production. Microbial electrodialysis cells, as a variant of MECs, demonstrate potential in organic removal and hydrogen production, with system performance further enhanced through the optimization of operational parameters and microbial communities [48].

Cluster #4, centered on “Exoelectrogenic Bacteria”, explores advanced microbial electrochemical technologies for treating petrochemical wastewater, focusing on key concepts like “microbial electrolysis cells”, “microbial fuel cells”, “microbial electrochemical technology”, “petrochemical wastewater”, “recalcitrant organic pollutants”, “bioelectrochemical systems”, “exoelectrogenic bacteria”, “acetoclastic methanogenesis”, “mesophilic anaerobic digesters”, and “anaerobic digestion models”. This cluster emphasizes the optimization of reactor design and operational parameters to enhance the dual goals of organic pollutant degradation and hydrogen production, particularly in the treatment of petrochemical wastewater laden with recalcitrant organic compounds. Microbial electrochemical technology, when integrated with exoelectrogenic bacteria, shows substantial promise in the effective degradation of complex organic pollutants. These bacteria play a vital role in facilitating electron transfer processes, which not only boosts pollutant degradation efficiency but also enhances hydrogen generation [49]. Reactor design innovations, particularly the optimization of mesophilic anaerobic digesters, are essential to address the high concentrations of organic pollutants in petrochemical wastewater. Acetoclastic methanogenesis, which converts acetate into methane, is a critical metabolic pathway in this context, driving efficient organic degradation and improving energy recovery from the system [50]. Furthermore, the development and optimization of anaerobic digestion models are pivotal in understanding microbial community dynamics, providing insights into how these communities influence both pollutant degradation and reactor performance [51]. The integration of bioelectrochemical systems enables MECs and MFCs to work synergistically within the same reactor, enhancing overall performance and energy recovery. By optimizing key operational parameters such as pH, temperature, and electrode materials, researchers can maximize both hydrogen yield and system efficiency. This approach not only improves the environmental quality of wastewater by removing recalcitrant organic pollutants but also facilitates the sustainable recovery and utilization of resources from petrochemical wastewater [52].

Cluster #5, centered on “Concentrate from EDR”, explores the integration of microbial electrochemical technologies, such as “microbial electrolysis cells” and “microbial fuel cells”, with a particular focus on optimizing proton exchange membranes to enhance both pollutant removal and hydrogen production. Key concepts such as “simultaneous removal”, “bacterial community”, “mixed culture”, “anaerobic wastewater treatment”, “sustainable power”, and “single chamber structure” are central to this cluster’s research. One of the primary objectives of this cluster is to optimize the application of proton exchange membranes in MECs, which play a pivotal role in ensuring efficient proton transport from the anode to the cathode. By preventing the cross-migration of electrons and other ions, these membranes help improve both the efficiency and selectivity of MECs, making them more effective for simultaneous pollutant removal and hydrogen generation [53]. Research highlights the critical impact of membrane material selection and modification on key properties such as conductivity, anti-fouling resistance, and durability, which in turn influence the overall performance of MECs [54]. In addition to membrane optimization, the role of bacterial communities and mixed cultures is emphasized in this cluster. Diverse microbial communities are essential for enhancing the degradation of organic matter and promoting efficient electron transfer, both of which are key for improving hydrogen production efficiency [10]. The concept of simultaneous removal is also central, where MECs are designed to remove not only organic pollutants but also nutrients like nitrogen and phosphorus, improving the overall performance of wastewater treatment systems [55]. The design of single-chamber structures is another significant aspect, as it simplifies the construction of MEC systems, reduces costs, and facilitates the optimization of electrode and membrane configurations. This design approach ultimately enhances both energy recovery and pollutant removal efficiency, making MECs more viable for sustainable wastewater treatment and power generation [56].

Cluster #6, centered on “Dark Fermentation”, encompasses key technologies and concepts such as “microbial electrolysis cells”, “dark fermentation”, “toxicity assessment”, “carbon nanotubes”, “electrochemical characterization”, “wastewater treatment”, “microbial fuel cells”, “bioelectrochemical systems”, “organic load”, and “cattle manure”. This cluster primarily focuses on utilizing MECs for the efficient removal of nitrogen pollutants from wastewater while generating hydrogen, thereby promoting sustainable energy production. Studies indicate that the dark fermentation process plays a pre-treatment role in MEC systems by converting complex organic pollutants into more degradable intermediate products, thereby enhancing nitrogen removal efficiency [57]. Additionally, carbon nanotubes, as advanced electrode materials, exhibit excellent conductivity and surface activity in electrochemical characterization, significantly enhancing electron transfer capabilities and improving the overall performance of MECs [58]. Toxicity assessments ensure the stability and reliability of MEC systems when treating high concentrations of nitrogen pollutants, preventing the formation of harmful byproducts [59]. The research also explores the impact of organic load and actual wastewater sources, such as cattle manure, on MEC systems, optimizing operational parameters to achieve efficient nitrogen removal and energy recovery [27]. The integrated application of bioelectrochemical systems enables MECs and MFCs to work synergistically, further enhancing the comprehensive efficacy of wastewater treatment and the depth of nitrogen removal [52].

Cluster #7, centered on “Photoelectrocatalysis”, encompasses key technologies and concepts such as “wastewater treatment”, “power generation”, “solar energy”, “advanced oxidation process”, “environmental remediation”, “MECs”, “light irradiation”, and “molybdenum deposition”. This cluster primarily focuses on optimizing the oxygen reduction reaction (ORR) within microbial electrolysis cells to enhance wastewater treatment efficiency and hydrogen generation performance while integrating solar energy technologies to achieve sustainable energy production. Research indicates that the oxygen reduction reaction is a crucial step in the cathodic processes of MECs, directly influencing the system’s electrical energy conversion efficiency and hydrogen yield [60]. By incorporating advanced techniques such as light irradiation and molybdenum deposition, researchers can significantly enhance the catalytic activity of ORR, reduce overpotential losses, and thereby improve the overall energy efficiency of the system [61]. Furthermore, the integration of solar energy technologies provides renewable energy input to MECs, further enhancing the system’s sustainability and energy self-sufficiency [62]. The application of advanced oxidation processes aids in the decomposition of complex organic pollutants, improving the thoroughness of wastewater treatment and environmental remediation outcomes [63].

Cluster #8, centered on “Microbial Electrolysis Cell”, encompasses key technologies and concepts such as “microbial electrolysis cells”, “wastewater treatment”, “electrode materials”, “bioenergy production”, “microbial community”, “hydrogen production”, “organic removal”, “electro-catalytic activity”, “high-strength wastewater”, and “hydrogen evolution reaction”. This cluster primarily focuses on the optimization and integration of BES for enhancing the efficiency of hydrogen production from wastewater while simultaneously achieving effective organic pollutant removal. Bioelectrochemical systems, particularly MECs, provide a promising platform for coupling wastewater treatment with renewable energy production. Electrode materials play a pivotal role in the performance of MECs, as they directly influence bacterial adhesion, electron transfer efficiency, and overall system stability. Carbon-based materials, such as carbon cloth, carbon felt, and graphite electrodes, are commonly employed for their high conductivity, stability, and biocompatibility, providing an ideal surface for the growth of electroactive microorganisms. Surface modifications, including doping with metal or non-metal elements, further enhance the electrocatalytic activity of these materials. Metallic materials like titanium and platinum, as well as metal oxides such as TiO₂ and MnO₂, are extensively used as cathode materials due to their superior conductivity and ability to facilitate the hydrogen evolution reaction (HER). However, their high cost limits large-scale applications, prompting research into cost-effective alternatives such as non-precious metal catalysts. Composite materials, which combine carbon substrates with metallic nanoparticles, have emerged as promising candidates, offering enhanced electron transfer rates and catalytic efficiency. Optimization strategies focusing on increasing surface area, reducing internal resistance, and improving surface properties are crucial for advancing electrode performance, thereby enabling more efficient and sustainable hydrogen production in MECs [64]. The integration of microbial communities in BES is also critical, as these microorganisms are responsible for organic pollutant degradation and the subsequent production of bioenergy. Mixed microbial communities are particularly advantageous for treating high-strength wastewater, which contains a complex mixture of organic compounds. These communities effectively degrade various pollutants while generating electrons that are ultimately utilized in hydrogen production at the cathode. The presence of diverse microbial species enhances system robustness and efficiency, allowing for the simultaneous treatment of pollutants and bioenergy recovery [65]. Furthermore, the cluster highlights the significance of optimizing operational parameters, such as current density, reactor configuration, and substrate concentration, to maximize the performance of BES in hydrogen production and wastewater treatment. The balance between effective organic removal and maximizing electrochemical output is a delicate aspect of system design, requiring careful control of microbial and electrochemical interactions [66].

Cluster #9, centered on “Syntrophic Interaction”, addresses the critical challenge of scaling up microbial electrochemical cells and microbial fuel cells from laboratory-scale experiments to large-scale systems for practical applications in wastewater treatment and bioenergy production. This cluster explores essential topics such as “wastewater treatment”, “microbial electrolysis cell”, “conduction-based mechanisms”, “extracellular electron transfer”, “microbial electrosynthesis”, “microbial electrocatalysis”, and “electrochemically active surface area”, all of which are crucial for successful upscaling and system optimization in bioelectrochemical technologies. A primary focus of this cluster is the optimization of key performance metrics and the identification of performance indicators (KPIs) that guide the design, scaling, and operation of large-scale MEC and MFC systems. Upscaling MECs presents significant challenges, particularly in maintaining efficient electron transfer, which is essential for both pollutant degradation and hydrogen production. To address this, conduction-based mechanisms, including the use of conductive materials in the electrode structure, are emphasized as essential for enhancing electron flow across the system, thereby improving system efficiency. The interaction between microbial electrocatalysis and extracellular electron transfer is a focal point in these upscaling studies [67]. By optimizing these interactions, it is possible to improve the bioelectrochemical performance of MECs at larger scales, where factors such as electrode surface area, conductivity, and microbial activity become increasingly important. Microbial electrosynthesis, which involves microorganisms converting CO₂ and other substrates into valuable products, is another key area explored in this cluster. This process extends the applications of MECs beyond energy production, enabling resource recovery and contributing to a more circular bioeconomy [68]. As MECs are scaled up, optimizing reactor configurations to enhance the electrochemically active surface area is critical for improving electron transfer rates. The integration of microbial electrocatalysis with advanced electrode materials facilitates these interactions, enabling microbial communities to more effectively interact with the electrodes, further boosting system performance. In addition to technical optimization, the upscaling process also requires addressing the economic feasibility and sustainability of large-scale systems. Research within this cluster includes techno-economic analyses of MECs and MFCs, focusing on the cost-effectiveness of scaling these systems for industrial applications, particularly in wastewater treatment and bioenergy production [69]. By refining both the technical and economic aspects of upscaling, this cluster aims to pave the way for the broader adoption of MEC and MFC technologies in real-world applications, driving sustainable solutions for wastewater management and renewable energy generation.

Cluster #10, centered on “Reuse”, explores the innovative combination of osmosis principles and bioelectrochemical systems to enhance both energy recovery and wastewater treatment. Key themes within this cluster include “energy recovery”, “bioelectrochemical systems”, “acetoclastic methanogenesis”, “mesophilic anaerobic digesters”, “anaerobic digestion models”, “organic loading rate”, and the integration of forward osmosis (FO) with microbial fuel cells. This approach leverages the unique benefits of both forward osmosis and BES to improve the efficiency and sustainability of wastewater treatment processes. Forward osmosis (FO) is a water treatment technique that uses an osmotic gradient to drive water through a semi-permeable membrane, which offers the potential for energy-efficient wastewater treatment and resource recovery. When integrated with BES, FO can significantly enhance energy recovery by utilizing osmotic pressure differences to concentrate wastewater. This concentration effect boosts the efficiency of microbial processes such as acetoclastic methanogenesis, a crucial pathway in anaerobic digestion that converts acetate into methane, thereby improving biogas production [70]. The research within this cluster also highlights the critical role of operational parameters, particularly the organic loading rate (OLR), in optimizing the performance of hybrid FO-BES systems. High organic loads can stimulate microbial growth and increase biogas production, but they must be carefully managed to prevent system overloads and ensure stable operation. Balancing OLR is essential to maximize system performance without compromising its efficiency or longevity [71]. Moreover, the integration of FO with BES can improve the overall efficiency of anaerobic digestion models by concentrating influent wastewater, which reduces the volume of waste sludge and, in turn, lowers operational costs. This process not only enhances the sustainability of the anaerobic digestion system but also promotes resource recovery by improving biogas yield. By refining the combination of FO and BES, this cluster aims to advance the efficiency of wastewater treatment systems, reduce energy consumption, and promote the sustainable reuse of water and resources in industrial applications.

Cluster #11, focused on “Reactor Design”, delves into the integration of microbial electrolysis cells with constructed wetland systems to enhance wastewater treatment and biohydrogen production. This cluster addresses key concepts such as “distillery wastewater”, “current density”, “reactor design”, “bifunctional electrochemistry”, “biohydrogen upgradation”, “electrochemical analyses”, and “microbial fuel cells”. The core objective is to combine the natural purification capabilities of constructed wetlands with the electrochemical efficiency of MECs to create a robust, sustainable system for wastewater treatment and energy recovery. Constructed wetlands are well-regarded for their cost-effectiveness and environmental benefits, particularly in the treatment of complex waste streams such as distillery wastewater, which is characterized by high concentrations of organic pollutants. The integration of MECs into these natural systems leverages the inherent microbial processes of wetlands—such as nutrient cycling and organic matter degradation—while boosting the production of biohydrogen at the cathode of the MEC. This synergy allows for the simultaneous treatment of wastewater and the generation of valuable bioenergy. By applying an external voltage, MECs enhance the electrochemical reduction of protons into hydrogen gas, a process further optimized through bifunctional electrochemistry, where the anode and cathode are engineered to simultaneously drive organic matter oxidation and hydrogen production. This dual functionality significantly enhances system efficiency by integrating pollutant removal with energy recovery [72,73]. Effective reactor design is a crucial aspect of optimizing the performance of these hybrid systems. The optimization of “current density” is key to maximizing biohydrogen production, as achieving high current densities supports the electrochemical processes required for hydrogen generation. This requires precise control of microbial electrochemical interactions to maintain stable and high-efficiency hydrogen production. In designing the reactor, factors such as electrode configuration, material selection, and hydraulic retention time must be meticulously considered to ensure optimal conditions for both pollutant degradation and biohydrogen upgradation. Electrochemical analyses serve an essential role in evaluating system performance by providing insights into important parameters such as electrode potentials, microbial community dynamics, and energy input requirements. Such analyses enable the identification of optimization opportunities that improve the overall efficiency and sustainability of the system [7].

Cluster #12, centered on “Circular Economy”, explores the integration of advanced and sustainable approaches within MEC systems to enhance wastewater treatment and hydrogen production. This cluster encompasses key topics such as “wastewater treatment”, “hydrogen production”, “NiFe layered double hydroxide”, “nickel foam”, “resource recovery”, “circular economy”, and “sewage sludge”. The primary focus of this research is to leverage eco-innovative materials and methodologies to improve the efficiency and sustainability of MECs, thereby contributing to both environmental remediation and renewable energy generation. One of the prominent aspects of this cluster is the use of advanced electrode materials, specifically NiFe-layered double hydroxides and nickel foam. NiFe-layered double hydroxides are recognized for their excellent catalytic properties, particularly in facilitating the hydrogen evolution reaction (HER) at the cathode. Their high electrochemical activity and stability make them ideal for enhancing hydrogen production rates in MEC systems. Nickel foam, with its high surface area and superior conductivity, serves as an effective scaffold for electrode construction, promoting efficient electron transfer and reducing overall system resistance. The combination of these materials significantly improves the performance of MECs, enabling higher hydrogen yields and more effective wastewater treatment [74]. Furthermore, Cluster #12 emphasizes the role of resource recovery and the circular economy in the context of MEC applications. By treating sewage sludge and other forms of wastewater, MECs not only mitigate environmental pollution but also convert waste into valuable resources such as hydrogen fuel. This aligns with the principles of the circular economy, which advocate for the continuous use and regeneration of resources, thereby minimizing waste and enhancing sustainability. The integration of MECs with eco-innovative technologies facilitates the dual objectives of pollution control and energy recovery, making the treatment processes more economically viable and environmentally friendly [75]. Additionally, the cluster highlights the importance of comprehensive resource recovery strategies, where MECs are employed to extract multiple forms of value from wastewater. This includes the simultaneous removal of organic pollutants and nutrients, the generation of bioenergy, and the recovery of valuable byproducts. By optimizing these processes, MECs can contribute to the sustainable management of wastewater resources, reducing the reliance on traditional treatment methods and decreasing the overall environmental footprint [76].

Cluster #13, centered on “Fermentative Hydrogen Production”, explores key aspects of bioelectrochemical systems, including “wastewater treatment”, “microbial fuel cells”, “bioelectrochemical systems”, “carbon dioxide reduction”, “based materials”, “microbial electrolysis cells”, “hydrogen production”, “life cycle assessment”, “electron transfer pathways”, and “power density”. This cluster investigates the complex interactions within microbial communities in BESs and their significant impact on optimizing both wastewater treatment and fermentative hydrogen production. A major focus of this cluster is understanding the dynamics of microbial consortia, which play a crucial role in facilitating electron transfer pathways that are vital for enhancing the power density of microbial electrolysis cells and microbial fuel cells. The efficiency of these systems relies heavily on the ability of microorganisms to transfer electrons effectively to the electrodes. The interaction between microbial communities and electrode materials is central to optimizing bioelectrochemical activity. The choice and modification of electrode materials (“based materials”) can significantly influence the stability and overall performance of these systems, making material selection a critical factor in advancing fermentative hydrogen production [33]. Additionally, this cluster explores how specific microbial communities can be engineered or selected to improve carbon dioxide reduction processes. By enhancing the microbial pathways involved in CO₂ reduction, these systems can not only generate hydrogen more efficiently but also contribute to reducing greenhouse gas emissions, thus supporting both sustainable energy production and climate change mitigation. The reduction of CO₂ plays a dual role in these systems, facilitating efficient hydrogen generation while also contributing to carbon sequestration. Another key aspect of the research within this cluster is the application of life cycle assessment (LCA) to evaluate the environmental and economic sustainability of bioelectrochemical systems. LCA provides comprehensive insights into the long-term viability of MECs and MFCs, helping to identify areas for optimization in terms of energy use, material inputs, and overall system efficiency. By considering the entire lifecycle of these systems, researchers can ensure that biohydrogen production is not only effective in meeting energy demands but also aligns with broader sustainability goals. Through the optimization of electron transfer mechanisms and the development of advanced materials, the performance of BESs can be significantly improved, leading to higher power densities and making these systems more competitive with conventional energy technologies. Ultimately, the combination of efficient hydrogen production and carbon dioxide reduction offers promising solutions for both renewable energy generation and climate change mitigation [77,78].

Cluster #14, centered on “Bioenergy”, delves into the critical aspects of integrating MFCs with MECs to enhance wastewater treatment and hydrogen production. This cluster encompasses key topics such as “wastewater treatment”, “microbial electrolysis cell”, “microbial fuel cells”, “electron transfer”, “key performance indicators”, “electrochemically-active surface area”, “microbial electrocatalysis”, and “microbial electrosynthesis”. The primary focus of this research is to optimize the synergistic interactions between MFCs and MECs to achieve efficient degradation of organic pollutants while simultaneously generating bioenergy and hydrogen. Central to this optimization is the enhancement of electron transfer processes, which are pivotal for maximizing the electrical output and hydrogen yield. By increasing the electrochemically active surface area of the electrodes, researchers aim to provide more active sites for microbial colonization and electron exchange, thereby improving the overall efficiency of the bioelectrochemical systems. KPIs play a crucial role in evaluating and benchmarking the performance of MFCs and MECs. Metrics such as power density, coulombic efficiency, and hydrogen production rate are essential for assessing the effectiveness of these systems in real-world applications [79]. Additionally, the role of microbial electrocatalysis is emphasized, where specific microbial communities are harnessed to facilitate more efficient electron transfer and catalytic reactions, enhancing both pollutant removal and energy recovery. Microbial electrosynthesis further extends the functionality of these systems by enabling the conversion of carbon dioxide and other substrates into valuable chemicals and fuels, thereby integrating resource recovery with energy production [80]. The integration of MFCs with MECs within BES offers a comprehensive approach to wastewater treatment, where MFCs primarily focus on generating electricity from organic matter, and MECs utilize this electricity to drive the production of hydrogen. This dual functionality not only improves the sustainability of wastewater treatment processes but also contributes to the circular economy by converting waste into renewable energy sources. Moreover, optimizing the electrochemically active surface area and enhancing microbial electrocatalysis is critical for scaling up these systems, making them viable for industrial applications [81].

Cluster #15, centered on “Refractory Pollutant”, focuses on the efficient removal of chemical oxygen demand from wastewater using bioelectrochemical systems, particularly microbial electrolysis cells and microbial fuel cells, while simultaneously producing hydrogen as a valuable byproduct. This cluster explores key technologies and concepts, including “wastewater treatment”, “microbial electrolysis cells”, “microbial fuel cells”, “Nafion membrane”, “bipolar membrane”, “hydrogen production”, “organic wet waste”, “hydrothermal liquefaction”, “process maturity”, and “oil palm waste”. One of the core focuses of this cluster is the integration of Nafion and bipolar membranes into MECs and MFCs to enhance the efficiency of COD removal and hydrogen production. These membranes play a crucial role by facilitating efficient proton exchange and minimizing ion crossover, which optimizes the overall performance of the system [82]. By improving the selectivity and efficiency of these processes, the use of Nafion and bipolar membranes significantly boosts the ability of MECs and MFCs to treat wastewater while generating hydrogen. Research within this cluster highlights the application of MECs and MFCs in treating various types of organic wet waste, including oil palm waste, which typically has high COD levels and complex organic compositions. The utilization of hydrothermal liquefaction as a pretreatment method is particularly important, as it helps break down recalcitrant organic compounds into simpler, more biodegradable forms, enhancing the efficiency of subsequent COD removal in the bioelectrochemical systems [47]. The concept of process maturity is also addressed in this cluster, emphasizing the need for advanced development and optimization of MEC and MFC technologies to ensure their readiness for large-scale, practical application. Achieving process maturity is essential for integrating these bioelectrochemical technologies into existing wastewater treatment infrastructures, allowing for reliable, efficient COD removal and sustainable hydrogen production [83]. Additionally, the research explores the synergistic relationship between COD removal and hydrogen production. The degradation of organic pollutants in MECs not only improves wastewater quality but also contributes to renewable energy generation, aligning with the principles of a circular economy. This dual functionality promotes resource recovery, minimizes environmental impact, and makes the process both sustainable and energy-positive [84]. Finally, optimizing key operational parameters—such as current density, reactor design, and membrane configuration—plays a critical role in maximizing the efficiency of COD removal and hydrogen yield. By fine-tuning these parameters, the performance of MECs and MFCs can be significantly enhanced, making these bioelectrochemical systems more viable for large-scale application in wastewater treatment and resource recovery [85].

Figure 7. A keyword cluster analysis of microbial electrolysis cell applications for hydrogen generation from acid mine drainage (2005–2024).

Figure 7. A keyword cluster analysis of microbial electrolysis cell applications for hydrogen generation from acid mine drainage (2005–2024).

3.7. Co-Citation Clustering Analysis of References

Previous research has laid a strong foundation for further investigations in the field. In general, later studies often cite earlier works that are either directly related or closely connected. When two articles are cited together within the same reference list, a co-citation relationship is established [86]. Co-citation analysis helps uncover the structure and interrelationships between research topics, as publications that are co-cited often share thematic similarities. By applying clustering methods to co-citation networks, references can be grouped into distinct clusters based on their citation patterns. Publications within the same cluster have a high degree of association, while those in different clusters are less closely related. In this study, a reference co-citation network was created and divided into 19 clusters, as shown in Figure 8. The average Q-value of 0.8296 and the average S-value of 0.935 indicate a high level of accuracy in the clustering analysis.

Table 7. Evaluation of document co-citation clusters and their characteristics.

Cluster ID	Cluster Name	Size	Silhouette	Mean (Year)	Top 3 Most Cited Publications
0	microbial fuel cell	94	0.969	2016	Escapa A (2016); Aiken DC (2019); Lu L (2016)
1	exoelectrogens	68	0.833	2019	Rousseau R (2020); Jayabalan T (2020); Logan BE (2019)
2	anaerobic wastewater treatment	50	0.939	2004	Oh SE (2005); Rabaey K (2005); Cheng S (2006)
3	photoelectrochemical cell	47	0.941	2012	Cusick RD (2011); Tartakovsky B (2009); Heidrich ES (2013)
4	costs estimation	37	0.923	2008	Call D (2008); Cusick RD (2010); Logan BE (2008)
5	petroleum wastewater	35	0.971	2019	Munoz-Cupa C (2021); Santoro C (2017); He L (2017)
6	microbial electrosynthesis	35	0.872	2010	Logan BE (2010); Rozendal RA (2009); Selembo PA (2010)
7	electron sink	33	0.919	2012	Logan BE (2012); Wang HM (2013); Chen SS (2012)
8	biological treatment	32	0.914	2020	Chen JW (2019); Banu JR (2020); Aydin MI (2021)
9	chemical production	29	0.929	2011	Logan BE (2009); Foley JM (2010); Borole AP (2011)
10	bioelectrochemical sensors	24	0.974	2008	Cheng SA (2011); Fan YZ (2012); Clauwaert P (2007)
11	animal wastewater	20	0.966	2005	Liu H (2005); Angenent LT (2004); Logan BE (2005)
12	water electrolysis	17	0.978	2021	Yang E (2021); Cui WJ (2021); Jadhav DA (2022)
13	ammonium salts	14	0.993	2014	Logan BE (2015); Kuntke P (2014); Dong Y (2015)
14	biofilm reactor	13	1.000	2006	Ciudad G (2007); Babu VL (2009); Atif AAY (2005)
15	microbial electrolyzers	13	0.983	2021	Katuri KP (2019); Arun J (2024); Xu ZC (2021)
16	syntrophic interaction	9	0.996	2017	Tang J (2018); Zakaria BS (2019); Ainsworth EV (2016)
17	metal recovery	8	0.994	2016	Yan WF (2019); Walters W (2016); Chen Y (2016)
18	acetate	8	0.993	2014	Feng YH (2015); Lu L (2012); Guo XS (2013)

provides detailed information about these clusters. From Figure 8 and Table 7, it is evident that there is significant variation in cluster sizes. The largest cluster (#0) contains 94 nodes, representing 16.04% of the total network nodes, while the smallest cluster (#18) includes only 1.37% of the nodes. The following clusters focus on the application of MECs for hydrogen production through the treatment of AMD: Cluster #0, titled “microbial fuel cell”, Cluster #1, “exoelectrogens”, Cluster #2, “anaerobic wastewater treatment”, Cluster #3, “photoelectrochemical cell”, Cluster #4, “costs estimation”, Cluster #5, “petroleum wastewater”, Cluster #6, “microbial electrosynthesis”, Cluster #7, “electron sink”, Cluster #8, “biological treatment”, Cluster #9, “chemical production”, Cluster #10, “bioelectrochemical sensors”, Cluster #11, “animal wastewater”, Cluster #12, “water electrolysis”, Cluster #13, “ammonium salts”, Cluster #14, “biofilm reactor”, Cluster #15, “microbial electrolyzers”, Cluster #16, “syntrophic interaction”, Cluster #17, “metal recovery”, and Cluster #18, “acetate”. Among these, Cluster #15 and Cluster #8 represent emerging research areas, while Cluster #11 and Cluster #14 are linked to earlier developments in the field of MECs for AMD treatment and hydrogen production.

Clusters #0, #15, #12, #9, and #10 focus on the application of MEC technology in hydrogen production. Cluster #0, “Microbial Fuel Cells”, serves as the foundation of MEC technology, exploring its core role in hydrogen generation. Escapa A et al. (2016) reviewed MECs, comparing them to MFCs and highlighting MECs’ potential for hydrogen production from wastewater. They discuss challenges such as material costs, scalability, and hydrogen management based on lab-to-pilot-scale studies. The paper emphasizes the need for optimization and integration with energy systems to improve commercialization prospects [87]. Cluster #15, “Microbial Electrolyzers”, specifically investigates the application of microbial electrolyzers in hydrogen production, with a particular emphasis on their unique advantages in the treatment of AMD. Katuri KP et al. (2019) reviewed recent advancements in MECs, emphasizing their integration with other wastewater treatment processes. While MECs convert organics into renewable energy, they are not standalone solutions for urban wastewater treatment. The paper highlights integration opportunities with technologies like membrane filtration, anaerobic ammonium oxidation, and anaerobic digestion. It also discusses challenges and new possibilities for enhancing the efficiency and applicability of MECs in both mainstream and side-stream urban wastewater treatment [88]. Cluster #12, “Water Electrolysis”, examines the potential of combining water electrolysis with MEC technology to enhance hydrogen production efficiency, aiming to optimize the electrolysis process and improve hydrogen yield. Yang E et al. (2021) reviewed MECs for hydrogen production, highlighting their lower energy requirements compared to water electrolysis. They address sustainability challenges due to external power needs and propose integrating MECs with carbon-neutral technologies like solar, microbial, and osmotic power to achieve self-sustainability. The review discusses strategies to overcome thermodynamic barriers and enhance MEC efficiency for practical hydrogen production [89]. Cluster #9, “Chemical Production”, explores the potential applications of hydrogen generated by MEC technology in chemical production, thus expanding its industrial utility, particularly in energy conversion and storage. Logan BE (2009) reviewed the recent progress in MECs, focusing on microorganisms capable of generating electrical currents. The article discusses the high power densities achieved by enriched anodic biofilms, reaching up to 6.9 W/m², approaching theoretical limits. It also explores the mechanisms of exocellular electron transfer, emphasizing cellular respiration and potential cell–cell communication, which are critical for understanding bacterial versatility in the electrical current generation and their potential for chemical production [90]. Cluster #10, “Bioelectrochemical Sensors”, investigates the use of bioelectrochemical sensors within MEC systems, enabling real-time monitoring of electrochemical reactions. These sensors optimize the hydrogen production process, enhancing the overall efficiency of the MEC system and further promoting hydrogen generation. Cheng SA et al. (2011) investigated factors critical for scaling up MECs and their implications for bioelectrochemical sensors. The study highlights that cathode-specific surface area significantly influences power density, with cathode size and solution conductivity being key factors, whereas substrate concentration impacts the anode. These findings underscore the importance of optimizing cathode design for high power densities, which is essential for enhancing MEC-based sensor performance [91].

Clusters #1, #6, #2, #16, and #8 focus on the application of microbial and bioelectrochemical processes in hydrogen production. Cluster #1, “Exoelectrogens”, examines the critical role of exoelectrogenic microbes in MEC systems, as these microbes directly facilitate hydrogen generation and enhance hydrogen yield. Rousseau R (2020) reviewed the potential and challenges of MECs for hydrogen production, focusing on the role of exoelectrogens. The paper highlights MECs’ lower energy needs compared to water electrolysis and discusses pilot-scale issues like electrode kinetics and electrolyte conductivity. Recommendations include improving current density and hydrogen evolution at neutral pH, with a focus on optimizing exoelectrogenic activity for better efficiency [92]. Cluster #6, “Microbial Electrosynthesis”, explores the microbial electrosynthesis process, where electrical energy is converted into hydrogen and other chemicals, with significant potential in wastewater and AMD treatment. Logan BE et al. (2010) reviewed recent advances in MEC technologies, highlighting power densities exceeding 1 kW/m³ and 6.9 W/m² under optimal conditions. The paper discusses the challenges of scaling MECs for practical bioenergy production, focusing on new electrode materials, the role of membranes and separators, and pilot-scale test results. It also explores the potential of MECs for microbial electrosynthesis, emphasizing their future application in renewable energy production and other fields [93]. Cluster #2, “Anaerobic Wastewater Treatment”, investigates the use of anaerobic microorganisms in wastewater treatment, particularly in creating conditions favorable for hydrogen production, with notable effectiveness in AMD treatment. Oh SE et al. (2005) demonstrated the potential of MECs for hydrogen production coupled with wastewater treatment. They show that high-sugar, high-COD wastewater, such as food processing effluents, can achieve significant hydrogen yields, with Cereal wastewater yielding the highest. The study also highlights the effectiveness of MFCs in anaerobic wastewater treatment, achieving up to 95% COD removal while generating electricity. The findings suggest that MECs can integrate hydrogen production with bioenergy generation and efficient wastewater treatment, offering a sustainable solution for anaerobic wastewater management [94]. Cluster #16, “Syntrophic Interactions”, focuses on the synergistic interactions between microorganisms, optimizing hydrogen production, particularly in complex AMD treatments, where microbial complementarity enhances hydrogen yield. Tang J et al. (2018) explored the impact of nanoparticles (NPs) on microbial aggregates, emphasizing the role of syntrophic interactions in reducing NP toxicity. Dense aggregate structures shield interior microorganisms, while stabilized microbial ecosystems enhance adaptation to prolonged NP exposure. The study highlights opportunities to leverage these interactions in wastewater treatment, such as designing NPs that are selectively toxic to pathogens while sparing beneficial microbes, thereby improving treatment efficiency and ecological balance [95]. Cluster #8, “Biological Treatment”, studies biological wastewater treatment technologies, especially for AMD, where biological processes contribute to hydrogen production, thereby providing effective support for MEC technologies. Chen JW (2019) performed an environmental life cycle assessment of a pilot-scale MEC for hydrogen production from wastewater. The study shows that optimizing parameters like cathodic gas recovery and hydrogen production rate reduces emissions. While MEC technology still needs improvement, it shows promise as a sustainable solution for hydrogen production and biological wastewater treatment [96].

Clusters #5, #11, #17, #7, and #14 explore the application of MEC technology in wastewater and effluent treatment, particularly in the context of hydrogen production and pollutant removal. Cluster #5, “Petroleum Wastewater”, investigates the similarities in treatment methods between petroleum wastewater and AMD, highlighting the significant potential of MEC technology for hydrogen production and wastewater purification, especially in petroleum wastewater treatment. Munoz-Cupa C (2021) reviewed the use of MECs for wastewater treatment, focusing on their ability to remove COD and generate electricity. The study discusses the impact of various operating conditions on COD removal and power production, highlighting the advantages and limitations of MECs for different wastewater types, including petroleum wastewater. It also addresses technical barriers and the economic feasibility of MECs, suggesting they could be a promising solution for efficient and sustainable petroleum wastewater treatment [97]. Cluster #11, “Animal Wastewater”, focuses on the treatment of animal wastewater, which shares similarities with AMD treatment; MEC technology can similarly be applied for hydrogen generation and effective pollutant removal. Liu H (2005) investigated electricity generation from fermentation products like acetate and butyrate in MECs, highlighting the higher power output from acetate (506 mW/m²) compared to butyrate (305 mW/m²). The study shows that acetate is a preferred substrate for MECs, with higher current densities and power production. The results also indicate significant electron and energy losses, emphasizing the need for improvements in energy recovery. These findings suggest the potential for MECs to generate electricity from organic waste, including animal wastewater, though efficiency improvements are needed for practical applications [98]. Cluster #17, “Metal Recovery”, examines how MEC technology can be used to simultaneously treat AMD and produce hydrogen during metal recovery processes, thereby achieving dual benefits in wastewater treatment and energy production. Yan WF (2019) reviewed BESs for antibiotic removal from wastewater, discussing the effects of parameters like electrochemical properties, antibiotic concentration, and temperature on system performance. The paper highlights the role of BESs in degrading antibiotic pollutants and their potential to address antibiotic resistance. It also explores the microbial mechanisms involved, degradation pathways, and the impact of BESs on antibiotic-resistance genes. Although the focus is on antibiotic removal, the principles of BESs could also be relevant for metal recovery and other waste treatment applications, offering a sustainable approach to environmental contamination [99]. Cluster #7, “Electron Sink”, explores the role of electron sinks in MEC systems, a crucial concept for hydrogen production and pollutant removal, particularly when treating AMD containing heavy metals, where the effective utilization of electron sinks can enhance reaction efficiency. Logan BE (2012) reviewed the use of exoelectrogenic microorganisms in microbial electrochemical technologies, like microbial fuel cells, for producing biofuels, hydrogen, and other chemicals. The paper discusses waste biomass as an electron source and highlights challenges such as efficiency, scalability, and system reliability. It emphasizes the role of electron sinks in optimizing microbial energy systems for sustainable applications [100]. Cluster #14, “Biofilm Reactor”, studies the application of biofilm reactors in MEC systems, which stabilize microbial communities and increase hydrogen production, making them particularly suitable for AMD and other wastewater treatments. Ciudad G (2007) investigated the use of sequencing batch and continuous operation modes in a biofilm rotating disk reactor for enhanced partial nitrification. The study examines different pH control strategies, with supervisory control at pH 7.5–8.6 proving most effective. This approach resulted in stable nitrite accumulation (>80%) and enriched ammonia-oxidizing bacteria (AOB) populations (>95%), even under oxygen-limiting conditions. The findings suggest that appropriate pH control can significantly enhance partial nitrification in biofilm reactors, optimizing performance for wastewater treatment [101].

Clusters #4, #3, #13, and #18 focus on the economics and optimization strategies of MEC technology in hydrogen production and practical applications. Cluster #4, “Costs Estimation”, conducts a cost–benefit analysis of MEC technology to evaluate its economic feasibility in hydrogen production and AMD treatment, helping to determine the commercialization potential of the technology. Call D (2008) investigated membrane-less MECs for hydrogen production, showing high recovery and production rates without the need for a membrane. The study highlights the cost-saving potential of this design, achieving efficient hydrogen production with a graphite fiber brush anode and close electrode spacing, offering a simpler and more affordable alternative for bioelectrochemical systems [102]. Cluster #3, “Photoelectrochemical Cell”, explores the integration of photoelectrochemical cells with MEC technology, utilizing solar energy to promote hydrogen generation, particularly in wastewater treatment, thereby improving energy efficiency and reducing costs. Cusick RD (2011) discussed a pilot-scale MEC for winery wastewater treatment, highlighting key factors like acetate amendments, temperature, and pH control to enhance biofilm enrichment and current generation. While the reactor achieved consistent SCOD removal (62%) and methane production, hydrogen recovery was limited. The study emphasizes the importance of initial inoculation, biofilm enrichment, and optimized operating conditions for scaling up MEC systems [103]. Cluster #13, “Ammonium Salts”, investigates technologies for treating ammonium salts, revealing that such treatments can enhance the hydrogen production efficiency of MEC systems and play a significant role in optimizing AMD treatment processes. Logan BE (2015) discussed the development of microbial electrochemical technologies for various applications, including wastewater treatment and biofuel production. The study highlights that while scale-up of MECs remains challenging, key factors such as electrode configuration and fuel type (wastewater vs. pure chemicals) are more influential on power production than system size. The research also addresses the limitations of high membrane costs and emphasizes the need for careful design in scaling up systems to maintain performance [104]. Cluster #18, “Acetate”, studies the application of acetate as an electron donor in MECs, where acetate effectively promotes hydrogen generation, especially in the treatment of organic wastewater, further enhancing the economic and practical benefits of MEC technology. Feng YH (2015) investigated the use of Fe/graphite electrodes in anaerobic digesters to enhance hydrogen production from sludge. The study demonstrates that anodic oxidation of sludge facilitated by exoelectrogens increased electron availability for cathodic hydrogen production, significantly boosting short-chain fatty acid generation (3.5 times higher) and hydrogen yield (90.6 mL gVSS⁻¹). Elevated pH inhibited methanogenesis, leading to reduced methane production. The findings highlight the role of electrode-assisted processes in improving acetate and hydrogen recovery from sludge under controlled voltage conditions [105].

Figure 8. A co-citation cluster analysis of the literature on microbial electrolysis cells for hydrogen generation from acid mine drainage (2005–2024).

Figure 8. A co-citation cluster analysis of the literature on microbial electrolysis cells for hydrogen generation from acid mine drainage (2005–2024).

In the field of MECs for hydrogen generation from AMD, nodes highlighted with a purple outer ring indicate publications that are connected through co-citation links with several other works. These nodes act as central hubs during specific periods, representing key trends and directions in research. Conversely, nodes with a red outer ring represent highly cited foundational works that play a critical role in advancing the understanding of MEC-based hydrogen production from AMD. These influential papers hold significant value and are likely to garner substantial attention from researchers in the field. The timeline view (Figure 9) offers a succinct overview of the evolving research trends, providing guidance for researchers exploring this topic.

For example, when searching for “exoelectrogens”, studies such as the one by Bajracharya S et al. (2016) demonstrate a representative example. This study focused on the role of exoelectrogens in BESs, which enable energy generation and hydrogen production. Exoelectrogens transfer electrons to electrodes, facilitating electricity production in MFCs and MECs. The study highlighted their potential to improve BES performance for wastewater treatment, nutrient recovery, and bioenergy generation. However, challenges remain in optimizing exoelectrogenic biofilms and electrode materials to enhance efficiency [106]. Recent research in this domain has concentrated on the role of exoelectrogens in MECs for biohydrogen production, as highlighted by Bora et al. (2022). These microbes facilitate electron transfer to electrodes, enabling efficient hydrogen generation. Studies emphasize optimizing reactor design, microbial communities, and electrode materials to enhance MEC performance. Challenges in scaling up and improving exoelectrogen activity remain key areas of focus for advancing this technology [107]. The year 2020 marked a significant milestone in the development of MEC technology for hydrogen production, particularly highlighting the crucial role of exoelectrogens, as discussed by Lim SS et al. (2020). This study emphasized the vital contribution of exoelectrogens in the bioanode, which efficiently utilized acetate and played a key role in energy recovery, reducing the dependency on external power. The bioanode’s activity was essential for maintaining the functionality of the biocathode, resulting in an overall energy efficiency of 29.4%, with substrate oxidation accounting for nearly one-third of the total energy recovery [108,109].

Figure 9. Timeline representation of 19 co-citation document clusters (2005–2024, analyzed in annual intervals).

Figure 9. Timeline representation of 19 co-citation document clusters (2005–2024, analyzed in annual intervals).

3.8. Recent Advancements and Emerging Trends in MECs for Hydrogen Generation from AMD

This section provides a comprehensive analysis of the key literature published over the past two decades, as well as the central research themes in the field of MECs for hydrogen production by treating acid mine drainage. It examines the primary research areas and development trends within this domain, highlighting the progress and innovations in utilizing MEC technology to simultaneously address contamination from acid mine drainage and facilitate hydrogen generation.

3.8.1. Application of MECs for Hydrogen Generation by Treating AMD

Microbial electrolysis cells are an advanced form of bioelectrochemical systems that employ electroactive microorganisms to facilitate the conversion of pollutants into valuable products under controlled electrochemical conditions. By leveraging these microbial communities, MECs can treat AMD—a wastewater stream rich in heavy metals, sulfates, and other contaminants—while concurrently producing hydrogen gas. Hydrogen, in this context, serves as a high-value energy vector, aligning well with sustainable energy goals and offering a cleaner alternative to conventional fossil fuels. As the process converts otherwise harmful pollutants into usable hydrogen, MECs present a promising strategy for enhancing resource utilization and mitigating the environmental burdens posed by AMD.

• Pollutant Transformation and Resource Valorization: In the treatment of AMD, microbial electrolysis cells primarily function by reducing and transforming various contaminants into less harmful or more valuable forms. Electroactive microorganisms are central to this process, as they oxidize organic or inorganic substrates in the anodic chamber, releasing electrons that migrate through an external circuit toward the cathode. At the cathode, these electrons participate in electrochemical reduction reactions, facilitating the formation of hydrogen gas from protons. Meanwhile, the microbial community’s metabolic activity can precipitate or convert heavy metals such as iron, copper, or zinc into more stable compounds or elemental forms. This not only diminishes the overall toxicity of the effluent but also offers the opportunity to recover metals as potentially marketable byproducts. In some instances, improved electron flow within MECs can enhance sulfate reduction, lowering the sulfate content of AMD and further improving its quality. By integrating pollutant transformation with hydrogen production, MECs capitalize on both environmental remediation and resource recovery, making the technology economically and ecologically attractive.
• Hydrogen Generation as a Clean Energy Output: A defining advantage of MECs over traditional biological or chemical treatment methods lies in their ability to generate hydrogen gas directly from AMD treatment processes. The hydrogen produced can serve as a versatile, clean-burning fuel, providing a renewable energy vector for regions lacking conventional power infrastructure. Hydrogen emerging from MEC operations holds promise for downstream applications, including direct use as a feedstock in industrial processes, in situ energy storage solutions, or as a clean fuel for transportation. By coupling environmental remediation with the on-site generation of hydrogen, MECs not only address local wastewater challenges but also contribute to broader sustainable energy objectives.
• Environmentally Sustainable Operation: Microbial electrolysis cells, when treating AMD, typically operate under moderate conditions without the need for harsh chemicals or extreme temperatures. In contrast to conventional remediation methods—such as chemical precipitation or high-energy membrane processes—MECs rely on microbial metabolic pathways and electrochemical gradients to drive pollutant transformation and hydrogen evolution. The minimal reliance on exogenous reagents reduces the risk of secondary pollution and diminishes both operational costs and environmental liabilities. Moreover, the mild reaction conditions limit the formation of hazardous byproducts, often resulting in cleaner effluent streams than those achievable through traditional remediation techniques. This intrinsically biological and electrochemical approach aligns with the principles of green chemistry, emphasizing reduced resource consumption, lower energy demands, and minimized ecological impact.
• Towards Scalable and Adaptable Solutions: As research progresses, MECs for hydrogen production from AMD continue to evolve, with ongoing efforts devoted to improving reactor configurations, electrode materials, and system-level integration. Strategies to enhance the activity of electroactive microorganisms, optimize electrode interfaces, and refine operational parameters are being explored to boost hydrogen production rates and contaminant removal efficiencies. Although challenges persist in scaling up laboratory-scale configurations to full-scale commercial operations, the multifaceted benefits—ranging from effective AMD treatment and metal recovery to sustainable hydrogen generation—underscore the potential of MECs as a transformative technology. By integrating MECs with ancillary treatment units or renewable energy systems, the approach can be adapted to various industrial or geographical contexts, facilitating the widespread adoption of this innovative platform for addressing AMD-related environmental issues while advancing the global transition towards cleaner energy sources.

3.8.2. Recent Research Advances in MECs for H₂ Generation by Treating AMD

In recent years, as MEC technology has matured, substantial advances have been realized in employing MECs for hydrogen production through the treatment of AMD. These developments have not only enhanced hydrogen yields and improved contaminant removal efficiencies but have also offered novel, sustainable pathways for transforming AMD from a severe environmental liability into a source of valuable resources. By integrating electroactive microbial consortia, advanced electrode materials, and optimized reactor configurations, current research efforts are driving forward the performance, scalability, and economic viability of MEC-based AMD treatment systems. The development trends in MEC technology for AMD treatment are driven by several key technological factors. The unique ability of MECs to simultaneously achieve wastewater treatment and resource recovery has established its core competitiveness in the environmental and energy sectors. The cathodic electrochemical reduction of metal ions into their elemental forms, coupled with the anodic degradation of organic pollutants to generate renewable hydrogen, underpins its dual functionality. Advances in material science have further propelled MEC research with the introduction of highly conductive electrode materials, such as nanocarbon materials and metal coatings, significantly enhancing electron transfer efficiency and electrocatalytic activity. Additionally, corrosion-resistant membranes have improved the stability of MECs in low-pH environments, making them more suitable for AMD treatment. The progress of MEC technology is also closely tied to multidisciplinary collaborations, encompassing biotechnology, electrochemistry, and environmental engineering. For instance, the cultivation of acid-tolerant microorganisms, optimization of electrode designs to enhance microbe–electrode interactions, and advancements in reactor configurations have all contributed to the practical application of MECs in complex wastewater treatment scenarios. Furthermore, the increasing global focus on renewable energy and environmental sustainability has provided policy support and industrial demand, which has expanded the scope and depth of academic research while facilitating the transition of MEC technology from laboratory studies to commercialization. These factors collectively explain the observed research trends and hotspots in this field.

• Advancement of High-Performance Electrode Materials: Electrode materials play a pivotal role in MEC systems for AMD treatment, as they directly influence the rate of electron transfer, the kinetics of hydrogen evolution, and the extent of contaminant removal. Recent research has focused on optimizing both anode and cathode materials to enhance the biocatalytic and electrochemical processes. In the case of anodes, conventional carbon-based substrates have been modified with bioinspired architectures, nanoscale carbon materials, and conductive polymers to increase biocompatibility, electron transfer efficiency, and microbial colonization. Such modifications boost the metabolic rates of electroactive microorganisms that oxidize reduced species within AMD, thus liberating more electrons for downstream hydrogen production. Similarly, cathode materials have evolved from relying heavily on precious metal catalysts to employing robust, low-cost, non-precious metal and metal oxide catalysts. For instance, cobalt- and iron-based catalysts, as well as doped carbon nanostructures, have demonstrated exceptional hydrogen evolution reaction (HER) activity, reducing the need for expensive platinum-based materials. Some approaches incorporate metal–organic frameworks or layered double hydroxides to further improve active site availability and electron transfer kinetics. By optimizing the electrode microstructure and surface chemistry, these novel electrodes can withstand highly acidic conditions, facilitating both stable hydrogen generation and the removal or recovery of dissolved metals within AMD.
• Innovative Reactor Designs and System Integration: Beyond electrode optimization, recent studies have pursued new reactor configurations and integrated treatment systems to maximize contaminant removal, hydrogen yields, and overall energy recovery. Innovative reactor designs include modular, stacked MEC configurations that increase volumetric productivity and adaptability to varying AMD flow rates and compositions. Flow-through reactors, incorporating three-dimensional electrodes, have shown promise in improving mass transfer and ensuring that the acidic influent thoroughly contacts the biocatalytic surfaces, thereby enhancing reaction efficiencies. Additionally, integration with complementary treatment technologies can further refine AMD quality and support robust hydrogen production. For example, coupling MECs with membrane-based units or precipitative reactors can pre-concentrate or selectively remove specific contaminants, thereby optimizing feed water conditions for the MEC. Similarly, integration with anaerobic digestion or sulfate-reducing bioreactors can adjust the redox environment, promoting microbial activities that improve both contaminant remediation and hydrogen evolution. These hybrid systems highlight a move towards holistic resource recovery platforms, wherein MECs serve not merely as standalone treatment units but as integral components in a larger network of sustainable wastewater management operations.
• Tailoring Electroactive Microbial Communities: The microbial consortia catalyzing oxidation and reduction processes within MECs are central to their efficiency and stability. Recent research has emphasized the directed manipulation of microbial communities to better handle AMD’s acidic, metal-rich conditions. Selective enrichment strategies target electroactive microorganisms adept at metal tolerance, proton reduction, and intermediate metabolite utilization. By providing optimal pH control, nutrient regimes, and redox conditions, engineers and microbiologists can sculpt communities enriched in microorganisms such as specialized Geobacter, Desulfovibrio, or Acidithiobacillus strains. These organisms either directly transfer electrons to electrodes or participate in syntrophic interactions that generate electron donors for hydrogen production. Beyond selective enrichment, genetic and metabolic engineering approaches are under investigation to enhance microbial electron transfer chains, metabolic resilience, and catalytic capabilities. The ultimate objective is to construct robust biofilms that thrive in the harsh AMD environment, efficiently transform contaminants, and maximize hydrogen evolution, thereby leveraging microbial metabolism to drive key electrochemical reactions at minimal energetic cost.
• Integrated Contaminant Mitigation and Resource Recovery: A key advantage of using MECs for hydrogen generation from AMD lies in the synergistic treatment of complex, multi-contaminant matrices. AMD often contains high levels of sulfate, heavy metals, and other inorganic or organic species. Emerging research addresses the simultaneous reduction of sulfate to hydrogen sulfide, precipitation of metals as insoluble sulfides or elemental forms, and production of hydrogen gas, all occurring in a single, integrated platform. MEC-driven processes can thus stabilize metals, reduce sulfate concentrations, and produce valuable hydrogen fuel, minimizing the formation of secondary pollutants and mitigating the environmental footprint of the treatment process. Moreover, effective strategies can harness AMD as a substrate that, under engineered conditions, leads to the recovery of metals as potentially marketable commodities. Such valorization not only decreases treatment costs and environmental risks but also enhances the economic viability of using MECs at scale. In some pilot demonstrations, coupling microbial electrolysis with pre- or post-treatment steps, such as selective ion exchange or advanced oxidation processes, refines the quality of treated effluent and concentrates valuable resources, further expanding the range of potential industrial and environmental applications.
• Towards Scalable and Sustainable Deployment: While laboratory and pilot-scale experiments have demonstrated the technical feasibility of MECs for H₂ generation from AMD, ongoing research focuses on scaling up these systems, improving their energy efficiency, and optimizing their long-term operational stability. Investigations into electrode longevity, fouling mitigation strategies, and closed-loop operational control algorithms are guiding progress toward robust and cost-effective full-scale implementations. Additionally, techno-economic evaluations and life cycle assessments are helping to identify barriers to commercialization, guiding the development of lower-cost materials, simplified reactor designs, and more resilient microbial communities. As knowledge accumulates, MECs are poised to transition from proof-of-concept experiments to widely applied technologies that alleviate the environmental burden of AMD while concurrently generating a valuable, renewable energy carrier.

3.8.3. Challenges and Future Prospects of MECells for H₂ Generation by Treating AMD

Despite the noteworthy advancements in applying MECs for hydrogen production from AMD, substantial challenges must be addressed before the technology can realize its full industrial potential. Overcoming these barriers requires progress in several key areas, including the enhancement of hydrogen yields, scaling to industrial levels, ensuring economic feasibility, maintaining long-term operational stability, and fostering a supportive policy environment. The following sections delineate the main challenges and potential future directions for MECs in this field.

• Enhancement of Hydrogen Yields and Efficiency: Although MECs have demonstrated the capability to convert AMD contaminants into valuable hydrogen, the current yields and conversion efficiencies often fall short of the demands required for large-scale implementation. Improving hydrogen production rates, electron recovery, and substrate-to-product conversion efficiencies remains a central research objective. One promising approach is the development of advanced electrode materials and catalysts, particularly those capable of withstanding highly acidic conditions while maintaining robust catalytic activity for hydrogen evolution. For instance, carbon-based supports functionalized with transition metals or doped with heteroatoms can offer enhanced durability, conductivity, and biocompatibility. Simultaneously, tailoring microbial consortia to include electroactive species with high electron transfer capabilities, stable activity at low pH, and resistance to toxic metal ions will help improve system performance. Additionally, optimizing reactor configurations—such as adjusting electrode spacing, flow regimes, or reactor orientation—can facilitate better mass transfer and reduce ohmic losses, thereby increasing hydrogen yields and overall energy efficiency.
• Scale-up and Integration with Industrial Operations: Translating laboratory-scale MEC results to industrial-scale AMD treatment poses significant engineering and operational challenges. At larger scales, controlling mass transfer limitations, mitigating electrode passivation, and maintaining consistent microbial community structures become more complex. Moreover, adapting MEC technology to fit into existing mining infrastructure necessitates modular and scalable reactor designs capable of processing large and variable wastewater streams. Efforts should focus on pilot-scale demonstrations that collect valuable operational data, inform robust design criteria, and offer insights into system resilience under fluctuating AMD compositions. Developing cost-effective modular units that can be assembled in a stepwise manner will help facilitate a gradual integration of MECs into industrial practices, enabling seamless transitions from small pilot systems to full-scale operations. Such adaptability will prove crucial in ensuring that MECs can effectively integrate with established AMD management strategies, such as lime neutralization or passive treatment wetlands, and complement them rather than compete for resources.
• Economic Feasibility and Resource Valorization: While MEC technology aligns well with sustainability goals, its economic viability is not yet assured. High costs associated with specialty electrodes, catalysts, and reactor components can deter initial investments, particularly in sectors sensitive to capital and operational expenditures. Improving cost-effectiveness requires the pursuit of low-cost, abundant electrode materials, potentially derived from industrial byproducts, biomass feedstocks, or recycled resources. Innovations in reactor design that reduce complexity, minimize maintenance, and extend operational lifetimes will also contribute to lowering long-term costs. Beyond cost reduction, the valorization of recovered resources, such as metals extracted from AMD or purified hydrogen, can enhance the economic attractiveness of MEC systems. If MECs can reliably convert AMD’s contaminant load into marketable commodities—be it hydrogen fuel, elemental metals, or metal-rich concentrates suitable for further processing—this added value will offset operational expenses and improve the overall economic balance.
• Long-Term Stability and Durability: The sustained performance of MECs under variable and harsh conditions is essential for real-world deployment. Over time, reactor components may experience degradation due to acidic environments, fluctuating contaminant loads, and microbial shifts. Corrosion of electrode materials, fouling due to precipitates or biofilm overgrowth, and a decline in microbial activity under stress conditions can all undermine long-term stability. To ensure durability, research must focus on developing electrodes and membranes with corrosion resistance, anti-fouling properties, and longevity in low pH and metal-rich conditions. Moreover, robust operational strategies—such as periodic maintenance protocols, in situ cleaning methods, and microbial community management—will be needed to sustain stable performance. Understanding and predicting community dynamics can guide interventions to preserve electroactive populations, enhance microbial resilience, and maintain consistent hydrogen production over extended operational periods.
• Regulatory Frameworks and Stakeholder Engagement: In addition to technical hurdles, the future success of MECs for AMD treatment and hydrogen generation depends on supportive policies, industry standards, and social acceptance. Currently, the lack of clear regulations, codes of practice, or recognized performance benchmarks for MEC-based processes hampers widespread adoption. Policymakers, industry consortia, and researchers must collaborate to develop guidelines that ensure safe, effective, and environmentally responsible operations. Financial incentives, subsidies, or tax breaks could spur early demonstrations and encourage commercial-scale deployments, particularly in regions where AMD pollution is a pressing concern. Simultaneously, raising public awareness and engaging local communities are critical for gaining social acceptance. By transparently communicating the environmental and economic benefits of MEC technology, alongside its potential to reduce reliance on traditional remediation strategies and non-renewable energy sources, stakeholders can foster a positive environment that promotes investment and long-term growth in the sector.

4. Conclusions

This study employed CiteSpace and Hiscite to thoroughly examine 213 publications indexed in the WOSCC from 2005 to 2024 concerning the application of MECs for hydrogen production by treating AMD. The analyses encompassed publication characteristics, journal performance, international and institutional collaborations, subject category co-occurrence, keyword clustering, and reference co-citation patterns. These findings collectively provide a valuable framework for understanding the current research landscape and future directions of MECs in AMD treatment and hydrogen generation.

First, the results demonstrate that since 2005, annual publications on MECs for AMD-derived hydrogen production have consistently increased, with a pronounced surge in output after 2019. By 1 December 2024, annual publication counts reached 24 articles, suggesting sustained and rapid growth in research activity. This trend reflects a global scholarly focus on leveraging MEC technology as a promising tool for both AMD remediation and renewable hydrogen production.

Second, the journal analysis identifies several high-impact sources—such as INTERNATIONAL JOURNAL OF HYDROGEN ENERGY, BIORESOURCE TECHNOLOGY, WATER RESEARCH, JOURNAL OF HAZARDOUS MATERIALS, and JOURNAL OF CLEANER PRODUCTION—that have significantly influenced this field. These journals not only publish substantial numbers of relevant studies but also exhibit strong performance metrics (e.g., impact factors, H-indices), underscoring their pivotal role in disseminating cutting-edge findings and driving advancements in MEC applications for AMD treatment.

Third, an examination of national and institutional collaborations indicates that countries like China, India, the United States, Vietnam, and Saudi Arabia, along with prominent research institutions such as the Council of Scientific & Industrial Research (CSIR)—India, Harbin Institute of Technology, Pennsylvania State University—University Park, and the Chinese Academy of Sciences, have contributed extensively to this domain. Their close cooperative networks have accelerated knowledge exchange, technological innovation, and capacity-building in the development of MEC-based hydrogen generation from AMD.

Furthermore, subject category co-occurrence analysis reveals the multidisciplinary nature of this research area, as it intersects environmental science, energy and fuels, chemical engineering, biotechnology, and applied microbiology. Such interdisciplinary collaboration fosters innovative perspectives and strategies for addressing the complex challenges inherent in AMD treatment.

Finally, keyword clustering and co-citation analyses reveal key research directions for MECs treating acid mine drainage to generate hydrogen. Core themes include improving energy efficiency, refining reactor design, advancing electrode materials, and cultivating robust exoelectrogenic communities. Studies also emphasize biofilm formation, syntrophic interactions, metal recovery, and integrating processes like dark fermentation or photoelectrocatalysis. These trends underscore MECs’ potential to transform AMD into a hydrogen resource, enhancing both environmental remediation and resource valorization.

Despite substantial advancements, MECs for hydrogen generation from AMD still face key challenges, including stable long-term performance, cost-effective scalability, and insufficient policy frameworks. Future research should concentrate on developing corrosion-resistant electrodes, refining electroactive microbial communities, optimizing reactor configurations, and designing modular, adaptable systems. Equally important is the need to strengthen collaboration among academic, industrial, and governmental stakeholders, enhance public awareness, and establish supportive policies, thereby fostering an environment that enables MEC technology to realize its full potential in transforming AMD into a renewable hydrogen resource.