Search Results (36,016)

This study examines the effects of supply chain pressure, smart AI, and socio-economic fairness on long-term economic sustainability. To this end, this study uses quarterly data from 1999 Q1 through 2024 Q4 for the United States and employs the recently introduced Wavelet Cross-Quantile Regression (WCQR) to analyze this relationship. This study finds that smart AI, supply chain pressure (SC), and renewable energy consumption (REC) significantly drive U.S. economic growth, with the strongest short-term effects appearing when adoption and output are in the lower quantiles, reflecting threshold and diffusion dynamics. SC enhances growth once supply chain networks reach a critical level of connectivity, while REC generates substantial gains at low penetration levels, illustrating a “catch-up” effect. In contrast, economic inequality (EI) generally dampens growth, especially at moderate to high inequality levels; however, long-term reductions in EI yield positive returns in high-growth states by improving social cohesion and workforce productivity. Based on these findings, this study proposes funding low-adoption AI now, scaling to mid-adoption users mid-term, and entrenching long-term gains through economy-wide upskilling. Full article

Green methane has been deemed as a low CO₂ emission gas. The cost to produce green ethane varies considerably by location and technologies (USD 15/GJ to USD 60/GJ). Although green methane has higher price than the average price of market natural gas in Australia (USD 11–40/GJ between 2019 and 2023), it is currently significantly lower than the production cost for green hydrogen, with the levelized cost of hydrogen (LCOH) at USD 6.6/kg. Green methane production can utilise different processing steps. Separation processes require energy to separate CO₂, with the remaining issue of safely storing the captured CO₂ or venting it to the atmosphere. Direct catalytic biogas methanation (e-methane) does not require the separation of CO₂ but converts CO₂ together with CH₄ to a purer stream of CH₄, converting the CO₂ to an energy product_. E-methane consequently can be considered as an alternative energy carrier to store off-peak electricity from the grid, commonly called power-to-gas technology (P2G). Furthermore, injecting green methane into gas pipelines does not require significant gas infrastructure upgrading and has no upper limit, as it is compatible with natural gas. Here we review the status of biogas and direct green methane production from biogas around the world and assess technologies that are used to produce green methane via separation or direct catalytic conversion. We evaluate their techno-economic assessment results, with a particular focus on e-methane, identifying the opportunity as a pathway to supply low-emission gas with the perspective of a future e-methane industry within Australia. Full article

This research introduces a novel hybrid forecasting framework for solar energy prediction in high-latitude regions with extreme seasonal variations. This approach uniquely employs General Type-2 Fuzzy Logic (GT2-FL) for data preprocessing and uncertainty handling, followed by two advanced neural architectures, including BiLSTM and SCINet with Time2Vec encoding and Variational Mode Decomposition (VMD) signal processing. Four configurations are systematically evaluated: BiLSTM-Time2Vec, BiLSTM-VMD, SCINet-Time2Vec, and SCINet-VMD, each tested with GT2-FL preprocessed data and raw input data. Using meteorological data from Lithuania (2023–2024) with extreme seasonal variations where daylight hours range from 17 h in summer to 7 h in winter, F-BiLSTM-Time2Vec achieved exceptional performance, with nRMSE = 1.188%, NMAE = 0.813%, and WMAE = 3.013%, significantly outperforming both VMD-based variants and SCINet architectures. Comparative analysis revealed that Time2Vec encoding proved more beneficial than VMD preprocessing, especially when enhanced with fuzzification. The results confirm that fuzzification, BiLSTM architecture, and Time2Vec encoding provide the most robust forecasting capability under various seasonal conditions. Full article

As a type of electrochemical energy storage, the vanadium redox flow battery system (VRFB) is currently one of the most promising large-scale energy storage methods. Nevertheless, the ability to accurately estimate the state of charge (SOC) is one of the critical factors restricting the commercialization of VRFBs. This review summarizes the estimation methods for the SOCs of VRFBs used by scholars in the past 10 years, comprehensively discusses the main factors affecting the accuracy of SOC estimation, and discusses the direct measurement methods, combined with modeling filter estimation methods and data-driven SOC estimation approaches currently investigated by mainstream scholars. Although several recent literature reviews describe the current modeling and estimation methods for VRFBs, there has been relatively little attention paid to the more common equivalent circuit modeling methods and parameter identification approaches. This review mainly focuses on common equivalent circuit model (ECM) modeling methods and filter estimation algorithms using modeling, and it summarizes their advantages and disadvantages. Finally, a description of potential research directions for VRFB modeling and SOC estimation in the future is presented. Full article

The increase in global demand for mineral resources with the energy transition is likely to intensify the consequences of mining, such as deforestation; biodiversity loss; soil, water, and air contamination; violations of civil, political, and labour rights; loss of livelihoods; and harm to health. It is a paradox that the quest for sustainability and transition away from fossil fuels are leading to another set of unsustainable practices. The paper analyses how one major faith actor, the Catholic Church, is dealing with this paradox and is translating its theological and moral commitment to integral ecology into practice in the context of mining. Based on a series of consultations with cross-continental actors, the paper aims to offer a typology of responses in order to inform the work of other actors in sustainable development and the transition to renewable energy. The paper examines five types of intertwined responses: (1) the accompaniment of mining-affected populations, which is the starting point of all responses; (2) the mediation of experience through theological and organisational resources and international policy frameworks; (3) the documentation of what is happening or likely to happen; (4) education and formation to address the structural causes of social and ecological degradation at a multi-scalar level; and (5) advocacy for policy and institutional change, including alternative modes of socio-economic development. The paper concludes by discussing some shortcomings in these responses, as well as avenues for broad-based coalitions for sustainability in the context of the mining requirements of the energy transition. Full article

Solar coatings have become increasingly relevant as a means to enhance the performance and efficiency of photovoltaic (PV) panels, playing a critical role in advancing sustainable solar energy solutions. This study employs the life cycle assessment (LCA) methodology to quantify the greenhouse gas (GHG) emissions associated with the production process of a coating used on solar PV panels. Actual data were collected for the manufacture of the solar coating, constituted by two layers: (i) tetraethyl orthosilicate (TEOS) and (ii) titanium isopropoxide (TTIP). Data on energy and material flows were compiled. The GHG emissions for the TEOS and TTIP coatings were 1.8977 and 6.3204 g CO₂-eq/mL, respectively. With experimental data demonstrating a 4.5% increase in panel efficiency from the coatings, a simulation was carried out to verify the impact of the solar coating on a 16.4 MW solar power plant. The results indicate lifetime avoided emissions of 98,029,294 kg CO₂-eq over 25 years. Sensitivity assessments verified the impact of shorter lifetimes of the coatings, and even with frequent reapplication—down to monthly intervals—the coating continues to provide net environmental benefits. This robustness reinforces the potential of solar coatings as a complementary strategy for decarbonizing PV systems. Full article

Ground engaging tools (GETs) are critical consumable components on mining excavators, and their timely replacement is essential to prevent risks and excessive downtime. This paper presents a monitoring method utilising the modal properties—natural frequencies and mode shapes. The method is applied in a test case to show how the GETs on an excavator bucket could be monitored. Modal analysis and dynamic analysis are conducted with ANSYS to verify the effectiveness of the proposed method. The finite element analysis models are validated by experimental vibration experiments. The results demonstrate a strong correlation between changes in natural frequencies and the conditions of the teeth on the excavator bucket, when comparing the intact to the worn-out condition. In conclusion, the presented method offers a promising approach for real-time monitoring of the GETs on mining excavators and similar equipment. It will contribute to efficient maintenance interventions and enhancing operational efficiency and safety. Full article

The energy transition is an issue of fundamental importance in the current global context, as an increasing number of countries are committed to searching for minerals and elements essential for the storage, distribution, and supply of energy derived from new renewable and sustainable sources. In some countries, these elements (such as boron, lithium, and strontium) are considered to be critical raw materials (CRMs) because of their limited occurrence within their own borders and are commonly found in minerals and geothermal–formation waters, especially in brackish to brine waters. In the Italian territory, CRM-rich waters have already been identified by previously published studies (i.e., with mean concentrations in the Salsomaggiore Terme of 390 mg/L of boron, 76 mg/L of lithium, and 414 mg/L of strontium); however, their extraction is hampered by several knowledge gaps. In particular, a comprehensive understanding of the origin, accumulation processes, and migration pathways of these CRM-rich waters is still lacking. These factors are closely linked to the geological framework and evolutionary history of each specific area. To address these gaps, we investigated the Salsomaggiore Structure that is located at the northwestern front of the Apennine in Italy by integrating geological data with hydrogeochemical results. We constructed new preliminary distribution maps of the most significant CRMs around the Salsomaggiore Structure, which can be used in the future for the National Mineral Exploration Program drawn up in accordance with the European Critical Raw Materials Act. These maps, combined with the interpretation of seismic reflection profiles calibrated with surface geology and wells, allowed us to establish a close relationship between water geochemistry/CRM contents and the geological evolution of the Salsomaggiore Structure. This structure can be considered representative of the frontal ranges of the Northwestern Apennine and other mountain chains associated with the foreland basin systems. Full article

In this work, we investigated how the electrical resistivity of LaNiO₃ thin films deposited on SrLaAlO₄ (100), LaAlO₃ (100), and MgO (100) single-crystal substrates by the pulsed laser deposition (PLD) technique can be controlled by femtosecond laser irradiation. Thin films were characterized by X-ray diffraction (XRD), field emission scanning electron microscopy (SEM-EDS), and temperature-dependent electrical resistivity measurements. The XRD data indicated good crystallinity and preferential crystallographic orientation. The electronic transport parameters of irradiated samples showed a remarkable decrease in the electrical resistivity for all studied films, which ranged from 38% to 52% depending on the temperature region considered and the type of substrate used. The results indicate a new and innovative route to decrease the electrical resistivity values in a precise, controlled, and localized manner, which could not be performed directly by well-known growth processes, allowing for direct application in non-volatile-memory electrodes. Full article

Hydrogen is gaining significant interest from researchers because of its renewable and clean nature. In this study, we explored the effects of promoters and oxygen addition on biogas reforming. The promotion of catalysts with alkaline earth metals (Ca and Mg) improved the basicity of the catalyst, leading to enhanced catalytic activity and stability. The promotion of the Ni/TiO₂ catalyst with Ca showed higher CH₄ conversion and H₂ yield compared to the bare and Mg-Ni/TiO₂ catalysts. The enhanced activity of Ca-Ni/TiO₂ could be attributed to its high dispersion, small particulate size, and strong metal–support interaction. Adding oxygen to the reactor feed improved the activity and stability of the catalyst due to the simultaneous occurrence of dry and partial oxidative reforming. The maximum CH₄ conversion and H₂ yield of 81.13 and 37.5% were obtained at 800 °C under dry reforming conditions, which increased to 96 and 57.6% under dry-oxidative reforming (O₂/CH₄ = 0.5). The CHNS analysis of the spent Ca-Ni/TiO₂ catalyst also showed carbon deposition of only 0.58% after 24 h of continuous dry-oxidative reforming compared to 25.16% under continuous dry reforming reaction. XRD analysis of the spent catalyst also confirmed the formation of carbon deposits under dry reforming. Adding oxygen to the feed resulted in the simultaneous removal of carbon species formed over the catalytic surface through gasification. These findings demonstrate that Ca promotion combined with oxygen addition significantly improves the catalyst efficiency and durability, offering a promising pathway for stable, long-term hydrogen generation. The results highlight the potential of Ca–Ni/TiO₂ catalysts for integration into biogas reforming units at an industrial scale, supporting renewable hydrogen production and carbon mitigation in future energy systems. Full article

Maieutics is a remarkable method for discovering new insights through deep dialogue. Defined as “relating to or resembling the Socratic method of eliciting new ideas from another”, the term originates from the Greek word for “midwifery”—as noted in the Merriam-Webster Dictionary. Recently, maieutics has gained renewed relevance in advanced discussions about artificial intelligence, the nature of the mind, and scientific inquiry. This contribution presents a real and extended dialogue, illustrating the power of the maieutic method in addressing key developments in the field of Automatic Control. Over the past 40 years, the authors have followed a unique intellectual path shaped by this method. Inspired by recent research, they have also applied maieutics in interaction with AI systems—particularly ChatGPT. This experiment aimed to replicate, in a condensed timeframe, the long intellectual journey taken over decades. The preliminary results suggest that although AI systems can retrieve historical information, they struggle to capture the deeper, guiding principles of this journey. The authors also identify a significant concern: while the maieutic approach with ChatGPT can serve as a valuable educational tool, it must be complemented by a strong knowledge of dynamical systems leading to innovative paradigms of learning. Full article

Predictive maintenance strategies in wind turbine operations have risen in popularity with the growth of renewable electricity demand. The capacity of the strategy to predict system health, especially for the wind turbine gearboxes, is critical in reducing wind turbine operation and maintenance cost. Driven by the emergence of the application of large language models (LLMs) in diverse domains, this work explores the potential of LLMs in the development of wind turbine gearbox prognosis. A comparative analysis is designed to investigate the capability of two state-of-the-art LLMs—GPT-4o and DeepSeek-V3—in proposing machine learning (ML) pipelines to classify gearbox conditions based on a labelled SCADA dataset. The LLMs were prompted with the context of the task and detailed information about the SCADA dataset investigated. The outputs generated by the LLMs were evaluated in terms of pipeline quality and prediction performance using the confusion metric. Baseline ML models were developed and fine-tuned as benchmarks using Python 3.12 libraries. Among the baseline models, the random forest and XGBoost models achieved the highest cross-validated average F1-scores. The results have shown that the ML pipeline proposed by DeepSeek-V3 was significantly better than both GPT-4o and baseline models in terms of data analytical scope and prediction accuracy. Full article

The significant rise of electric vehicles in urban areas calls for research on smart charging to promote electric mobility. Existing research is fragmented, with inconsistent findings, focusing on single aspects of smart charging, such as challenges, charging technologies, and sustainability concerns. Thus, a bibliometric analysis was conducted to identify the key themes and propose future research agendas on smart charging for electric mobility in urban areas, to guide policy formulation and promote widespread uptake of electric vehicles. A total of 201 publications covering the period 2005 to 2025 were extracted from the Scopus database; the first was published in 2011 and numbers peaked in 2024, with 39 publications. The topic is young, with an average age per publication of 4.17 years, with China as the top-ranked country, with 97 publications. Research on smart charging for e-mobility in urban areas focuses on four key themes: smart charging technologies and optimisation strategies, grid integration and vehicle-to-grid systems, renewable energy and environmental sustainability, and urban mobility systems and infrastructure development. Despite their importance, real-world testing and smarter integration with cities and grids remain largely underexplored, especially in developing countries. Future research should focus on large-scale vehicle-to-grid integration, user behaviour analysis, and coordinated planning of smart charging with urban transport and policy frameworks. Full article

Water resources allow us to trace the history of many of our towns. In settings with limited surface water, a very interesting case study is represented by the presence/preservation of water in the rupestrian towns located along the rocky walls of canyons (locally named “gravine”) southward, cutting the Murge karst area (Puglia, Southern Italy). In some sections of their valleys, soft rocks, easy to dig, are exposed, and, along the canyon flanks, favored the development of rupestrian towns (cities where dwellings are carved in these soft rocks). Here, before the construction of aqueducts that now bring water from the “distant” Apennines (at least 30 km away), the building of historical fountains, in addition to the collection of rainwater in cisterns, testifies to the presence of an aquifer now undervalued as a local water resource useful for human settlements in a predominantly karst territory. Our study regards an aquifer feeding the Mascheroni Fountain (Great Masks Fountain) through a short qanat that allowed for the development of the old town of Laterza, in Puglia (Southern Italy). Starting from the attractiveness of the ancient fountain, the connection between geological features of the area and the ancestral origin of the city could be proposed to a large audience, representing an intriguing opportunity to develop themes useful for geotouristic purposes and disseminating concepts about sustainability and the importance of preserving local renewable resources. This topic is of paramount importance since the town of Laterza is located at the boundary between the UNESCO MurGEopark and the “Terra delle Gravine” Regional Park, making it the ideal starting point for both parks. Full article

To meet the massive increase in energy demand, extensive research has been conducted over the past few decades on developing clean and sustainable energy storage methods. Hydrogen is considered as one of the most promising future energy carriers due to its high energy density and renewability, but it requires storage. Storing hydrogen using metal hydride offers several advantages, including stability, safety compactness and reversibility of the hydrogen absorption/desorption process. Thermal management during hydrogen storage using metal hydride is critically important since the reaction between the metal and hydrogen is highly exothermic. We are aiming to develop thermal storage systems based on composite phase change materials (CPCMs) that absorb the heat generated during hydrogen absorption and release it during desorption, in an effort to improve energy storage efficiency. Lightweight, shape-stable CPCMs are prepared by loading the selected organic phase change materials into expanded graphite and hydrophobic monolithic silica aerogel. The chemical structure, microstructure, thermal properties and leakage of CPCMs are investigated. These samples were subjected to variable power electrical heating to simulate the heat generated during hydrogen reaction, forming lanthanum hydride, according to its published reaction kinetics. Full article