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Review

A Bibliometric Analysis of the Studies on Self-Healing Concrete Published between 1974 and 2021

by
Mohammed H. Alzard
1,
Hilal El-Hassan
1,*,
Tamer El-Maaddawy
1,
Marwa Alsalami
2,
Fatma Abdulrahman
2 and
Ashraf Aly Hassan
1
1
Department of Civil and Environmental Engineering, United Arab Emirates University, Al Ain P.O. Box 15551, United Arab Emirates
2
Ministry of Energy and Infrastructure, Dubai P.O. Box 1828, United Arab Emirates
*
Author to whom correspondence should be addressed.
Sustainability 2022, 14(18), 11646; https://doi.org/10.3390/su141811646
Submission received: 5 July 2022 / Revised: 1 September 2022 / Accepted: 9 September 2022 / Published: 16 September 2022
(This article belongs to the Special Issue High Performance and Advanced Construction Materials)
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Abstract

:
Research on self-healing concrete has flourished in recent years. This paper aims to comprehensively understand the current research situation and future development directions of self-healing concrete. It summarizes and analyzes the publications on self-healing concrete from 1974 to 2021 to reveal the current key research topics and development trends and identifies the most productive research constitutes. The bibliometric analysis software Biblioshiny was used to analyze 1433 documents written by 2961 authors and published in 450 sources retrieved from Scopus. The analysis included an overview of the leading information and an analysis of the authors, countries, universities/institution, publications, and keywords. Results obtained from the author analysis suggest that tracking the work of the most productive authors is essential, as it will provide researchers with valuable information, such as possible leads and ideas for future research work and collaboration opportunities. Countries, universities/institutes, and publications analysis revealed that more collaboration leads to more exposure and a higher citation rate, significantly promoting self-healing research development. A keywords analysis highlighted the focus areas in self-healing concrete and presented potential gaps in the literature. The findings of this study will provide scholars with a comprehensive understanding of the current research work in the field of self-healing concrete and its future directions. Results can also benefit stakeholders in making effective decisions to direct the development of the self-healing industry.

1. Introduction

Due to its unique mechanical and durability properties, concrete has been one of the most extensively used materials worldwide. However, despite its superior performance, concrete has weaknesses affecting its performance, such as low tensile strength and ductility. Such weaknesses make concrete prone to developing cracks throughout its service life [1]. Even though cracks might not affect the strength of concrete at an early age, their formation and propagation expose the steel reinforcement and reduce the long-term durability and serviceability. This facilitates the ingress of undissolved particles of undesirable fluids and gases through the concrete [2]. Such cracks can be reduced once detected by various techniques, such as grouting [3], epoxy sealing [4], and stitching [5]. However, these methods are primarily inefficient, costly, do not last more than 10–15 years, and require external interference [6]. Therefore, past research has observed different efficient and cost-effective methods to repair the concrete with minimal human interference. As a result of the continuous research in the field, concrete that could repair or heal itself, i.e., self-healing concrete, was developed.
Self-healing concrete can repair microcracks with limited or no external action or human involvement, making it a promising approach to rehabilitating microcracks in concrete structures [1,7]. Approaches and techniques used to achieve self-healing in concrete can be categorized into two groups, autogenous and autonomous self-healing. Autogenous self-healing of concrete is a phenomenon where cracks are sealed due to the reaction of unhydrated cement particles with moisture in the air, resulting in crystalline materials forming [8,9,10]. Indeed, this method has great potential but has some drawbacks. The quantity of self-healing products resulting from the continuous hydration of cement depends on the amount of unhydrated particles in the concrete matrix. These particles are typically minimal, thereby limiting the reaction efficiency and formation of sufficient self-healing products to fully seal the developed cracks [11]. On the other hand, autonomous self-healing depends on adding engineered materials to the concrete to repair or seal larger cracks. Past research has highlighted an improvement in the ability of concrete to self-heal using this technique [12]. Several autonomous self-healing approaches have been investigated, such as electrodeposition technology [13], embedding shape memory alloy (SMA) [6], capsules [14], vascular technology [15], and bacteria utilization [16].
Research on self-healing concrete has expanded drastically in recent years. As a result, a vast collection of state-of-the-art review papers that collect and analyze such work were produced [17]. Even though several review articles covered self-healing concrete, most of these reviews do not show how the process took place, making it harder to replicate them. Some of these papers examined the subject from a comprehensive perspective [6], while others investigated specific topics [2,6,7,18]. Usually, the process of selecting the papers, which is typically limited to the topic, is not described sufficiently. To overcome these shortcomings, the use of bibliometric reviews has become more prevalent in different disciplines. Unlike other techniques, bibliometric reviews provide more structured, reliable, and objective-based analyses of a large body of information. It helps in inferring trends of a particular topic over time and identifying researched themes. It can also identify shifts in the boundaries of the disciplines and pinpoint the most prolific scholars and institutions. Ultimately, bibliometric analyses present an overall view of the conducted research [17,19]. In fact, it has been utilized in various fields [14,16,20,21,22] and proved its usefulness. However, such an approach has not been applied to the field of self-healing concrete as of yet.
This paper aims to map the evolution and research trends in self-healing concrete by utilizing bibliometric analysis of the relevant literature obtained from the Scopus database between 1974 and 2021. It determines the key contributors, research themes, and critical publication outlets and topics to collectively analyze the findings and identify the gaps in the literature for future studies. The outcomes of this paper can be a valuable reference for practitioners and researchers to have a complete knowledge of the current research situation and future development directions on self-healing concrete. In addition, decision-makers can utilize the outcomes of this paper in making effective decisions to further develop the research field.

2. Methods

The methodology to conduct the bibliometric analysis presented in this paper is summarized in Figure 1.

2.1. Data Collection

The first step in conducting a bibliometric analysis is setting a precise and a clear aim. This step is crucial as it will aid in selecting the best bibliometric analysis technique and, subsequently, choosing the proper data format required [20]. The aim of this study, as mentioned earlier, is to employ the bibliometric analysis to the field of self-healing concrete and identify the productivity of the research elements, including authors, countries, journals, universities/institutions, etc. Furthermore, it reveals the bibliometric structure that encompasses the interaction between the different aspects of research contributing to the intellectual and social systems.
Data collection is usually divided into three stages: data retrieval, data loading and converting, and data cleaning [21]. In the first stage, i.e., data retrieval, the bibliographic information was extracted from Scopus, one of the largest databases for academic abstracts and citations, covering nearly 50 million pieces of literature published since 1823 [20,22]. Data retrieval resulted in obtaining 1652 documents (journal articles, conference articles, and books) published between 1974 and 2021 worldwide by searching the Scopus database for self-healing concrete with the search query: TITLE-ABS-KEY’ self-healing AND concrete’. Since the present study was conducted between April and May 2022, the time frame selected considered all the publications on the topic up to 2021. The published research was written in English (94%), Chinese (5%), German (0.84%), and other languages, including French, Russian, Japanese, and Korean (0.16%). In this study, only sources that were written in English were considered. These sources were further filtered so that only sources with complete bibliographical information were included; for example, sources that did not have an author name were eliminated. The final sources count was 1433.
The second data collection stage involved loading and converting the obtained bibliometric database into a suitable format for the employed bibliometric tool. The database utilized in this analysis was in BibTeX format, as it was supported by the “Bibliometrix” R package. In the final stage, a quality assurance measure was applied, as the quality of the results depended on that of the data. Microsoft Excel was employed on the retrieved database to check for duplicates, misspelled words, and incomplete bibliographic information. These identified errors were filtered and removed before running the analysis.

2.2. Software Selection

To perform a proper bibliometric analysis, appropriate software is required. Many tools and software packages capable of performing a bibliometric analysis, including visualization and quantitative analysis, single analysis, or both at the same time, are available, such as “CiteSpace”, “CitNetExplorer”, “VOSviewer”, and “Bibliometrix”. Bibliometrix is an open-source tool developed by Aria and Cuccurullo [17]. Unlike the other software solutions, it provides rapid analysis and establishes data matrices for performance analysis and science mapping of the bibliographic collection. In addition, the latest application of Bibliometrix, Biblioshiny, is available for scholars with little to no coding background. Biblioshiny is a web-based application that is accessible through R-studio. In this study, the latest version of the Bibliometrix R package was used through the web-based app, Biblioshiny [21]. In addition to Bibiloshiny, Microsoft Excel was used to perform data quality checks and to generate some graphs.

2.3. Analysis

Aspects considered in this paper for analysis included quantitative and qualitative analyses. The quantitative analysis covered the areas of research, publication year, writing language, journal distribution, and information related to the research constituents (authors, countries, universities/institutes, and publications). The qualitative analysis considered the thematic areas and keyword/term mapping. Bearing in mind the importance of bibliometrics and the analysis of keywords, the present work introduces an in-depth analysis of the authors’ keywords in the area of self-healing concrete. Subsequently, the analysis was conducted, and the results were reported, as shown in the following section.

3. Results and Discussion

3.1. Overview of the Retrieved Data

Bibliometric performance analysis encompasses descriptive metrics related to the scientific field publication, citation, frequency, and trends (or “hot topics”). As shown in Table 1, 1433 studies on self-healing concrete were retrieved from Scopus across 450 sources between 1974 and 2021. These studies were written by 2961 authors, with 98% being written by multiple authors. This results in an average of 4.49 publications per year and a collaboration index of 2.19.
The collected documents are categorized in Figure 2 to illustrate the types of documents found in the literature. The majority of the documents were article publications, representing 60.6% of the total documents. The second most published type of documents was conference papers with a percentage of 25.9%, and the third was review papers with 6%. Fewer documents (with a percentage less than 4%), were published in the form of book chapters, conference reviews, books, and others.
Figure 3 provides insights into the evolution of interest in self-healing concrete by presenting the yearly distribution of the analyzed 1433 documents. The results show that only 46 documents were published between 1974 and 2006, after which a gradual increase in the number of publications was noted with an annual growth rate of 20.4% up to 2021, portraying that the self-healing concrete field is growing and significant and presents ample space for research and development. This provides evidence of the interest in self-healing concrete, considering its vast benefits and advantages.
Figure 4 shows the areas of research where the documents are published. Clearly, the research on self-healing concrete has been studied and published in broad subject areas. However, it seems to be studied mainly in the engineering and material science subject areas, followed by physics and astronomy, environmental science, chemistry, chemical engineering, and energy. This indicates that self-healing concrete is an interdisciplinary field requiring knowledge from different disciplines that are dedicated to understanding the behavior, manufacturing, and performance of self-healing concrete. Furthermore, the selected documents were published in 450 international sources, indicating the broad interest in self-healing concrete.
Table 2 shows the top 10 sources based on the number of publications. Most articles were published in top-tier journals, such as Construction and Building Materials, Materials, Cement and Concrete Composites, with impact factors ranging from 1.768 (Journal of Advanced Concrete Technology) to 10.933 (Cement and Concrete Research). The scope of these journals covered civil engineering construction and materials, which belong to the subject areas of engineering and material science (Figure 4). These sources are a critical platform for publications in self-healing concrete and are recommended as publication sources for scholars interested in the field.
Table 3 shows the top 10 sources based on h-, g-, and m- indexes. These metrics aid researchers in selecting high-quality publishing outlets. H-index is the maximum value of h such that the given author/journal has published at least h papers that have each been cited at least h times [23]. The m-index is a variant of the h-index that considers years since first publication and is more relevant to a new source than the h-index [24]. The g-index gives more weight to highly-cited articles. It can be defined as the (unique) most significant number such that the top g articles received (together) at least g2 citations [23]. Construction and Building Materials and Cement and Concrete Composites journals dominated the top rankings regardless of the index type.

3.2. Research Constituents Analysis

3.2.1. Authors

In any discipline, the influence of any researcher can be determined by the total number of citations they received [25]. The leading authors in the self-healing concrete field with the most publications and citations are displayed in Table 4. It should be noted that the citations listed in Table 4 are only reflecting the number of citations each author got for a publication in the self-healing concrete field and not their overall citations. Nele De Belie was the most influential among the listed authors, with more than 6000 citations and 107 publications. Data presented in Table 4 shows that having a high number of citations is not necessarily associated with a high number of publications. Henk M. Jonkers, for example, has a total citation of 2838, which places him in second place, whereas in terms of the number of publications, he was placed at rank six with a total of 34 publications. Similarly, using the ‘citations per year’ metric, this author is only fourth highest, preceded by Willy Verstraete and Kim Van Tittelboom. In fact, the more recent publications of these latter authors were more influential than those of Henk M. Jonkers. In addition, Willy Verstraete had the most impactful research with the highest ‘citations per publication’. The high number of citations can indicate the quality of the work published by the author and the extent of exposure and spreadability the work has in the scientific community. It should be noted that authors collaborate on a regular basis and produce multiple publications. This should be considered when determining the effectiveness of an author.
Another helpful analysis obtained from the bibliometric analysis is the co-authorship analysis. The co-authors’ analysis offers valuable information that reveals the influential authors and how closely they are related. Also, self-healing concrete research trends can be revealed by following the research interests of the authors. In this study, a co-authorship network with 45 nodes, each reflecting an author and multiple links, is shown in Figure 5. The node size gives a visual indication of each author’s number of articles, whereas the links between the nodes illustrate the collaboration relationships of the authors. Thicker links between nodes indicate a high collaboration rate between the authors [26,27]. As shown in Figure 5, Nele De Belie, Willy Verstraete, and Kim Van Tittel-boom, among others, who belong to the red cluster, had the highest collaboration rate. A high collaboration rate within a cluster can be attributed to the fact that most of the authors that belong to the cluster are working on similar areas in the self-healing concrete field and are affiliated to the same institution and/or reside in the same country or region, rendering collaboration easier. For example, the authors in the red cluster are mainly from Belgium, while authors belonging to the purple cluster are mainly from China, and the authors in the green cluster are mainly from Italy. This finding confirms the high number of citations each of these authors has. High collaboration rates highlight current collaborations and reflect possible future collaboration opportunities with the authors.

3.2.2. Countries and Institution Analysis

Figure 6 presents the scientific production of countries. At first glance, it can be seen that the research on self-healing concrete has left its footprint across all continents. Yet, little to no research has been carried out in parts of South America, Eastern Europe, Russia, and Africa. Countries are colored with a color hue in relation to the number of documents published. Table 5 presents the top 10 contributing countries and relevant affiliations to scientific publications on self-healing concrete. Throughout the years, 57 countries have been interested in the field of self-healing concrete. Of these 57 countries, 14 have published more than 20 articles in the field. Results obtained from the analysis show that the top 5 countries, China, the United States of America (USA), India, Belgium, and the Netherlands, outperformed the remaining 52 countries. Among these five countries, China, the USA, and India are among the top five countries in concrete production [28]. This can explain the high interest in self-healing concrete in these countries. It should be noted that the frequencies reported in Table 5 for the universities/institutions (affiliations) consider the total number of particular universities/institutions that appeared in the analyzed documents. This means that the productivity of one research constituent does not mean that it has the highest contributing university/institution. For instance, in terms of scientific production, the most productive country is China, whereas, in relevant affiliation, the ranking was not led by a Chinese institution. Instead, Ghent University was the most prolific institution, with 203 publications, followed by the Delft University of Technology with 103 publications. A three-field plot, presented in Figure 7, between authors (AU), affiliation (AU_UN), and countries (AU_CO) shows the dynamic between these research constituents, which also confirms the above finding.
The relationships relevant to the intellectual interactions and structural connections among the research constituents were also obtained from Bibiloshiny. The collaboration network among countries is presented in Figure 8. It can be seen that high collaboration rates exist between countries located within the same geographical area, e.g., the European Union, and those across different continents and speaking different native languages, e.g., the USA and China. In fact, these two countries have more collaborations with other countries than any of the others identified in the present work, explaining their high number of publications (96 and 214, respectively).
Analysis of international collaboration can also be obtained by counting the number of articles published by authors from the same country and articles with authors from different countries. Accordingly, articles can be categorized into two types, namely single country publication (SCP) and multiple country publication (MCP). In SCP, all authors resided in the same country, and such publications represented intra-country collaboration. In MCP, authors were from different countries, representing inter-country collaboration, i.e., international collaboration. Figure 9 presents the SCP and MCP for the top 20 countries. Based on the percentage of MCP (of the total number of publications per country), Malaysia, Singapore, and Turkey ranked first, second, and third, respectively. Authors from these countries have more collaborations with authors from different countries. Figure 9 illustrates that single country publications were higher than the multiple country publications for the listed 20 countries, except for Malaysia. In terms of SCP percentage, Brazil, Iran, and India were the top countries.
Figure 10 presents the collaboration network between 19 research universities/institutions, each represented with a node. Similar to Figure 5, the node size represents the scientific production of each institute, and the width of the line signifies the intensity of collaboration between the nodes. The universities/institutions are clustered into five groups. From Figure 10, it can be seen that these universities/institutions are located in the same geographical location, which somehow facilitates a higher collaboration rate. This was also proved with the collaboration of authors discussed in Section 3.2.1. A high collaboration is noted between Ghent University (Belgium) and Delft University of Technology (Netherlands), with 203 and 103 frequencies (Table 5), respectively. This is supported by the authors’ collaboration network in Figure 5, which displays extensive collaborations among authors from these two universities/institutions. Collaborations between universities/institutes in different regions of the world are also present.

3.2.3. Publication Analysis

Information related to the citations of the analyzed publications was drawn from the results obtained from Biblioshiny. The 10 most cited documents identified after the bibliographic search are shown in Table 6. The total citations for these documents ranged from 281 to 820. The most cited document was the journal review article Microbial carbonate precipitation in construction materials: A review co-authored by Willem De Muynck, Nele De Belie, and Willy Verstraete, published by Elsevier in the Ecological Engineering journal in 2010, with a total citation of 820. The high number of citations for review articles is owed to their comprehensive analysis of results from different documents while highlighting research gaps and directions for future research.
Furthermore, five of the top ten documents were related to the self-healing of concrete using bacteria, i.e., microbially induced carbonate precipitation, which were authored by Willem De Muynck, Nele De Belie, Willy Verstraete, Henk M. Jonkers, Arjan Thijssen, Gerard Muyzer, Oguzhan Copuroglu, Erik Schlangen, Virginie Wiktor, and Jianyun Wang. This indicates that researchers have been utilizing naturally existing means to simulate the self-healing phenomena in materials rather than manufactured products. Based on the results presented in Section 3.2.1., these authors have a high collaboration rate, which might justify the high number of citations their work gained. Also, numerous authors from disparate geographical regions were connected via citations in the field of self-healing concrete, as shown in Figure 11. The articles presented in Table 6, produced by international collaboration, or MCP, have a higher number of citations per article than articles produced without international collaboration (or SCP). This indicates that international collaboration is essential in increasing the number of citations.
Another useful metric to measure the impact of a publication is the number of citations per year (C/Y). This metric helps reveal how the publication has been used over the years since it was published. Table 6 shows the citation per year for the top 10 cited documents. Among these documents, the review paper Microbial carbonate precipitation in construction materials: A review has the highest C/Y. This paper had a huge impact on the scientific community interested in the self-healing concrete field, considering the fact that it was published back in 2010. The second highest paper based on C/Y was Application of bacteria as self-healing agent for the development of sustainable concrete, authored by Henk M. Jonkers, Arjan Thijssen, Gerard Muyzer, Oguzhan Copuroglu, and Erik Schlangen. Part of this paper’s impact can be attributed to the media coverage for one of its authors. Also, several YouTube videos for the same author can be found. This shows that social media and other media platforms can be utilized in spreading and distributing knowledge. Conversely, the paper entitled Water Permeability and Autogenous Healing of Cracks in Concrete [32] was ranked as the fourth most cited paper with 628 citations but only 28.5 C/Y. This is possibly due to the low interest in this research topic in recent years.
The top ten countries based on the total number of citations are presented in Table 7. Belgium topped the ranks with a total of 6288 citations. In fact, six out of the 10 papers listed in Table 6 were published by authors from Belgium, and they accounted for 50% of these citations. Interestingly, when comparing Table 7 and Figure 9, it can be seen that countries with the highest percentage of international collaboration, i.e., high multiple country publication (MCP), such as Belgium, the Netherlands, and the USA, had the highest number of citations per article. Also, the collaboration network presented in Figure 8 and Figure 9 shows a high collaboration rate between China and the USA, which again explains the high number of citations in these countries. Meanwhile, countries with low international collaboration have a low number of citations. For example, Brazil is listed as one of the top 20 productive countries, but it has low international collaboration, which translates to low citations.

3.3. Keyword Analysis

Keywords represent the essence and summary of the critical points of a research article. Analyzing keywords can help in identifying the research hotspots, trends, topics, and directions. This analysis can be performed in time slices or different periods of the entire analyzed time span. This reveals specific details within each time slice, which can be interpreted later to identify the shifts in directions in a particular research field.
In the 1433 analyzed documents, 2586 authors’ keywords were identified. Out of the total keywords identified in Figure 12, the top 15 keywords frequently used by authors are: self-healing (515), concrete (192), self-healing concrete (141), bacteria (125), crack (114), durability (81), compressive strength (63), mechanical properties (35), microcapsules (34), asphalt concrete (33), mortar (31), permeability (30), calcium carbonate (27), fly ash (27), and Bacillus subtilis (25). A higher occurrence of the keyword self-healing and concrete is expected, as it was used as the research query in Scopus.
Usually, in keywords analysis, two critical means are used, namely word clouds and the dynamic of the keywords. Word clouds are an important tool for presenting an overview of the literature in any field for a specific time slice. Word clouds are made of the most frequently used keywords. The size of the word gives an indication of how frequently authors used it in their publications. A word cloud for the most frequent authors’ keywords is shown in Figure 12. In addition to the keywords identified earlier, keywords like biomineralization, crack healing, crystalline admixtures, encapsulation, flexural strength, MICP, microstructures, and corrosion were noted. Some of these words are related to the two mechanisms of the self-healing concrete itself (autogenous and autonomous self-healing), e.g., biomineralization, MICP (i.e., microbially induced calcite precipitation), crystalline admixtures, and encapsulation. Other keywords reflect the evaluation techniques used to measure the efficiency of the self-healing itself, including compressive strength, flexural strength, microstructure, and permeability. Meanwhile, some terms were seldom used, such as autogenous and autonomous self-healing, which describe the two main categories of self-healing concrete. Although many researchers studied both categories extensively, they did not frequently appear as a keyword. This can be explained by the tendency of some authors to describe the work based on the techniques used (e.g., MICP, encapsulation) and the performance evaluation means (e.g., compressive and flexural strengths) rather than the general terms.
The dynamic of the authors’ keywords is presented in Figure 13. This figure illustrates the co-occurrence of the top authors’ keywords. Co-occurrence of the keywords is a meaningful way to reveal the main content in the research field [38]. Terms that are closely associated, usually used together, are structured together into clusters and denoted by the same cluster color [39]. Also, the distances between the keywords represent a connection between them in terms of co-occurrence links, i.e., closer keywords have a closer connection [40]. In Figure 13, four clusters were observed and differentiated with different colors. In the first cluster (purple), keywords like self-healing, mechanical properties, cement, mortar, engineered cementitious composites, and cementitious materials can be found. From this cluster, it can be concluded that the self-healing phenomena was not only studied in concrete but also in mortars and other cementitious materials. In fact, research on mortars is more extensive than on concrete itself. This is because most self-healing concrete techniques are still studied on a small scale in laboratories [6,41]. The frequency of the keyword ‘concrete’ is higher than ‘mortar’ because some authors tend to use “concrete” more than ‘mortar’ when they select the keywords, which leads to the misrepresentation of the work. In the same cluster, keywords related to capsules (e.g., materials used in the capsules such as polymers, and crystalline admixtures, in addition to encapsulation and microcapsules), can be found. Capsulation is one of the techniques used for autonomous self-healing. The high frequency of these words in this cluster indicates that it is a hot topic, and much research is moving in this direction.
In the second cluster (red), keywords like calcium carbonate, MICP, bacteria, and biomineralization can be found in high frequencies. This shows that the utilization of bacteria as a self-healing agent is another hot topic in the field of self-healing concrete. Bacteria is mixed with concrete either directly or capsulated. It can precipitate calcium carbonate (or calcite) in developed cracks and seal them. This process is called biomineralization [42].
In the third cluster, keywords like water absorption, compressive strength, and flexural strength are the most frequent. These metrics are ubiquitous in the characterization of concrete properties. The same metrics are also applied to self-healing concrete to measure its performance. By examining the keywords in this cluster and other clusters, it can be seen that some other properties characterizations metrics are not showing, such as workability. This shows a potential gap in the literature, which is the lack of characterizing the fresh properties of self-healing concrete.
As mentioned earlier, the distances between the keywords reveal their relationship. Keywords that are close to each other are often used together. For instance, self-healing and cracks are proximate to each other. The main advantage of self-healing concrete is its ability to seal cracks with minimal external action or human interference. On the other hand, keywords far from each other may represent a potential gap in the literature [43]. For example, mechanical properties and asphalt concrete or superabsorbent polymers are placed far from each other. As such, it can be seen that the literature still lacks research that studies the mechanical properties of self-healing asphalt concrete and superabsorbent polymers. Nevertheless, it should be taken into consideration that the minimum number of occurrences of the authors’ keywords used in this study was five. This means that these distances (or gaps) might be filled with other keywords less frequently used in the literature.
The trends during the overall investigated period (1974–2021) were also examined. The examined articles were divided into three time slices (or periods), 1974–2000, 2001–2010, and 2011–2021. The word cloud for each time slice is presented in Figure 14, along with the 30 most frequent words. In the first time slice (1974–2000) in Figure 14a, keywords such as cracks, degradation, strength, durability, bridges, dams, natural frequencies, earthquakes, chloride mitigation, repair, water, and reinforced concrete were commonly used. This indicates that the early research on self-healing concrete mainly focused on repairing cracks in infrastructure elements that may have resulted from earthquakes, loading, or deterioration. The purpose was to prevent water from seeping into the concrete and corroding the steel reinforcement, which leads to a loss in strength and durability performance. The low frequency number in this time period provides evidence of the limited number of publications, as shown in Figure 3.
In the second time slice (2001–2010) in Figure 14b, the term ‘self-healing’ was introduced and widely used by scholars. The most frequent keywords in this time slice suggest that the research in this period focused extensively on utilizing bacteria and capitalizing on its ability to precipitate calcite. Other materials such as fly ash, polymers, microcapsules, and fibers were also apparent in this time slice. Keywords including landfill, waste disposal, and sustainability were also presented in this period. This indicates that self-healing was considered a sustainable option for use in concrete structures. Indeed, since self-healing tends to increase the durability of concrete structures, the construction and demolition waste will be reduced, leading to a reduction in the waste disposal in landfills, thus promoting sustainability. Furthermore, this time slice witnessed the emergence of new terms that defined the processes utilized in self-healing and the tests used to determine the efficiency of such a process. In fact, compared to the first time slice (1974-2000), it can be seen that some keywords were more frequently used, including mortar, durability, and compressive strength. Also, the frequencies of the keywords used in this time slice were higher than those found in the first one. This can be attributed to the increase in publications about self-healing concrete during this period (Figure 3).
In the final period of 2011–2021, research in the field of self-healing concrete using bacteria prospered, as is shown in Figure 14(c). An increase in the frequencies of the keywords was noted in this time slice with values reaching up to 560, owing to the further increase in the number of publications. The analysis revealed that research on bacteria has been increasing since 2001. The frequency of the keyword ‘bacteria’ increased from eight in the second time slice to 225 in the third time slice and will probably continue to grow in the future. In this period, more emphasis on the mechanical and durability properties and microstructure were detected, given that more terms related to these properties started to appear in high frequencies. Also, it can be seen that there was a necessity to use specific keywords to describe the published work, as mentioned earlier. For example, instead of using ‘self-healing or self-healing’, ‘concretes’, and ‘self-healing concrete or self-hearing concretes’ separately, authors tended to use one term that combined the phenomena and the material as ‘self-healing concrete’.
By analyzing these three time slices, several research gaps can be identified. First, real-life applications of self-healing concrete were not well represented in the keywords, which means that research on the performance of self-healing concrete in real-life applications is lacking. Also, as noted earlier, terms relating to the rheological and fresh properties and the optimization of self-healing mechanisms were not identified. Microstructure techniques other than scanning electron microscopy could be used to understand post-repair changes. Environmental and cost analyses were also missing. Such analyses are crucial since they can be utilized as a convincing point for the applicability of the self-healing concrete to stakeholders and decision-makers. Additionally, the use of the self-healing technique on different types of concrete is not investigated. Thus, further research in these areas should be carried out. Yet, it should be noted that some of these gaps might not be reflected in the authors’ keywords, as authors tend to use general keywords to describe their work. This should not be the case, as keywords should represent the specific research conducted and make it easier for scholars to find it.

4. Limitations

Bibliometric analysis provides various benefits that can be utilized to explore different topics and research constituents further but still possesses some limitations. Therefore, it can complement rather than replace qualitative evaluation methods. Some of the limitations include the misrepresentation of one or more research constituents. For example, bibliometric analysis can only be applied to literature published in indexed journals and does not cover unpublished research, research in non-indexed journals, and non-journal printed research work such as books, dissertations, reports, or government documents, which are not tracked well in bibliometric databases such as Web of Science and Scopus (Figure 2). Therefore, scholars who write books or book chapters may have their impact misrepresented when measured by these methods. Also, the analysis may be unfair to the high-quality work published in specialized journals that few scholars usually read.
Even though a tremendous effort is dedicated to reducing the measurements and technical issues, a bibliometric analysis can still encounter them. These issues include spelling mistakes, name changes, homonyms, synonyms, clerical errors, and changes in citation databases over time [44]. The bibliometric databases usually obtained from scientific databases such as Scopus and Web of Science are not produced exclusively for bibliometric analysis. Therefore, these databases can contain errors that will negatively affect the results of the analysis performed on them [20]. Scholars can avoid such errors by carefully inspecting the obtained database and removing any errors and issues they might encounter.
Another major limitation to bibliometric analysis is the authors citing themselves, colleagues, mentors, editors, or even friends. Also, authors may sometimes cite inaccurate work and fail to cite the more prominent work. This can lead to drawing attention in the wrong direction. Moreover, citations are treated equally regardless of whether a work is cited for its positive contribution or is criticized for its poor quality. In addition, large research teams in some disciplines may produce many research papers with the names of the whole team. A large set of diverse authors on papers may increase the likelihood of inflating the citation rates, which might not accurately reflect the individuals’ prominence within the field, thus negatively affecting analyses that depend on these rates [45]. Therefore, in future publications, it is essential to control the number of authors to avoid inflated citation counts and to enable more precise estimates of performance and impact.

5. Conclusions

In recent years, an increasing amount of research has been dedicated to self-healing concrete to seek solutions to the performance deterioration of concrete structures due to crack development, which is a challenging topic worldwide. The field of self-healing concrete is vast. Therefore, there is a need for a comprehensive and quantitative literature review to understand its progress and current standing, highlight the most prolific research constitutes, and somehow predict its future direction. This paper aims to present the aforementioned for the field of self-healing concrete by analyzing 1433 documents that have been published in the literature about the topic using the bibliometric analysis software Biblioshiny to conduct visual and quantitative analyses. The analyzed documents were obtained from the Scopus database and were published between 1974–2021 worldwide in 450 different sources. The high number of sources indicates an increasing interest in the field of self-healing concrete. The majority of the published documents were journal papers (60.6%) published in different subject areas, including engineering, material science, and environmental science. The top publishing journals in the field cover topics related to engineering and material science.
The analysis revealed that the top contributing authors, based on the total number of citations, were Nele De Belie, Henk M. Jonkers, and Willy Verstraete, among others. These authors have a high collaboration rate. It can be noted that the authors with high co-cited literature generally published more papers demonstrating that these authors have been committing to this field. As such, tracking their work can provide researchers with valuable information. Furthermore, the top contributing countries, based on the number of publications, were China, the USA, India, and Belgium, whereas the top contributing universities/institutes were Ghent University (Belgium), Delft University of Technology (Netherlands), and Southeast University (China). A publication analysis revealed that the high citation rate could be attributed to multiple country publication (MCP), i.e., more collaboration led to more exposure, which is vital to promoting the development of self-healing concrete research.
Keywords analysis, based on co-occurrence and evolution analysis, revealed that as the study continued in the self-healing concrete field, a growing number of keywords were constantly emerging without a big node in the past few years. This means that researchers are trying to manifest the self-healing phenomena through the application of different strategies. One of the most frequently used terms was bacteria. The analysis conducted on different time slices showed that research on utilizing bacteria in self-healing concrete was still being carried out since 2001 and will probably continue to grow in the future. The keywords analysis also showed the potential gaps in the literature, such as the lack of fresh properties characterization of the self-healing concrete, the optimization of the self-healing techniques, real-life applications, the applicability to different types of concrete, and both environmental and cost life cycle assessments. These gaps can be considered an opportunity for research and development, portraying a great potential to further grow and enrich the field of self-healing concrete.

Author Contributions

Conceptualization, M.H.A., H.E.-H., T.E.-M. and A.A.H.; methodology, M.H.A.,; software, M.A.; validation, M.H.A., H.E.-H., T.E.-M. and A.A.H.; formal analysis, M.A. and H.E.-H.; investigation, M.A. and H.E.-H.; resources, H.E.-H., T.E.-M. and A.A.H.; data curation, M.A.; writing—original draft preparation, M.A.; writing—review and editing, H.E.-H., T.E.-M., A.A.H., F.A. and M.A.; visualization, M.A.; supervision, H.E.-H., T.E.-M. and A.A.H.; project administration, H.E.-H., T.E.-M. and A.A.H.; funding acquisition, H.E.-H., T.E.-M. and A.A.H. All authors have read and agreed to the published version of the manuscript.

Funding

This research was funded by the United Arab Emirates University, grant number 12N044, and the Ministry of Energy and Infrastructure in UAE, grant number 21R084.

Institutional Review Board Statement

Not applicable.

Informed Consent Statement

Not applicable.

Data Availability Statement

Not applicable.

Conflicts of Interest

The authors declare no conflict of interest.

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Figure 1. Summary of the methodology followed in the bibliometric analysis.
Figure 1. Summary of the methodology followed in the bibliometric analysis.
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Figure 2. The distribution of the different types of the analyzed documents.
Figure 2. The distribution of the different types of the analyzed documents.
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Figure 3. Annual scientific production between 1974 and 2021.
Figure 3. Annual scientific production between 1974 and 2021.
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Figure 4. The number of publications within the different subject areas between 1974 and 2021.
Figure 4. The number of publications within the different subject areas between 1974 and 2021.
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Figure 5. Co-authorship network.
Figure 5. Co-authorship network.
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Figure 6. Scientific productivity of countries worldwide.
Figure 6. Scientific productivity of countries worldwide.
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Figure 7. Three-field plot analysis of authors (AU), affiliation (AU_UN), and authors’ countries (AU_CO).
Figure 7. Three-field plot analysis of authors (AU), affiliation (AU_UN), and authors’ countries (AU_CO).
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Figure 8. Country collaboration network.
Figure 8. Country collaboration network.
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Figure 9. Top 20 countries of publication based on SCP and MCP.
Figure 9. Top 20 countries of publication based on SCP and MCP.
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Figure 10. Collaboration network among research universities/institutions.
Figure 10. Collaboration network among research universities/institutions.
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Figure 11. Co-citation network among authors.
Figure 11. Co-citation network among authors.
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Figure 12. Word cloud of the most used keywords in the self-healing concrete field.
Figure 12. Word cloud of the most used keywords in the self-healing concrete field.
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Figure 13. Co-occurrence network of authors’ keywords in self-healing concrete field.
Figure 13. Co-occurrence network of authors’ keywords in self-healing concrete field.
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Figure 14. Word cloud of authors’ keywords in (a) 1974–2000, (b) 2001–2010, (c) 2011–2021.
Figure 14. Word cloud of authors’ keywords in (a) 1974–2000, (b) 2001–2010, (c) 2011–2021.
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Table
Table 1. Data on the main information obtained from the extracted publications (1974–2021).
Table 1. Data on the main information obtained from the extracted publications (1974–2021).
Description
Sources (Journals, Books, etc.)450
Documents1433
Average citations per document24.04
Average citations per year per doc3.40
References46,308
Document contents
Keywords plus 6389
Author’s keywords2584
Authors
Authors2961
Author appearances5677
Authors of single-authored documents57
Authors of multi-authored documents2904
Authors collaboration
Single-authored documents106
Documents per Author0.48
Authors per Document2.07
Co-Authors per Documents3.96
Collaboration index *2.19
* The total number of authors of multi-authored articles divided by the total number of multi-authored articles.
Table
Table 2. Top ten productive sources.
Table 2. Top ten productive sources.
RFrequent SourcePublisherP
1Construction and Building MaterialsElsevier201
2MaterialsMultidisciplinary Digital Publishing Institute73
3Cement and Concrete CompositesElsevier55
4IOP Conference: Materials Science & EngineeringIOP Publishing33
5Journal of Materials in Civil EngineeringAmerican Society of Civil Engineers31
6Materials Today: ProceedingsElsevier28
7Lecture Notes in Civil EngineeringSpringer25
8Cement and Concrete ResearchElsevier24
9Rilem BookseriesSpringer21
10Journal of Advanced Concrete TechnologyJapan Concrete Institute18
R = Rank; P = Number of publications.
Table
Table 3. Top ten sources based on h-index, g-index, and m-index.
Table 3. Top ten sources based on h-index, g-index, and m-index.
H-IndexG-IndexM-Index
RSourceScoreSourceScoreSourceScore
1Construction and Building
Materials		49Construction and Building
Materials		85Construction and Building
Materials		3.3
2Cement and Concrete Composites32Cement and Concrete Composites53Cement and Concrete Composites2.1
3Cement and Concrete Research20Materials38Materials
4Materials20Journal of Materials in Civil
Engineering		25Applied Microbiology and
Biotechnology		1.7
5Journal of Materials in Civil
Engineering		15Cement and Concrete Research24Journal of Materials in Civil
Engineering		1.5
6Applied Microbiology and
Biotechnology		12Journal of Advanced Concrete Technology18Smart Materials and Structures1.3
7Journal of Advanced Concrete Technology12Smart Materials and Structures17Journal of Building Engineering1.3
8Smart Materials and Structures12Applied Microbiology and
Biotechnology		15Materials Today: Proceedings1.3
9ACI Materials Journal10ACI Materials Journal12Sustainability (MDPI)1
10Journal of Intelligent Material Systems and Structures8Transportation Research Record10Journal of Materials Research and Technology1
Table
Table 4. Top contributing authors based on the number of citations and publications.
Table 4. Top contributing authors based on the number of citations and publications.
Author *Total
Citations		Number of PublicationsPublishing StartCitations
per Year **		Citations
per Publication ***
Nele De Belie65261072010593.361.0
Henk M. Jonkers2838342007202.783.5
Willy Verstraete2700112010245.5245.5
Kim Van Tittelboom2463452010223.954.7
Erik Schlangen2433412007173.859.3
Victor C. Li1635152007116.8109.0
Didier Snoeck1581272012175.758.6
Jianyun Wang1303212012144.862.0
Liberato Ferrara1235412012137.230.1
Feng Xing1111392011111.128.5
* Authors are ranked based on the total number of citations (1–10); ** Calculated as the ratio of total citations to the number of years since publication; *** Calculated as the ratio of total citations to the number of publications.
Table
Table 5. Top ten productive countries and productive universities/institutions.
Table 5. Top ten productive countries and productive universities/institutions.
RCountryPUniversities/InstitutionsFreq.
1China214Ghent University, Belgium203
2USA96Delft University of Technology, Netherlands103
3India95Southeast University, China71
4Belgium91Tongji University, China63
5Netherlands58Shenzhen University, China56
6Korea57Politecnico Di Milano, Italy44
7United Kingdom56Universiti Teknologi Malaysia, Malaysia28
8Italy37Wuhan University of Technology, China28
9Canada32Hanyang University, South Korea25
10Malaysia29University of Cambridge, UK23
R = Rank; P = Number of Publications; Freq. = Frequencies of appearance.
Table
Table 6. Top ten most cited papers.
Table 6. Top ten most cited papers.
RPaper TitleCitationsYearC/YCountrySource-Publisher
1Microbial carbonate precipitation in construction materials: A review [29]820201074.5BelgiumEcological Engineering—Elsevier
2Application of bacteria as self-healing agent for the development of sustainable concrete [30]770201070.0BelgiumEcological Engineering—Elsevier
3Self-Healing Materials [31]763201069.4GermanyAdvanced Materials—Wiley Online Library
4Water Permeability and Autogenous Healing of Cracks in Concrete [32]628199928.5DenmarkMaterials Journal—American Concrete Institute
5Quantification of crack-healing in novel bacteria-based self-healing concrete [33]582201158.2NetherlandsCement and Concrete Composites—Elsevier
6Self-Healing in Cementitious Materials—A Review [34]486201360.8BelgiumMaterials—MDPI
7Self-healing concrete by use of microencapsulated bacterial spores [14]471201467.3BelgiumCement and Concrete Research—Elsevier
8Use of silica gel or polyurethane immobilized bacteria for self-healing concrete [35]415201246.1BelgiumConstruction & Building Materials—Elsevier
9Permeability and self-healing of cracked concrete as a function of temperature and crack width [36]408200322.7GermanyCement and Concrete Research—Elsevier
10Application of hydrogel encapsulated carbonate precipitating bacteria for approaching a realistic self-healing in concrete [37]281201440.1BelgiumConstruction & Building Materials—Elsevier
R = Rank, C/Y = Citation per year.
Table
Table 7. Top ten countries based on the total number of citations.
Table 7. Top ten countries based on the total number of citations.
CountryTotal CitationsCitations per Published Articles *
Belgium628869.10
China431120.14
USA359437.44
Netherlands340758.74
Germany154557.22
India147915.57
United Kingdom117821.04
Japan95634.14
Italy88123.81
France82555.00
* Citations per published articles = Total citations/Number of publications (listed in Table 5).
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MDPI and ACS Style

Alzard, M.H.; El-Hassan, H.; El-Maaddawy, T.; Alsalami, M.; Abdulrahman, F.; Hassan, A.A. A Bibliometric Analysis of the Studies on Self-Healing Concrete Published between 1974 and 2021. Sustainability 2022, 14, 11646. https://doi.org/10.3390/su141811646

AMA Style

Alzard MH, El-Hassan H, El-Maaddawy T, Alsalami M, Abdulrahman F, Hassan AA. A Bibliometric Analysis of the Studies on Self-Healing Concrete Published between 1974 and 2021. Sustainability. 2022; 14(18):11646. https://doi.org/10.3390/su141811646

Chicago/Turabian Style

Alzard, Mohammed H., Hilal El-Hassan, Tamer El-Maaddawy, Marwa Alsalami, Fatma Abdulrahman, and Ashraf Aly Hassan. 2022. "A Bibliometric Analysis of the Studies on Self-Healing Concrete Published between 1974 and 2021" Sustainability 14, no. 18: 11646. https://doi.org/10.3390/su141811646

APA Style

Alzard, M. H., El-Hassan, H., El-Maaddawy, T., Alsalami, M., Abdulrahman, F., & Hassan, A. A. (2022). A Bibliometric Analysis of the Studies on Self-Healing Concrete Published between 1974 and 2021. Sustainability, 14(18), 11646. https://doi.org/10.3390/su141811646

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