Mesoporous materials are substances whose pores maintain diameters between 2 and 50 nm, according to IUPAC nomenclature. This paper presents a comprehensive scientometrics on the existing trend on mesoporous materials in chemistry. The study uses Web of Science database as the primary source of value added articles and performs different methods for detecting highly cited articles, most active countries, etc. The search of articles using Web of Science was accomplished with two keywords “Mesoporous materials” and “Chemistry”. In Web of Science, there were about 800 articles related to these keywords over the period 1900-2019. Then the articles were arranged according to the citation order in non-increasing order, and among them, we found about 200 highly cited articles. According to our survey, green chemistry, water, heterogeneous catalysis and aqueous-solution build a structure on mesoporous materials. Moreover, conversion, guest molecules, triblock, oxidation, heterogeneous catalysts set the corner of other structure of the study. The survey also indicates that there were three clusters associated with mesoporous materials in chemistry. In the first cluster silica appears to be the most important word followed by molecularsieves and MCM-41. Organic-group is the most important word in the second cluster followed by hybrid materials. In cluster 3, nanoparticles appears to be the most important word followed by functionalization. In our study, absorption, nanoparticles and drug-delivery are detected as the emerging keywords and future studies could be concentrated on these subjects.

Metal–organic frameworks (MOFs) are combinations of metal ions or clusters accommodated to organic ligands to shape different dimensional structures. MOFs are considered as a subclass of coordination polymers, with the possible characteristics that they are normally porous. The metals are considered to offer flexible, co-ordination environment under virtually various topologies. Besides, because of the usual liability of metal complexes, the shape of the coordination bonds between the metal ions and the organic linkers can be reversible and this helps the rearrangement of metal ions and organic linkers through the process of polymerization to give highly ordered framework structures. The study has indicated that MOFs has maintained extensive applications in Biological imaging and sensing, Drug delivery systems, Methane storage, Semiconductors, Bio-mimetic mineralization, Carbon capture, Desalination/ion separation, Water vapor capture and Ferroelectrics and Multiferroics. This paper presents a scientometrics study on 1273 papers published articles, books, patents, etc. indexed in Web of Science database over the period 2001-2019. The study presents the most popular keywords used in the literature, determines the network of scientific scholars and discusses the clusters of keywords used for different surveys. The results indicate that metalorganic frameworks and zeoitic imidazolate frameworks are two keywords considered as motor keywords in MOFs studies.

During the past century, humans have increased atmospheric CO₂ concentration by at least a third, which is considered as the most important long-lived “forcing” of climate change. Scientists all over the world are responsible to do their best on offering practical solutions to reduce the effects of CO₂ on environment. This paper uses data envelopment analysis to measure the effects of researches accomplished by scientists from 30 countries which are representative of producing over 80% of CO₂ in the world. The study uses 10034 articles published in Scopus database from 1959 to March, 2019. The study uses the amount of CO₂ produced by each country as the input and total publications, h-index and I-10 as the output of the DEA model. The results indicate that despite the fact that China was responsible for producing nearly 30% of the CO₂, the scientists of this country contributed the least on carbon dioxide emissions. In addition, United Kingdom was responsible for about one percent of CO₂ emissions but the researchers of UK performed the best in terms of offering good quality studies.

In project management, a schedule is considered as a list a project's milestones, activities, and deliverables, normally with some start and finish time schedule, which are estimated by some information incorporated in the project schedule including resource allocation, budget, task duration, and linkages of dependencies and scheduled events. This paper presents a comprehensive review of the studies associated with project scheduling. The study uses Scopus database as a primary search engine and covers 3370 records over the period 1963-2019. The records are statistically analyzed and categorized in terms of different criteria. Based on the survey, "decision support systems" is the keyword which has carried the highest densities followed by heuristics methods. Among the most cited articles, papers published by researchers in Germany have received the highest citations (9084), followed by United States (7058) and Belgium with 4853 citations.

The purpose of this research is to study the role of the social media for knowledge sharing. The study presents a comprehensive review of the researches associated with the effect of knowledge management in social media. The study uses Scopus database as a primary search engine and covers 1858 of highly cited articles over the period 1994-2019. The records are statistically analyzed and categorized in terms of various criteria using an open source software package named R. The findings show that researches have grown exponentially during the recent years and the trend has continued at relatively stable rates. Based on the survey, knowledge management is the keyword which has carried the highest citations followed by social media and social networking. Among the most cited articles, papers published by researchers in United States have received the highest citations, followed by United Kingdom and China.

The purpose of this research is to investigate the status and the evolution of the scientific studies for the effect of social networks on big data and usage of big data for modeling the social net-works users’ behavior. This paper presents a comprehensive review of the studies associated with big data in social media. The study uses Scopus database as a primary search engine and covers 2000 of highly cited articles over the period 2012-2019. The records are statistically analyzed and categorized in terms of different criteria. The findings show that researches have grown exponentially since 2014 and the trend has continued at relatively stable rates. Based on the survey, decision support systems is the keyword which has carried the highest densities followed by heuristics methods. Among the most cited articles, papers published by researchers in United States have received the highest citations (7548), followed by United Kingdom (588) and China with 543 citations. Thematic analysis shows that the subject nearly maintained an important and well-developed research field and for better results we can merge our research with “big data analytics” and “twitter” that are important topics in this field but not developed well.

The purpose of this research is to investigate the status and the evolution of the scientific studies on the effect of social networks on e-commerce. The study seeks to address the status of a set of scientific productions of researchers in the world indexed in Scopus based on scientometrics indicators. In total, 1926 articles were found and the collected data were analyzed using quantitative and qualitative indicators of scientometrics with bibliometrix R software package. The findings show that researches have grown exponentially since 2009 and the trend has continued at relatively stable rates. Thematic analysis shows that the subject had a significant but not well-developed research field. There is a high rate of cooperation with a rich research network among institutions in United States, European and Asian countries. Studies also show that research interest in this area is prevalent in developed countries. In addition, the lack of funds and complex analytical tools may be due to lack of studies in developing countries, especially in Africa. The study of the global trend of research through scientometrics helps managers and researchers in identifying countries and institutions with the greatest potential for scientific production, which allows them to develop their professions.

Digital twin technology, which creates virtual replicas of physical entities, has emerged as a transformative paradigm in healthcare engineering, enabling personalized medicine, surgical simulation, and real-time patient monitoring. This study presents a comprehensive scien-tometric analysis of 200 highly cited articles retrieved from Scopus using a targeted search string focused on digital twins, virtual patients, and patient avatars in healthcare. The analysis characterizes publication trends, citation impact, leading contributors, thematic clusters, and collaborative networks. Results indicate that research output has accelerated dramatically since 2019, with 2021–2024 representing the most productive period. The highest citation concentrations are found in studies applying digital twins to cardiology, oncology, surgical planning, and healthcare system optimization. The United States, China, Germany, and the United Kingdom dominate production, with strong interdisciplinary collaborations among en-gineering, computer science, and clinical departments. Co-occurrence analysis of author keywords reveals six major thematic clusters: cardiovascular digital twins, surgical simulation and virtual patients, personalized and precision medicine, enabling technologies (IoT, AI, blockchain), healthcare system digital twins, and ethical and regulatory considerations. This scientometric mapping provides researchers, clinicians, and policymakers with an evidence-based roadmap of a rapidly evolving field positioned at the intersection of engineering and medicine.

Waste management has evolved from a local sanitation issue to a global interdisciplinary challenge, integral to circular economies, public health, and climate change mitigation. This scientometric survey analyzes the intellectual landscape of highly cited waste management research. Using a dataset of two hundred highly cited documents retrieved from Scopus, this study employs performance analysis and science mapping techniques to examine publication trends, influential authors, core journals, and dominant research themes. The analysis reveals a significant concentration of influence among a limited number of authors and journals, with a marked increase in publications after 2015. The intellectual structure is anchored by several major themes: plastic and microplastic pollution, circular economy frameworks, biological treatment technologies (anaerobic digestion, composting), chemical and thermal conversion (pyrolysis, gasification), material-specific recycling (e-waste, construction and demolition waste, batteries, steel slags), and advanced wastewater and soil remediation. A notable focus on the environmental and health impacts of pollutants, particularly from plastics and pharmaceuticals, coexists with technological solutionism. The field is shifting from end-of-pipe solutions to upstream strategies like prevention and circular design. Future research must prioritize the social and economic dimensions of implementation, develop standardized methods for emerging contaminants like microplastics, and address the challenges exacerbated by crises like the COVID-19 pandemic.

Heart disease is one of the most common causes for death among human nations for many years. There have been substantial efforts to reduce heart diseases in the world. It is essential to implement the recent advances of data science to discover any symptoms of cardiovascular disease (CVD). Machine learning (ML) has given scientists a tool to detect early causes of such disease and this survey uses the combination of ML and CVD as a search keyword to determine 200 highly cited articles from the Scopus database. The study performs a survey on the data which were published from 2018 to 2025 and present possible road-map for future studies. The results indicate that a significant number of highly cited articles are published in Open Access journals such as PlosOne, IEEE Access and Scientific Report. In addition, the study presents seven different areas of research which have been under significant progress.