Bibliometric analysis of artificial intelligence in high-to-room temperature superconductors: insights from the Scopus database

Purpose
This bibliometric analysis aims to comprehensively explore the intersection of artificial intelligence (AI) and high-to-room-temperature superconductors. Focusing on scientific literature, the study investigates trends, collaboration patterns and impactful publications in this interdisciplinary field.

Design/methodology/approach
The research employs an advanced search query in the Scopus database, targeting articles on the development of superconductors using artificial intelligence. Data collection involves executing the query, saving the results as a CSV file and analyzing it using R-Studio and VOSviewer. Statistical tools, T-tests, regression analysis and Python coding are utilized to enhance the depth of analysis.

Findings
The analysis spans various dimensions, including the overview of bibliometric characteristics, annual scientific production, average citations per year, sources of publications and source production over time. Noteworthy findings include a sustained growth in annual scientific production, a peak in average citations in specific years and the identification of influential journals shaping the field.

Research limitations/implications
While the analysis provides valuable insights, limitations include the potential influence of research biases and the exclusion of non-English articles. Further exploration is encouraged to address these limitations and gain a more nuanced understanding of the field.

Practical implications
Practically, this study aids researchers, practitioners and stakeholders in staying informed, identifying collaboration opportunities and contributing meaningfully to the ongoing growth and impact of high-to-room-temperature superconductors using artificial intelligence.

Social implications
Socially, the study underscores the collaborative and global nature of research in this field, emphasizing the shared endeavor worldwide to advance the understanding and application of superconductors through artificial intelligence.

Originality/value
This research contributes to the originality of the scientific landscape by offering a comprehensive analysis of the development of high-to-room-temperature superconductors with artificial intelligence. The utilization of advanced bibliometric techniques and the identification of key trends and sources enhance the understanding of this emerging and interdisciplinary research domain.