## 2 Methodology  
Within a landscape characterized by a notable surge in academic publications and segmented research streams, bibliometrics presents a robust methodology, facilitating a systematic, transparent, and replicable review process. Its relevance has magnified in an era of exponential information growth, nuanced conceptual advancements, and burgeoning data. Hence, structured analysis employing a wide spectrum of information becomes an influential instrument, yielding substantial contributions to scientific cartography. Bibliometric analysis is a cornerstone in unveiling temporal patterns, evolving research themes, and shifts within disciplinary confines, simultaneously spotlighting distinguished researchers and academic institutions. This technique offers a panoramic view of current research, delivering evidence-based insights that shape professional practice and bolster expert judgment. Adopting bibliometrics enables a more expansive and precise comprehension of the scholarly terrain, thereby fostering data-driven decisions and unveiling gaps in existing knowledge. Specifically, bibliometric analysis is based on the exploratory analysis of one or more databases of articles, and after defining a theme to be analyzed, the steps can be divided as follows [2]:  
1. Selection of one or more databases to be searched;
2. Definition of keywords;
3. Search in the database for various combinations;
4. Compilation of metadata and export to Bibitex;
5. Evaluation of citations;
6. Thematic analysis;
7. Graphical analysis. These steps can be performed iteratively with the others until the theme analysis is exhausted. This work used bibliometric analysis to filter and analyze the AR and DT literature related to chemical engineering. In the context of our methodology, bibliometric analysis integrates several components to map and interpret the academic landscape systematically. It establishes a metadatabase, starting with bibliographic data collection, allowing for citation analysis to gauge individual publications' influence. Co-citation and co-authorship analyses build on this by revealing thematic clusters, foundational studies, and collaboration networks, thus illustrating both intellectual and social structures within the field. Keyword analysis then identifies key themes and emerging topics, while data visualization synthesizes these findings into clear, interpretable patterns. The main components of bibliometric analysis typically include the following:  
1. Bibliographic Data Collection: The first step in a bibliometric analysis is gathering the bibliographic data. This involves identifying and extracting metadata from relevant academic sources. 2. Citation Analysis: Citation analysis explores a publication's impact and influence by evaluating its citations' frequency and patterns in other works. Co-citation Analysis: This component examines how frequently two works are cited together, which can identify core papers in a field or reveal relationships between different works. * Co-authorship Analysis: This part of the analysis examines collaboration between researchers, institutions, or countries, offering insights into the social structure of research fields. * Keyword Analysis: This step helps identify prominent themes and trends in a field over time, aiding in the discovery of emerging topics and the evolution of existing ones. * Visualization of Bibliometric Data: The final component is the visualization of the derived bibliometric data, which aids in interpreting the relationships, trends, and patterns identified in the analysis. By incorporating bibliometric analysis into our methodology, we enable a rigorous and objective assessment of the academic field under study. This provides valuable insights to guide future research, inform policy and decision making, and contribute to our understanding of scientific knowledge production and dissemination dynamics.