From Arrhenius to Artificial Intelligence: The evolution of acid-base theories in modern chemistry

Background and Objectives: The study of acids and bases, as one of the central concepts of chemistry, has undergone a profound transformation from initial qualitative descriptions to complex quantitative models. This review article is designed to systematically examine the evolution of acid and base theories from elementary definitions to modern computational approaches and artificial intelligence (AI). The main focus is on analyzing historical milestones, identifying the limitations of each theory, and evaluating practical applications in various scientific and industrial fields. The study also explores the potential of computational approaches in modern chemistry education, particularly focusing on acid-base concepts. Methods: This study used a review-analytical research method. By comprehensively searching reputable databases, relevant scientific articles, and sources from the early years to the most recent studies were collected and reviewed. The research process included careful screening, critical evaluation, and qualitative and quantitative content analysis. Findings: The results of this study demonstrate that combining classical theories with advanced computational methods has led to a fundamental transformation in the prediction and understanding of acid and base behavior. The most significant accomplishments include the development of highly precise targeted medicine designs, smart catalysts with remarkable efficiency, and novel environmental technologies. However, significant issues still need to be addressed in the areas of energy consumption, material stability in challenging operating environments, and the interpretability of intricate models. Conclusion: Developing cutting-edge materials with self-healing properties which are capable of autonomously detecting and recovering from damage, enhancing interdisciplinary partnerships, and creating more precise and useful computational models are all necessary for the field's future study. The above approach can effectively address current issues and push the limits of current understanding in this area.