Teaching Process-Based Clay Modification: An AI-Based Illustrative Approach for Environmental and Technical Applications

The rapid expansion and structural complexity of applied clay science create a pressing need for process-oriented educational frameworks to replace traditional descriptive instruction. To address this challenge, this technical note introduces an illustrative, process-based approach supported by generative artificial intelligence (AI) tools to clarify clay mineral modification pathways. Utilizing AI-enhanced prompt workflows integrated with literature synthesis, we developed a systematic "toolbox" framework that visually categorizes key physical and chemical pathways, including acid/alkali etching, thermal activation, mechanochemical milling, organo-functionalisation, and nanoparticle decoration; They link directly to property outcomes and target applications. Furthermore, we map the innovation pathway from laboratory synthesis to commercial production, detailing critical high-attrition failure points along the translation process. This AI-powered visual strategy bridges fundamental clay mineralogy with real-world technological, environmental, and agricultural applications.