Division/Committee: [I&EC] Division of Industrial and Engineering Chemistry

Soft material includes surfactant, polymer, soft assembly and complex, nanoparticle, organic small molecule, pharmaceutical compound, protein, and more. It governs many important performances and applications that are critical in Nature and in our society. Data Analytics and AI are expected to rapidly revolutionize our current technologies and chemistries in soft materials. This symposium aims to collect the most recent updates on data analytics and AI for soft materials. These updates can be divided into four Sessions: 1) Manufacturing, 2) Healthcare, 3) Fundamental Understanding, and 4) Other related topics. The specific areas of research can include but not limited to: • Theory and modeling of soft material • Fundamental understanding of driving forces and mechanism for soft material in manufacturing and healthcare • Data analytics and AI in synthesis of novel soft materials for self-assembly, crystallization, patterning • Time series analysis of sensors, energy storage and energy harvest devices • Process optimization for electronics • Anomaly detection, casual inference, uncertainty quantification, risk assessment for manufacturing and healthcare • Data analytics and AI for new characterization, monitoring, process control, in-situ or in-operando techniques including deep learning of medical imaging • Data analytics and AI for structure–property correlations of soft materials in healthcare and manufacturing. • Supervised and Unsupervised Machine learning and AI for soft material and healthcare • Data analytics and AI for flow chemistry, 3D printing, and other soft material processes • Potential applications of data analytics and AI for soft materials in manufacturing and healthcare

jihua chen

Oak Ridge National Laboratory

Appearances