[Book] Case Studies of Bayesian Optimization (No. 2286)

[Available for trial reading] Material exploration / Property prediction / Optimization of formulation and process conditions

★ Explanation of the selection and determination points for multiple material properties related to objective and explanatory variables! －－－－－－－－－－－－－－－－－－－－－ ■ Key Points of This Book Exploration of new materials, automation and acceleration of formulation design - Optimization of multiple material composition ratios - Extraction of desired material properties from limited experimental data - Improvement of model accuracy through descriptor selection - Discovery of unknown components through the fusion of domain knowledge Practical informatics for process and equipment development - Quantification of the tacit knowledge of experienced engineers - Setting the exploration space and selecting initial data - Measures against temperature changes, equipment variability, measurement errors, etc. - Detailed explanation of tips for choosing surrogate models Utilization and operational examples - Monomer sequences of biodegradable polymers - Prediction of tensile strength of synthetic rubber - Development of CO₂ resource recycling catalysts - Development of low-temperature manufacturing processes for ceramics - Exploration and selection of pharmaceutical additives formulations

Technical and Reference Books