Exploring chemical reaction space with machine learning models: Representation and feature perspective
Chemical reactions serve as foundational building blocks for organic chemistry and drug
design. In the era of large AI models, data-driven approaches have emerged to innovate the …
design. In the era of large AI models, data-driven approaches have emerged to innovate the …
Optimized machine learning techniques enable prediction of organic dyes photophysical properties: Absorption wavelengths, emission wavelengths, and quantum …
Applications of organic dyes, ranging from basic research to industry, are functions of their
photophysical properties. Two important aspects—(1) knowledge of the photophysical …
photophysical properties. Two important aspects—(1) knowledge of the photophysical …
Machine Learning Enables a Top-Down Approach to Mechanistic Elucidation
General reaction behavior is rarely reported in asymmetric catalysis, not simply because it is
difficult to achieve, but also due to the methods used for its identification and study …
difficult to achieve, but also due to the methods used for its identification and study …
Computational predictions and reactivity analyses of organic reactions
CC Lam - 2024 - repository.cam.ac.uk
This thesis focuses on computational reactivity analyses and predictions for organic
systems. The research began with studies on specific reactions using quantum mechanics …
systems. The research began with studies on specific reactions using quantum mechanics …