[HTML][HTML] Bayesian optimization as a flexible and efficient design framework for sustainable process systems

JA Paulson, C Tsay - Current Opinion in Green and Sustainable Chemistry, 2024 - Elsevier
Bayesian optimization (BO) is a powerful technology for optimizing noisy expensive-to-
evaluate black-box functions, with a broad range of real-world applications in science …

Cost-informed Bayesian reaction optimization

AA Schoepfer, J Weinreich, R Laplaza, J Waser… - Digital …, 2024 - pubs.rsc.org
Bayesian optimization (BO) is an efficient method for solving complex optimization problems,
including those in chemical research, where it is gaining significant popularity. Although …

Accelerating reaction optimization through data-rich experimentation and machine-assisted process development

JP McMullen, JA Jurica - Reaction Chemistry & Engineering, 2024 - pubs.rsc.org
The field of reaction engineering is in a constant state of evolution, adapting to new
technologies and the changing demands of process development on accelerated timelines …

Dynamic flow experiments for Bayesian optimization of a single process objective

F Florit, KY Nandiwale, CT Armstrong… - Reaction Chemistry & …, 2025 - pubs.rsc.org
A new method, named dynamic experiment optimization (DynO), is developed for the current
needs of chemical reaction optimization by leveraging for the first time both Bayesian …

A parallel chemical reaction optimization method based on preference-based multi-objective expected improvement

M Jiang, Z Wang, Z Sun, J Wang - Chinese Journal of Chemical …, 2025 - Elsevier
Optimizing chemical reaction parameters is an expensive optimization problem. Each
experiment takes a long time and the raw materials are expensive. High-throughput …

SANE: Strategic Autonomous Non-Smooth Exploration for Multiple Optima Discovery in Multi-modal and Non-differentiable Black-box Functions

A Biswas, R Vasudevan, R Pant, I Takeuchi… - arxiv preprint arxiv …, 2024 - arxiv.org
Both computational and experimental material discovery bring forth the challenge of
exploring multidimensional and multimodal parameter spaces, such as phase diagrams of …