Results 131 to 140 of about 288,690 (232)
This work investigates the optimal initial data size for surrogate‐based active learning in functional material optimization. Using factorization machine (FM)‐based quadratic unconstrained binary optimization (QUBO) surrogates and averaged piecewise linear regression, we show that adequate initial data accelerates convergence, enhances efficiency, and ...
Seongmin Kim, In‐Saeng Suh
wiley +1 more source
Accelerate Flash Removal of PFAS from Soil by Human-Guided Bayesian Optimization and Interpretable Machine Learning. [PDF]
Qin J +5 more
europepmc +1 more source
A machine learning‐guided self‐driving laboratory screened over 500 nickel‐based layered double‐hydroxide catalysts for alkaline oxygen evolution. Out of the eight metals, the robot uncovered a quaternary Ni–Fe–Cr–Co catalysts requiring only 231 mV overpotential to reach 20 mA cm−2.
Nis Fisker‐Bødker +3 more
wiley +1 more source
An AI‐assisted approach is introduced to decode synthesis–performance relationships in metal‐organic framework‐derived supercapacitor materials using Bayesian optimization and predictive modeling, streamlining the search for optimal energy storage properties.
David Gryc +8 more
wiley +1 more source
Autonomous Bayesian Optimization-Based Control System for Droplet Generation. [PDF]
Cho S, Kim H, Shin S, Lee M, Lee J.
europepmc +1 more source
Heat generation in lithium‐ion batteries affects performance, aging, and safety, requiring accurate thermal modeling. Traditional methods face efficiency and adaptability challenges. This article reviews machine learning‐based and hybrid modeling approaches, integrating data and physics to improve parameter estimation and temperature prediction ...
Qi Lin +4 more
wiley +1 more source
Interpretable Bayesian optimization for catalyst discovery.
Nair AS, Foppa L, Scheffler M.
europepmc +1 more source
Optimized CNN framework with VGG19, EfficientNet, and Bayesian optimization for early colon cancer detection. [PDF]
Rahman T +7 more
europepmc +1 more source
This article establishes a Taguchi–Bayesian sampling strategy to reconstruct polymer processing–property landscape at minimal sampling cost, generically building the roadmap for materials database construction from sampling their vast design space. This sampling strategy is featured by an alternating lesson between uniformity and representativeness ...
Han Liu, Liantang Li
wiley +1 more source
Part-level 3D shape generation driven by user intention inference with preferential Bayesian optimization. [PDF]
Lee SW, Choi J, Hyun KH.
europepmc +1 more source

