Results 201 to 210 of about 56,420 (266)

Data‐Guided Photocatalysis: Supervised Machine Learning in Water Splitting and CO2 Conversion

Advanced Intelligent Discovery, EarlyView.
This review highlights recent advances in supervised machine learning (ML) for photocatalysis, emphasizing methods to optimize photocatalyst properties and design materials for solar‐driven water splitting and CO2 reduction. Key applications, challenges, and future directions are discussed, offering a practical framework for integrating ML into the ...
Paul Rossener Regonia, Christian Mark Pelicano   +1 more
wiley   +1 more source

Bayesian Optimization for High-Dimensional Coarse-Grained Model Parameterization: A Case Study on Pebax Polymer. [PDF]

J Chem Theory Comput
Martins CA, Damasceno DA, Hue KY, Rodrigues Miranda C, Müller EA, Vargas-Hernández RA.   +5 more
europepmc   +1 more source

Factorization Machine‐Based Active Learning for Functional Materials Design with Optimal Initial Data

Advanced Intelligent Discovery, EarlyView.
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

Batched Bayesian Optimization by Maximizing the Probability of Including the Optimum. [PDF]

J Chem Inf Model
Fromer J, Wang R, Manjrekar M, Tripp A, Hernández-Lobato JM, Coley CW.   +5 more
europepmc   +1 more source

FastCat: Autonomous Discovery of Multielement Layered Double Hydroxide Alloy Catalysts for Alkaline Oxygen Evolution Reaction

Advanced Intelligent Discovery, EarlyView.
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, Enzo Raffaele Moretti, Jin Hyun Chang, Tejs Vegge   +3 more
wiley   +1 more source

Organic photovoltaic prediction model based on Bayesian optimization and explainable AI. [PDF]

Sci Rep
Abdelghafar S, Alshater H, Abouelmagd LM, Darwish A, Hassanien AE.   +4 more
europepmc   +1 more source

Bayesian Exploration of Metal‐Organic Framework‐Derived Nanocomposites for High‐Performance Supercapacitors

Advanced Intelligent Discovery, EarlyView.
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, Pritam Banerjee, Felipe Jacques Lima Duarte, Joerg R. Jinschek, Premkumar Murugesan, Babak Rezaei, Stephan Sylvest Keller, Roland A. Fischer, Mian Zahid Hussain   +8 more
wiley   +1 more source

Tuning Deep Learning for Predicting Aluminum Prices Under Different Sampling: Bayesian Optimization Versus Random Search. [PDF]

Entropy (Basel)
Antonio Figueroa AE, Lahmiri S.
europepmc   +1 more source

Advances in Thermal Modeling and Simulation of Lithium‐Ion Batteries with Machine Learning Approaches

Advanced Intelligent Discovery, EarlyView.
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, Kang Fu, Junjie Ding, Kai Sun, Peng Tan   +4 more
wiley   +1 more source

Dual-metric Bayesian optimization of B-spline mesh size for 4DCT lung registration. [PDF]

Eur J Radiol Open
Tan L, Chen L, Luo H, Yang X, Feng B, Jin F.   +5 more
europepmc   +1 more source