Results 131 to 140 of about 51,507 (261)

Smart Exploration of Perovskite Photovoltaics: From AI Driven Discovery to Autonomous Laboratories

Advanced Energy Materials, EarlyView.
In this review, we summarize the fundamentals of AI in automated materials science, and review AI applications in perovskite solar cells. Then, we sum up recent progress in AI‐guided manufacturing optimization, and highlight AI‐driven high‐throughput and autonomous laboratories.
Wenning Chen, Zheyu Zhang, Kelvian T. Mularso, Bonghyun Jo, Hyun Suk Jung   +4 more
wiley   +1 more source

Data variability in neural network Bayesian inference

Physical Review Research
Bayesian inference and kernel methods are well established in machine learning. The neural network Gaussian process in particular provides a concept to investigate neural networks in the limit of infinitely wide hidden layers by using kernel and ...
Javed Lindner, David Dahmen, Michael Krämer, Moritz Helias   +3 more
doaj   +1 more source

Machine Learning Interatomic Potentials for Energy Materials: Architectures, Training Strategies, and Applications

Advanced Energy Materials, EarlyView.
Machine learning interatomic potentials bridge quantum accuracy and computational efficiency for materials discovery. Architectures from Gaussian process regression to equivariant graph neural networks, training strategies including active learning and foundation models, and applications in solid‐state electrolytes, batteries, electrocatalysts ...
In Kee Park, Saeed Pourasad, Jinhong Mun, Arunkumar Chitteth Rajan, Tae Hyeon Park, Anand Rohit, Mohammad Zafari, Tan‐Lien Pham, Eunjae Jung, Bonseung Koo, Miran Ha, Gi Beom Sim, Hyun Gyu Park, Won Woong Choi, Kwanghyeon Jo, Soohaeng Yoo Willow, David ChangMo Yang, Chang Woo Myung, Geunsik Lee, Kwang S. Kim   +19 more
wiley   +1 more source

Physics‐encoded transfer learning for scale‐up modeling of CHO cell bioreactors

AIChE Journal, EarlyView.
Abstract Developing reliable predictive models for mammalian cell bioreactors, particularly Chinese hamster ovary (CHO) cultures widely used in biopharmaceutical manufacturing, remains challenging due to severe data scarcity in industrial‐scale reactors.
Muyang Li, Ming Xiao, Zhe Wu
wiley   +1 more source

Triple equivalence for the emergence of biological intelligence

Communications Physics
Intelligent algorithms developed evolutionarily within neural systems are considered in this work. Mathematical analyses unveil a triple equivalence between canonical neural networks, variational Bayesian inference under a class of partially observable ...
Takuya Isomura
doaj   +1 more source

Toward Knowledge‐Guided AI for Inverse Design in Manufacturing: A Perspective on Domain, Physics, and Human–AI Synergy

Advanced Intelligent Discovery, EarlyView.
This perspective highlights how knowledge‐guided artificial intelligence can address key challenges in manufacturing inverse design, including high‐dimensional search spaces, limited data, and process constraints. It focused on three complementary pillars—expert‐guided problem definition, physics‐informed machine learning, and large language model ...
Hugon Lee, Hyeonbin Moon, Junhyeong Lee, Seunghwa Ryu   +3 more
wiley   +1 more source

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

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

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

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