Results 181 to 190 of about 6,363 (257)

Stable and Highly Efficient Photocatalysis with Two-Dimensional Organic-Inorganic Hybrid Perovskites. [PDF]

ACS Omega
Wang M, Zhang X, Liu L, Zhang X, Yan J, Jin W, Zhang P, Wang J.   +7 more
europepmc   +1 more source

A Generalized Framework for Data‐Efficient and Extrapolative Materials Discovery for Gas Separation

Advanced Intelligent Discovery, EarlyView.
This study introduces an iterative supervised machine learning framework for metal‐organic framework (MOF) discovery. The approach identifies over 97% of the best performing candidates while using less than 10% of available data. It generalizes across diverse MOF databases and gas separation scenarios.
Varad Daoo, Jayant K. Singh
wiley   +1 more source

Effect of Dual-Organic Cations on the Structure and Properties of 2D Hybrid Perovskites as Scintillators. [PDF]

ACS Appl Mater Interfaces
Kuddus Sheikh MA, Maddalena F, Kowal D, Makowski M, Mahato S, Jȩdrzejewski R, Bhattarai R, Witkowski ME, Drozdowski KJ, Drozdowski W, Dang C, Rhone TD, Birowosuto MD.   +12 more
europepmc   +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

Tuning Electronic and Optical Properties of 2D/3D Interfaces of Hybrid Perovskites through Interfacial Charge Transfer: Prediction of Higher-Efficiency Interface Solar Cells Using Hybrid-DFT Methods. [PDF]

ACS Appl Mater Interfaces
Banerjee H, Nazeeruddin MK, Chakraborty S.   +2 more
europepmc   +1 more source

Discovery of Novel Materials with Giant Dielectric Constants via First‐Principles Phonon Calculations and Machine Learning

Advanced Intelligent Discovery, EarlyView.
We discovered novel materials with giant dielectric constants by combining first‐principles phonon calculations and machine learning. Screening 525 perovskites identified six candidates. RbNbO3 was synthesized under pressure and showed ε ≈ 800–1000. This validates our framework as a powerful tool for high‐performance dielectric materials discovery.
Hiroki Moriwake, Kazuki Shitara, Rie Yokoi, Takeharu Kato, Isao Tanaka, Ayako Yamamoto, Kimitoshi Murase, Yosuke Hamasaiki, Yoshitaka Ehara, Mitsuru Itoh   +9 more
wiley   +1 more source

Cation Dynamics as Structure Explorer in Hybrid Perovskites-The Case of MAPbI₃. [PDF]

Cryst Growth Des
Drużbicki K, Gila-Herranz P, Marin-Villa P, Gaboardi M, Armstrong J, Fernandez-Alonso F.   +5 more
europepmc   +1 more source

Toward Capacitive In‐Memory‐Computing: A Device to Systems Level Perspective on the Future of Artificial Intelligence Hardware

Advanced Intelligent Discovery, EarlyView.
Capacitive, charge‐domain compute‐in‐memory (CIM) stores weights as capacitance,eliminating DC sneak paths and IR‐drop, yielding near‐zero standbypower. In this perspective, we present a device to systems level performance analysis of most promising architectures and predict apathway for upscaling capacitive CIM for sustainable edge computing ...
Kapil Bhardwaj, Ella Paasio, Sayani Majumdar   +2 more
wiley   +1 more source

Elucidating the Non-Covalent Interactions that Trigger Interdigitation in Lead-Halide Layered Hybrid Perovskites. [PDF]

Inorg Chem
Maufort A, Cerdá J, Van Hecke K, Deduytsche D, Verding A, Ruttens B, Li W, Detavernier C, Lutsen L, Quarti C, Vanderzande D, Beljonne D, Van Gompel WTM.   +12 more
europepmc   +1 more source

Gaussian Process Regression–Neural Network Hybrid with Optimized Redundant Coordinates: A New Simple Yet Potent Tool for Scientist's Machine Learning Toolbox

Advanced Intelligent Discovery, EarlyView.
A machine learning method, opt‐GPRNN, is presented that combines the advantages of neural networks and kernel regressions. It is based on additive GPR in optimized redundant coordinates and allows building a representation of the target with a small number of terms while avoiding overfitting when the number of terms is larger than optimal.
Sergei Manzhos, Manabu Ihara
wiley   +1 more source