Results 271 to 280 of about 156,150 (344)

Harnessing Machine Learning to Understand and Design Disordered Solids

Advanced Intelligent Discovery, EarlyView.
This review maps the dynamic evolution of machine learning in disordered solids, from structural representations to generative modeling. It explores how deep learning and model explainability transform property prediction into profound physical insight.
Muchen Wang, Yue Fan
wiley   +1 more source

Promotional Effect of Mn On NH₃ Synthesis Over Inverse Iron Catalyst. [PDF]

ChemSusChem
Jing Y, Hattori M, Hara M.
europepmc   +1 more source

Multi‐Property Machine Learning Models to Accelerate the Transition Toward Bio‐Based Emulsion Polymers

Advanced Intelligent Discovery, EarlyView.
A machine learning framework simultaneously predicts four critical properties of monomers for emulsion polymerization: propagation rate constant, reactivity ratios, glass transition temperature, and water solubility. These tools can be used to systematically identify viable bio‐based monomer pairs as replacements for conventional formulations, with ...
Kiarash Farajzadehahary, Nicholas Ballard   +1 more
wiley   +1 more source

Origin of giant dielectric permittivity and localized polaron-supported electrical conduction in CaCu₃Ti₄O₁₂ for extreme environment energy storage applications. [PDF]

Sci Rep
Karmakar S, Ashok K, Basha NH, Koochana PK, Boddhula R, Patwari M, Rajashekhar G, Kar B, Mohanty HS, Borkar H.   +9 more
europepmc   +1 more source

Model Arrhenius untuk Pendugaan Laju Respirasi Brokoli Terolah Minimal

, 2016
Nurul Imamah, Rokhani Hasbullah, Lilik Pujantoro Eko Nugroho   +2 more
openalex   +1 more source

Predicting Crystal Structures and Ionic Conductivities in Li3 YCl6−x Brx Halide Solid Electrolytes Using a Fine‐Tuned Machine Learning Interatomic Potential

Advanced Intelligent Systems, EarlyView.
This study refines the Crystal Hamiltonian Graph Network to predict energies, structures, and lithium‐ion dynamics in halide electrolytes. By generating ordered structural models and using an iterative fine‐tuning workflow, we achieve near‐ab initio accuracy for phase stability and ionic transport predictions.
Jonas Böhm, Aurélie Champagne
wiley   +1 more source

Superprotonic Conduction in Donor Co-Doped Perovskites. [PDF]

Angew Chem Int Ed Engl
Umeda K, Saito K, Honda T, Yashima M.
europepmc   +1 more source

Natural Aging of Biomaterials in Ambient and Physiological Environments

Advanced NanoBiomed Research, EarlyView.
Biomaterials used in biomedical applications can change their physical properties over time, even under ambient and physiological conditions. This review highlights key studies on the natural aging of materials ranging from soft hydrogels to metals and ceramics, emphasizing how time‐dependent changes influence function and performance.
Shuyu Zhang, Anne E. Staples
wiley   +1 more source

Threshold-Filtered Kinetic Monte Carlo Simulation for Real-Time Simulation and Control of Biomass Fractionation. [PDF]

Ind Eng Chem Res
Kim J, Ryu J, Yang Q, Yoo CG, Kwon JS.
europepmc   +1 more source