Results 171 to 180 of about 22,587 (278)

Lattice Coherency‐Driven (111)‐Oriented Wide Bandgap Perovskite Films

open access: yesAdvanced Energy Materials, EarlyView.
Methylammonium lead chloride (MAPbCl3)‐derived seed templates regulate wide‐bandgap perovskite crystallization through coupled thermodynamic and kinetic effects. Lattice‐coherent templating lowers the energy cost for (111) epilayer growth, while growth retardation controls crystallization kinetics, ultimately producing highly crystalline face‐up (111 ...
Yu‐Na Lee   +5 more
wiley   +1 more source

Multiscale Perspectives on Perovskite Instability: From Atomistic Deformation to Device Degradation in Perovskite Solar Cells

open access: yesAdvanced Energy Materials, EarlyView.
Multiscale perspectives on how excess charges in soft lead halide perovskites induce operational instability in photovoltaic devices are presented. Localized carriers formed under thermodynamic non‐equilibrium states modify atomistic interactions and drive lattice distortions, accelerating device degradation.
Joo‐Hong Lee   +6 more
wiley   +1 more source

From continuous to interruptible distillation: Flexible electric heating column architecture with fast start‐up

open access: yesAIChE Journal, EarlyView.
Abstract Electrification of distillation offers a promising route to reducing scope‐1 emissions from one of the chemical industry's most energy‐intensive unit operations. However, conventional adiabatic columns are dynamically inflexible: Long, energy‐intensive start‐ups make shutdown and restart impractical under variable electricity prices and ...
Samuel Mercer, Michael Baldea
wiley   +1 more source

Designing electrolytes by thermodynamics. [PDF]

open access: yesNatl Sci Rev
Wang Y   +5 more
europepmc   +1 more source

A Comprehensive Assessment and Benchmark Study of Large Atomistic Foundation Models for Phonons

open access: yesAdvanced Intelligent Discovery, EarlyView.
We benchmark six large atomistic foundation models on 2429 crystalline materials for phonon transport properties. The rapid development of universal machine learning potentials (uMLPs) has enabled efficient, accurate predictions of diverse material properties across broad chemical spaces.
Md Zaibul Anam   +5 more
wiley   +1 more source

Residue-Level Affinity Decomposition via Quantum Electron Density: A Multivariable Framework Applied to HIV-1 Protease Inhibitors. [PDF]

open access: yesJ Phys Chem B
Gutiérrez-Flores J   +7 more
europepmc   +1 more source

Topology‐Aware Machine Learning for High‐Throughput Screening of MOFs in C8 Aromatic Separation

open access: yesAdvanced Intelligent Discovery, EarlyView.
We screened 15,335 Computation‐Ready, Experimental Metal–Organic Frameworks (CoRE‐MOFs) using a topology‐aware machine learning (ML) model that integrates structural, chemical, pore‐size, and topological descriptors. Top‐performing MOFs exhibit aromatic‐enriched cavities and open metal sites that enable π–π and C–H···π interactions, serving as ...
Yu Li, Honglin Li, Jialu Li, Wan‐Lu Li
wiley   +1 more source

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

open access: yesAdvanced 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   +1 more
wiley   +1 more source

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