Results 221 to 230 of about 224,948 (306)

Configurational Entropy and Compositional Effects in Fe‐Based Oxide 2D Sheets for Nitrate Electroreduction

open access: yesAdvanced Energy Materials, EarlyView.
FeCuCoMnZnOx integrates diverse heteroatomic bridge‐site environments and composition‐dependent electronic structures to promote nitrate activation and sequential hydrogenation toward ammonia, demonstrating that nitrate reduction reaction performance is governed by the combined effects of composition and local coordination rather than configurational ...
Muhammad Usman   +14 more
wiley   +1 more source

Chloride‐Mediated Activation of Aluminum‐Alloyed Liquid Metal Anodes for Stretchable Asymmetric Energy Storage

open access: yesAdvanced Energy Materials, EarlyView.
A gallium‐centered cell pairs an aluminum‐alloyed GaIn anode with a GaOOH cathode in a chloride‐rich water‐in‐ionic‐liquid electrolyte. Chlorogallate ions dissolve the native oxide that normally seals the liquid metal, and preferentially reduce indium seeds to oxide‐free clusters on which gallium plates and strips reversibly.
Adit Gupta   +3 more
wiley   +1 more source

Comparison of DeePMD, MTP, GAP, ACE and MACE Machine‐Learned Potentials for Radiation‐Damage Simulations: A User Perspective

open access: yesAdvanced Intelligent Discovery, EarlyView.
The authors evaluated six machine‐learned interatomic potentials for simulating threshold displacement energies and tritium diffusion in LiAlO2 essential for tritium production. Trained on the same density functional theory data and benchmarked against traditional models for accuracy, stability, displacement energies, and cost, Moment Tensor Potential ...
Ankit Roy   +8 more
wiley   +1 more source

AI‐Driven Cancer Multi‐Omics: A Review From the Data Pipeline Perspective

open access: yesAdvanced Intelligent Discovery, EarlyView.
The exponential growth of cancer multi‐omics data brings opportunities and challenges for precision oncology. This review systematically examines AI's role in addressing these challenges, covering generative models, integration architectures, Explainable AI for clinical trust, clinical applications, and key directions for clinical translation.
Shilong Liu, Shunxiang Li, Kun Qian
wiley   +1 more source

Catalyst‐Specialized Chemical Language Model Based on Transformer Variational Autoencoder for Catalyst Design and Discovery

open access: yesAdvanced Intelligent Discovery, EarlyView.
We present CatTransVAE, a catalyst‐specialized chemical language model (CLM) built on a transformer variational autoencoder (VAE), developed through pretraining on general compounds followed by fine‐tuning on diverse catalyst databases. A template‐guided generation framework is introduced to enable controlled catalyst design under structural ...
Apakorn Kengkanna, Masahito Ohue
wiley   +1 more source

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