Results 221 to 230 of about 20,207 (328)

Insights into the Degradation Mechanism of Aqueous LiMn2O4–Cathode Interfaces by Computational Vibrational Spectroscopy

open access: yesAngewandte Chemie, EarlyView.
LiMn2O4${\rm LiMn}_2{\rm O}_4$ is of high interest for sustainable energy storage and conversion. Its mixed‐valence Mn3+${\rm Mn}^{3+}$/Mn4+${\text{Mn}}^{4+}$ structure drives site‐specific behavior at aqueous interfaces, featuring proton‐generating Mn4+${\text{Mn}}^{4+}$ centers and electron‐rich Mn3+${\rm Mn}^{3+}$ sites that render the surrounding ...
K. Nikolas Lausch   +3 more
wiley   +2 more sources

From Data to Discovery: Machine Learning–Enabled Intelligent Characterization of Two‐Dimensional Materials

open access: yesAdvanced Intelligent Discovery, EarlyView.
Machine learning serves as a central engine for the intelligent characterization of two‐dimensional materials by integrating multimodal techniques, including optical microscopy, spectroscopy, electron microscopy, and scanning probe microscopy (SPM). This unified framework enables automated, high‐throughput, and quantitative extraction of structural ...
Zhi‐Long Cao, Jia‐Xu Yan
wiley   +1 more source

Compositional and Structural Diversity in Cesium Superhydrides at High Pressure

open access: yesAngewandte Chemie, EarlyView.
Through high pressure‐high temperature diamond anvil cell experiments combined with density functional theory calculations, cesium is demonstrated to have remarkably complex and diverse hydride chemistry culminating in the formation of CsH25${\rm CsH}_{25}$, the most hydrogen‐rich metal hydride reported to date.
Mikhail A. Kuzovnikov   +7 more
wiley   +2 more sources

Crystal Structure Prediction of Inorganic Materials: A Benchmark and Modern Evaluation

open access: yesAdvanced Intelligent Discovery, EarlyView.
Predicting a crystal’s structure from composition alone is a long‐standing challenge in materials discovery. The CSP180 benchmark of 180 inorganic crystals evaluates thirteen crystal structure prediction algorithms requiring no density functional theory (DFT) against DFT‐based baselines across twelve metrics.
Lai Wei   +9 more
wiley   +1 more source

Revealing Hidden Raman Signatures Through Attention‐Based Spectral Unmixing

open access: yesAdvanced Intelligent Systems, EarlyView.
Weak Raman signatures are recovered from background‐dominated spectra using a transformer‐based, reference‐free spectral unmixing AI framework. Self‐attention reconstructs substrate contribution directly from mixed data, enabling reliable extraction of previously inaccessible vibrational features.
Dmitriy A. Poteryayev   +9 more
wiley   +1 more source

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