Results 61 to 70 of about 1,788 (162)

Stochastic analysis of compact stars under composite polytropes. [PDF]

Sci Rep
Nouh MI, El-Essawy SH, Foda MM, Aboueisha MS.   +3 more
europepmc   +1 more source

Ether‐Based Electrolytes and the Solvation Structure in Sodium Ion Batteries

Advanced Energy Materials, EarlyView.
Ether electrolytes enable high‐performance sodium‐ion batteries through their unique physicochemical properties, particularly distinctive solvation structures and co‐intercalation behavior. However, the localized solvation structure and its dynamic evolution during electrochemical processes remain a “black box”.
Jiaxin Ding, John T. S. Irvine
wiley   +1 more source

Lone black holes promise fresh insights into the fates of massive stars. [PDF]

Proc Natl Acad Sci U S A
Croswell K.
europepmc   +1 more source

Hybrid Ionomer‐Free Porous Transport Electrodes With Catalyst Coated Membranes for Enhanced Water Electrolysis

Advanced Energy Materials, EarlyView.
We demonstrate how improved electrochemical performance during water electrolysis is achieved when a porous transport electrode (PTE) is coupled with a traditional catalyst coated membrane (CCM). Using operando neutron radiography, a more homogenous water distribution near the catalyst layer‐membrane interface is revealed in PTE‐based designs due to ...
Tess Seip, Lijun Zhu, Salvatore Ranieri, James Torres, Yuxuan Zhang, Roger Hobbs, Hassina Bilheux, Jean‐Christophe Bilheux, Aimy Bazylak   +8 more
wiley   +1 more source

Monitoring the Microwave Synthesis of d0‐Free Disordered Rocksalt Cathodes Using In Situ Infrared Pyrometry

Angewandte Chemie, EarlyView.
Despite its promise for producing metastable materials, the mechanisms underlying solid‐state microwave synthesis remain poorly understood. By combining in situ thermography with x‐ray diffraction and solid‐state NMR, this study uncovers a surprising order–disorder–order reaction pathway during the microwave synthesis of the Li1.1Mn0.9O1.9F0.1${\rm Li ...
Erick A. Lawrence, Matthew A. Wright, Tianyu Li, Euan N. Bassey, Vijay Kumar, Shiyu Yuan, Yangying Zhu, Pierre‐Etienne Cabelguen, Raphaële J. Clément   +8 more
wiley   +2 more sources

Isotropic fluid structures and role of non-metricity on their dynamics governed by an electric charge: A theoretical study. [PDF]

PLoS One
Naseer T, Sharif M, Waqas M, Andrade J, Emara A.   +4 more
europepmc   +1 more source

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

Advanced 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, Ram Devanathan, Sarah Allec, Giridhar Nandipati, Andrew M. Casella, David J. Senor, Duane D. Johnson, Ganesh Balasubramanian, Ayoub Soulami   +8 more
wiley   +1 more source

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

Angewandte 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, Redouan El Haouari, Philipp Schienbein, Jörg Behler   +3 more
wiley   +2 more sources

Direct spectroscopic observation of matter falling onto a compact stellar object. [PDF]

Sci Adv
Rahin R, Ballhausen R, Islam N, Leutenegger MA, Behar E, Zamora D, Coley J, Hell N, Kallman T, Lorenz M, Pradhan P, Wilms J, Zainab A.   +12 more
europepmc   +1 more source

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

Advanced 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