Results 141 to 150 of about 16,942 (259)

Machine Learning Interatomic Potentials for Energy Materials: Architectures, Training Strategies, and Applications

Advanced Energy Materials, EarlyView.
Machine learning interatomic potentials bridge quantum accuracy and computational efficiency for materials discovery. Architectures from Gaussian process regression to equivariant graph neural networks, training strategies including active learning and foundation models, and applications in solid‐state electrolytes, batteries, electrocatalysts ...
In Kee Park, Saeed Pourasad, Jinhong Mun, Arunkumar Chitteth Rajan, Tae Hyeon Park, Anand Rohit, Mohammad Zafari, Tan‐Lien Pham, Eunjae Jung, Bonseung Koo, Miran Ha, Gi Beom Sim, Hyun Gyu Park, Won Woong Choi, Kwanghyeon Jo, Soohaeng Yoo Willow, David ChangMo Yang, Chang Woo Myung, Geunsik Lee, Kwang S. Kim   +19 more
wiley   +1 more source

Assessing Photovoltaic Recycling Capacities and Policy Gaps in the European Union

Advanced Energy and Sustainability Research, EarlyView.
This study maps photovoltaic recycling capacity in the EU and key global regions, highlighting gaps between growing waste volumes and available infrastructure. It combines survey insights and policy analysis to identify recycling bottlenecks and offers recommendations to boost circularity in the solar sector.
Nieves Espinosa, Silvia Bobba, Cynthia E. L. Latunussa, Enrica Leccisi   +3 more
wiley   +1 more source

Atomistic Insights into Hydrogen Diffusion and Deformation Mechanisms in FeCrNi-Based Austenitic Stainless Steels: Effects of Alloying, Temperature, and Hydrogen Concentration. [PDF]

Molecules
Li J, Huang Z, Zhang L, Zheng Z, Zhang C, Rao S, Teng L, Jiang L.   +7 more
europepmc   +1 more source

Flow characteristics and regime transitions in fluidization systems of Group C+ particles

AIChE Journal, EarlyView.
Abstract Fine and ultrafine particles are attractive for fluidized bed reactors because their high surface area benefits catalytic processes, but their cohesive nature complicates regime characterization. Nanoparticle modulation improves the flowability of Group C powders, yet their bubbling to turbulent transition remains unclear.
Yue Song, Jiaying Wang, Xiaoyang Wei, Jesse Zhu   +3 more
wiley   +1 more source

Scalable Boltzmann generators for equilibrium sampling of large-scale materials. [PDF]

Nat Commun
Schebek M, Noé F, Rogal J.
europepmc   +1 more source

Machine Learning‐Assisted Second‐Order Perturbation Theory for Chemical Potential Correction Toward Hubbard U Determination

Advanced Intelligent Discovery, EarlyView.
In this work, the Doubao large language model (LLM) is involved in the formula derivation processes for Hubbard U determination regarding the second‐order perturbations of the chemical potential. The core ML tool is optimized for physical domain knowledge, which is not limited to parameter prediction but rather serves as an interactive physical theory ...
Mingzi Sun, Tong Wu, Baian Chen, Zikang Li, Qiuyang Lu, Lu Lu, Hon Ho Wong, Cheuk Hei Chan, Bolong Huang   +8 more
wiley   +1 more source

Geometric Nonuniformity Localizes Valence Orbitals in Gold Clusters: Case Study on [Au23(SC6H11)16]–

Angewandte Chemie, EarlyView.
The electronic structure of [Au23(SC6H11)16]–, a monolayer‐protected gold cluster with a nonuniform Au13 core, was investigated. Anion photoelectron spectroscopy and density functional theory calculations revealed that the highest occupied molecular orbital (HOMO) and HOMO‐1 are localized on the two triangular Au3 units at the ends of the Au13 core ...
Yosuke Asami, Shun Ito, Kiichirou Koyasu, Tatsuya Tsukuda   +3 more
wiley   +2 more sources

Site-Specific Raman Probes Reveal Droplet Aging and Residue-Level Fibril Polymorphism in TDP-43_CTD. [PDF]

J Am Chem Soc
Watson MD, Lee JC.
europepmc   +1 more source

Toward Predictable Nanomedicine: Current Forecasting Frameworks for Nanoparticle–Biology Interactions

Advanced Intelligent Discovery, EarlyView.
Predictive models successfully screen nanoparticles for toxicity and cellular uptake. Yet, complex biological dynamics and sparse, nonstandardized data limit their accuracy. The field urgently needs integrated artificial intelligence/machine learning, systems biology, and open‐access data protocols to bridge the gap between materials science and safe ...
Mariya L. Ivanova, Michael Nicholls, Nicola Russo, Gueorgui Mihaylov, Konstantin Nikolic   +4 more
wiley   +1 more source

Twinning-Dominated Plasticity and Structural Stability of NiCoCrX_0.1 (X= Mo, Ti) MEA under 52 GPa Pressure. [PDF]

ACS Omega
Ding B, Pu J, Zeng Y, Liang H, Li T, Zhang W.   +5 more
europepmc   +1 more source