Results 161 to 170 of about 296,500 (268)

Effects of hydrodynamic nonlocality on electromagnetic wave propagation and topological properties of magnetoplasmas. [PDF]

Sci Rep
Amrollahzadeh M, Yahaghi A, Pakniyat S, Gomez-Diaz JS.   +3 more
europepmc   +1 more source

Topological Vector Spaces I

, 1979
openaire   +2 more sources

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

Experimental observation of energy-band Riemann surface. [PDF]

Sci Adv
Cheng D, Wang H, Zhong J, Lustig E, Roques-Carmes C, Fan S.   +5 more
europepmc   +1 more source

Topological Properties of International Commodity Market: How Uncertainty Affects the Linkages?

Agribusiness, EarlyView.
ABSTRACT The study aims to explore the network topology of the international commodity market by examining the interconnections among 21 commodity futures across various categories, including energy, precious and industrial metals, and agriculture. We analyze the market structure of these commodity futures under both low and high uncertainty conditions
Ibrahim Yagli, Bayram Deviren
wiley   +1 more source

Topological Engineering of Chiral Anomalies in Janus Nanoribbons. [PDF]

Nano Lett
Saroka VA, Demin VA, Pizzochero M.
europepmc   +1 more source

SigmaFormer: Augmenting transformer encoders with COSMO sigma profiles for pure component property prediction

AIChE Journal, EarlyView.
Abstract Transformer‐based molecular models pretrained on SMILES strings demonstrate strong performance in property prediction. However, these model often lack explicit integration of molecular surface charge distributions that govern intermolecular interactions such as hydrogen bonding and polarity.
Tae Hyun Kim, Silabrata Pahari, Joseph Sang‐Il Kwon   +2 more
wiley   +1 more source

Twisted optical fibres as photonic topological insulators. [PDF]

Nat Photonics
Roberts N, Salter B, Binysh J, Mosley PJ, Souslov A.   +4 more
europepmc   +1 more source

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

Advanced 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

Revealing the topological nature of entangled orbital angular momentum states of light. [PDF]

Nat Commun
de Mello Koch R, Ornelas P, Gounden N, Lu BQ, Nape I, Forbes A.   +5 more
europepmc   +1 more source