Results 191 to 200 of about 4,107,768 (302)

ML Workflows for Screening Degradation‐Relevant Properties of Forever Chemicals

Advanced Science, EarlyView.
The environmental persistence of per‐ and polyfluoroalkyl substances (PFAS) necessitates efficient remediation strategies. This study presents physics‐informed machine learning workflows that accurately predict critical degradation properties, including bond dissociation energies and polarizability.
Pranoy Ray, Andrew R. Castillo, Manoj Kolel‐Veetil, Surya R. Kalidindi   +3 more
wiley   +1 more source

Transparent Topological Meta-Diplexer via Tightly Confined Valley Surface States. [PDF]

Adv Sci (Weinh)
Li S, Li P, Lan Z, Li Y, Wong H, Chen MLN.   +5 more
europepmc   +1 more source

Function space topologies [PDF]

Pacific Journal of Mathematics, 1970
openaire   +3 more sources

Overcoming Artificial Structures in Resolution‐Enhanced Hi‐C Data by Signal Decomposition and Multi‐Scale Attention

Advanced Science, EarlyView.
Deep‐learning‐based signal enhancement is an effective way to recover high‐resolution details from a low‐resolution chromatin contact map. However, due to computational challenges, existing methods commonly divide up the contact map into small patches and create artificial discontinuities at patch boundaries.
Qinyao Li, Kelly Yichen Li, Chiara Nicoletti, Stephen Kwok‐Wing Tsui, Pier Lorenzo Puri, Qin Cao, Kevin Y. Yip   +6 more
wiley   +1 more source

Remote engineering of particle-like topologies to visualise entanglement dynamics. [PDF]

Light Sci Appl
Nothlawala F, Sephton B, Ornelas P, Koni M, Piccirillo B, Feng L, Nape I, D'Ambrosio V, Forbes A.   +8 more
europepmc   +1 more source

Type‐II Dirac Fermions in Monolayer In2O: Interplay of Magnetotransport, Spin Hall Effect, and Superconductivity

Advanced Science, EarlyView.
First‐principles calculations reveal that monolayer In2O${\rm In}_2{\rm O}$ hosts type‐II Dirac fermions near the Fermi level, which split into Weyl points under spin‐orbit coupling. The material exhibits negative and giant magnetoresistance, a pronounced spin Hall effect, and phonon‐mediated superconductivity at 1.5 K, establishing it as a unique ...
Qing‐Bo Liu, De‐Ming Feng, Wen‐Neng Zhao, Yu‐Yang Zhao, Lun Xiong, Xing‐Yi Tan, Hua‐Hua Fu   +6 more
wiley   +1 more source

Stable real-space invariants and topology beyond symmetry indicators. [PDF]

Nat Commun
Hwang Y, Gupta V, Schindler F, Elcoro L, Song Z, Bernevig BA, Bradlyn B.   +6 more
europepmc   +1 more source

Unifying Composition and Process Design: A Heterogeneous Graph Neural Network for Discovering High‐Performance Cu Alloys

Advanced Science, EarlyView.
By overcoming the fixed‐path limitations of conventional machine learning, a heterogeneous graph neural network fundamentally reconstructs material data representation. Integrating variable processing sequences with intrinsic elemental features, this framework enables exploratory optimization across high‐dimensional spaces.
Jie Yin, Qian Lei, Wei Yan, Yue Li, Tong Xie, Shuang Zhou, Chong Wang, Bram Hoex, Qiang Long, Caoyang Jiang, Min Song, Zhou Li, Zhangwei Wang   +12 more
wiley   +1 more source

Topological Data Analysis-Driven fNIRS Signal Processing for Alzheimer's Disease Stage Identification. [PDF]

Sensors (Basel)
Liu S, Wu H, Sun C, Qiu Y, Wu H, Wei Y, Lv Y, Yang Z.   +7 more
europepmc   +1 more source

High‐Throughput Data Generation and Transfer Learning Enabled Microstructure‐Property Integrated Design of Nickel‐Based Powder Metallurgy Superalloy

Advanced Science, EarlyView.
An integrated transfer learning framework integrates CALPHAD simulations, diffusion‐multiple experiments, and literature data to predict long‐term microstructural stability and short‐term mechanical properties of Ni‐based powder metallurgy superalloys. Based on these model predictions, a high‐performance, low‐density alloy, USTB‐PM750, is designed from
Zixin Li, Hongtao Zhang, Zichao Peng, Yuheng Zhang, Qian Lv, Yihuan Cao, Xuqing Wang, Huadong Fu, Jianxin Xie   +8 more
wiley   +1 more source