Results 141 to 150 of about 3,679,425 (232)

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

open access: yesAdvanced 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   +6 more
wiley   +1 more source

Solutions of Kirchhoff plate equations with internal damping and logarithmic nonlinearity

open access: yesElectronic Journal of Differential Equations, 2021
Ducival Pereira   +3 more
doaj  

Nanosecond phase ordering in ultra-large spin Hall nano-oscillator lattices for unconventional computing. [PDF]

open access: yesNat Nanotechnol
Behera N   +7 more
europepmc   +1 more source

Insights Into CO2 Loss, pH Effects, and Tafel Kinetics in Ni Single Atom‐Driven Bicarbonate Electroreduction

open access: yesAdvanced Science, EarlyView.
Selective CO formation in bicarbonate electrolysis is achieved by retaining reactive CO2 and tuning pH, while the competing hydrogen evolution reaction occurs at the interface. The rate‐determining step couples the chemical equilibrium of bicarbonate/CO2 with electrochemical charge transfer, offering insight into optimizing reaction conditions for ...
Lin Li   +7 more
wiley   +1 more source

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

open access: yesAdvanced 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   +8 more
wiley   +1 more source

Interpretable Machine Learning Framework for Nb─Si Based Alloy Design with Enhanced Fracture Toughness

open access: yesAdvanced Science, EarlyView.
An interpretable machine learning framework integrating SHAP and PDP analysis identifies critical design descriptors from 139 physicochemical features for Nb─Si alloys. The framework achieves <7% prediction error and guides the discovery of Nb38.5Ti38.5Si3Zr18V2 alloy with 22.791 MPa·m1/2 fracture toughness, breaking the 20 MPa·m1/2 barrier.
Dezhi Chen   +7 more
wiley   +1 more source

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