Results 151 to 160 of about 247,052 (213)

Physics‐Embedded Neural Network: A Novel Approach to Design Polymeric Materials

Advanced Science, EarlyView.
Traditional black‐box models for polymer mechanics rely solely on data and lack physical interpretability. This work presents a physics‐embedded neural network (PENN) that integrates constitutive equations into machine learning. The approach ensures reliable stress predictions, provides interpretable parameters, and enables performance‐driven, inverse ...
Siqi Zhan, Hengheng Zhao, Haotian Wang, Zhanjie Liu, Qian Li, Weifeng Zhang, Qingsong Zhao, Liqun Zhang, Jun Liu   +8 more
wiley   +1 more source

Psychosocial Factors Explaining Academic Dropout among Scholarship Students at a Public University in Peru. [PDF]

F1000Res
Llonto-Caicedo Y, Alarcón-Villanueva G, Jiménez-Garay OD, De Jesus Paredes-Olano DM, Acuña-Romero YM, Ruiz-Díaz IG, Sánchez-Alamo DM, Vargas-Espinoza JL, Zambrano-Infante OJ, Morán-Santamaría RO.   +9 more
europepmc   +1 more source

Synergistic Spin‐Polarization and Single‐Atom Engineering in Magnetic Heterojunctions for Efficient Solar Water Splitting

Advanced Science, EarlyView.
High‐throughput screening led to the identification of 67 Z‐scheme heterojunctions (comprising 2D magnetic transition metal halides and non‐magnetic transition metal chalcogenides). For CrI3/MoTe2 and CrI3/WTe2, electronic structure analysis demonstrated that synergistic crystallographic point group and built‐in electric field effects generate a ...
Hongyang Ren, Zhenzhou Guo, Huirong Wu, Peilin Huang, Jie Yang, Jie Zhang, Guangqian Ding, Hongkuan Yuan, Biao Wang   +8 more
wiley   +1 more source

An applied scholarship framework for population health impact: adapting the Boyer model for public health faculty. [PDF]

Front Public Health
Upshaw VM, Ahsan KZ, Sowah DN, Ramaswamy R, Tang W.   +4 more
europepmc   +1 more source

Ethical Precision in Nanoscale Brain Interfacing

Advanced Science, EarlyView.
As brain interfaces approach the nanoscale, precision no longer only measures—it knows, predicts, and potentially reshapes the mind. This work argues that traditional ethics fails under such conditions and proposes a shift toward continuous, operation‐based governance using the recovery–discovery framework to track, constrain, and responsibly steer ...
Guilherme Wood
wiley   +1 more source

Celebrating 10 Years of Research Excellence at the <i>Canadian Journal of Pain</i>. [PDF]

Can J Pain
Katz J, Waisman A, Lumsden-Ruegg H.
europepmc   +1 more source

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

Advanced 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, Yi‐Jie Kong, Ting Zhang, Xu Han, Kristine Aalestrup, Steen Uttrup Pedersen, Xin‐Ming Hu, Kim Daasbjerg   +7 more
wiley   +1 more source

Da art of storytellin': hip-hop epistemology, hip-hop theorization, and the discursive continuity of black cultural expression in/through sport. [PDF]

Front Sports Act Living
Foster SJL, Klein M.
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

High‐Throughput Screening and Interpretable Machine Learning for Rational Design of Bimetallic Catalysts for Methane Activation

Advanced Science, EarlyView.
ABSTRACT Methane's efficient catalytic removal is vital for sustainable development. Bimetallic catalysts, though promising for methane activation, pose a design challenge due to their complex compositional space. This work introduces an integrated framework that combines high‐throughput density functional theory (DFT) and interpretable machine ...
Mingzhang Pan, Tian Zhang, Jiawei Dong, Yubao Xie, Kaifeng Zhong, Wei Guan, Haiqiao Wei, Changcheng Fu, Yaqiong Su   +8 more
wiley   +1 more source