Results 211 to 220 of about 7,894,957 (258)

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

Life-Cycle Assessment of Laboratory-Scale Extrusion of Virgin and Recycled Polyolefins: Influence of Operating Duration on Life-Cycle Inventory Development. [PDF]

Polymers (Basel)
Saleem J, Moghal ZKB, Mckay G.
europepmc   +1 more source

Integrating Machine Learning With Constant‐Potential Simulation to Unravel Charge‐Transfer Mechanisms in Electrochemical Nitrogen Fixation

Advanced Science, EarlyView.
Integrating interpretable machine learning with the fixed‐potential method reveals a novel mechanism: the catalytic activity of the electrochemical nitrogen reduction reaction is governed by partial charge transfer, induced by variations in the intermediate potential of zero charge under constant potential.
Yufei Xue, Dushuo Feng, Yuefei Zhang, Yang Zhang, Yalong Jiao, Aijun Du, Guoping Gao   +6 more
wiley   +1 more source

Biogeochemical Assessment of Short-Term Hydrogen Storage in Methane Reservoirs with Field Sample Characterization and Reactor Experiments. [PDF]

ACS Omega
Tinker KA, Ross DE, Beebe MN, Bagwell CE, Smallwood CR, Davis RW, Gulliver DM.   +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

Thermodynamic calculation of metallic Fe yield and CO₂ emissions in gas-based shaft furnace direct reduction process. [PDF]

Sci Rep
Jiang X, Deng X, Fan X, Zhou Y, Li L, Zheng H, Gao Q, Shen F.   +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

Coaxially nested component with asymmetric fiber resonant cavity and separation membrane for gaseous and dissolved gases detection. [PDF]

Nat Commun
Wan F, Kong W, Sun H, Ran T, Chen W.
europepmc   +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