Results 201 to 210 of about 52,159,458 (292)

Configurational Entropy and Compositional Effects in Fe‐Based Oxide 2D Sheets for Nitrate Electroreduction

Advanced Energy Materials, EarlyView.
FeCuCoMnZnOx integrates diverse heteroatomic bridge‐site environments and composition‐dependent electronic structures to promote nitrate activation and sequential hydrogenation toward ammonia, demonstrating that nitrate reduction reaction performance is governed by the combined effects of composition and local coordination rather than configurational ...
Muhammad Usman, Zhehao Sun, Yi‐Lun Chen, Kaili Liu, Xuechen Jing, Soshan Cheong, Zeno R. Ramadhan, Jiayi Chen, Shuwen Cheng, Ary Anggara Wibowo, Daniel Macdonald, Lucy Gloag, Nicholas Cox, Richard D. Tilley, Zongyou Yin   +14 more
wiley   +1 more source

Radiation emergency preparedness in the middle east: Public health consequences, water security vulnerabilities, and evidence-based countermeasures. [PDF]

EXCLI J
Ben Saad H, Dergaa I, Ceylan HI, de Giorgio A, Bragazzi NL.   +4 more
europepmc   +1 more source

Evaluation of plasma‐reaction‐driving capability in dielectric barrier discharge systems: Insights from CH4 splitting

AIChE Journal, EarlyView.
Abstract Dielectric barrier discharge (DBD) plasma systems are promising routes for CH4 splitting to COx‐free hydrogen, but their optimization has historically been hindered by the lack of a universal descriptor linking electrical input with chemical output.
Nan Zou, Joshua M. Pearce, Amarjeet Bassi, Michael S. H. Boutilier, Ying Zheng   +4 more
wiley   +1 more source

Phase-Specific Assessment of Corrosion Susceptibility in Inconel 625 and SA508 Low-Alloy Steel Under Molten Chloride Conditions. [PDF]

Materials (Basel)
Ham S, Jin HH, Kim C, Zhang J, Kim S.
europepmc   +1 more source

Sonocatalytic carbon dioxide reduction for syngas production over surface‐roughened CuxO catalyst

AIChE Journal, EarlyView.
Abstract The transition to a carbon‐circular economy requires efficient technologies for converting CO2 into value‐added chemical feedstocks. Sonocatalytic CO2 conversion has recently emerged as a compelling approach to drive this conversion. Here, we report a surface‐roughened CuxO catalyst for sonocatalytic CO2 reduction in aqueous media, achieving a
Dong Xia, Yi Qin, Hessan Khalid, Yagya N. Regmi, Laurie A. King, James Kwan   +5 more
wiley   +1 more source

Model analysis of plasma incineration system of radioactive waste: A case in São Paulo, Brazil. [PDF]

Waste Manag Res
Gonçalves MFS, Massi M, Rosa RA, Couto AA, Mol MPG.   +4 more
europepmc   +1 more source

Comparison of DeePMD, MTP, GAP, ACE and MACE Machine‐Learned Potentials for Radiation‐Damage Simulations: A User Perspective

Advanced Intelligent Discovery, EarlyView.
The authors evaluated six machine‐learned interatomic potentials for simulating threshold displacement energies and tritium diffusion in LiAlO2 essential for tritium production. Trained on the same density functional theory data and benchmarked against traditional models for accuracy, stability, displacement energies, and cost, Moment Tensor Potential ...
Ankit Roy, Ram Devanathan, Sarah Allec, Giridhar Nandipati, Andrew M. Casella, David J. Senor, Duane D. Johnson, Ganesh Balasubramanian, Ayoub Soulami   +8 more
wiley   +1 more source

AI‐Guided Co‐Optimization of Advanced Field‐Effect Transistors: Bridging Material, Device, and Fabrication Design

Advanced Intelligent Discovery, EarlyView.
This article outlines how artificial intelligence could reshape the design of next‐generation transistors as traditional scaling reaches its limits. It discusses emerging roles of machine learning across materials selection, device modeling, and fabrication processes, and highlights hierarchical reinforcement learning as a promising framework for ...
Shoubhanik Nath, Shauryaraj K. Jilkar, Aditya Udgaonkar, Yu (Joe) Lu, Ali Mesbah   +4 more
wiley   +1 more source

The numerical reactor system for China's new-generation exascale supercomputer. [PDF]

Innovation (Camb)
Miao X, Wang J, Bai H, Wang Y, Wu Z, Lin Q, Zhang S, He X, Yang R, Nie N, Zhou C, Cao R, Wang Z, Hu Y, Yang W.   +14 more
europepmc   +1 more source

Multi‐Property Machine Learning Models to Accelerate the Transition Toward Bio‐Based Emulsion Polymers

Advanced Intelligent Discovery, EarlyView.
A machine learning framework simultaneously predicts four critical properties of monomers for emulsion polymerization: propagation rate constant, reactivity ratios, glass transition temperature, and water solubility. These tools can be used to systematically identify viable bio‐based monomer pairs as replacements for conventional formulations, with ...
Kiarash Farajzadehahary, Nicholas Ballard   +1 more
wiley   +1 more source