Results 211 to 220 of about 167,663,748 (283)

RuKY Catalyst-Packed Permeation Membrane for Quantitative Ammonia and d3-Ammonia Dehydrogenation to Ultrapure Hydrogen. [PDF]

ChemistryOpen
Koch CJ, Naglic J, Kelly JT, Kearney L, Arregui-Mena JD, Lauterbach J, Angelette LM, Guin T.   +7 more
europepmc   +1 more source

Present Status of Nuclear Calculations of Reactor Design, (II)

Journal of the Atomic Energy Society of Japan / Atomic Energy Society of Japan, 1967
openaire   +2 more sources

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

Systematic Evaluation of Reaction Phase Effects on Photocatalytic CO₂ Reduction Using Cu-Doped SrTiO₃. [PDF]

Glob Chall
Bajiri MAM, Khan N, Diaz JCCA, Vieira GN, Araújo YJK, Paquini LD, Hezam A, Lima FHB, Wender H, Gonçalves RV.   +9 more
europepmc   +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

Direct cyanation of aromatic rings using dinitrogen and methane promoted by nonthermal plasma. [PDF]

Sci Adv
Yu L, Zhang S, Liu L, Li D, Cai Y, Wu C, Hua L, Li H, Deng D, Chen P, Chen P, Xi Z, Guo J, Wei J.   +13 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

First-Principles Investigation of Helium Incorporation Effects on the Structural Stability and Electrochemical Performance of Thorium-Based Mixed Oxide Nuclear Fuels. [PDF]

Materials (Basel)
Zhu L, Zhao S, Cheng Z, Sheng S, Liu Y, Wei Q, Wang BT.   +6 more
europepmc   +1 more source

Revealing Hidden Raman Signatures Through Attention‐Based Spectral Unmixing

Advanced Intelligent Systems, EarlyView.
Weak Raman signatures are recovered from background‐dominated spectra using a transformer‐based, reference‐free spectral unmixing AI framework. Self‐attention reconstructs substrate contribution directly from mixed data, enabling reliable extraction of previously inaccessible vibrational features.
Dmitriy A. Poteryayev, Pietro Novelli, Annalisa Coriolano, Riccardo Dettori, Valentina Tozzini, Fabio Beltram, Massimiliano Pontil, Antonio Rossi, Stiven Forti, Camilla Coletti   +9 more
wiley   +1 more source