Results 161 to 170 of about 115,969 (299)

Roadmap on Artificial Intelligence‐Augmented Additive Manufacturing

Advanced Intelligent Systems, EarlyView.
This Roadmap outlines the transformative role of artificial intelligence‐augmented additive manufacturing, highlighting advances in design, monitoring, and product development. By integrating tools such as generative design, computer vision, digital twins, and closed‐loop control, it presents pathways toward smart, scalable, and autonomous additive ...
Ali Zolfagharian, Liuchao Jin, Qi Ge, Wei‐Hsin Liao, Andrés Díaz Lantada, Francisco Franco Martínez, Tianyu Zhang, Tao Liu, Charlie C. L. Wang, Mohammad Hossein Mosallanejad, Reza Ghanavati, Abdollah Saboori, Alejandro De Blas De Miguel, William Solórzano‐Requejo, Yi Cai, Xiangyang Dong, Huangyi Qu, Najmeh Samadiani, Guangyan Huang, Austin Downey, Yanzhou Fu, Lang Yuan, Tsz‐Kwan (Glory) Lee, Arbind Agrahari Baniya, Eisha Waseem, Abdul Rahman Sani, Abbas Z. Kouzani, Yijia Wu, Markus P. Nemitz, Masoud Shirzad, Dageon Oh, Seung Yun Nam, Amedeo Franco Bonatti, Irene Chiesa, Gabriele Maria Fortunato, Giovanni Vozzi, Carmelo De Maria, Mahdi Bodaghi   +37 more
wiley   +1 more source

Accelerating Catalyst Materials Discovery With Large Artificial Intelligence Models

Angewandte Chemie, EarlyView.
AI‐empowered catalysis research via integrated database platform, universal machine learning interatomic potentials (MLIPs), and large language models (LLMs). ABSTRACT The integration of artificial intelligence (AI) into catalysis is fundamentally reshaping the research paradigm of catalyst discovery.
Di Zhang, Yuanzheng Chen, Chuanyu Liu, Yan Liu, Hongliang Xin, Jiayu Peng, Pengfei Ou, Hao Li   +7 more
wiley   +2 more sources

Protein Structure Determination by Racemic and Quasi-Racemic X-Ray Crystallography. [PDF]

Chembiochem
Kent SBH.
europepmc   +1 more source

Bayesian Optimisation for the Experimental Sciences: A Practical Guide to Data‐Efficient Optimisation of Laboratory Workflows

Advanced Intelligent Systems, EarlyView.
This study provides an introduction to Bayesian optimisation targeted for experimentalists. It explains core concepts, surrogate modelling, and acquisition strategies, and addresses common real‐world challenges such as noise, constraints, mixed variables, scalability, and automation.
Chuan He, Martin Singull, T. Jesper Jacobsson   +2 more
wiley   +1 more source

On the Structure and Redox Behavior of Ni and Cu Single Atoms Supported on Carbon Nitride

Angewandte Chemie, EarlyView.
Magnetic and electronic spectroscopies, combined with DFT, establish the MN4 binding site of Ni and Cu single atoms on carbon nitride and elucidate their redox photochemistry. Ni undergoes geometry‐preserving, reversible M2+/M+ cycling, whereas Cu collapses to an irreversible low‐coordinate Cu+ state, suppressing photocatalysis.
Giovanni Colonnello, Ksenija Maver, Arianna Actis, Gaia Grando, Giacomo Filippini, Tiziano Montini, Michele Melchionna, Paolo Fornasiero, Lucia Nasi, Iztok Arčon, Lorenzo Donà, Bartolomeo Civalleri, Enrico Salvadori, Mario Chiesa   +13 more
wiley   +2 more sources

Artificial Intelligence for Multiscale Modeling in Solid‐State Physics and Chemistry: A Comprehensive Review

Advanced Intelligent Systems, EarlyView.
This review explores the transformative impact of artificial intelligence on multiscale modeling in materials research. It highlights advancements such as machine learning force fields and graph neural networks, which enhance predictive capabilities while reducing computational costs in various applications.
Artem Maevskiy, Vitalii Kapitan, Andrey Ustyuzhanin   +2 more
wiley   +1 more source

Optimized Generalized LDPC Convolutional Codes. [PDF]

Entropy (Basel)
Deng L, Tao K, Shi Z, Zhang Y, Shi Y, Wang J, Liu T, Wang Y.   +7 more
europepmc   +1 more source

Causal analysis of trade loss from pathogens: A global study of foot and mouth disease impacts on meat exports

American Journal of Agricultural Economics, EarlyView.
Abstract Our general interest is in global trade loss from livestock pathogens, specifically exports. We adopt a causal inference approach that considers animal disease outbreaks over time as non‐staggered binary treatments with the potential for switching in (infection) and out of treatment (recovery) within the sample period. The outcome evolution of
Mohammad Maksudur Rahman, Thomas L. Marsh   +1 more
wiley   +1 more source

Odd-even conductance oscillations in <i>meta</i>-cycloparaphenylenes. [PDF]

Sci Adv
Song X, Gao JN, Song K, Jing C, Liu B, Zhang M, Lin J, Lü JT, Wang Y, Cong H, Zhu D, Zang Y.   +11 more
europepmc   +1 more source

Computational and experimental determination of electrochemical standard rate constant from cyclic voltammetry: insights into <i>α</i> + <i>β</i> ≠ 1 systems. [PDF]

RSC Adv
Saad Guermeche R, Affoune AM, Houam S, Atek I, Vautrin-Ul C, Nacef M, Chelaghmia ML, Girault HH, Banks CE, Djaghout I.   +9 more
europepmc   +1 more source