Results 231 to 240 of about 149,306 (281)

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

Carbon efficient quantum AI: an empirical study of ansätz design trade-offs in QNN and QLSTM models. [PDF]

Sci Rep
Tripathi S, Upadhyay H, Soni J.
europepmc   +1 more source

Maneuverable Multilegged Locomotion through Anisotropically Arranged Soft Backbones in a Single‐Actuator Modular Miniature Robot

Advanced Intelligent Systems, EarlyView.
A modular eight‐legged robot exploits anisotropically oriented soft I‐beam backbones to transmit vibration from a single unbalanced‐mass actuator, producing frequency‐dependent multimodal gaits. A pseudo‐rigid‐body model enables high‐fidelity MuJoCo simulation, while Bayesian parameter identification and reinforcement learning yield robust control ...
Yiğit Yaman, Burak Arslan, Ömer Çağrı Ergin, Daniel M. Aukes, Onur Özcan   +4 more
wiley   +1 more source

Bayesian machine learning for inverse design of ultra-high-performance concrete. [PDF]

Philos Trans A Math Phys Eng Sci
Childs C, Miller A, Neiswanger W, Poczos B, Stewart L, Kurtis K, Washburn N.   +6 more
europepmc   +1 more source

Speciation, Structural Refinement, and Distribution of Ti Sites in Titanium Silicalite‐1 From 47/49Ti NMR Crystallography at 28.2 Tesla

Angewandte Chemie, EarlyView.
Titanium silicalite‐1 (TS‐1), used in industrial selective oxidation processes, depends on specific, yet still unresolved Ti sites, dispersed within the framework of an MFI‐zeolite. Applying high field (28.2 T) 47/49Ti NMR and 17O NMR spectroscopy for an array of TS‐1 catalysts enables the development of an NMR crystallography protocol and the ...
Christoph J. Kaul, Jonas Koppe, Lukas Lätsch, Michael Wörle, Sadig Aghazada, Jacob B. Holmes, Christina Wartmann, Mingji Zheng, Albrecht Berkessel, Trees De Baerdemaeker, Andrei‐Nicolae Parvulescu, Karsten Seidel, J. Henrique Teles, Alexander V. Yakimov, Christophe Copéret   +14 more
wiley   +1 more source

Landmark matching and B-spline implicit neural representations for diffusion-weighted imaging distortion correction. [PDF]

Phys Med Biol
Li Y, Liao YP, Dai Y, Deng J, Zhang Y.
europepmc   +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   +1 more source

Generalized Additive Modeling of Ecological Data With mgcv: New Adequacy Assessment Tools. [PDF]

Ecol Evol
Mainguy J, McInerney R, Millar RB, Valiquette E, Bélanger M, Moral RA.   +5 more
europepmc   +1 more source

Staged Diversity‐Constrained Machine Learning for High‐Dimensional Reaction Condition Optimization

Angewandte Chemie, EarlyView.
Staged diversity‐constrained modeling enables efficient navigation of high‐dimensional reaction spaces, validated on cross‐coupling HTE data and applied to ruthenium‐catalyzed meta‐C─H functionalization. ABSTRACT Optimizing reaction conditions in high‐dimensional chemical spaces remains a central challenge in modern synthesis.
Shu‐Wen Li, Shan Chen, João C. A. Oliveira, Shuo‐Qing Zhang, Lutz Ackermann, Xin Hong   +5 more
wiley   +1 more source

Phishing threat mitigation in E-commerce using a quantum-enhanced hybrid AI framework. [PDF]

Sci Rep
Gupta BB, Pan SH, Gaurav A, Arya V, Attar RW, Alhazmi AH, Alhomoud A, Chui KT.   +7 more
europepmc   +1 more source