Results 41 to 50 of about 95,003 (214)

Dispersive Full‐Channel Jones Matrix Modulation in Elliptical Polarization Bases via a Single‐Layered Metasurface

Advanced Science, EarlyView.
This work presents a dispersive full‐channel Jones matrix modulation strategy using single‐layer metasurface. By synergizing wavelength dispersion engineering with elliptical polarization bases, independent control of four Jones matrix channels is achieved across multiple wavelengths.
Hairong He, Guangtao Cao, Shuhao Zhang, Hui Xu, Zhiquan Chen, Meiyu Peng, Yuting Jiang, Yueqiang Hu, Hui Jing, Huigao Duan, Hui Yang   +10 more
wiley   +1 more source

New Applications of Clifford’s Geometric Algebra

Advances in Applied Clifford Algebras, 2022
Stéphane Breuils, K. Tachibana, E. Hitzer   +2 more
semanticscholar   +1 more source

The Evolution of Gas Sensors Into Neuromorphic Systems

Advanced Electronic Materials, EarlyView.
Gas sensors are vital for various applications, but conventional designs rely on separate sensing, memory, and processing units, limiting speed, power efficiency, and adaptability. Neuromorphic gas sensing overcomes these constraints by integrating all functions in a single device.
Kevin Dominguez, Dhananjay D. Kumbhar, Abdul Momin Syed, Regina C. Martin, Nazek El‐Atab   +4 more
wiley   +1 more source

CrossMatAgent: AI‐Assisted Design of Manufacturable Metamaterial Patterns via Multi‐Agent Generative Framework

Advanced Intelligent Discovery, EarlyView.
CrossMatAgent is a multi‐agent framework that combines large language models and diffusion‐based generative AI to automate metamaterial design. By coordinating task‐specific agents—such as describer, architect, and builder—it transforms user‐provided image prompts into high‐fidelity, printable lattice patterns.
Jie Tian, Martin Taylor Sobczak, Dhanush Patil, Jixin Hou, Lin Pang, Arunachalam Ramanathan, Libin Yang, Xianyan Chen, Yuval Golan, Xiaoming Zhai, Hongyue Sun, Kenan Song, Xianqiao Wang   +12 more
wiley   +1 more source

Deep Learning‐Assisted Design of Mechanical Metamaterials

Advanced Intelligent Discovery, EarlyView.
This review examines the role of data‐driven deep learning methodologies in advancing mechanical metamaterial design, focusing on the specific methodologies, applications, challenges, and outlooks of this field. Mechanical metamaterials (MMs), characterized by their extraordinary mechanical behaviors derived from architected microstructures, have ...
Zisheng Zong, Pu Wen, Zhiping Chai, Dunxuan Wu, Han Ding, Zhigang Wu   +5 more
wiley   +1 more source

Large Language Model in Materials Science: Roles, Challenges, and Strategic Outlook

Advanced Intelligent Discovery, EarlyView.
Large language models (LLMs) are reshaping materials science. Acting as Oracle, Surrogate, Quant, and Arbiter, they now extract knowledge, predict properties, gauge risk, and steer decisions within a traceable loop. Overcoming data heterogeneity, hallucinations, and poor interpretability demands domain‐adapted models, cross‐modal data standards, and ...
Jinglan Zhang, Xinyi Chen, Xu Ye, Yulin Yang, Bin Ai   +4 more
wiley   +1 more source

A Physics Constrained Machine Learning Pipeline for Young's Modulus Prediction in Multimaterial Hyperelastic Cylinders Guided by Contact Mechanics

Advanced Intelligent Discovery, EarlyView.
A physics‐guided machine learning framework estimates Young's modulus in multilayered multimaterial hyperelastic cylinders using contact mechanics. A semiempirical stiffness law is embedded into a custom neural network, ensuring physically consistent predictions. Validation against experimental and numerical data on C.
Christoforos Rekatsinas, Panagiotis Krokidas, Vasileios Vavourakis, Clara Essmann, George Giannakopoulos   +4 more
wiley   +1 more source

Programmable Nanoscale Motion via Molecular Patterning on DNA Origami

Angewandte Chemie, EarlyView.
DNA origami nanorods enable precise urease placement with tunable coverage and asymmetry, revealing that propulsion depends on a balance of catalytic loading and geometry. Maximum speed occurs at ∼25% end‐coverage and declines as enzyme distribution becomes more symmetrical.
Lars Paffen, Maurik Engelbert van Bevervoorde, Andoni Rodriguez‐Abetxuko, Loai Abdelmohsen, Remco van der Hofstad, Jan C.M. van Hest, Tania Patiño Padial   +6 more
wiley   +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

Interpretability and Representability of Commutative Algebra, Algebraic Topology, and Topological Spectral Theory for Real‐World Data

Advanced Intelligent Discovery, EarlyView.
This article investigates how persistent homology, persistent Laplacians, and persistent commutative algebra reveal complementary geometric, topological, and algebraic invariants or signatures of real‐world data. By analyzing shapes, synthetic complexes, fullerenes, and biomolecules, the article shows how these mathematical frameworks enhance ...
Yiming Ren, Guo‐Wei Wei
wiley   +1 more source