Results 181 to 190 of about 31,846 (225)

Holographic Mapping of Orbital Angular Momentum using a Terahertz Diffractive Optical Neural Network

Advanced Intelligent Discovery, EarlyView.
A compact six‐layer diffractive optical neural network enables direct recognition and spatial mapping of terahertz (THz) orbital angular momentum (OAM) beams. Fabricated by 3D printing, the system distinguishes nine OAM modes and their superpositions with high fidelity, good efficiency, and low crosstalk, offering a scalable solution for THz ...
Wei Jia, Miguel Gomez, Steve Blair, Berardi Sensale‐Rodriguez   +3 more
wiley   +1 more source

Realization of a Pre-Sample Photonic-Based Free-Electron Modulator in Ultrafast Transmission Electron Microscopes. [PDF]

ACS Photonics
Ferrari BM, Duncan CJR, Yannai M, Dahan R, Rosi P, Ostroman I, Bravi MG, Niedermayr A, Abudi TL, Adiv Y, Fishman T, Park ST, Masiel D, Lagrange T, Carbone F, Grillo V, García de Abajo FJ, Kaminer I, Vanacore GM.   +18 more
europepmc   +1 more source

Explaining the Origin of Negative Poisson's Ratio in Amorphous Networks With Machine Learning

Advanced Intelligent Discovery, EarlyView.
This review summarizes how machine learning (ML) breaks the “vicious cycle” in designing auxetic amorphous networks. By transitioning from traditional “black‐box” optimization to an interpretable “AI‐Physics” closed‐loop paradigm, ML is shown to not only discover highly optimized structures—such as all‐convex polygon networks—but also unveil hidden ...
Shengyu Lu, Xiangying Shen
wiley   +1 more source

Multimode OAM antenna with reduced beam divergence for 6G networks. [PDF]

Sci Rep
Rao MV, Bhattacharyya B, Ram GC, Yuvaraj S, Malik J, Ismail AM, Yasin MNM, Johari S.   +7 more
europepmc   +1 more source

Harnessing Machine Learning to Understand and Design Disordered Solids

Advanced Intelligent Discovery, EarlyView.
This review maps the dynamic evolution of machine learning in disordered solids, from structural representations to generative modeling. It explores how deep learning and model explainability transform property prediction into profound physical insight.
Muchen Wang, Yue Fan
wiley   +1 more source

Micro-pacing and performance determinants in skiathlon: linking speed profiles, sub-technique selection, and cycle characteristics. [PDF]

BMC Sports Sci Med Rehabil
Shang L, Yu H, Shi R, Zhang D, Staunton CA.   +4 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

Computational study of unsteady Homann type flow of ternary hybrid nanofluid in the presence of induced magnetic forces and time relaxation. [PDF]

Discov Nano
Ahmad L, Khan AA, Javed S, Khan U, Bashatah JA.   +4 more
europepmc   +1 more source

Autonomous AI‐Driven Design for Skin Product Formulations

Advanced Intelligent Discovery, EarlyView.
This review presents a comprehensive closed‐loop framework for autonomous skin product formulation design. By integrating artificial intelligence‐driven experiment selection with automated multi‐tiered assays, the approach shifts development from trial‐and‐error to intelligent optimisation.
Yu Zhang, Yongrui Xiao, Chunlin Chen, Dimitrios Tsaoulidis, Kai Yang, Tao Chen   +5 more
wiley   +1 more source

Complex Fluids in a Multifractal Space: Scale Covariance and the Emergence of the Fractal Force. [PDF]

Entropy (Basel)
Rusu DI, Ghizdovat V, Ochiuz L, Rusu O, Oprea I, Dobreci L, Agop M, Vasincu D.   +7 more
europepmc   +1 more source