Results 221 to 230 of about 17,806 (305)
Advanced Intelligent Discovery, EarlyView.Predictive models successfully screen nanoparticles for toxicity and cellular uptake. Yet, complex biological dynamics and sparse, nonstandardized data limit their accuracy. The field urgently needs integrated artificial intelligence/machine learning, systems biology, and open‐access data protocols to bridge the gap between materials science and safe ...
Mariya L. Ivanova +4 more
wiley +1 more source
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
Maximum-entropy and subspace methods for high-resolution relaxation-diffusion distribution estimation. [PDF]
Imaging Neurosci (Camb)Ning L.
europepmc +1 more source
Machine Learning Driven Inverse Design of Broadband Acoustic Superscattering
Advanced Intelligent Discovery, EarlyView.Multilayer acoustic superscatterers are designed using machine learning to achieve broadband superscattering and strong sound insulation. By incorporating a weighted mean absolute error into the loss function, the forward and inverse neural networks accurately map structural parameters to spectral responses.
Lijuan Fan, Xiangliang Zhang, Ying Wu
wiley +1 more source
First-principles simulation of spin diffusion in static solids using dynamic mean-field theory. [PDF]
Sci AdvGräßer T, Uhrig GS, Ernst M.
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
An Adaptive Multiparameter Penalty Selection Method for Multiconstraint and Multiblock ADMM. [PDF]
IEEE Open J Signal ProcessLozenski L, McCann MT, Wohlberg B.
europepmc +1 more source
Toward Intelligent Multimodal Holography for Real‐Time Chemical Imaging of Dynamic Ion Separation
Advanced Intelligent Discovery, EarlyView.Intelligent multimodal holography integrates digital off‐axis holography, spectroscopic imaging, and AI‐driven reconstruction to visualize ion transport and chemical dynamics in real time. In this perspective paper, we outline how this approach enables label‐free, chemically specific monitoring of complex environments and discuss its potential to ...
Giovanna Ricchiuti +3 more
wiley +1 more source
Implementing physics-informed neural networks with deep learning for differential equations. [PDF]
Front Artif IntellEmmert-Streib F +3 more
europepmc +1 more source
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 +4 more
wiley +1 more source