Results 71 to 80 of about 32,131 (190)

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

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

Self‐Limiting Polymerization‐Induced Crystallization‐Driven Self‐Assembly (SL‐PI‐CDSA) Enables Templated Synthesis of Chiral Plasmonic, Hybrid 2D Hexagonal Assemblies

Angewandte Chemie, EarlyView.
This work details the rapid generation (t ≤ 5 min) of size‐tunable, ultralow dispersity (Ð ≤ 1.01) 2D hexagonal nanosheets by self‐limiting polymerization‐induced crystallization‐driven self‐assembly (SL‐PI‐CDSA) of modular and templating poly(aryl isocyanide) block copolymers, with functions that permit post‐polymerization modifications. Specifically,
Randall A. Scanga, Sean H. Sarault, Amin Kiani, Patryk Wąsik, Anthony J. Branco, Sophie A. Harris, Sangmin Jeong, Ali Shahrokhinia, Jake Borges, Cassidy M. Anunciacao, Jayant Kumar, Lawrence M. Wolf, Michael B. Ross, James F. Reuther   +13 more
wiley   +2 more sources

Why Physics Still Matters: Improving Machine Learning Prediction of Material Properties With Phonon‐Informed Datasets

Advanced Intelligent Discovery, EarlyView.
Phonons‐informed machine‐learning predictive models are propitious for reproducing thermal effects in computational materials science studies. Machine learning (ML) methods have become powerful tools for predicting material properties with near first‐principles accuracy and vastly reduced computational cost.
Pol Benítez, Cibrán López, Edgardo Saucedo, Teruyasu Mizoguchi, Claudio Cazorla   +4 more
wiley   +1 more source

Harmonic fields and the mechanical response of a cellular monolayer to ablation. [PDF]

J Math Biol
Jensen OE, Revell CK.
europepmc   +1 more source

Sound‐Based Assembly of Magnetically Actuated Soft Robots Toward Enhanced Release of Extracellular Vesicles

Advanced Intelligent Systems, Volume 7, Issue 3, March 2025.
Magnetic soft robots offer promise in biomedicine due to their wireless actuation and rapid response, but current fabrication methods are complex and have limited cellular compatibility. A new, contactless bioassembly strategy using hydrodynamic instabilities is introduced, enabling customizable, centimeter‐scale robots.
Wei Gao, Riccardo Tognato, Micaela Natta, Elena Della Bella, Alessandro Cianciosi, Tiziano Serra   +5 more
wiley   +1 more source

Topological data analysis and topological deep learning beyond persistent homology: a review. [PDF]

Artif Intell Rev
Su Z, Liu X, Hamdan LB, Maroulas V, Wu J, Carlsson G, Wei GW, Wei GW.   +7 more
europepmc   +1 more source

A Novel Parameter Estimation Method for Pneumatic Soft Hand Control Applying Logarithmic Decrement for Pseudo‐Rigid Body Modeling

Advanced Intelligent Systems, Volume 7, Issue 3, March 2025.
In this research, a paradigm of parameter estimation method for pneumatic soft hand control is proposed. The method includes the following: 1) sampling harmonic damping waves, 2) applying pseudo‐rigid body modeling and the logarithmic decrement method, and 3) deriving position and force control.
Haiyun Zhang, Kelvin HoLam Heung, Gabrielle J. Naquila, Ashwin Hingwe, Ashish D. Deshpande   +4 more
wiley   +1 more source

SHI: a framework for spatial harmonic imaging. [PDF]

Sci Rep
Diaz JLB, Korvink JG, Kunka D.
europepmc   +1 more source