Results 141 to 150 of about 27,546 (304)
Flexible tactile sensors have considerable potential for broad application in healthcare monitoring, human–machine interfaces, and bioinspired robotics. This review explores recent progress in device design, performance optimization, and intelligent applications. It highlights how AI algorithms enhance environmental adaptability and perception accuracy
Siyuan Wang +3 more
wiley +1 more source
Harnessing Digital Microstructure for Simulation‐Guided Optimization of Permanent Magnets
An experimental‐to‐computational workflow is presented that transforms experimental 3D focused ion beam‐scanning electron microscopy data into a simulation‐ready digital microstructure for multiphase functional materials. Using heavy‐rare‐earth‐free Nd–Fe–B magnets as a model system, the approach quantifies grain connectivity across complex secondary ...
Nikita Kulesh +4 more
wiley +1 more source
Pirolisis Kayu Ketapang (Terminalia Catappal) Menjadi Bio-oil Menggunakan Katalis NiMo/Lempung [PDF]
Recently, the avaibility of petroleum fuels is became limited. It is because the petroleum fuels was not balanced with the community consumption to petroleum fuels is very high.
', K. (Khairat) +2 more
core
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
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
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
Alternative catalysts for low-temperature CO-oxidation [PDF]
MnO sub x, Ag/MnO sub x, Cu/MnO sub x, Pt/MnO sub x, Ru/MnO sub x, Au/CeO sub x, and Au/Fe2O3 were synthesized and tested for CO oxidation activity in low concentrations of stoichiometric CO and O2 at 30 to 75 C.
Brown, David R. +5 more
core +1 more source
A multimodal laser‐induced graphene (LIG)‐based flexible sensor is developed to detect proximity and contact signals. Integrated into a soft robotic hand, it enables vision‐free object searching and grasping. Combined with a convolutional neural network, the system achieves accurate material and texture recognition, enhancing the capability of ...
Youning Duo +9 more
wiley +1 more source
A machine learning‐driven digital twin simulates an aptamer‐functionalized BioFET measuring 17β‐estradiol. Real‐time Isd signals are processed, features are extracted, and trained models estimate hormone concentration. In parallel, a one‐step‐ahead forward model learns biosensor dynamics and generates realistic synthetic signals, enabling in silico ...
Anastasiia Gorelova +4 more
wiley +1 more source
Artificial intelligence (AI) enables the systematic analysis and comparative evaluation of experimental and theoretical data, optimizes the catalytic reaction research workflow, and accelerates the discovery of high‐performance electrocatalysts. ABSTRACT Copper (Cu)‐based single‐atom alloys (SAAs) represent a promising strategy for optimizing the ...
Xuning Wang +5 more
wiley +2 more sources

