Results 61 to 70 of about 9,063 (196)
Deep Learning‐Assisted Coherent Raman Scattering Microscopy
The analytical capabilities of coherent Raman scattering microscopy are augmented through deep learning integration. This synergistic paradigm improves fundamental performance via denoising, deconvolution, and hyperspectral unmixing. Concurrently, it enhances downstream image analysis including subcellular localization, virtual staining, and clinical ...
Jianlin Liu +4 more
wiley +1 more source
A two‐nanosensor electrochemical strategy quantitatively distinguishes reactive oxygen species (ROS) in stress granules (SGs) from catecholamines in vesicles inside living cells. Chronic SGs formed under prolonged stress show elevated ROS and slower release, consistent with SG aging, and promote neurotransmitter loading likely through vesicle fusion ...
Hui Gu +3 more
wiley +2 more sources
Deep Learning‐Assisted Design of Mechanical Metamaterials
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 +5 more
wiley +1 more source
Modular Assembly of Dynamic Polymer Networks From Heteroaffinity Cross‐Links to Multivalent Proteins
This study develops a method to modularly assemble oligomeric binding proteins, like streptavidin, using heterobifunctional cross‐linkers that have both a strong‐ and a weak‐affinity binding moiety. These dynamic cross‐linkers enable the assembly of polymer networks with unique meta‐stable nonequilibrium topologies, and that exhibit chemically tunable ...
Tianyue Dai +6 more
wiley +2 more sources
Evolution of Physical Intelligence Across Scales
By following the evolution of physical intelligence across scales, this article shows how intelligence arises from materials, structures, physical interactions, and collectives. It establishes physical intelligence as the evolutionary foundation upon which embodied intelligence is built.
Ke Liu +7 more
wiley +1 more source
Visualizing and Quantifying microRNA‐Induced DNA Origami Separation at the Nanoscale
Clinically relevant miRNA biomarkers trigger the disassembly of DNA origami dimers into monomers through a toehold‐mediated strand displacement reaction. High‐speed AFM was used to visualize this reaction in real time, while solid‐state nanopore measurements quantified the populations of dimers and monomers, as well as the resulting miRNA concentration,
Chalmers C. C. Chau +4 more
wiley +2 more sources
The approach of physical in materia computing incorporates parallel computing within the medium itself. A scalable and energy‐efficient, oxide‐based computational platform is realized in form of a nanoporous network of volatile niobium oxide memristors sandwiched between top and bottom metallic electrodes, and then tested for prediction and ...
Joshua Donald +7 more
wiley +1 more source
A volatile‐switching compact model of electrochemical metallization memory cells for neuromorphic architecture is developed and validated by reliable reproduction of device characterization measurements: I−V sweeps, SET kinetics, relaxation dynamics.
Rana Walied Ahmad +4 more
wiley +1 more source
Enabling Stochastic Dynamic Games for Robotic Swarms
This paper scales stochastic dynamic games to large swarms of robots through selective agent modeling and variable partial belief space planning. We formulate these games using a belief space variant of iterative Linear Quadratic Gaussian (iLQG). We scale to teams of 50 agents through selective modeling based on the estimated influence of agents ...
Kamran Vakil, Alyssa Pierson
wiley +1 more source
This review explores the transformative impact of artificial intelligence on multiscale modeling in materials research. It highlights advancements such as machine learning force fields and graph neural networks, which enhance predictive capabilities while reducing computational costs in various applications.
Artem Maevskiy +2 more
wiley +1 more source

