Results 191 to 200 of about 366,366 (282)

ML Workflows for Screening Degradation‐Relevant Properties of Forever Chemicals

open access: yesAdvanced Science, EarlyView.
The environmental persistence of per‐ and polyfluoroalkyl substances (PFAS) necessitates efficient remediation strategies. This study presents physics‐informed machine learning workflows that accurately predict critical degradation properties, including bond dissociation energies and polarizability.
Pranoy Ray   +3 more
wiley   +1 more source

Fabrication of High‐Density Multimodal Neural Probes Based on Heterogeneously Integrated CMOS

open access: yesAdvanced Science, EarlyView.
A chiplet‐based methodology democratizes active neural probe development on standard bulk CMOS services. This yields the first probe combining high‐density electrophysiology (416 electrodes) with calcium imaging (832 photodiodes) and complete on‐chip signal processing across 13 shanks.
Ju Hee Mun   +10 more
wiley   +1 more source

Single‐Particle Mid‐Infrared Photothermal Imaging Reveals Hidden Heterogeneity in Real‐World Micro‐ and Nanoplastics

open access: yesAdvanced Science, EarlyView.
Mid‐infrared photothermal imaging enables multidimensional profiling of micro‐ and nanoplastics in bottled water. A total of 9.9 × 104 particles L−1 is detected, with 64% in the nanoscale regime. Spectral evolution, including peak narrowing and band shifts, reveals local chain reorganization in polyethylene terephthalate (PET), highlighting intrinsic ...
Xinyu Deng   +4 more
wiley   +1 more source

Cells Dynamically Adapt Their Nuclear Volumes and Proliferation Rates During Single to Multicellular Transitions

open access: yesAdvanced Science, EarlyView.
It is currently not well understood how cells regulate basic properties, e.g., volume and mechanics within dense multicellular environments like tumors. Here, we show that different cell types of cancer and also normal cells largely decrease their nuclear and cellular volumes in emerging cell clusters and that this is partly driven by cell cycle shifts.
Vaibhav Mahajan   +13 more
wiley   +1 more source

Physical Implementation of Optical Material‐Based Neural Networks Processing Enabled by Long‐Persistent Luminescence

open access: yesAdvanced Science, EarlyView.
This study reports on the physical implementation of optical material‐based neural processing using long‐persistent luminescence as memory‐retention and nonlinear optical material. The system performs optical‐domain preprocessing with opto‐electronic interfaces for stimulus delivery and readout, enabling real‐time demonstrations including Pong gameplay
Sangwon Wi, Yunsang Lee
wiley   +1 more source

Integrating Machine Learning With Constant‐Potential Simulation to Unravel Charge‐Transfer Mechanisms in Electrochemical Nitrogen Fixation

open access: yesAdvanced Science, EarlyView.
Integrating interpretable machine learning with the fixed‐potential method reveals a novel mechanism: the catalytic activity of the electrochemical nitrogen reduction reaction is governed by partial charge transfer, induced by variations in the intermediate potential of zero charge under constant potential.
Yufei Xue   +6 more
wiley   +1 more source

Real‐Time In Vivo Visualization of Tumor‐Associated Macrophage Reprogramming Using a Nitric Oxide‐Activatable NIR‐II Nanoinducer

open access: yesAdvanced Science, EarlyView.
Reprogramming tumor‐associated macrophages is a promising therapeutic strategy for solid tumors. Here, a nitric oxide (NO)‐activatable NIR‐II fluorescence/photoacoustic nanoinducer (I/E@M2pep) that simultaneously facilitates and visualizes the repolarization of TAMs to an M1‐like phenotype is reported, thereby enhancing anti‐tumor efficacy through M1 ...
Qian Chen   +8 more
wiley   +1 more source

Efficient Screening of Organic Singlet Fission Molecules Using Graph Neural Networks

open access: yesAdvanced Science, EarlyView.
A high‐throughput screening framework based on graph neural networks (GNNs) and multi‐level validation facilitates the identification of singlet fission (SF) candidates. By efficiently predicting excitation energies across 20 million molecules, and integrating TDDFT calculations, synthetic accessibility assessments, and GW+BSE calculations, this ...
Li Fu   +5 more
wiley   +1 more source

Ferroelectric Devices for In‐Memory and In‐Sensor Computing

open access: yesAdvanced Science, EarlyView.
Inspired by biological systems, in‐memory and in‐sensor computing overcome von Neumann bottlenecks. Ferroelectric devices can mimic synaptic functions and sense stimuli like light or force, therefore are ideal for these paradigms. This review introduces the ferroelectric devices applied for in‐memory and in‐sensor computing, covering their structures ...
Hong Fang   +5 more
wiley   +1 more source

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