Results 171 to 180 of about 89,843 (211)

A Biomimetic Solvatochromic Chip With Optimized Chemical Diversity for On‐Site Liquid Identification

open access: yesAdvanced Science, EarlyView.
A compact biomimetic photonic‐gustatory chip uses Hansen‐solubility‐parameter‐guided solvatochromic disks to create distinct color patterns in organic liquids. An optimized four‐disk array distinguishes solvent types, ratios, homologues, isomers, and alcoholic beverages. Coupled with smartphone imaging and deep learning, it identifies 80 liquid classes
Jintao Zhang   +9 more
wiley   +1 more source

Massively Multiplexed Photonic Chip With Cross‐Channel Fusion For Harmonized Biosensing

open access: yesAdvanced Science, EarlyView.
We introduce a transformative sensing platform integrating photonic multiplexing with over 10 000 sensors and a deep‐learning framework that combines domain adaptation and cross‐channel fusion for harmonized operation across heterogeneous chips. The platform achieves 99.3% identification accuracy and relative prediction errors of 10−4$^{-4}$ for ...
Ivan Saetchnikov   +3 more
wiley   +1 more source

AI‐EXAFS: Physics‐Informed Prediction of EXAFS from Atomic Structure

open access: yesAdvanced Science, EarlyView.
AI‐EXAFS presents a neural network to reproduce EXAFS. Trained on synthetic data and with a careful selection of the settings both for the physical representation of the system and following the experimental heuristic loss functions, the model is capable of reproducing EXAFS spectra for molecules from the tridimensional structure.
Javier Heras‐Domingo   +6 more
wiley   +1 more source

Physics‐Guided Multi‐Channel Restoration for Efficient and Accurate Atomic Force Microscopy Imaging

open access: yesAdvanced Science, EarlyView.
Schematic figure of restoring noisy atomic force micrscopy (AFM) image via physics‐guided multi‐channel restoration. The lighter neural network models with multiple‐channel input from auxiliary signals outperforms heavier model with single‐channel input.
Jaeuk Sung   +13 more
wiley   +1 more source

From Artificial to Embodied and Physical Intelligence in Smart Manufacturing

open access: yesAdvanced Science, EarlyView.
Smart manufacturing is reframed through complementary artificial, embodied, and physical intelligence, spanning computational reasoning, perception‐action coupling, and material‐level adaptation. Their integration across design, fabrication, operation, and maintenance reveals how intelligence can be co‐designed across algorithms, embodied agents, and ...
Kang Wang   +9 more
wiley   +1 more source

An AI‐Driven Framework for Directed Self‐Assembly Toward Design‐Technology Co‐Optimization

open access: yesAdvanced Science, EarlyView.
An artificial intelligence (AI)‐driven closed‐loop framework integrates experiment, three‐dimensional physics‐based simulation, and template design for directed self‐assembly (DSA). Guided by experimental data, AI‐assisted calibration accelerates model optimization, supports morphology prediction, and identifies template windows.
Caiwei Shang   +9 more
wiley   +1 more source

Multifunctional Vertical Bulk‐Heterojunction Transistors With Amorphous GaOx for Neuromorphic Perception‐to‐Decision

open access: yesAdvanced Science, EarlyView.
A multifunctional vertical bulk‐heterojunction transistor (MVBT) with amorphous GaOx integrates four functionalities within a single neuromorphic device. Gate‐source operation enables 254 nm deep‐ultraviolet sensing and threshold neuronal firing, whereas three‐terminal operation supports broadband UV–vis‐NIR synaptic functions and bias‐controlled ...
Jinkui Si   +12 more
wiley   +1 more source

SpaCut: Transcript‐Aware Morphology Fusion for Robust Cell Segmentation in Subcellular Spatial Transcriptomics

open access: yesAdvanced Science, EarlyView.
Subcellular spatial transcriptomics enables high‐resolution mapping of gene expression within tissues, but accurate cell segmentation is essential for assigning transcripts to individual cells. We present SpaCut, a deep learning framework that integrates transcriptomic features with nucleus‐guided morphological information to precisely delineate cell ...
Yongheng Li, Fangfang Zhu, Wenwen Min
wiley   +1 more source

XChrom: A Cross‐Cell Chromatin Accessibility Prediction Model Integrating Genomic Sequence and Cellular Context

open access: yesAdvanced Science, EarlyView.
XChrom is a deep learning framework that integrates genomic sequence and single‐cell context to predict chromatin accessibility. It generalizes to unseen cells and genomic regions, enabling cross‐sample and cross‐species analysis. Applied to COVID‐19 patient data, XChrom reveals key transcriptional regulatory mechanisms and disease‐associated ...
Yuanyuan Miao   +5 more
wiley   +1 more source

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