Results 171 to 180 of about 6,691 (300)

Understanding strain localization in metallic materials: a review of high-resolution digital image correlation and related techniques. [PDF]

Sci Technol Adv Mater
Briffod F, Edwards TEJ, da Fonseca JQ, Stinville JC, Texier D, Vermeij T.   +5 more
europepmc   +1 more source

When Biology Meets Medicine: A Perspective on Foundation Models

Advanced Intelligent Discovery, EarlyView.
Artificial intelligence, and foundation models in particular, are transforming life sciences and medicine. This perspective reviews biological and medical foundation models across scales, highlighting key challenges in data availability, model evaluation, and architectural design.
Kunying Niu, Yuxing Wang, Limin Zou, Jing Huang   +3 more
wiley   +1 more source

Enhanced Wear Resistance of Tungsten-Reinforced Brass Surface Composite Produced Through Friction Stir Processing at Varying Tool Rotational Speed. [PDF]

Materials (Basel)
Alswat HM, Sivaraman K, Chinnasamy B, Soundararaja Perumal V, Aziz EIA.   +4 more
europepmc   +1 more source

AI‐Driven Cancer Multi‐Omics: A Review From the Data Pipeline Perspective

Advanced Intelligent Discovery, EarlyView.
The exponential growth of cancer multi‐omics data brings opportunities and challenges for precision oncology. This review systematically examines AI's role in addressing these challenges, covering generative models, integration architectures, Explainable AI for clinical trust, clinical applications, and key directions for clinical translation.
Shilong Liu, Shunxiang Li, Kun Qian
wiley   +1 more source

Effect of Al and Mo Redistribution on α/β Interface Stability in Dual-Phase Titanium Alloys During Plastic Deformation. [PDF]

Materials (Basel)
Zhang W, Shi M, Guo Z, Ma S, Chen Q.
europepmc   +1 more source

Uncertainty‐Guided Selective Adaptation Enables Cross‐Platform Predictive Fluorescence Microscopy

Advanced Intelligent Discovery, EarlyView.
Deep learning models often fail when transferred to new microscopes. A novel framework overcomes this by selectively adapting the early layers governing low‐level image statistics, while freezing deep layers that encode morphology. This uncertainty‐guided approach enables robust, label‐free virtual staining across diverse systems, democratizing ...
Kai‐Wen K. Yang, Andrew Bai, Alexandra Bermudez, Yunqi Hong, Zoe Latham, Iris Sloan, Michael Liu, Vishrut Goyal, Cho‐Jui Hsieh, Neil Y. C. Lin   +9 more
wiley   +1 more source

Thermally Induced Creep and Viscoelastic Behavior of Copper Micropillar Arrays. [PDF]

Adv Sci (Weinh)
Wang M, Zhang J, Gao L, Chen H, Luo W, Li W, Chen M, Li M, Wang D, Li S, Liu T, Cai X, Li Y, Peng B, Zhang W.   +14 more
europepmc   +1 more source

AI‐BioMech: Deep Learning Prediction of Mechanical Behavior in Aperiodic Biological Cellular Materials

Advanced Intelligent Discovery, EarlyView.
AI‐BioMech is a deep learning framework that predicts the mechanical behavior of biological cellular materials directly from 2D images. By replacing traditional finite element analysis with semantic segmentation, it identifies stress and strain distributions with 99% accuracy, offering a high‐speed, scalable alternative for analyzing complex, aperiodic
Haleema Sadia, Marcelo A. Dias, Parvez Alam   +2 more
wiley   +1 more source

Mechanical and Thermal Properties of AlN-SiC Composite Ceramics Fabricated by In Situ Reaction Hot-Pressing Sintering. [PDF]

Materials (Basel)
Zhao X, Wang B, He P, Qiu S, Zhang X, Xin W, Pang J, Huang R.   +7 more
europepmc   +1 more source

From Data to Discovery: Machine Learning–Enabled Intelligent Characterization of Two‐Dimensional Materials

Advanced Intelligent Discovery, EarlyView.
Machine learning serves as a central engine for the intelligent characterization of two‐dimensional materials by integrating multimodal techniques, including optical microscopy, spectroscopy, electron microscopy, and scanning probe microscopy (SPM). This unified framework enables automated, high‐throughput, and quantitative extraction of structural ...
Zhi‐Long Cao, Jia‐Xu Yan
wiley   +1 more source