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A groundbreaking study published in 2025 introduces an innovative computer vision-driven framework designed to automatically identify and analyze plastic deformation events from high-resolution digital image correlation (HR‑DIC) data . https://www.sciencedirect.com/science/article/pii/S1044580325006953 Key Highlights: Automated Extraction of Deformation EventsThe method captures localized plastic deformation with high precision, streamlining what has traditionally been a time-consuming and subjective analysis …

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Pleased to share our new article published in International Journal of Plasticity:“Strain localization induced by closely spaced lamellae structure in a Mg alloy containing long period stacking ordered structure”  https://www.sciencedirect.com/science/article/pii/S0749641925001822 This study advances our fundamental understanding of deformation mechanisms in magnesium alloys and provides guidance for the design of rare-earth-containing Mg alloys. Proud of this …

Plasticity in Magnesium alloys Read More »

Modeling the evolution of slip localization: Realization of link to material strength Check out our latest co-authored article, “Modeling the evolution of slip localization: Realization of link to material strength,” recently published in Acta Materialia, in collaboration with the UCSB team. In this work, we combine multiscale modeling with experimental datasets across a wide range …

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New publication details a novel ML-based method for accelerated mechanical properties prediction from encoding and mapping metal plasticity. Encoding metal plasticity captured from high-resolution digital image correlation (DIC) can be leveraged to predict a wide range of monotonic and cyclic macroscopic properties of metallic materials. To capture the spatial heterogeneity of plasticity that develops in …

Plasticity Encoding for Accelerated Mechanical Properties Prediction Read More »

New publication details a novel method for accelerated mechanical properties prediction! We developed a method that integrates additively manufactured functionally graded materials, automated high resolution measurements, and leverage fundamental relationships between local plasticity and macroscopic properties to rapidly predict the fatigue strength of metallic materials. Recent improvements in additive manufacturing and high-throughput material synthesis have …

High-throughput Prediction of Metal Fatigue Strength Read More »

The group published a new study in materials informatics, introducing a machine learning encoding approach for automatically identifying metal microstructures. This advancement paves the way for autonomous metal characterization. Article: https://arxiv.org/abs/2501.18064 Abstract: To leverage advancements in machine learning for metallic materials design and property prediction, it is crucial to develop a data-reduced representation of metal …

Learning Metal Microstructure through AI Read More »

Explore our group’s latest publication in Acta Materialia, led by Dhruv Anjaria. Our research focuses on the plasticity of a FCC material at cryogenic temperatures (liquid nitrogen and helium temperatures). We discovered a novel deformation mechanism where deformation twinning and slip compete, causing the delocalization of plastic deformation, which impacts the properties of metallic materials …

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Check out our latest publication in Acta Materialia: https://lnkd.in/gNftY7e6 Utilizing high-temperature, high-resolution digital image correlation, we’ve been able to observe the temperature-dependence of plastic localization at the nanoscale across a wide field of view. This approach has led to a deeper understanding of the microstructure-dependence of diffusion creep (Coble creep) phenomena during the deformation of …

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Our research team has made a breakthrough in understanding the micro-mechanisms that contribute to fatigue damage under tension-tension loading. These findings are detailed in our recent publication in the journal Acta Materialia. The paper, authored by R.L. Black, D. Anjaria, J. Genée, V. Valle, and J. C. Stinville, is titled “Micro-Strain and Cyclic Slip Accumulation …

Cyclic Slip Accumulation in Structural Metals Read More »

The Stinville group, in partnership with researchers from UCSB, Mines ParisTech, UIUC, and BAM, has recently published an article in the prestigious ARMR journal. The paper presents groundbreaking research endeavors focused on comprehending the localization of plasticity in metals. Insights into Plastic Localization by Crystallographic Slip from Emerging Experimental and Numerical Approaches Annual Review of …

Annual Review of Materials Research Read More »