A5031082318- Metallic Glasses and Amorphous Alloys
- Material Dynamics and Properties
- Theoretical and Computational Physics
- Glass properties and applications
- Surface Roughness and Optical Measurements
- Cultural and Historical Studies
- Landslides and related hazards
- Textile materials and evaluations
- Tree-ring climate responses
- Silicon Nanostructures and Photoluminescence
- Phase-change materials and chalcogenides
Yale University
2019-2023
Interface (United States)
2019
University of Illinois Urbana-Champaign
2016-2017
Complex materials science problems such as glass formation must consider large system sizes that are many orders of magnitude too to be solved by first-principles calculations. The successful application machine learning (ML) in various other fields suggests ML could useful address complex science. To test its efficacy, we attempt predict bulk metallic using ML. Surprisingly, find a recently developed model based on 201 alloy features constructed simple combinations 31 elemental is...
Abstract Slowly strained solids deform via intermittent slips that exhibit a material-independent critical size distribution. Here, by comparing two disparate systems - granular materials and bulk metallic glasses we show evidence not only the statistics of but also their dynamics are remarkably similar, i.e. independent microscopic details material. By resolving full time evolution avalanches in materials, uncover regime universal deformation dynamics. We experimentally verify predicted...
Extracting avalanche distributions from experimental microplasticity data can be hampered by limited time resolution. We compute the effects of low resolution on size and give quantitative criteria for diagnosing circumventing problems associated with show that traditional analysis obtained at acquisition rates lead to incorrect power-law exponents or no scaling all. Furthermore, we demonstrate it apparent collapses cutoff exponents. propose new methods analyze low-resolution stress-time...
Micro- and nanoresonators have important applications including sensing, navigation, biochemical detection. Their performance is quantified using the quality factor Q, which gives ratio of energy stored to dissipated per cycle. Metallic glasses are a promising material class for micro- nanoscale resonators since they amorphous can be fabricated precisely into complex shapes on these length scales. To understand intrinsic dissipation mechanisms that ultimately limit large Q-values in metallic...
Universality in materials deformation is of intense interest: universal scaling relations if exist would bridge the gap from microscopic to macroscopic response a single material-independent fashion. While recent agreement force statistics deformed nanopillars, bulk metallic glasses, and granular with mean-field predictions supports idea relations, here for first time we demonstrate that universality extends beyond statistics, applies slip dynamics as well. By rigorous comparison two very...
Metallic glasses are frequently used as structural materials. Therefore, it is important to develop methods predict their mechanical response a function of the microstructure prior loading. We coarse-grained spring network model, which describes metallic using an equivalent series springs, can break and re-form mimic atomic rearrangements during deformation. To validate we perform simulations quasistatic, uniaxial tension Lennard-Jones embedded atom method (EAM) potentials for...
A coarse-grained spring network model is proposed for the prediction of mechanical response metallic glasses as a function microstructure prior to loading. This describes using parallel springs that can break and reform, mimicking atomic rearrangements during deformation. We compare predictions stress versus strain results from numerical simulations athermal quasistatic, uniaxial tensile deformation ${\mathrm{Cu}}_{50}{\mathrm{Zr}}_{50}$ Lennard-Jones (LJ) embedded atom method (EAM)...