A5035563258- Microstructure and mechanical properties
- Nuclear Materials and Properties
- Machine Learning in Materials Science
- Fusion materials and technologies
- Ion-surface interactions and analysis
- nanoparticles nucleation surface interactions
- Solidification and crystal growth phenomena
- Composite Material Mechanics
- Advanced Materials Characterization Techniques
- High Temperature Alloys and Creep
- Nuclear reactor physics and engineering
- Metal and Thin Film Mechanics
- Integrated Circuits and Semiconductor Failure Analysis
- Fatigue and fracture mechanics
- High-Velocity Impact and Material Behavior
- Manufacturing Process and Optimization
- Semiconductor materials and devices
- Nuclear and radioactivity studies
- Diamond and Carbon-based Materials Research
- Hydrogen embrittlement and corrosion behaviors in metals
- High Entropy Alloys Studies
- Nuclear materials and radiation effects
- Microstructure and Mechanical Properties of Steels
- Metallurgy and Material Forming
- Electron and X-Ray Spectroscopy Techniques
Center for Integrated Nanotechnologies
2018-2025
Sandia National Laboratories
2016-2025
Georgia Institute of Technology
2005-2022
Sandia National Laboratories California
2012-2022
John Brown University
2022
New York University
2010
Office of Scientific and Technical Information
2009
National Technical Information Service
2009
Woodruff Health Sciences Center
2006
Abstract The phase-field method is a powerful and versatile computational approach for modeling the evolution of microstructures associated properties wide variety physical, chemical, biological systems. However, existing high-fidelity models are inherently computationally expensive, requiring high-performance computing resources sophisticated numerical integration schemes to achieve useful degree accuracy. In this paper, we present inexpensive, accurate, data-driven surrogate model that...
Abstract Phase-field modeling is an effective but computationally expensive method for capturing the mesoscale morphological and microstructure evolution in materials. Hence, fast generalizable surrogate models are needed to alleviate cost of taxing processes such as optimization design The intrinsic discontinuous nature physical phenomena incurred by presence sharp phase boundaries makes training model cumbersome. We develop a framework that integrates convolutional autoencoder architecture...
This Letter explores the stability of disconnections (step-dislocation defects) at grain boundaries in binary alloys. We introduce interfacial defect diagrams, derived from atomistic simulations and segregation theory, to predict temperature-solute concentration phase space relate it governing mechanisms. These diagrams reveal multiple regimes influenced by solute-induced clustering pinning effects impacting thermal migration offering insights into their thermodynamics kinetic properties....
While lattice metamaterials can achieve exceptional energy absorption by tailoring periodically distributed heterogeneous unit cells, relatively little focus has been placed on engineering heterogeneity above the unit-cell level. In this work, energy-absorption performance of with a spatial layout different cell architectures was studied. Such multi-morphology lattices harness distinct mechanical properties cells while being composed out single base material. A rational design approach...
The phase-field method is a popular modeling technique used to describe the dynamics of microstructures and their physical properties at mesoscale. However, because in these simulations microstructure described by system continuous variables evolving both space time, models are computationally expensive. They require refined spatio-temporal discretization parallel computing approach achieve useful degree accuracy. As an alternative, we present discuss accelerated which uses recurrent neural...
Digital twins are emerging as powerful tools for supporting innovation well optimizing the in-service performance of a broad range complex physical machines, devices, and components. A digital twin is generally designed to provide accurate in-silico representation form (i.e., appearance) functional response specified (unique) twin. This paper offers new perspective on how concept could be applied accelerate materials efforts. Specifically, it argued that material itself can considered highly...
Abstract Materials simulations based on direct numerical solvers are accurate but computationally expensive for predicting materials evolution across length- and time-scales, due to the complexity of underlying equations, nature multiscale spatiotemporal interactions, need reach long-time integration. We develop a method that blends with neural operators accelerate such simulations. This methodology is integration community solver U-Net operator, enhanced by temporal-conditioning mechanism...
Metals subjected to irradiation environments undergo microstructural evolution and concomitant degradation, yet the nanoscale mechanisms for such remain elusive. Here, we combine in situ heavy ion irradiation, atomic resolution microscopy, atomistic simulation elucidate how radiation damage interfacial defects interplay control grain boundary (GB) motion. While classical notions of under rest on simple ideas curvature-driven motion, reality is far more complex. Focusing an ion-irradiated Pt...
Abstract The increasing demand for high‐performance piezoelectric materials and toxicity thermal stability issues of the widely used lead zirconate titanates (PZT) have spurred a search better alternatives in electronic devices. In comparison to PZT, group III nitrides such as aluminum nitride (AlN), are only weakly piezoelectric, but doping AlN with scandium (Sc) improves response by nearly 500%. Relative doped‐AlN advantageous because they far more compatible complementary...
The interaction of energetic ions with the electronic and ionic system target materials is an interesting but challenging multiscale problem, understanding early stages after impact heavy, initially charged particularly poor. At same time, energy deposition during these determines later formation damage cascades. We address character by combining real-time time-dependent density functional theory for electron dynamics molecular simulations Our first-principles prove that core electrons...
Twinning is a frequent deformation mechanism in nanocrystalline metals, and segregation of solute atoms at twin boundaries thermodynamic process that plays an important role the stability strengthening these materials. In pristine, defect-free boundaries, generally follows single- or multilayer patterned coverage solutes uniformly symmetrically distributed sites across boundary. However, when disconnection, type interfacial line defect, present boundary, we report possible discontinuity...
The acquisition of large atomic-force-microscopy (AFM) scans at nanoscale resolutions can take hours and produce datasets with millions pixels, which is time consuming computationally expensive to analyze. In this paper, we present an approach speed up process by using a computer-vision algorithm, namely the Noise2Noise reconstruct high-resolution, low scan AFM data from high-speed, noisy, sparsely sampled data. This algorithm trained on various noise types reproduce different sources...
We present a high-level architecture for how artificial intelligences might advance and accumulate scientific technological knowledge, inspired by emerging perspectives on human such knowledge. Agents knowledge exercising technoscientific method—an interacting combination of engineering methods. The method maximizes quantity we call "useful learning" via more-creative implausible utility (including the "aha!" moments discovery), as well less-creative plausible utility. Society accumulates...
We introduce physics-informed multimodal autoencoders (PIMA) - a variational inference framework for discovering shared information in datasets. Individual modalities are embedded into latent space and fused through product-of-experts formulation, enabling Gaussian mixture prior to identify features. Sampling from clusters allows cross-modal generative modeling, with mixture-of-experts decoder that imposes inductive biases scientific knowledge thereby imparts structured disentanglement of...
Sputter-deposited Pt-Au thin films have been reported to develop a hard, stable, nanocrystalline structure, yet little is known about how these characteristics vary with PtxAu1−x composition and process conditions. Toward this end, document describes an extensive, combinatorial film library including characterized compositions, properties. Complemented by kinematic Monte Carlo simulations of codeposition, broad range compositions (from x ∼ 0.02 0.93) was first established sputtering varied...