Computational modeling of dislocation evolution and strain hardening in deformed metals

We develop a continuum model of dislocation dynamics that predicts the main features of the crystal plasticity at the mesoscale. The model is based on a set of kinetic equations of the curl type that govern the space and time evolution of the dislocation density in all slip systems. These equations can take cross-slip and short range reactions into account. The kinetic equations are coupled with crystal mechanics, stress equilibrium, through a staggered finite element scheme customized to capture the crystallographic nature. The results for the evolution of dislocation density, dislocation patterns, lattice rotation field, and stress–strain relationships are going to be presented. These features are compared with X-ray measurements and that obtained by discrete dislocation dynamics. This study was supported by the U.S. DOE Office of Basic Energy Sciences, Division of Materials Science & Engineering via contract # DEFG02-08ER46494 at Florida State University and by funding from the School of Nuclear Engineering at Purdue University

Multiscale Simulation of Thermo-mechanical Processes in Irradiated Fission-reactor Materials

This report contains a summary of progress made on the subtask area on phase field model development for microstructure evolution in irradiated materials, which was a part of the Computational Materials Science Network (CMSN) project entitled: Multiscale Simulation of Thermo-mechanical Processes in Irradiated Fission-reactor Materials. The model problem chosen has been that of void nucleation and growth under irradiation conditions in single component systems

A quantitative phase-field model for void evolution in defect supersaturated environments: a novel introduction of defect reaction asymmetry

Voids develop in crystalline materials under energetic particle irradiation, as in nuclear reactors. Understanding the underlying mechanisms of void nucleation and growth is of utmost importance as it leads to dimensional instability of the metallic materials. In the past two decades, researchers have adopted the phase-field approach to study the phenomena of void evolution under irradiation. The approach involves modeling the boundary between the void and matrix with a diffused interface. However, none of the existing models are quantitative in nature. This work introduces a thermodynamically consistent, quantitative diffuse interface model based on KKS formalism to describe the void evolution under irradiation. The model concurrently considers both vacancies and self-interstitials in the description of void evolution. Unique to our model is the presence of two mobility parameters in the equation of motion of the phase-field variable. The two mobility parameters relate the driving force for vacancy and self-interstitial interaction to the interface motion, analogous to dislocation motion through climb and glide processes. The asymptotic matching of the phase-field model with the sharp-interface theory fixes the two mobility parameters in terms of the material parameters in the sharp-interface model. The Landau coefficient, which controls the height of the double-well function in the phase field variable, and the gradient coefficient of the phase field variable are fixed based on the interfacial energy and interface width of the boundary. With all the parameters in the model determined in terms of the material parameters, we thus have a new phase field model for void evolution. Simple test cases will show the void evolution under various defect supersaturation to validate our new phase-field model

End-to-end Phase Field Model Discovery Combining Experimentation, Crowdsourcing, Simulation and Learning

The availability of tera-byte scale experiment data calls for AI driven approaches which automatically discover scientific models from data. Nonetheless, significant challenges present in AI-driven scientific discovery: (i) The annotation of large scale datasets requires fundamental re-thinking in developing scalable crowdsourcing tools. (ii) The learning of scientific models from data calls for innovations beyond black-box neural nets. (iii) Novel visualization and diagnosis tools are needed for the collaboration of experimental and theoretical physicists, and computer scientists. We present Phase-Field-Lab platform for end-to-end phase field model discovery, which automatically discovers phase field physics models from experiment data, integrating experimentation, crowdsourcing, simulation and learning. Phase-Field-Lab combines (i) a streamlined annotation tool which reduces the annotation time (by ~50-75%), while increasing annotation accuracy compared to baseline; (ii) an end-to-end neural model which automatically learns phase field models from data by embedding phase field simulation and existing domain knowledge into learning; and (iii) novel interfaces and visualizations to integrate our platform into the scientific discovery cycle of domain scientists. Our platform is deployed in the analysis of nano-structure evolution in materials under extreme conditions (high temperature and irradiation). Our approach reveals new properties of nano-void defects, which otherwise cannot be detected via manual analysis

The Latest Trends in Electric Vehicles Batteries

Global energy demand is rapidly increasing due to population and economic growth, especially in large emerging countries, which will account for 90% of energy demand growth to 2035. Electric vehicles (EVs) play a paramount role in the electrification revolution towards the reduction of the carbon footprint. Here, we review all the major trends in Li-ion batteries technologies used in EVs. We conclude that only five types of cathodes are used and that most of the EV companies use Nickel Manganese Cobalt oxide (NMC). Most of the Li-ion batteries anodes are graphite-based. Positive and negative electrodes are reviewed in detail as well as future trends such as the effort to reduce the Cobalt content. The electrolyte is a liquid/gel flammable solvent usually containing a LiFeP6 salt. The electrolyte makes the battery and battery pack unsafe, which drives the research and development to replace the flammable liquid by a solid electrolyte