A5056192170- High Entropy Alloys Studies
- Metallic Glasses and Amorphous Alloys
- Advanced Materials Characterization Techniques
- Glass properties and applications
- High-Temperature Coating Behaviors
- Additive Manufacturing Materials and Processes
- Material Dynamics and Properties
- Magnetic Properties and Applications
- Microstructure and Mechanical Properties of Steels
- Machine Learning in Materials Science
- Fusion materials and technologies
- Phase-change materials and chalcogenides
- Theoretical and Computational Physics
- Advancements in Battery Materials
- Supercapacitor Materials and Fabrication
- Advanced Battery Materials and Technologies
- Electromagnetic Effects on Materials
Materials Center Leoben (Austria)
2022-2024
Erich Schmid Institute of Materials Science
2019-2021
Austrian Academy of Sciences
2019-2021
While first-principles methods have been successfully applied to characterize individual properties of multi-principal element alloys (MPEA), their use in searching for optimal trade-offs between competing is hampered by high computational demands. In this work, we present a framework explore Pareto-optimal compositions integrating advanced ab initio-based techniques into Bayesian multi-objective optimization workflow, complemented simple analytical model providing straightforward analysis...
Metallic glass composites with shape memory crystals show enhanced plasticity and work-hardening capability. We investigate the influence of various critical structural aspects such as, density crystalline precipitates, their distribution size, features intrinsic properties phase on deformation behavior metallic amorphous Cu 64 Zr 36 B2 CuZr inclusions using molecular dynamics simulations. find that a low small spacing smaller than shear band length controls formation plastic zones in...
Shear transformation zone (STZ) remains the fundamental unit to explain plastic flow in metallic glasses (MGs). Although STZs have been known and characterized for decades now morphological dynamical characteristics of are not fully understood yet. Here, simulating athermal quasistatic shearing processes, atomic-level mechanisms underlying elastic deformation MGs disclosed. Given highly heterogeneous nature glassy materials related rugged energy landscape activation is observed from an early...
Boron solubility and segregation in paramagnetic (PM) fcc iron have been investigated by means of DFT calculations. The results focus on the site preference both bulk coincidence lattice model $\mathrm{\ensuremath{\Sigma}}5$ (012) GB Fe evaluate validity different approaches for modeling PM state. are predicted to form an interstitial solid solution. state pressure correction introduced into 0 K calculations as a function its thermal expansion within temperature range 0--1670 K. relatively...
The effects of cooling rate, temperature, and applied strain rate on the tensile deformation behavior a Cu64Zr36 metallic glass (MG) are investigated using large-scale molecular dynamics simulations. An increase in quenching during sample preparation, as well an temperature or affects activation shear transformation zones (STZs) and, consequently, shear-banding processes, which ultimately causes brittle-to-ductile transition MGs. A quantitative interpretation for observed enhanced ductility...
Abstract The cycling stability of Li-ion batteries is commonly attributed to the formation solid electrolyte interphase (SEI) layer, which generated on active material surface during electrochemical reactions in battery operation. Silicon experiences large volume changes upon Li-insertion and extraction, leading amorphization silicon-interface due permeation Li-ions into silicon. Here, we discover how non-hydrostatic strain further triggers dislocation eventually shear band within...
High entropy alloys (HEA) represent a class of materials with promising properties, such as high strength and ductility, radiation damage tolerance, etc. At the same time, combinatorially large variety compositions complex structure render them quite hard to study using conventional methods. In this work, we present computationally efficient methodology based on ab initio calculations within coherent potential approximation. To make predictive, apply an exchange-correlation correction...
The efficient energy use in multiple sectors of modern industry is partly based on the high-strength, high-performance alloys that retain remarkable mechanical properties at elevated and high temperatures. High-entropy (HEAs) represent most recent class these materials with a potential for high-temperature high-strength applications. Aside from their chemical composition microstructure-property relationship, limited information effect heat treatment as decisive factor alloy design available...
High entropy alloys (HEA) represent a class of materials with promising properties, such as high strength and ductility, radiation damage tolerance, etc. At the same time, combinatorially large variety compositions complex structure render them quite hard to study using conventional methods. In this work, we present computationally efficient methodology based on ab initio calculations within coherent potential approximation. To make predictive, apply an exchange-correlation correction...
Impurities can strongly influence dislocation behavior and thus impact plasticity. Quantifying dislocation-impurity interactions in $\alpha$-Fe from ab initio across a wide temperature range is challenging due to paramagnetism at elevated temperatures. In this work, we investigate the energy profiles segregation of various 3d elements - V, Cr, Mn, Cu, Ni, Co around $1/2\langle111\rangle$ screw dislocations ferromagnetic paramagnetic state with latter being modeled through both disordered...
While first-principles methods have been successfully applied to characterize individual properties of multi-principal element alloys (MPEA), their use search for optimal trade-offs between competing is hampered by high computational demands. In this work, we present a novel framework explore Pareto-optimal compositions integrating advanced ab-initio-based techniques into Bayesian multi-objective optimization method. We benchmark the applying it solid solution strengthening and ductility...