Abstract

High-Entropy Alloys (HEAs) are an emergent class of crystalline materials have exhibited unique mechanical properties and high-temperature functionality. Their unusual composition, having multiple principal elements in contrast to common alloys that use one principal element, results in a variety of useful, and in many cases unexpected characteristics. This project, in partnership with experimentalists at the Idaho National Laboratory and machine learning scientists at the University of Utah, explores these characteristics and composition-property relationships in HEAs. Utilizing Molecular Dynamics (MD) simulations, three HEAs, namely FeNiCr, FeNiCrCo, and FeNiCrCoCu, are studied in detail. The radial distribution function (RDF) and tensile strength (TS) are calculated for each alloy, and their values compared as a function of temperature, chemical content, and slip orientation. We used RDF analysis as a basis to examine the stability of HEAs; Fe- and Ni-dominant alloys consistently show five narrow RDF peaks, indicating a strong fit to the desired FCC lattice. We used this strategy to ensure the accuracy of further calculations as well as to demonstrate that MD offers a cost-effective tool for the qualitative analysis of materials. Additionally, we show that RDF analysis can be used as a basic predictive model for more complicated mechanical properties of a crystal, an important asset in material design and machine learning. Finally, we tested these predictions via study of stress-strain curves to evaluate TS of various alloys. We observe that Fe- and Ni-dominant alloys are strongest with peak values ranging from 23 to 26 GPa, while Co- and Cu-dominant alloys are weakest with peak values of 17 and 13 GPa respectively. We uncover fundamental relationships between TS and chemical composition in HEAs – especially the identity of the dominant element – as well as temperature and slip orientation, all of which are critical variables to consider in material design and functionality. Overall, the results in this work offer basic guidelines to design stable high temperature alloys and further highlight the importance of understanding composition-property relationships in HEAs. This work also underlines the power of MD, as it serves as a first step in establishing a high-throughput computational framework to study diverse alloys, with the ultimate goal of understanding the behavior of HEAs in its entirety.

Library of Congress Subject Headings

Metallic composites--Mechanical properties; Alloys--Mechanical properties; Molecular dynamics--Computer simulation

Publication Date

7-15-2021

Document Type

Thesis

Student Type

Graduate

Degree Name

Materials Science and Engineering (MS)

Department, Program, or Center

School of Chemistry and Materials Science (COS)

Advisor

Pratik Dholabhai

Advisor/Committee Member

Moumita Das

Advisor/Committee Member

Christina Goudreau-Collison

Campus

RIT – Main Campus

Plan Codes

MSENG-MS

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