Machine Learning Algorithm Prediction and Synthesis of Next Generation Superhard Functional Materials
The goal of this project is to discover new materials that possess the properties needed to enable the technologies of the future. Many materials have outstanding properties that make them desirable for some applications but are deficient in other properties that limit their use. A well-known example is diamond, which is the hardest known material but is also an electrical insulator. Is there a material yet to be discovered that could satisfy the need for a superhard material that also has the high electrical conductivity of a metal or other useful properties?
This project will combine diverse areas of expertise to search for new superhard materials that also possess other desirable properties that enable them to fulfill uniquely demanding technological requirements. Both three-dimensional and two-dimensional forms of these materials will be synthesized. A feedback loop between experiment and theory will be used to characterize the materials, rationally design those with desired properties, and optimize the synthesis protocols. Students will be trained in an interdisciplinary collaborative team of theoreticians and experimentalists whose expertise includes chemistry, physics, and materials science and engineering.
This project will combine diverse areas of expertise to search for new superhard materials that also possess other desirable properties that enable them to fulfill uniquely demanding technological requirements. Both three-dimensional and two-dimensional forms of these materials will be synthesized. A feedback loop between experiment and theory will be used to characterize the materials, rationally design those with desired properties, and optimize the synthesis protocols. Students will be trained in an interdisciplinary collaborative team of theoreticians and experimentalists whose expertise includes chemistry, physics, and materials science and engineering.
Publications
Powder X-ray diffraction assisted evolutionary algorithm for crystal structure prediction
S. Racioppi, A. Otero-de-la-Roza, S. Hajinazar, and E. Zurek
1/1/2025
Impact of data bias on machine learning for crystal compound synthesizability predictions
A. Davariashtiyani, B. Wang, S. Hajinazar, E. Zurek, and S. Kadkhodaei
11/26/2024
Effect of low-temperature compression on superconductivity and crystal structure in strontium metal
J. Lim, S. Sinha, D. E. Jackson, R. S. Kumar, C. Park, R. J. Hemley, D. VanGennep, Y. K. Vohra, R. G. Hennig, P. J. Hirschfeld, G. R. Stewart, and J. J. Hamlin
11/25/2024
High-pressure characterization of Ag3AuTe2: Implications for strain-induced band tuning
J. Won, R. Zhang, C. Peng, R. Kumar, M. S. Gebre, D. Popov, R. J. Hemley, B. Bradlyn, T. P. Devereaux, and D. P. Shoemaker
11/18/2024
XtalOpt version 13: Multi-objective evolutionary search for novel functional materials
S. Hajinazar, and E. Zurek
11/1/2024
Structural transition and uranium valence change in
UTe 2
at high pressure revealed by x-ray diffraction and spectroscopy
Y. Deng, E. Lee-Wong, C. M. Moir, R. S. Kumar, N. Swedan, C. Park, D. Y. Popov, Y. Xiao, P. Chow, R. E. Baumbach, R. J. Hemley, P. S. Riseborough, and M. B. Maple
8/21/2024
Pressure dependence of intermediate-range order and elastic properties of glassy Baltic amber
S. N. Tkachev, C. M. Zoller, C. Kenney-Benson, M. Ahart, R. J. Hemley, V. N. Novikov, and S. Kojima
8/2/2024
Identification of a Stable B2H2 Intermediate in the Decomposition of Zr(BH4)4 on the Pd(111) Surface
R. Ranjan, M. Redington, A. Ologun, E. Zurek, D. P. Miller, and M. Trenary
7/22/2024
Thermally frustrated phase transition at high pressure in B2-ordered FeV
H. Reyes-Pulido, B. K C, R. S. Kumar, R. J. Hemley, and J. A. Muñoz
7/1/2024
High-temperature concomitant metal-insulator and spin-reorientation transitions in a compressed nodal-line ferrimagnet Mn3Si2Te6
R. A. Susilo, C. I. Kwon, Y. Lee, N. P. Salke, C. De, J. Seo, B. Kang, R. J. Hemley, P. Dalladay-Simpson, Z. Wang, D. Y. Kim, K. Kim, S. Cheong, H. W. Yeom, K. H. Kim, and J. S. Kim
5/11/2024
Heating samples to 2000 °C and above for scanning tunneling microscopy studies in ultrahigh vacuum
B. S. A. Gedara, and M. Trenary
1/1/2024
Formation energy prediction of crystalline compounds using deep convolutional network learning on voxel image representation
A. Davariashtiyani, and S. Kadkhodaei
12/8/2023
Structurally Constrained Evolutionary Algorithm for the Discovery and Design of Metastable Phases
B. Wang, K. P. Hilleke, S. Hajinazar, G. Frapper, and E. Zurek
10/19/2023
Niobium substitution suppresses the superconducting critical temperature of pressurized
MoB 2
J. Lim, S. Sinha, A. C. Hire, J. S. Kim, P. M. Dee, R. S. Kumar, D. Popov, R. J. Hemley, R. G. Hennig, P. J. Hirschfeld, G. R. Stewart, and J. J. Hamlin
9/1/2023
P-V-T
equation of state of boron carbide
M. Somayazulu, M. Ahart, Y. Meng, J. Ciezak, N. Velisavlevic, and R. J. Hemley
8/28/2023
Conventional High-Temperature Superconductivity in Metallic, Covalently Bonded, Binary-Guest C–B Clathrates
N. Geng, K. P. Hilleke, L. Zhu, X. Wang, T. A. Strobel, and E. Zurek
1/9/2023
Creating superconductivity in WB2 through pressure-induced metastable planar defects
J. Lim, A. C. Hire, Y. Quan, J. S. Kim, S. R. Xie, S. Sinha, R. S. Kumar, D. Popov, C. Park, R. J. Hemley, Y. K. Vohra, J. J. Hamlin, R. G. Hennig, P. J. Hirschfeld, and G. R. Stewart
12/22/2022
The Microscopic Diamond Anvil Cell: Stabilization of Superhard, Superconducting Carbon Allotropes at Ambient Pressure
X. Wang, D. M. Proserpio, C. Oses, C. Toher, S. Curtarolo, and E. Zurek
6/24/2022
Predicting synthesizability of crystalline materials via deep learning
A. Davariashtiyani, Z. Kadkhodaie, and S. Kadkhodaei
11/18/2021
View All Publications
Research Highlights
Impact of Data Bias on Machine Learning for Crystal Compound Synthesizability Predictions
Sara Kadkhodaei (U. Illinois - Chicago) Eva Zurek (SUNY – Buffalo)
2/4/2025
Heating Samples to 2000° C for Scanning Tunneling Microscopy Studies in Ultrahigh Vacuum
Michael Trenary (U. Illinois - Chicago)
2/4/2025
XtalOpt: Multi-objective Evolutionary Search for Novel Functional Materials
Eva Zurek (SUNY-Buffalo)
2/4/2025
Ultrahard WB2 Superconducts under Pressure
R. Hemley (U. IL-Chicago)R. Hennig, J. Hamlin, P. Hirshfeld, G. Stewart (U. FL)
5/25/2023
View All Highlights