Qijun Hong
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Mail code: 6106Campus: Tempe
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Qijun Hong is an assistant professor of materials science and engineering in the School for Engineering of Matter, Transport and Energy. Hong obtained his PhD from the California Institute of Technology in 2014 and BS from Fudan University, China in 2009. Before joining ASU, Hong was a postdoctoral research associate at Brown University from 2014 to 2020 and was a Machine Learning Scientist at Amazon.com, Inc. from 2020 to 2021.
The Hong Group is looking for talented and motivated graduate students. Visit group website here.
Hong's research focuses on materials design and discovery based on density functional theory calculations, machine learning and automation. By combining materials science and machine learning, Hong predicted the material with the world’s highest melting temperature, which was later confirmed by experiments. The research discovery received extensive media coverage from numerous news outlets, including from the Washington Post, Business Insider, United Press International, Science and IEEE Spectrum.
More specifically, Hong's research centers around density functional theory materials predictions, e.g., melting temperature, heat of fusion, heat capacity, thermal expansion, enthalpy, and diffusion, via first-principles molecular dynamics simulations and machine learning.
Hong is the developer of the Solid and Liquid in Ultra Small Coexistence with Hovering Interfaces (SLUSCHI) code, a software package that enables first-principles calculations of melting temperature, heat of fusion, enthalpy, etc (available here).
In his spare time, Hong built a COVID-19 model based on machine learning. The model is ranked as one of the top performing models nationwide and is featured by CDC.
- Ph.D. Physical Chemistry, California Institute of Technology, 2014
- B.S. Chemistry, Fudan University, China, 2009
Prediction of materials properties, materials design and discovery based on density functional theory calculations, deep learning and automation.
Calculations of melting temperature, heat of fusion, heat capacity, thermal expansion, enthalpy, and diusion, via first principles molecular dynamics simulations and deep learning.
Co-PI, Collaborative Research: Rare Earth Materials Under Extreme Conditions, National Science Foundation.
Co-PI, MURI: Emergent Refractory Behaviors in Earth and Extraterrestrial Materials, Army Research Office, Department of Defense.
The Hong Research Group is looking for talented and motivated graduate students. Visit group webpage here.
1. S. V. Ushakov, Q.-J. Hong, D. Gilbert, A. van de Walle, and A. Navrotsky, Thorium and rare earth compounds with rocksalt structures, Materials, 16:1350, 2023.
2. Q.-J. Hong, S. V. Ushakov, K. Lilova, A. Navrotsky, and S.J. McCormack, Structure and thermodynamics of oxides/carbides/nitrides/borides at high temperature (STOHT2). ACerS Bulletin, 102:28, 2023.
3. Q.-J. Hong, A. van de Walle, S.V. Ushakov, and A. Navrotsky, Integrating computational and ex- perimental thermodynamics of refractory materials at high temperature, CALPHAD, 79:102500, 2022. (Invited)
4. Q.-J. Hong, S.V. Ushakov, A. Navrotsky, and A. van de Walle, Melting temperature prediction using a graph neural network model: from ancient minerals to new materials, PNAS - Proceedings of the National Academy of Sciences, 119:e2209630119, 2022.
5. Q.-J. Hong, Melting temperature prediction via first principles and deep learning, Computational Materials Science, 214:111684, 2022. (Invited)
6. E. Y. Cramer, et al., The United States COVID-19 Forecast Hub dataset, Scientific Data, 9:1, 2022.
7. E. Y. Cramer, et al., Evaluation of individual and ensemble probabilistic forecasts of COVID-19 mortality in the US, PNAS - Proceedings of the National Academy of Science, 119:e2113561119, 2022.
8. Q.-J. Hong, J. Schroers, D. Hofmann, S. Curtarolo, M. Asta, and A. van de Walle, Theoretical prediction of high melting temperature for a Mo-Ru-Ta-W HCP multi-principal element alloy, npj Computational Materials, 7:1, 2021.
9. Q.-J. Hong and A. van de Walle, Re-entrant melting of sodium, magnesium and aluminum, and its general trend, Physical Review B Rapid Communications, 100:140102, 2019.
10. S. V. Ushakov, A. Navrotsky, Q.-J. Hong, and A. van de Walle, and, Carbies and nitrides of Zirconium and Hafnium, Materials, 12:2728, 2019.
11. A. van de Walle and Q.-J. Hong, Assessing phase diagram accuracy, Journal of Phase Equilibria and Diusion, 2:170, 2019.
12. M. Fyhrie, Q.-J. Hong, D. Kapush, S. V. Ushakov, A. van de Walle, and A. Navrotsky, Fusion enthalpies of Tm2O3, Yb2O3, and Lu2O3 from drop and catch calorimetry and first principles calculations, Journal of Chemical Thermodynamics, 132:405, 2019.
13. Q.-J. Hong, S. V. Ushakov, D. Kapush, C. J. Benmore, R. J. K. Weber, A. van de Walle, and A. Navrotsky, Combined computational and experimental investigation of high temperature thermodynamics and structure of cubic ZrO2 and HfO2, Scientic Reports, 8:14962, 2018.
14. Q.-J. Hong and A. van de Walle, A tetrahedron tiling method for crystal structure prediction, Physical Review Materials Rapid Communications, 1:020801, 2017.
15. A. van de Walle, R. Sun, Q.-J. Hong, S. Kadkhodaei, Software tools for high-throughput CALPHAD from first-principles data, Calphad: Computer Coupling of Phase Diagrams and Thermochemistry, 58:70, 2017.
16. A. van de Walle, S. Kadkhodaei, R. Sun, Q.-J. Hong, Epicycle method for elasticity limit calculations, Physical Review B, 95:144113, 2017.
17. D. Kapush, S. V. Ushakov, A. Navrotsky, Q.-J. Hong, H. Liu, and A. van de Walle, A combined experimental and theoretical study of enthalpy of phase transition and fusion of yttria above 2000°C using drop-n-catch calorimetry and first-principles calculation, Acta Materialia, 124:204, 2017.
18. S. Kadkhodaei, Q.-J. Hong and A. van de Walle, Free energy calculation of mechanically unstable but dynamically stabilized bcc titanium, Physical Review B, 95:064101, 2017.
19. Q.-J. Hong and A. van de Walle, A user guide for SLUSCHI (Solid and Liquid in Ultra Small Coexistence with Hovering Interfaces). Calphad: Computer Coupling of Phase Diagrams and Thermochemistry, 52:88, 2016. (Invited article)
20. A. van de Walle, Q.-J. Hong, S. Kadkhodaei and R. Sun, The free energy of mechanically unstable phases. Nature Communications, 6:7559, 2015.
21. Q.-J. Hong and A. van de Walle. Prediction of the material with highest known melting point from ab initio molecular dynamics calculations. Physical Review B Rapid Communications, 92:020104(R), 2015. (Featured in the Washington Post, in Materials Today, in IEEE Spectrum, in the Tech insider, in the Daily Mail (UK), among other media outlets.)
22. L. Miljacic, S. Demers, Q.-J. Hong and A. van de Walle, Equation of state of solid, liquid and gaseous tantalum from rst principles. Calphad: Computer Coupling of Phase Diagrams and Thermochemistry, 51:133, 2015.
23. Q.-J. Hong, S. V. Ushakov, A. Navrotsky and A. van de Walle, Combined computational and experimental investigation of the refractory properties of La2Zr2O7. Acta Materialia, 84:275, 2015.
24. A. van de Walle, Q.-J. Hong, L. Miljacic, C. Balaji Gopal, S. Demers, G. Pomrehn, A. Kowalski and P. Tiwary. Ab initio calculation of anisotropic interfacial excess free energies. Physical Review B, 89:184101, 2014.
25. Q.-J. Hong and A. van de Walle. Solid-liquid coexistence in small systems: A statistical method to calculate melting temperatures. Journal of Chemical Physics, 139:094114, 2013.
26. Q.-J. Hong and A. van deWalle. Direct first-principles chemical potential calculations of liquids. Journal of Chemical Physics, 137:094114, 2012.
27. Q.-J. Hong and Z.-P. Liu. Mechanism of CO2 hydrogenation over Cu/ZrO2(212) interface from first-principles kinetics Monte Carlo simulations. Surface Science, 604:1869, 2010.
28. Q.-L. Tang, Q.-J. Hong, and Z.-P. Liu. CO2 xation into methanol at Cu/ZrO2 interface from first-principles kinetic Monte Carlo. Journal of Catalysis, 263:114, 2009.
Courses
2023 Fall
| Course Number | Course Title |
|---|---|
| MAE 792 | Research |
| MSE 792 | Research |
| MSE 457 | Quantum Mechanics:Atoms&Solids |
| MSE 598 | Special Topics |
| MSE 598 | Special Topics |
2023 Summer
| Course Number | Course Title |
|---|---|
| MAE 792 | Research |
| MAE 792 | Research |
| MSE 792 | Research |
| MSE 792 | Research |
2023 Spring
| Course Number | Course Title |
|---|---|
| MSE 458 | Electronic,Mag,Optical Prpties |
| MSE 792 | Research |
| MAE 792 | Research |
| MSE 515 | Electronc,Magnetc,Optical Prop |
2022 Fall
| Course Number | Course Title |
|---|---|
| MAE 792 | Research |
| MSE 792 | Research |
| MSE 457 | Quantum Mechanics:Atoms&Solids |
| MSE 598 | Special Topics |
| MSE 598 | Special Topics |
2022 Summer
| Course Number | Course Title |
|---|---|
| MAE 792 | Research |
| MSE 792 | Research |
| MSE 792 | Research |
2021 Fall
| Course Number | Course Title |
|---|---|
| MSE 457 | Quantum Mechanics:Atoms&Solids |
| MSE 598 | Special Topics |
| MSE 598 | Special Topics |
MSE 457 Quantum Mechanics: Atoms & Solids