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.
https://faculty.engineering.asu.edu/hong/
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). SLUSCHI has been downloaded more than 3,000 times with its website visited 15,000 times worldwide.
Hong is the developer of the Materials Properties Predicction (MAPP) project, a framework and cyber infrastructure available here that enables rapid calculations of melting temperature, heat of fusion, enthalpy, etc. MAPP has been utilized by users across the world by more than 7,000 (web) and 300,000 (API) times. Hong's melting temperature model is featured by the Materials Project.
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.
Co-PI, DOE Earthshots: Fundamental Studies of Hydrogen Arc Plasmas for High-efficiency and Carbonfree Steelmaking, Department of Energy
The Hong Research Group is looking for talented and motivated graduate students. Visit group webpage here.
35. S.V. Ushakov, Q.-J. Hong, A. Pavlik III, A. van de Walle, A. Navrotsky.
Thermal expansion and enthalpies of phase transformation and fusion of Er2O3 and Tm2O3 from experiment and computation.
Chemistry of Materials, In revision
34. Q.-J. Hong, P. D. Tepesch, and A. van de Walle.
Combined experimental and computational assessment of the Li2O-La2O3-ZrO2 phase diagram.
Journal of the American Ceramic Society, Accepted
33. J. Yan, W. Xiao, R. Zeng, Q.-J. Hong, X. Li, L. Wang.
Pivotal role of Ce3+ polarons on promoting oxygen reduction reaction activity of Pt1/CeO2 catalysts.
Journal of Power Sources, 603 , 234393 (2024). [DOI]
32. X. Hu, Z. Zhao, Y. Zhao, X. Wang, S. Sainio, D. Nordlund, C. Ruse, X.-D. Zhou, S. Boettcher, D. Hou, Q.-J. Hong, L. Mu.
Interfacial degradation of the NMC/Li6PS5Cl composite cathode in all-solid-state batteries.
Journal of Materials Chemistry A, 12 , 3700 (2024). [DOI]
31. B. Brugman, Y. Han, L. Leinbach, K. Leinenweber, A. van de Walle, S. Ushakov, Q.-J. Hong, and A. Navrotsky.
Computationally led high pressure synthesis and experimental thermodynamics of rocksalt yttrium monoxide.
Chemistry of Materials, 36 , 332 (2024). [DOI]
30. S. Hao, Q.-J. Hong, and M. C. Gao.
A prediction of the thermodynamic, thermophysical, and mechanical properties of CrTaO4 from first principles.
Journal of the American Ceramic Society, 106, 7654 (2023). [DOI]
29. 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). [DOI]
28. 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). [DOI]
27. 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). [DOI]
26. Q.-J. Hong, S. V. Ushakov, A. van de Walle, and A. Navrotsky.
Melting temperature prediction using a graph neural network model: from ancient minerals to new materials.
Proceedings of the National Academy of Sciences, 119, e2209630119 (2022). [DOI]
25. Q.-J. Hong.
Melting temperature prediction via first principles and deep learning.
Computational Materials Science, 214, 111684 (2022). [DOI]
24. E. Y. Cramer et al.
The United States COVID-19 Forecast Hub dataset.
Scientific Data, 9, 1-15 (2022). [DOI]
23. E. Y. Cramer et al.
Evaluation of individual and ensemble probabilistic forecasts of COVID-19 mortality in the United States.
Proceedings of the National Academy of Sciences, 119, e2113561119 (2022). [DOI]
22. H. Chen, Q.-J. Hong, S. Ushakov, A. Navrotzky, and A. van de Walle.
A simple method for computing the formation energies of metal oxides.
Computational Materials Science, 198, 110692 (2021). [DOI]
21. Q.-J. Hong, J. Schroer, D. Hofmann, S. Curtarolo, M. Asta, and A. van de Walle.
Theoretical prediction of melting temperature for a Mo-Ru-Ta-W HCP multi-principal element alloy.
NPJ Computational Materials, 7, 1 (2021). [DOI]
20. Q.-J. Hong and A. van de Walle
Reentrant melting of sodium, magnesium, and aluminum: General trend.
Physical Review B Rapid Communications, 100, 140102 (2019). [DOI]
19. S. V. Ushakov, A. Navrotsky, Q.-J. Hong, and A. van de Walle
Carbides and Nitrides of Zirconium and Hafnium.
Materials, 12, 2728 (2019). [DOI]
18. M. Fyhrie, Q.-J. Hong, D. Kapush, S. V. Ushakov, H. Liu, A. van de Walle, and A. Navrotsky
Energetics of melting of Yb2O3 and Lu2O3 from drop and catch calorimetry and first principles computations.
The Journal of Chemical Thermodynamics, 132, 405-410 (2019). [DOI]
17. A. van de Walle and Q.-J. Hong
Assessing Phase Diagram Accuracy.
Journal of Phase Equilibria and Diffusion, 40, 170-175 (2019). [DOI]
16. 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.
Scientific Reports, 8, 14962 (2018). [DOI]
15. A. van de Walle, R. Sun, Q.-J. Hong, and S. Kadkhodaei
Software tools for high-throughput CALPHAD from first-principles data.
Calphad: Computer Coupling of Phase Diagrams and Thermochemistry, 58, 70 (2017). [DOI]
14. A. van de Walle, S. Kadkhodaei, R. Sun, and Q.-J. Hong
Epicycle method for elasticity limit calculations.
Physical Review B, 95, 144113 (2017). [DOI]
13. Q.-J. Hong and A. van de Walle
A tetrahedron tiling method for crystal structure prediction.
Physical Review Materials Rapid Communications, 1, 020801 (2017). [DOI]
12. 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). [DOI]
11. 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, 204-209 (2017). [DOI]
10. 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, 88-97 (2016). [DOI]
9. L. Miljacic, S. Demers, Q.-J. Hong, and A. van de Walle
Equation of state of solid, liquid and gaseous tantalum from first principles.
Calphad: Computer Coupling of Phase Diagrams and Thermochemistry, 51, 133-143 (2015). [DOI (open access)].
8. 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). [DOI]
Selected as an Editors' Suggestion. Featured in Kaleidoscope. Featured in The Washington Post, the Daily Mail and Brown News.
7. A. van de Walle, Q.-J. Hong, S. Kadkhodaei, and R. Sun
The free energy of mechanically unstable phases.
Nature Communications, 6, 7559 (2015). [DOI]
6. 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, 275-282 (2015). [DOI]
5. A. van de Walle, Q.-J. Hong, L. Miljacic, B. G. Chirranjeevi, S. Demers, G. Pomrehn, A. Kowalski, and P. Tiwary
Ab initio calculation of anisotropic interfacial excess free energies.
Physical Review B 89 (18), 184101 (2014). [DOI]
4. 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 (9), 094114 (2013). [DOI]
3. Q.-J. Hong and A. van de Walle
Direct first-principles chemical potential calculations of liquids.
Journal of Chemical Physics 137 (9), 094114 (2012). [DOI]
2. 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 (21), 1869-1876 (2010). [DOI]
1. Q.-L. Tang, Q.-J. Hong, and Z.-P. Liu
CO2 fixation into methanol at Cu/ZrO2 interface from first principles kinetic Monte Carlo.
Journal of Catalysis 263 (1), 114-122 (2009). [DOI]
Courses
2025 Spring
Course Number | Course Title |
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MSE 792 | Research |
MAE 792 | Research |
MAE 799 | Dissertation |
MSE 599 | Thesis |
2024 Fall
Course Number | Course Title |
---|---|
MAE 792 | Research |
MSE 792 | Research |
MSE 799 | Dissertation |
MSE 457 | Quantum Mechanics:Atoms&Solids |
MSE 598 | Special Topics |
MSE 598 | Special Topics |
MAE 792 | Research |
MSE 415 | Math/Computer Mthds-Materials |
MSE 511 | Math and Comp Methods Material |
MSE 599 | Thesis |
2024 Summer
Course Number | Course Title |
---|---|
MAE 792 | Research |
MAE 792 | Research |
MSE 792 | Research |
MSE 792 | Research |
2024 Spring
Course Number | Course Title |
---|---|
MSE 792 | Research |
MAE 792 | Research |
MAE 799 | Dissertation |
MSE 599 | Thesis |
MSE 792 | Research |
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