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Path-integral simulations of solid and liquid atomic hydrogen
Ly, Kevin Kim
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https://hdl.handle.net/2142/124476
Description
- Title
- Path-integral simulations of solid and liquid atomic hydrogen
- Author(s)
- Ly, Kevin Kim
- Issue Date
- 2023-11-30
- Director of Research (if dissertation) or Advisor (if thesis)
- Ceperley, David M
- Doctoral Committee Chair(s)
- Schleife, André
- Committee Member(s)
- Lorenz, Virginia O
- Gammie, Charles F
- Department of Study
- Physics
- Discipline
- Physics
- Degree Granting Institution
- University of Illinois at Urbana-Champaign
- Degree Name
- Ph.D.
- Degree Level
- Dissertation
- Keyword(s)
- Quantum Monte Carlo
- Atomic Hydrogen
- Machine Learning
- Lattice Dynamics
- Language
- eng
- Abstract
- For decades, the characterization of bulk hydrogen and its phases has challenged experimentalists and theorists alike. Solid atomic hydrogen, which requires extremely high pressures and has yet to be produced in the lab, seems just within reach. Accurate calculations of the solid phase are necessary to inform the next generation of experiments. For the theorist, hydrogen’s unique and erratic behavior requires novel and powerful techniques in simulation. We calculated the phonons of solid atomic hydrogen with reptation quantum Monte Carlo (RQMC). This is the first phonon calculation of this kind, made possible with a simple trick that we devised. We also simulated the lattice dynamics of LaH10, an analogue of solid atomic hydrogen which displays high- temperature superconductivity, with path-integral molecular dynamics. The resolution of our simulations allowed us to identify an intrinsic distortion of the superconducting structure which was previously thought to be extrinsic. Further investigation of this structural transformation also provided some insight into the design of hydrogen-rich superconductors. The improved resolution was enabled by the development of a machine-learned model that learned ab-initio calculations. Finally, we simulated the melting of solid atomic hydrogen. By combining RQMC and thermodynamic path-integral Monte Carlo, we believe that our results are the most accurate to date. Once again, these simulations were made possible by a machine-learned model. We found the melting line to be higher than previously suggested, though still below the projected superconducting temperature. We also found a clear decrease in the melting line with increasing pressure, reviving hopes that the liquid may be stable down to very low temperatures.
- Graduation Semester
- 2024-05
- Type of Resource
- Text
- Handle URL
- https://hdl.handle.net/2142/124476
- Copyright and License Information
- Copyright 2024 Kevin Ly
Owning Collections
Graduate Dissertations and Theses at Illinois PRIMARY
Graduate Theses and Dissertations at IllinoisDissertations and Theses - Physics
Dissertations in PhysicsManage Files
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