Bio

I am currently a postdoctoral researcher at Columbia University, following a Hess Postdoctoral Fellowship at Princeton University from 2024–2025.

I received my PhD from Columbia University in 2024, where I worked with Professor Renata Wentzcovitch. I earned my bachelor’s degree from Nanjing University in 2017.

Research Focus

My research lies at the intersection of mineral physics, computational materials science, and geophysics. I combine ab initio calculations, deep-learning molecular dynamics, and thermodynamic modeling to study Earth-forming materials at high pressures and temperatures. I use these mineral-scale insights to understand how compositional and thermal heterogeneity shapes the thermochemical structure of the lower mantle.

Hydrogen-bond disordering in δ-AlOOH

δ-AlOOH is a high-pressure hydrous phase capable of transporting water to the lowermost mantle and a model system for hydrogen-bearing minerals at extreme conditions. Using first-principles calculations and machine-learning molecular dynamics, we connect its hydrogen-bond disordering, symmetrization, and proton diffusion with elasticity, acoustic velocities, and spectroscopic signatures. This work establishes a framework for investigating hydrogen behavior and its effects on the physical properties of other complex hydrous phases.

• C. Luo, K. Umemoto, and R. M. Wentzcovitch, Ab Initio Investigation of H-Bond Disordering in δ-AlOOH, Phys. Rev. Research 4, 023223 (2022). [preprint]
• C. Luo, Y. Sun, and R. M. Wentzcovitch, Probing the state of hydrogen in δ-AlOOH at mantle conditions with machine learning potential, Phys. Rev. Research 6, 013292 (2024). [preprint]
• C. Luo, Y. Sun, and R. M. Wentzcovitch, Elasticity and acoustic velocities of δ-AlOOH at extreme conditions: A methodology assessment, Phys. Rev. Materials 8, 103601 (2024). [preprint]
• C. Luo, S. Lee, H. Wang, Z. Zhang, and R. M. Wentzcovitch, Lattice dynamics and the spectroscopic signatures of H-bond disorder in δ-AlOOH, arXiv:2606.14590 (2026).

Deep-learning molecular dynamics of hydrous phases

Deep-learning potentials enable large-scale, GPU-accelerated molecular dynamics with ab initio accuracy for studying hydrous phases at mantle conditions.

• J. Zeng et al., DeePMD-Kit v2: A Software Package for Deep Potential Models, The Journal of Chemical Physics (2023). [preprint]

Thermoelasticity

The cij Python package implements the SAM-C_ij formalism for high-pressure, high-temperature thermoelastic calculations across crystal systems.

• C. Luo, X. Deng, W. Wang, G. Shukla, Z. Wu, and R. M. Wentzcovitch, Cij: A Python Code for Quasiharmonic Thermoelasticity, Computer Physics Communications (2021). [preprint]

Third-order elastic constants

We extend third-order elasticity to finite pressure, enabling first-principles predictions of strain-induced changes and pressure derivatives in second-order elastic coefficients.

• C. Luo, J. Tromp, and R. Wentzcovitch, Ab initio calculations of the third-order elastic coefficients, Physical Review B (2022). [preprint]

Physical properties of sheet-hydrous minerals

Using first-principles and machine-learning methods, we study how the stability, elasticity, and anisotropy of serpentines and brucite shape water transport and seismic signatures in subduction zones.

• X. Deng, C. Luo, R. Wentzcovitch, G.A. Abers, Z. Wu, Elastic anisotropy of lizardite at subduction zone conditions, Geophysical Research Letters (2022) [preprint]
• H. Wang, C. Luo, and R. M. Wentzcovitch, Machine learning potential for serpentines, Journal of Geophysical Research: Machine Learning and Computation 1, e2024JH000434 (2024).
• H. Wang, C. Luo, and R. M. Wentzcovitch, Ab initio study of the stability and elasticity of brucite, Phys. Rev. B 109, 214103 (2024). [preprint]

Other work

VLab’s Rock property calculator Frontend for Abers & Hacker (2016)’s MATLAB code, as part of VLab’s website.

Phase diagram calculator The phdg Python code computes phase diagram vs. pressure and temperature based on qha’s Gibbs free enengy results.

The qha code The qha Python package employs the quasi-harmonic approximation (QHA) to compute the thermodynamic properties of crystalline materials at finite pressure and temperature.