Research Interests

Anh Pham is a Deputy Group Leader of the Quantum Simulations Group. His research interests lie in the integration of atomistic simulation, high performance computing, and data science for predicting properties of functional materials under non-equilibrium conditions. A particular focus is approaches for bridging simulation methods across broad scales, and for accelerating theory-experiment feedback. Primary topics of interest include energy conversion and storage, degradation and corrosion science, and chemical separation.

Dr. Pham is a Thrust-lead of the Center for Enhanced Nanofluidic Transport, an Energy Frontier Research Center that aims to establish the scientific foundation for developing transformative molecular separation technologies. Additionally, he co-leads the crosscutting modeling and simulation activities for the HydroGEN—a hydrogen production consortium in the DOE Hydrogen & Fuel Cell Technologies Office. At LLNL, he currently serves as a coordinator for AI/ML activities across the Physical and Life Sciences Directorate. He also the thrust lead for degradation science within the PLS Strategic Science Engagement Office (SSEO) and leads efforts in degradation science and sustainable materials of the Laboratory for Energy Applications for the Future (LEAF) Center. In this role, he coordinates cross-division and cross-directorate efforts to understand, predict and mitigate degradation of our nation’s infrastructure for energy production and delivery.

Since 2017, Dr. Pham has served as Director/co-Director of the Summer Institute on Computational Materials Science and Chemistry (CCMS), a two-month summer school and mentorship program for graduate students at LLNL.

Ph.D., Physical Chemistry, University of California at Davis, 2014

M.Sc., Condensed Matter Physics, Abdus Salam International Center for Theoretical Physics, 2008

B.S., Physics, Hanoi National University of Education, Vietnam, 2006

Google Scholar Profile; Google Sites

Selected Publications:

• P. Xiao, C. A. Orme, S. R. Qiu, T. A. Pham, S. Cho, M. Bagge-Hansen, and B. C. Wood, Atomic-scale understanding of oxide growth and dissolution kinetics of Ni/Cr alloys, Nat. Comm. (2024).
• H. Kwon, T. Hsu, W. Sun, W. Jeong, F. Aydin, J. Chapman, X. Chen, M. R. Carbone, D. Lu, F. Zhou, and T. A. Pham, Spectroscopy-Guided Discovery of Three-Dimensional Structures of Disordered Materials with Diffusion Models, Machine Learning: Science and Technology (2024).
• W. Jeong, W. Sun, M. F. C. Andrade, L. F. Wan, Trevor M. Willey, M. H. Nielsen, and T. A. Pham, Integrating Machine Learning Potential and X-ray Absorption Spectroscopy for Predicting Chemical Speciation of Disordered Carbon Nitrides, Chem. Mat. 36, 4144 (2024).
• M. F. C. Andrade, N. Aluru, and T. A. Pham, Non-linear effects of hydrophobic confinement on the electronic structures and dielectric response of water, J. Phys. Chem. Lett. 15, 26, 6872–6879 (2024).
• J. Qi, T. W. Ko, B. C. Wood, T. A. Pham, and S. P. Ong, Robust Training of Machine Learning Interatomic Potentials with Dimensionality Reduction and Stratified Sampling, npj Computational Materials 10, 43 (2024).
• M. F. C. Andrade, S. Li, T. A. Pham, S. A. Akhade, and S. H. Pang, Machine Learning Demonstrates the Impact of Proton Transfer and Solvent Dynamics on CO2 Capture in Liquid Ammonia, Chem. Sci. 15, 13173-13180 (2024).
• H. Kwon, M. F. C. Andrade, S. Ardo, D. Esposito, T. A. Pham, and T. Ogitsu, Confinement Effects on Proton Transfer in TiO2 Nanopores from Deep Potential Molecular Dynamics Simulations, ACS Appl. Mater. Interfaces 16, 31687 (2024).
• H. Kwon, W. Sun, T. Hsu, W. Jeong, F. Aydin, S. Sharma, F. Meng, M. R. Carbone, X. Chen, D. Lu, L. F. Wan, M. H. Nielsen, and T. A. Pham, Harnessing Neural Networks for Elucidating X-Ray Absorption Structure-Spectrum Relationships in Amorphous Carbon, J. Phys. Chem. C 127, 16473 (2023).
• M. F. C. Andrade, and T. A. Pham, Probing Confinement Effects on the Infrared Spectra of Water with Deep Potential Molecular Dynamics Simulations, J. Phys. Chem. Lett. 14, 5560 (2023).
• K. Kim, A. Zagalskaya, J. L. Ng, J. Hong, V. Alexandrov, T. A. Pham, X. Su, Electrochemically-mediated reactive separation of nitrate to ammonia through bifunctional redox-electrodes, Nat. Comm. 14, 823 (2023).
• J. W. Polster, F. Aydin, P. D. Souza, M. Z. Bazant, T. A. Pham, Z. S. Siwy, Rectified and Salt Concentration Dependent Wetting of Hydrophobic Nanopores, J. Am. Chem. Soc. 144, 11693 (2022).
• C. L. Ritt, M. Liu, T. A. Pham, R. Epsztein, H. Kulik, M. Elimelech, Machine learning enables the discovery of key ion selectivity mechanisms in polymeric membranes with sub-nanometer pores, Sci. Adv. 8, eabl5771 (2022).
• W. Chen, J. Gu, Q. Liu, M. Yang, C. Zhan, X. Zang, T. A. Pham, G. Liu, W. Zhang, D. Zhang, B. Dunn, Y. M. Wang, Two-dimensional quantum sheet films with sub-1.2 nm channels for ultra-high-rate electrochemical capacitance, Nat. Nanotechnol 17, 153 (2022).
• G. Zeng, T. A. Pham, S. Vanka, G. Liu, C. Song, J. K. Cooper, Z. Mi, T. Ogitsu, and F. M. Toma, Development of a Photoelectrochemical Self-Improving Si/GaN Photocathode for Efficient and Durable H2 Production, Nat. Mat. 20, 1130 (2021).
• X. Zhou, Z. Wang, R. Epsztein, C. Zhan, W. Li, J. Fortner, T. A. Pham, J. Kim, and M. Elimelech, Intra-pore Energy Barriers Govern the Selectivity of Desalination Membranes, Sci. Adv.  6, eabd9045 (2020).
• Y. Li, Z. Li, F. Aydin, J. Quan, X. Chen, Y. Yao, C. Zhan, Y. Chen, T. A. Pham, and A. Noy, Water-Ion Permselectivity of Narrow Diameter Carbon Nanotubes, Sci. Adv. 6, eaba9966 (2020).
• C. Zhan, M. Cerón, S. Hawks, M. Otani, B. Wood, T. A. Pham, M. Stadermann, and P. Campbell, Specific Ion Effects at Graphitic Interfaces, Nat. Comm. 10, 4858 (2019).
• A. Gaiduk, T. A. Pham, M. Govoni, F. Paesani and G. Galli, Electron Affinity of Liquid Water, Nat. Comm. 9, 247 (2018).
• R. H. Tunuguntla, R. Y. Henley, Yun-Chiao Yao, T. A. Pham, M. Wanunu, and A. Noy, Enhanced water permeability and tunable ion selectivity in subnanometer carbon nanotube porins, Science, 357, 792 (2017).
• T. A. Pham, M. Govoni, R. Seidel, S. Bradforth, E. Schwegler and G. Galli, Electronic structure of aqueous solutions: Bridging the gap between theory and experiments, Sci. Adv. 3, 1603210 (2017).
• T. A. Pham, Y. Ping and G. Galli, Modeling Heterogeneous Interfaces for Solar Water Splitting, Nat. Mat. 16, 401, (2017).
• T. A. Pham, D. Lee, E. Schwegler and G. Galli, Interfacial effects on the band edges of functionalized Si surfaces in liquid water, J. Am. Chem. Soc. 136, 17071 (2014).

• Scialog Fellow in Sustainable Minerals, Metals, and Materials; Research Corporation for Science Advancement, 2024.
• ACS Early-Career and Emerging Researchers in Physical Chemistry, 2023.
• Early and Mid-Career Recognition Award, LLNL, 2022.
• Directorate Award for Excellence in Publication, Physical and Life Sciences, LLNL, 2021.
• Deputy Director for Science and Technology Excellence in Publication Awards, 2018.
• LLNL Outstanding Mentor Award, 2018.
• Physical & Life Sciences Best Poster Awards, 2017.
• PCTC Postdoctoral Fellowship, 2017.
• Lawrence Fellow, Lawrence Livermore National Laboratory, 2014-2017.
• Outstanding Chemistry Dissertation Award, University of California Davis, 2014.
• Lawrence Scholar, Lawrence Livermore National Laboratory, 2011-2014.