Biography

Zirui Mao is a researcher in the Computational Math Group within the Physical and Computational Sciences Directorate at Pacific Northwest National Laboratory (PNNL). His work at PNNL emphasizes the development of advanced computational tools for modeling and simulation across a variety of multiphysics processes, including contributions to address challenges in battery electrode drying, nuclear waste treatment, radiation damage, critical minerals separation, plasma etching, earthquake-induced landslides, polymeric material processing, and metals microstructure evolution.

Mao earned a PhD in aerospace engineering from the University of Cincinnati in 2019 and then served as a postdoctoral researcher at Texas A&M University. At Texas A&M, he developed a reinforcement learning-based controller for a phase field method to optimize material microstructure evolution for superior mechanical properties.

With a specialized background in computational mechanics, Mao combines expertise in traditional numerical methods, emerging machine learning algorithms, and high-performance computing to simulate realistic engineering systems with reduced simplifications. His research interests span computational mechanics, numerical methods, AI/ML algorithms and applications, and high-performance computing, all serving realistic engineering applications. Mao’s work continues to advance the intersection of mechanics, mathematics, and modern computational techniques in understanding and designing complex systems characterized with multi-scale, multi-phase, and multi-physics.

Publications

2025

  • Mao Z., S. Hu, and A. Li. 2025. "A GPU accelerated mixed-precision Finite Difference informed Random Walker (FDiRW) solver for strongly inhomogeneous diffusion problems." International Journal for Numerical Methods in Fluids 97, no. 8:1104-1119. PNNL-SA-201895. doi:10.1002/fld.5394
  • Mao Z., Y. Li, G. Park, B. Beeler, and S. Hu. 2025. "A Finite Difference Informed Random Walk Solver for Simulating Radiation Defect Evolution in Polycrystalline Structures with Strongly Inhomogeneous Diffusivity." Computational Materials Science 246, no. _:Art No. 113371. PNNL-SA-198772. doi:10.1016/j.commatsci.2024.113371
  • Mao Z., Y. Li, R.O. Montgomery, A. Grandjean, H. zur Loye, and S. Hu. 2025. "A Finite Difference informed Random Walker (FDiRW) solver for strongly inhomogeneous diffusion problems." Computational Materials Science 246, no. _:Art. No. 113474. PNNL-SA-203260. doi:10.1016/j.commatsci.2024.113474

2024

  • Mao Z., X. Li, S. Hu, G. Gopalakrishnan, and A. Li. 2024. "A GPU accelerated mixed-precision Smoothed Particle Hydrodynamics framework with cell-based relative coordinate." Engineering Analysis with Boundary Elements 161. PNNL-SA-190575. doi:10.1016/j.enganabound.2024.01.020
  • Mao Z., X. Zhang, Y. Li, V. Proust, A. Gossard, T. David, and R.O. Montgomery, et al. 2024. "Phase field-volumetric lattice Boltzmann model of ion uptake in porous nuclear waste form materials under continuous flow." Journal of Nuclear Materials 596. PNNL-SA-192472. doi:10.1016/j.jnucmat.2024.155103
  • Proust V., A. Leybros, A. Gossard, T. David, Z. Mao, Y. Li, and S. Hu, et al. 2024. "Influence of porous aluminosilicate grain size materials in experimental and modelling Cs+ adsorption kinetics and wastewater column process." Journal of Water Process Engineering 66, no. _:Art No. 106066. PNNL-SA-203747. doi:10.1016/j.jwpe.2024.106066
  • Zhang X., Z. Mao, F.W. Hilty, Y. Li, A. Grandjean, R. Montgomery, and H. zur Loye, et al. 2024. "Volumetric lattice Boltzmann method for pore-scale diffusion-advection process in geopolymer porous structures." Journal of Rock Mechanics and Geotechnical Engineering 16, no. 6:2126-2136. PNNL-SA-193162. doi:10.1016/j.jrmge.2024.03.006