Honors & Awards

  • Wiley Computers in Chemistry Outstanding Postdoc Award, American Chemical Society (ACS) (2024)
  • AFOSR Scholar Award, American Conference on Theoretical Chemistry (ACTC) (2022)

Professional Education

  • Ph.D., Stanford University, Mechanical Engineering (2019)
  • M.S., Northwestern University, Mechanical Engineering (2014)
  • B.S., Shanghai Jiao Tong University, Mechanical Engineering (2012)

Stanford Advisors

Lab Affiliations

All Publications

  • Foundational Fuel Chemistry Model 2-iso-Butene chemistry and application in modeling alcohol-to-jet fuel combustion COMBUSTION AND FLAME Zhang, Y., Dong, W., Xu, R., Smith, G. P., Wang, H. 2024; 259
  • Efficient Acceleration of Reaction Discovery in the Ab Initio Nanoreactor: Phenyl Radical Oxidation Chemistry. The journal of physical chemistry. A Chang, A. M., Meisner, J., Xu, R., Martínez, T. J. 2023


    Over the years, many computational strategies have been employed to elucidate reaction networks. One of these methods is accelerated molecular dynamics, which can circumvent the expense required in dynamics to find all reactants and products (local minima) and transition states (first-order saddle points) on a potential energy surface (PES) by using fictitious forces that promote reaction events. The ab initio nanoreactor uses these accelerating forces to study large chemical reaction networks from first-principles quantum mechanics. In the initial nanoreactor studies, this acceleration was done through a piston periodic compression potential, which pushes molecules together to induce entropically unfavorable bimolecular reactions. However, the piston is not effective for discovering intramolecular and dissociative reactions, such as those integral to the decomposition channels of phenyl radical oxidation. In fact, the choice of accelerating forces dictates not only the rate of reaction discovery but also the types of reactions discovered; thus, it is critical to understand the biases and efficacies of these forces. In this study, we examine forces using metadynamics, attractive potentials, and local thermostats for accelerating reaction discovery. For each force, we construct a separate phenyl radical combustion reaction network using solely that force in discovery trajectories. We elucidate the enthalpic and entropic trends of each accelerating force and highlight their efficiency in reaction discovery. Comparing the nanoreactor-constructed reaction networks with literature renditions of the phenyl radical combustion PES shows that a combination of accelerating forces is best suited for reaction discovery.

    View details for DOI 10.1021/acs.jpca.3c05484

    View details for PubMedID 37934692

  • HOMO-LUMO energy gaps of complexes of transition metals with single and multi-ring aromatics COMBUSTION AND FLAME Kateris, N., Xu, R., Wang, H. 2023; 257
  • First principles reaction discovery: from the Schrodinger equation to experimental prediction for methane pyrolysis. Chemical science Xu, R., Meisner, J., Chang, A. M., Thompson, K. C., Martínez, T. J. 2023; 14 (27): 7447-7464


    Our recent success in exploiting graphical processing units (GPUs) to accelerate quantum chemistry computations led to the development of the ab initio nanoreactor, a computational framework for automatic reaction discovery and kinetic model construction. In this work, we apply the ab initio nanoreactor to methane pyrolysis, from automatic reaction discovery to path refinement and kinetic modeling. Elementary reactions occurring during methane pyrolysis are revealed using GPU-accelerated ab initio molecular dynamics simulations. Subsequently, these reaction paths are refined at a higher level of theory with optimized reactant, product, and transition state geometries. Reaction rate coefficients are calculated by transition state theory based on the optimized reaction paths. The discovered reactions lead to a kinetic model with 53 species and 134 reactions, which is validated against experimental data and simulations using literature kinetic models. We highlight the advantage of leveraging local brute force and Monte Carlo sensitivity analysis approaches for efficient identification of important reactions. Both sensitivity approaches can further improve the accuracy of the methane pyrolysis kinetic model. The results in this work demonstrate the power of the ab initio nanoreactor framework for computationally affordable systematic reaction discovery and accurate kinetic modeling.

    View details for DOI 10.1039/d3sc01202f

    View details for PubMedID 37449065

    View details for PubMedCentralID PMC10337770

  • Neural network approach to response surface development for reaction model optimization and uncertainty minimization COMBUSTION AND FLAME Zhang, Y., Dong, W., Vandewalle, L. A., Xu, R., Smith, G. P., Wang, H. 2023; 251
  • Natural gas versus methane: Ignition kinetics and detonation limit behavior in small tubes COMBUSTION AND FLAME Crane, J., Shi, X., Xu, R., Wang, H. 2022; 237
  • Stable sodium-sulfur electrochemistry enabled by phosphorus-based complexation. Proceedings of the National Academy of Sciences of the United States of America Wang, C., Zhang, Y., Zhang, Y., Luo, J., Hu, X., Matios, E., Crane, J., Xu, R., Wang, H., Li, W. 2021; 118 (49)


    A series of sodium phosphorothioate complexes are shown to have electrochemical properties attractive for sodium-sulfur battery applications across a wide operating temperature range. As cathode materials, they resolve a long-standing issue of cyclic liquid-solid phase transition that causes sluggish reaction kinetics and poor cycling stability in conventional, room-temperature sodium-sulfur batteries. The cathode chemistry yields 80% cyclic retention after 400 cycles at room temperature and a superior low-temperature performance down to -60°C. Coupled experimental characterization and density functional theory calculations revealed the complex structures and electrochemical reaction mechanisms. The desirable electrochemical properties are attributed to the ability of the complexes to prevent the formation of solid precipitates over a fairly wide range of voltage.

    View details for DOI 10.1073/pnas.2116184118

    View details for PubMedID 34857631

  • A physics-based approach to modeling real-fuel combustion chemistry - VII. Relationship between speciation measurement and reaction model accuracy COMBUSTION AND FLAME Xu, R., Wang, H. 2021; 224: 126–35
  • Impact of vitiation on flow reactor studies of jet fuel combustion chemistry COMBUSTION AND FLAME Wang, K., Xu, R., Bowman, C. T., Wang, H. 2021; 224: 66–72
  • A physics-based approach to modeling real-fuel combustion chemistry - VI. Predictive kinetic models of gasoline fuels COMBUSTION AND FLAME Xu, R., Saggese, C., Lawson, R., Movaghar, A., Parise, T., Shao, J., Choudhary, R., Park, J., Lu, T., Hanson, R. K., Davidson, D. F., Egolfopoulos, F. N., Aradi, A., Prakash, A., Mohan, V., Cracknell, R., Wang, H. 2020; 220: 475–87
  • A physics-based approach to modeling real-fuel combustion chemistry - V. NOx formation from a typical Jet A COMBUSTION AND FLAME Saggese, C., Wan, K., Xu, R., Tao, Y., Bowman, C. T., Park, J., Lu, T., Wang, H. 2020; 212: 270–78
  • Principle of large component number in multicomponent fuel combustion - a Monte Carlo study PROCEEDINGS OF THE COMBUSTION INSTITUTE Xu, R., Wang, H. 2019; 37 (1): 613–20
  • A high pressure shock tube study of pyrolysis of real jet fuel Jet A PROCEEDINGS OF THE COMBUSTION INSTITUTE Han, X., Liszka, M., Xu, R., Brezinsky, K., Wang, H. 2019; 37 (1): 189–96
  • A Physics-based approach to modeling real-fuel combustion chemistry - III. Reaction kinetic model of JP10 COMBUSTION AND FLAME Tao, Y., Xu, R., Wang, K., Shao, J., Johnson, S. E., Movaghar, A., Han, X., Park, J., Lu, T., Brezinsky, K., Egolfopoulos, F. N., Davidson, D. F., Hanson, R. K., Bowman, C. T., Wang, H. 2018; 198: 466–76
  • A physics based approach to modeling real-fuel combustion chemistry - IV. HyChem modeling of combustion kinetics of a bio-derived jet fuel and its blends with a conventional Jet A COMBUSTION AND FLAME Wang, K., Xu, R., Parise, T., Shao, J., Movaghar, A., Lee, D., Park, J., Gao, Y., Lu, T., Egolfopoulos, F. N., Davidson, D. F., Hanson, R. K., Bowman, C. T., Wang, H. 2018; 198: 477–89
  • A physics-based approach to modeling real-fuel combustion chemistry - II. Reaction kinetic models of jet and rocket fuels COMBUSTION AND FLAME Xu, R., Wang, K., Banerjee, S., Shao, J., Parise, T., Zhu, Y., Wang, S., Movaghar, A., Lee, D., Zhao, R., Han, X., Gao, Y., Lu, T., Brezinsky, K., Egolfopoulos, F. N., Davidson, D. F., Hanson, R. K., Bowman, C. T., Wang, H. 2018; 193: 520–37
  • A physics-based approach to modeling real-fuel combustion chemistry - I. Evidence from experiments, and thermodynamic, chemical kinetic and statistical considerations COMBUSTION AND FLAME Wang, H., Xu, R., Wang, K., Bowman, C. T., Hanson, R. K., Davidson, D. F., Brezinsky, K., Egolfopoulos, F. N. 2018; 193: 502–19
  • Fuel effects on lean blow-out in a realistic gas turbine combustor COMBUSTION AND FLAME Esclapez, L., Ma, P. C., Mayhew, E., Xu, R., Stouffer, S., Lee, T., Wang, H., Ihme, M. 2017; 181: 82–99
  • Binary diffusion coefficients and non-premixed flames extinction of long-chain alkanes PROCEEDINGS OF THE COMBUSTION INSTITUTE Liu, C., Zhao, R., Xu, R., Egolfopoulos, F. N., Wang, H. 2017; 36 (1): 1523-1530
  • A Mixed Double-Sided Incremental Forming Toolpath Strategy for Improved Geometric Accuracy JOURNAL OF MANUFACTURING SCIENCE AND ENGINEERING-TRANSACTIONS OF THE ASME Zhang, Z., Ren, H., Xu, R., Moser, N., Smith, J., Ndip-Agbor, E., Malhotra, R., Xia, Z. C., Ehmann, K. F., Cao, J. 2015; 137 (5)

    View details for DOI 10.1115/1.4031092

    View details for Web of Science ID 000370851000008