I am currently working as a postdoctoral scholar in SUNCAT Center for Interface Science and Catalysis at SLAC National Accelerator Laboratory & Stanford University. Feel free to contact me if you have any inquiry for me.
- Atomistic simulations (e.g., density functional theory, DFT) for computational catalysis combined with artificial intelligence (AI)
- Navigation of experiments aided by AI to build machine learning model or optimize target property of catalytic materials
- PyCatRobin: Python module to analyze time-on-stream Catalyst testing results from Round Robin test (on-going) (See it from SUNCAT)
- CatDegUS: Python module for Catalysts' Degradation navigated by Uncertainty Sampling (See it from SUNCAT)
- GA4Qsys: Genetic algorithm (GA) code for structural optimization of supported nanoparticle model in a queueing system
- SegrDNN: Code for hyper-parameter tuning of DNN model for surface segregation energy
- pydrifts3d: Python-based code to convert experimental DRIFTS data to 3D contour plot
- Ab_initio_thermo_HgOx: Ab-initio thermodynamic approach for the stability of SCR catalysts with different VOx structures
-
BO-literature: Bayesian optimization of a heterogeneous catalyst using literature data (private
$\because$ on-going work)
- Bayesian_opt_tutorial: From-scratch tutorials of BO (for study)
- MDUI: From-scratch molecular dynamics (MD) code (C language) and graphic user interface (GUI) (Java) for study
- time_propagator: Code to quantum mechanically simulate the time propagation of a wavefunction under a defined potential (scientific integrity has not been validated).
- Atomistic_GA: ASE-based code to globally optimize the atomic configuration of a bulk bimetallic material.
- pde_by_FDM: C-based solution of an elliptic partial differential equation (PDE) by finite difference method (FDM)