Computational Skills
Quantum Chemistry Program Packages:
• (i) Molecular-level Simulation Codes: Gaussian 09/16 (ground-state calculation), D3-Mol, MOLPRO (excited-state calculation), MOLCAS (magnetic property), ORCA, PySOC, Q-Chem, ADF 2013/14/19 (EDA-NOCV calculation), AIMALL & Multiwfn (chemical bonding), NWChem, NBO 6.0 (NPA charge calculation), and UCA-FUKUI (chemical reactivity calculation).
(ii) Period-level Computational Codes: Materials Studio, VASP, CASTEP, CP2K, Crystal 17, VNLATK.
(iii) Molecular Dynamics Simulator: LAMMPS, VENUS-MOPAC, Ab Initio MD Simulator.
• Languages: Fortran 77/90/95, Python
• Plotting Interfaces: Qt/Xmgrace, GNU Plot, Interactive-Data Editor, Origin 6/8
• Modelling & Visualization GUI: Gauss View 3.0/5.0/6.0, Vesta, Chemcraft, Chemdraw, Avogadro, Cylview, ORTEP,
Mercury, Molekel, VMD, PyMol, MolDraw, Crystal Explorer, Molden, IQMol, XcrysDen
• Operating Systems: Ubuntu (/WSL), Linux, CentOS, Windows XP/7/8/10
Density Functional Theory (DFT), Ab Initio Molecular Dynamics (AIMD), Molecular Dynamics (MD), and Python-based workflow platform that aligns well with your research on electronic structure theory, catalysis, nanomaterials, polymers, and renewable energy materials. It provides a unified environment for studying molecular systems, solids, surfaces, interfaces, and nanostructures from first principles.
1. Electronic Structure Calculations (DFT & Ab Initio Methods)
Perform first-principles DFT calculations to determine electronic structure, total energy, charge density, band structure, density of states, and molecular orbitals.
Investigate molecular, cluster, periodic, and nanostructured systems with high accuracy.
Study the influence of defects, dopants, and chemical environments on material properties.
2. Quantum Mechanics & Ab Initio Molecular Dynamics
Perform Ab Initio Molecular Dynamics (AIMD) simulations to investigate finite-temperature structural evolution and reaction dynamics.
Study atomic diffusion, bond breaking/forming processes, and thermal stability of catalytic and functional materials.
Model dynamic behavior under realistic operating conditions.
3. Advanced DFT Studies
Investigate spin-polarized systems using spin-DFT, enabling studies of magnetic catalysts and transition-metal complexes.
Calculate electronic excitation-related properties using interfaces to external workflows where appropriate.
Analyze charge transfer and electronic redistribution in catalytic and functional materials.
4. Bonding and Non-Bonding Interaction Analysis
Analyze charge density, electrostatic potential, electron localization, and chemical bonding characteristics.
Investigate hydrogen bonding, van der Waals interactions, adsorption mechanisms, and intermolecular interactions.
Study adsorption of molecules on catalyst surfaces and nanomaterials.
5. Solvation and Interface Studies
Investigate solvent effects through explicit solvent models using atomistic simulations.
Model solid–liquid interfaces relevant to catalysis, electrochemistry, and energy storage.
Study adsorption and reaction mechanisms at catalyst–electrolyte interfaces.
6. Catalytic Materials Design
Design and screen molecular catalysts, nanoclusters, 2D materials, heterostructures, and bulk catalysts.
Calculate adsorption energies, reaction intermediates, and electronic descriptors that govern catalytic activity.
Accelerate catalyst discovery through computational screening.
7. Nanomaterials for Catalysis & Sensing
Model graphene, MXenes, transition-metal dichalcogenides, metal oxides, and hybrid nanostructures.
Investigate defect engineering, surface functionalization, and dopant effects.
Optimize nanomaterials for sensing and catalytic applications.
8. Renewable Energy Materials
Design materials for:
Hydrogen evolution reaction (HER)
Oxygen evolution reaction (OER)
Oxygen reduction reaction (ORR)
CO₂ reduction
Hydrogen storage
Energy storage materials
Analyze electronic structure and reaction energetics to identify high-performance catalysts.
9. Heterogeneous & Homogeneous Catalysis
Investigate catalytic reaction pathways using DFT.
Calculate adsorption energies, activation barriers, and reaction thermodynamics.
Identify active catalytic sites and understand structure–activity relationships.
10. Electrocatalysis
Study catalyst surfaces under electrochemical conditions.
Evaluate adsorption and reaction energetics of electrochemical intermediates.
Screen catalysts for renewable energy applications.
11. Reaction Mechanism Analysis
Map reaction pathways and determine thermodynamic stability of intermediates.
Calculate reaction energetics to complement experimental kinetic studies.
12. Polymer Design
Investigate interactions between polymers and nanomaterials.
Study structural stability, molecular organization, and interface properties.
Computational design of functional polymer-based materials.
13. High-Throughput Materials Discovery
Automate DFT workflows using Python scripting.
Generate computational datasets for machine learning and data-driven materials discovery.
Accelerate screening of catalysts, nanomaterials, and energy materials.