Our Research Areas
Explore our research expertise, ongoing projects, laboratory capabilities, and scientific achievements in computational chemistry and advanced energy materials.
Modeling and Investigating COF-Based Electrode Materials for Sodium-Ion Batteries
Model COF frameworks with pore sizes, channel geometries, and redox-active linkages tailored to the ionic radius and coordination preferences of Na?
Use DFT-based calculations to evaluate Na? binding energies, insertion/extraction voltage profiles, and diffusion barriers within candidate COF structures
Assess the structural and electrochemical stability of COF electrodes over repeated sodiation/desodiation cycles, identifying frameworks resistant to volume expansion and structural collapse
Compare computed performance metrics (theoretical capacity, average voltage, ion mobility) across a library of COF designs to identify structure-property relationships specific to sodium-ion storage systems
Significance
This project addresses a key bottleneck in SIB technology the lack of electrode materials optimized for the unique demands of sodium chemistry by leveraging the structural tunability of COFs. Findings from this work are intended to guide the experimental synthesis of next-generation, low-cost, and sustainable electrode materials suited for grid-scale and large-format energy storage applications where lithium supply constraints or cost are prohibitive.
Computational Designing of COFs-based Cathode Materials for Lithium-Ion Batteries
Design COF architectures incorporating redox-active functional groups (e.g., quinone, imine, triazine, or other electroactive linkages) capable of reversible lithium-ion coordination and electron transfer
Employ Density Functional Theory (DFT) and related quantum chemical methods to predict and optimize key electrochemical parameters, including theoretical capacity, redox potential, band gap, and structural stability upon lithiation/delithiation
Investigate Li? ion diffusion pathways and binding energies within COF pore channels to assess rate capability and cycling performance
Screen and rank candidate COF structures based on computed thermodynamic stability, electronic conductivity, and specific capacity to identify high-performance cathode candidates prior to experimental synthesis
Significance
By using computational modeling to pre-screen COF candidates, this project aims to accelerate the discovery of sustainable, high-capacity, and structurally robust cathode materials — reducing dependence on critical/rare metals while offering a design-flexible platform for tuning electrochemical performance at the molecular level.