Research Areas and Methodologies
CCMSI integrates electronic-structure theory, molecular dynamics, and high-performance computing to investigate structural, thermodynamic, and response properties of molecules and condensed-phase environments. Our research balances algorithmic innovation with careful application, enabling credible predictions for systems ranging from small model compounds to biologically relevant assemblies. Emphasis is placed on convergence diagnostics, basis-set completeness, treatment of electron correlation, and robust solvation models. We document algorithmic choices and numerical thresholds to facilitate reuse and comparison.
Topical Focus
- Electric Response in Conjugated Chains. Prediction of polarizabilities and hyperpolarizabilities; assessment of method/basis trade-offs for optoelectronic materials.
- Dynamics of Ureic Compounds. Time-domain simulations to probe stability, hydrogen-bonding motifs, and environment-dependent reactivity.
- Conformations of Esters and Amides. Potential-energy surface scans, barrier estimation, and solvent effects on rotational preferences.
- Nucleic-Acid Bases in Polar Solvents. Explicit/implicit solvation models, hydrogen-bond statistics, and stacking interactions under thermodynamic control.
Methodological Toolkit
Our toolkit spans Hartree–Fock, correlated ab initio methods, DFT with contemporary functionals, and classical or ab initio molecular dynamics. Hybrid schemes—QM/MM, polarizable continua combined with explicit shells, and enhanced sampling—are used when appropriate. Workflow orchestration ensures consistent preprocessing, job submission, and post-processing, with validation against reference datasets from the literature where feasible. Visualization tools assist in identifying structural motifs and diagnosing calculation pathologies early in the pipeline.
CCMSI disseminates well-annotated input templates, convergence checklists, and analysis notebooks that illustrate end-to-end studies—from model selection through uncertainty estimation. By pairing methodological rigor with transparent reporting, our research supports reproducible insights that can inform materials screening, mechanistic hypotheses, and design of complementary experiments.