PyCDFT
PyCDFT performs constrained density functional theory (CDFT) calculations to compute diabatic states and electronic couplings by adding constraint potentials to the Kohn–Sham Hamiltonian.
Key Features:
- Object-oriented framework: Provides an object-oriented and customizable Python framework for implementing CDFT workflows.
- Constrained DFT (CDFT): Generates diabatic states using density-based constraints applied during electronic structure calculations.
- Self-consistent-field (SCF) calculations: Supports single-point SCF calculations with applied constraints.
- Geometry optimizations: Performs constrained geometry optimizations of electronic states.
- Constraint incorporation: Incorporates constraint potentials directly into the Kohn–Sham Hamiltonian of underlying DFT codes.
- First-principles MD interfacing: Interfaces with first-principles molecular dynamics codes, explicitly demonstrated with Qbox.
- Parallel scalability: Designed for use in large-scale parallel computations with external DFT/MD codes.
- Benchmark validation: Validated by benchmarking electronic couplings between diabatic states across various organic molecules, producing results consistent with established CDFT implementations.
Scientific Applications:
- Diabatic state generation: Construction and analysis of diabatic states for charge-transfer and nonadiabatic studies.
- Electronic coupling calculation: Computation of electronic couplings between diabatic states in organic molecules.
- Constrained geometry studies: Exploration of potential energy surfaces and optimized geometries under electronic constraints.
- First-principles molecular dynamics: Integration with MD codes such as Qbox to study dynamical behavior of constrained electronic states.
- Quantum mechanical characterization: Investigation of quantum mechanical properties of molecular systems using CDFT.
Methodology:
PyCDFT adds constraint potentials to the Kohn–Sham Hamiltonian and performs self-consistent-field calculations and constrained geometry optimizations, interfaces with external DFT and first-principles MD codes (e.g., Qbox), and has been benchmarked via electronic coupling calculations between diabatic states in organic molecules.
Topics
Details
- Programming Languages:
- Python
- Added:
- 1/18/2021
- Last Updated:
- 1/30/2021
Operations
Publications
Ma H, Wang W, Kim S, Cheng M, Govoni M, Galli G. <scp>PyCDFT</scp>: A Python package for constrained density functional theory. Journal of Computational Chemistry. 2020;41(20):1859-1867. doi:10.1002/jcc.26354. PMID:32497321.