pyRUQT

Modular Python-based Code for Multiconfigurational Non-Equilibrium Green's Function Methodologies

Update (7/1/2024): Added ability to run PySCF calculations with periodic boundary conditions through pyRUQT and added the ability to use PySCF (without PBC) as a calculator for the wbl_negf module, a new KEYWORD file with detailed explanations of all sie_negf keywords, this changelog file, and minor bugfixes/updates to wbl_negf.

This is the Python-based successor to the Rowan University Transport (RUQT) code. It is designed to provide a modular framework for calculating charge transport using non-equilibrium Green's functions built from multiconfigurational electronic structure methods. It can use both an optmized version of the orginial RUQT code (RUQT-Fortran) or the Atomic Simulation Engine (ASE) for transport calculations and is currently capable of performing NEGF-MCPDFT, NEGF- DFT (PySCF), and mixed method NEGF calculations (ex. MC-PDFT for extended molecule region and DFT for electrodes). Support for NEGF-RDM to come in future (NEGF-RDM will require the Maple Quantum Chemistry Toolbox).

Each currently supported NEGF engine types (ASE and RUQT-Fortran) offer a different approach to treating electrode-extended molecule interactions and coupling:

1. ASE Transport Engine (sie_negf class): Semi-infinite leads determined with an efficient decimation technique to determine Fermi level, device/electrode interactions, and coupling (see Paper #2). Separate Hamiltonian and Overlap matrices for the extended molecule and repeating electrode blocks are used to construct the Green's functions unless using the supercell option.

2. RUQT-Fortran Transport Engine (wbl_negf class): Metal wide band limit approximation with user provided Fermi level and coupling constants (Papers 1 & 3). Only 1 Hamiltonian and Overlap matrix is used to contruct the Green's Functions which are divided by program into the electrode and extended molecule regions based on number of electrode atoms specified by user.

This software runs the standard Landuaer current, conductance, and zero-bias transmission calculations found in RUQT-Fortran/ASE and adds additional calculation types and features not found in either program:

New Calculation Types:

1. Differential Conductance (using both RUQT-Fortran and ASE engines)
2. Supercell calculations with ASE (no separate electrode required)

New features:

1. Automatically run simple Molcas MC-PDFT and pySCF DFT calculations (with or without periodic boundary conditions) from pyRUQT for transport calculations
2. Full alignment of diagonal elements of electrode/extended molecule Hamiltonians for ASE calculations
3. Options to include additional electrode-molecule coupling for ASE NEGF caculations
4. Automatic plotting of transport results in PNG format

Required:

Python3, Numpy, Scipy, and Matplotlib

MKL (RUQT-Fortran)

NEGF Transport Calculator Options. Only 1 of the following are required but both are recommended to enable both NEGF calculators.

For sie_negf class: Atomic Simulation Environment from https://wiki.fysik.dtu.dk/ase/

For wbl_negf class: Compiled RUQT executable. Compile the RUQT.x executable in the RUQT subdirectory.

Electronic Structure Calculator Options. Only 1 of the following are required but both recommended:

OpenMolcas(sandx_fock branch) installation (best run as separate calculations but can be run by pyRUQT) from https://gitlab.com/Molcas/OpenMolcas/-/tree/sandx_fock

PySCF (enables non-Molcas NEGF-DFT calculations and mixed DFT/PDFT transport calculations by pyRUQT) from https://pyscf.org/

Quick Installation (for now, Python package install coming in future)

Put the pyruqt.py and ruqt.py files in your python module folder.

Install ASE, OpenMolcas(sandx_fock branch), and optionally PySCF for all users.

Check the examples folder for scripts to get started running calculations.

If you use this code in your research please cite:

1. Andrew M. Sand, Justin T. Malme, and Erik P. Hoy, “A multiconfigurational pair-density functional theory approach to molecular junctions”, J. Chem. Phys., 155(11), 114115 (2021). https://doi.org/10.1063/5.0063293

If you use the ASE transport engine also cite:

2. Ask Hjorth Larsen et al. J. Phys.: Condens. Matter 29, 273002 (2017). https://doi.org/10.1088/1361-648X/aa680e

If you use the RUQT-Fortran transport engine also cite:

3. Erik P. Hoy, David A. Mazziotti, and Tamar Seideman, “Development and application of a 2-electron reduced density matrix approach to electron transport via molecular junctions”, J. Chem. Phys. 147, 184110 (2017). https://doi.org/10.1063/1.4986804