yu-mcal 0.4.0

Program for the calculation of mobility tensor for organic semiconductor crystals

mcal: Program for the calculation of mobility tensor for organic semiconductor crystals

Overview

mcal is a tool for calculating mobility tensors of organic semiconductors. It calculates transfer integrals and reorganization energy from crystal structures, and determines mobility tensors considering anisotropy and path continuity.

Requirements

• Python 3.9 or newer
• NumPy
• Pandas
• Matplotlib
• yu-tcal==4.0.3

Quantum Chemistry Calculation Tools

At least one of the following is required:

• Gaussian 09 or 16
• PySCF (macOS / Linux / WSL2(Windows Subsystem for Linux))
• GPU4PySCF (macOS / Linux / WSL2(Windows Subsystem for Linux))

Important notice

• When using Gaussian, the path of the Gaussian must be set.
• PySCF is supported on macOS / Linux. Windows users must use WSL2.

Installation

Using Gaussian 09 or 16 (without PySCF)

pip install yu-mcal

Using PySCF (CPU only, macOS / Linux / WSL2)

pip install "yu-mcal[pyscf]"

Using GPU acceleration with PySCF (macOS / Linux / WSL2)

1. Check your installed CUDA Toolkit version

nvcc --version

2. Install tcal with GPU acceleration

If your CUDA Toolkit version is 12.x, install tcal with GPU acceleration:

pip install "yu-mcal[gpu4pyscf-cuda12]"

If your CUDA Toolkit version is 11.x, install tcal with GPU acceleration:

pip install "yu-mcal[gpu4pyscf-cuda11]"

Verify Installation

After installation, you can verify by running:

mcal --help

mcal Usage Manual

Basic Usage

mcal <cif_filename or pkl_filenname> <osc_type> [options]

Required Arguments

• cif_filename: Path to the CIF file
• pkl_filename: Path to the pickle file
• osc_type: Organic semiconductor type
  • p: p-type semiconductor (uses HOMO level)
  • n: n-type semiconductor (uses LUMO level)

Basic Examples

# Calculate as p-type semiconductor
mcal xxx.cif p

# Calculate as n-type semiconductor
mcal xxx.cif n

Options

Calculation Settings

-M, --method <method>

Specify the calculation method used in Gaussian calculations.

• Default: B3LYP/6-31G(d,p)
• Example: mcal xxx.cif p -M "B3LYP/6-31G(d)"

-c, --cpu <number>

Specify the number of CPUs to use.

• Default: 4
• Example: mcal xxx.cif p -c 8

-m, --mem <memory>

Specify the amount of memory in GB.

• Default: 10
• Example: mcal xxx.cif p -m 16

-g, --g09

Use Gaussian 09 (default is Gaussian 16).

• Example: mcal xxx.cif p -g

PySCF Settings

--pyscf

Use PySCF instead of Gaussian for all calculations. Requires yu-mcal[pyscf].

• Example: mcal xxx.cif p --pyscf

--gpu4pyscf

Use GPU acceleration via gpu4pyscf. Automatically enables PySCF mode (no need to specify --pyscf). Requires yu-mcal[gpu4pyscf-cuda11] or yu-mcal[gpu4pyscf-cuda12].

• Example: mcal xxx.cif p --gpu4pyscf

--cart

Use Cartesian basis functions instead of spherical harmonics (PySCF only).

• Example: mcal xxx.cif p --pyscf --cart

Calculation Control

-r, --read

Read results from existing files without executing calculations. With Gaussian, reads from log files; with PySCF, reads from checkpoint (.chk) files.

• Example: mcal xxx.cif p -r

-rp, --read_pickle

Read results from existing pickle file without executing calculations.

• Example: mcal xxx_result.pkl p -rp

--resume

Resume calculation using existing results. With Gaussian, checks log file termination; with PySCF, checks for existing checkpoint (.chk) files.

• Example: mcal xxx.cif p --resume

--fullcal

Disable all speedup processing and calculate transfer integrals for all pairs from scratch. The following two optimizations are disabled:

1. Pair screening: pairs are normally skipped based on moment of inertia and center-of-mass distance; --fullcal disables this screening
2. Monomer caching: monomer SCF calculations for the same molecule type are normally skipped by reusing a previously computed result file; --fullcal forces all monomer calculations to be performed from scratch

• Example: mcal xxx.cif p --fullcal

--no-monomer-cache

Disable only monomer caching. Pair screening remains active. All monomer SCF calculations are performed from scratch instead of reusing previously computed result files. When performing detailed transfer integral analysis using tcal, it is recommended to use this option.

• Example: mcal xxx.cif p --no-monomer-cache

--cellsize <number>

Specify the number of unit cells to expand in each direction around the central unit cell for transfer integral calculations.

• Default: 2 (creates 5×5×5 supercell)
• Examples:
  • mcal xxx.cif p --cellsize 1 (creates 3×3×3 supercell)
  • mcal xxx.cif p --cellsize 3 (creates 7×7×7 supercell)

Output Settings

-p, --pickle

Save calculation results to a pickle file.

• Example: mcal xxx.cif p -p

--plot-plane <plane>

Plot mobility tensor as a 2D polar plot on specified crystallographic plane.

• Available planes: ab, ac, ba, bc, ca, cb
• Default: None (no plot generated)
• Examples:
  • mcal xxx.cif p --plot-plane ab (plot on ab-plane)
  • mcal xxx.cif p --plot-plane bc (plot on bc-plane)

Practical Usage Examples

Basic Calculations

# Calculate mobility of p-type xxx
mcal xxx.cif p

# Use 8 CPUs and 16GB memory
mcal xxx.cif p -c 8 -m 16

High-Precision Calculations

# Calculate transfer integrals for all pairs (high precision, time-consuming)
mcal xxx.cif p --fullcal

# Use larger supercell to widen transfer integral calculation range
mcal xxx.cif p --cellsize 3

# Use different basis set
mcal xxx.cif p -M "B3LYP/6-311G(d,p)"

PySCF Calculations

# Calculate using PySCF (CPU)
mcal xxx.cif p --pyscf

# Calculate using PySCF with GPU acceleration (no --pyscf needed)
mcal xxx.cif p --gpu4pyscf

# Use 8 CPUs and 16GB memory with PySCF
mcal xxx.cif p --pyscf -c 8 -m 16

# Resume interrupted PySCF calculation
mcal xxx.cif p --pyscf --resume

# Read from existing PySCF checkpoint files
mcal xxx.cif p --pyscf -r

Reusing Results

# Read from existing calculation results
mcal xxx.cif p -r

# Read from existing pickle file
mcal xxx_result.pkl p -rp

# Resume interrupted calculation
mcal xxx.cif p --resume

# Save results to pickle file
mcal xxx.cif p -p

Output

Standard Output

• Reorganization energy
• Transfer integrals for each pair
• Diffusion coefficient tensor
• Mobility tensor
• Eigenvalues and eigenvectors of mobility

Generated Files

Reorganization Energy Files

The following files are generated during reorganization energy calculation (where c = cation for p-type, a = anion for n-type):

Gaussian

• xxx_opt_n.gjf / xxx_opt_n.log — geometry optimization of neutral molecule
• xxx_c.gjf / xxx_c.log (or xxx_a) — SP energy of ion at neutral geometry
• xxx_opt_c.gjf / xxx_opt_c.log (or xxx_opt_a) — geometry optimization of ion
• xxx_n.gjf / xxx_n.log — SP energy of neutral at ion geometry

PySCF

• xxx_opt_n.xyz / xxx_opt_n.chk — geometry optimization of neutral molecule
• xxx_c.chk (or xxx_a.chk) — SP energy of ion at neutral geometry
• xxx_opt_c.xyz / xxx_opt_c.chk (or xxx_opt_a) — geometry optimization of ion
• xxx_n.chk — SP energy of neutral at ion geometry

Transfer Integral Files

mcal generates calculation files named using the (s_t_i_j_k) notation:

Symbol	Meaning
s	Molecule index in the reference unit cell (0,0,0)
t	Molecule index in the neighboring unit cell
i	Translation index along the a-axis
j	Translation index along the b-axis
k	Translation index along the c-axis

Example: xxx-(0_0_1_0_0) represents the transfer integral between the 0th molecule in the (0,0,0) cell and the 0th molecule in the (1,0,0) cell.

Gaussian

• xxx-(s_t_i_j_k).gjf / xxx-(s_t_i_j_k).log — dimer
• xxx-(s_t_i_j_k)_m1.gjf / xxx-(s_t_i_j_k)_m1.log — monomer 1
• xxx-(s_t_i_j_k)_m2.gjf / xxx-(s_t_i_j_k)_m2.log — monomer 2

PySCF

• xxx-(s_t_i_j_k).xyz / xxx-(s_t_i_j_k).chk — dimer
• xxx-(s_t_i_j_k)_m1.chk — monomer 1
• xxx-(s_t_i_j_k)_m2.chk — monomer 2

Notes

1. Calculation Time: Calculation time varies significantly depending on the number of molecules and cell size. By default, two speedup mechanisms are enabled: pair pre-screening (skipping pairs unlikely to have significant transfer integrals) and monomer caching (reusing the isolated-molecule SCF result for molecule types already computed). Use --fullcal to disable both.
2. Memory Usage: Ensure sufficient memory for large systems
3. Gaussian Installation: Gaussian 09 or Gaussian 16 is required
4. Dependencies: Make sure all required Python libraries are installed

Troubleshooting

If calculation stops midway

# Resume with --resume option
mcal xxx.cif p --resume

Memory shortage error

# Increase memory amount
mcal xxx.cif p -m 32

To reduce calculation time

# Enable speedup processing (default)
mcal xxx.cif p

# Use smaller supercell for faster calculation
mcal xxx.cif p --cellsize 1

# Increase number of CPUs
mcal xxx.cif p -c 16

Authors

Matsui Laboratory, Research Center for Organic Electronics (ROEL), Yamagata University
Hiroyuki Matsui, Koki Ozawa
Email: h-matsui[at]yz.yamagata-u.ac.jp
Please replace [at] with @

Acknowledgements

This work was supported by JSPS Grant-in-Aid for JSPS Fellows Grant Number JP25KJ0647.

References

[1] Qiming Sun et al., Recent developments in the PySCF program package, J. Chem. Phys. 2020, 153, 024109.
[2] Lee-Ping Wang, Chenchen Song, Geometry optimization made simple with translation and rotation coordinates, J. Chem. Phys. 2016, 144, 214108.