Initial commit: PS4-centered Li/I density analysis
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佐久間 美波
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#+TITLE: Li2S-P2S5-LiI Glass: PS4-Centered Ion Density Analysis
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#+AUTHOR: Minami Sakuma
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#+OPTIONS: toc:2 num:nil
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* Overview
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This repository contains Python scripts for analyzing and visualizing
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Li and I spatial probability distributions around =PS4^{3-}= units in
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Li2S-P2S5-LiI glass trajectories.
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The workflow consists of two steps:
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1. =dump2cube.py=
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- Reads a LAMMPS trajectory.
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- Aligns each =PS4^{3-}= tetrahedron using the nearest I^- ion.
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- Accumulates Li and I positions in the aligned coordinate system.
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- Outputs three-dimensional probability-density data in Gaussian cube format.
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2. =cube2mayavi.py=
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- Reads the generated cube file.
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- Visualizes the spatial probability density as an isosurface using Mayavi.
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- Displays the reference =PS4^{3-}= tetrahedron.
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The scripts are intended to analyze the local geometrical relationship
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between I^- ions and =PS4^{3-}= units in Li2S-P2S5-LiI glasses.
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* Files
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| File | Description |
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|---+---|
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| =dump2cube.py= | Converts a LAMMPS trajectory into Li/I probability-density cube files. |
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| =cube2mayavi.py= | Visualizes a cube file with Mayavi. |
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| =050Li3PS4-050LiI.lammpstrj= | Example LAMMPS trajectory. |
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| =050Li3PS4-050LiI_PS4_I.cube= | Example I^- probability-density cube file. |
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* Requirements
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The scripts require Python 3 and the following packages:
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- NumPy
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- Mayavi
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- VTK
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- Traits
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- PyQt5 or PySide6, depending on the Mayavi installation
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Example installation using conda:
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#+begin_src bash
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conda create -n ps4-density python=3.10
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conda activate ps4-density
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conda install -c conda-forge numpy mayavi pyqt
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#+end_src
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Alternatively, NumPy can be installed using pip:
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#+begin_src bash
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pip install numpy
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#+end_src
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Mayavi installation is generally more stable with conda-forge.
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* Input Trajectory Format
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=dump2cube.py= assumes a LAMMPS trajectory containing the following
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atom columns:
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#+begin_example
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ITEM: ATOMS id type element mol x y z
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#+end_example
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The trajectory must contain at least the following elements:
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- Li
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- P
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- S
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- I
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The script assumes that P and S atoms belonging to the same
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=PS4^{3-}= unit share the same molecule ID (=mol=).
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* Analysis Procedure
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For each trajectory frame:
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1. Each P atom is selected as the center of a reference =PS4^{3-}= unit.
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2. The four nearest I^- ions are identified.
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3. The nearest I^- ion is used to define the orientation of the =PS4^{3-}= unit.
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4. The =PS4^{3-}= tetrahedron is rotated into a common reference frame.
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5. Li positions within the cutoff distance are accumulated.
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6. The positions of the four nearest I^- ions are accumulated.
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7. Three-dimensional histograms are written as cube files.
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The reference orientation is defined as follows:
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- The S atom farthest from the nearest I^- ion is aligned with the z axis.
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- A second S atom is used to fix the rotation around the z axis.
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* Usage
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** Generate Cube Files
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#+begin_src bash
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python dump2cube.py \
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-i 050Li3PS4-050LiI.lammpstrj \
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-m 160 160 160 \
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-cut 8
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#+end_src
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Arguments:
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| Argument | Description |
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|---+---|
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| =-i=, =--trjfile= | Input LAMMPS trajectory file. |
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| =-m=, =--mesh= | Number of grid points in x, y, and z directions. |
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| =-cut=, =--cutoff= | Spatial cutoff radius in angstrom. |
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Expected output files:
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#+begin_example
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050Li3PS4-050LiI_PS4_Li.cube
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050Li3PS4-050LiI_PS4_I.cube
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#+end_example
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** Visualize I^- Probability Density
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#+begin_src bash
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python cube2mayavi.py \
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-i 050Li3PS4-050LiI_PS4_I.cube \
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-atom I \
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-iso 1.26483e-09
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#+end_src
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** Visualize Li+ Probability Density
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#+begin_src bash
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python cube2mayavi.py \
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-i 050Li3PS4-050LiI_PS4_Li.cube \
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-atom Li \
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-iso 1.0e-09
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#+end_src
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The appropriate isovalue depends on the trajectory length, mesh size,
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cutoff radius, and probability-density distribution. It should therefore
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be adjusted for each dataset.
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* Output
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The cube files contain:
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- A reference =PS4^{3-}= tetrahedron:
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- P atom at the origin
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- Four S atoms in the aligned coordinate system
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- A three-dimensional spatial probability-density field for Li or I
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The cube files can be visualized using:
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- Mayavi
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- VMD
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- PyMOL
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- ParaView
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- Other software supporting Gaussian cube files
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* Visualization Colors
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The default visualization settings in =cube2mayavi.py= are:
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| Object | Color |
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|---+---|
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| P | Purple |
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| S | Yellow |
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| Li probability density | Blue |
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| I probability density | Red |
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| P-S bonds | Gray |
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* Notes
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- The trajectory is treated using periodic boundary conditions.
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- Coordinates are converted to fractional coordinates before alignment.
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- The current implementation assumes an orthorhombic simulation box for
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the trajectory parsing procedure.
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- The script includes a triclinic-cell lattice conversion function, but
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the exact input format should be checked before applying it to
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triclinic LAMMPS trajectories.
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- Large trajectory and cube files can exceed the standard GitHub file-size
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limit. Git LFS is recommended when files are larger than 100 MB.
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* Citation
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If this repository is used in research, please cite the corresponding
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publication or presentation describing the Li2S-P2S5-LiI glass analysis.
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* License
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This repository is intended for academic research use.
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