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Amorphous Oxides Structure Analysis

ai2-kit algorithm aosa

Introduction

A set of tools and Python functions to analyze statistic properties of structure in amorphous oxides.

Usage

Effective Coordination Number (ECN)

ai2-kit algorithm aosa ecn-analysis

This command is used to calculate the average bond length and effective coordination number in a given trajectory, and dump results as a new file.

Options

Option Description Type Default Example
input_traj The trajectory you need to input for analysis. str (Required) --input_traj ./in2o3-eq.xyz
out_dir Dump the result of analysis result (per frame) and average (average values) in a new directory. str (Required) --out_dir ./out
center Reference atom (Central atom), in the format of MDA select_atoms str (Required) --center 'name In'
ligand Configuration atom (Coordination atom), use the same format of center str (Required) --ligand 'name O'
cell Setting the parameters of the cell. list[float] (Required) --cell '[10.2, 10.2, 10.2, 90, 90, 90]'

Examples

We could run this method by the following command:

ai2-kit algorithm aosa ecn-analysis \
    --input_traj ./in2o3-eq.xyz \
    --out_dir ./out \
    --center 'name In' \
    --ligand 'name O' \
    --cell '[20.238452856, 20.23845286, 20.23845286, 90, 90, 90]'

The output would be written in a new directory : ./out/raw.txt and ./out/stat.txt.

In the file raw.txt:

# frame_index   l_av   ECN
    0        2.1778   5.3359
    1        2.1793   5.3555
    2        2.1789   5.3492
    3        2.1771   5.3276
    4        2.1771   5.3290
    ...      ...      ...

In the file stats.txt:

l_av = 2.1752
ECN = 5.2832

Counting Polyhedra

ai2-kit algorithm aosa count-shared-polyhedra

This command is used to count the numbers and fractions of polyhedra linked in different forms, including "Corner-share", "Edge-share" and "Face-share".

Options

Option Description Type Default Example
input_traj The trajectory you need to input for analysis. str (Required) --input_traj ./in2o3-eq.xyz
out_dir Dump the result of analysis result (per frame) and average (average values) in a new directory. str (Required) --out_dir ./out
center Reference atom (Central atom), in the format of MDA select_atoms str (Required) --center 'name In'
ligand Configuration atom (Coordination atom), use the same format of center str (Required) --ligand 'name O'
cell Setting the parameters of the cell. list[float] (Required) --cell '[10.2, 10.2, 10.2, 90, 90, 90]'
cutoff Setting the cutoff distance to define a bond. float (Required) --cutoff 2.36
coord_num Provide the coordination number of polyhedra that you want to count. For example, you could set 6 for $octahedra$. In particular, -1 corresponds to counting $All\ categories\ of\ the\ polyhedra$. int -1 --coord_num 6

Examples

We could run this method by the following command :

ai2-kit algorithm aosa count-shared-polyhedra \
    --input_traj ./in2o3-eq.xyz \
    --out_dir ./out \
    --center 'name In' \
    --ligand 'name O' \
    --cell '[20.23845286, 20.23845286, 20.23845286, 90, 90, 90]' \
    --cutoff 2.36 \
    --coord_num 6

The output would be written in a new directory : ./out/raw.txt and ./out/stats.txt.

In the file raw.txt:

# frame_index   corner   edge   face
    0        1106.0000   290.0000   0.0000
    1        1098.0000   300.0000   0.0000
    2        1134.0000   286.0000   2.0000
    3        1116.0000   288.0000   2.0000
    4        1114.0000   287.0000   2.0000
    ...      ...         ...        ...

In the file stats.txt:

Corner-share = 1096.4817
Edge-share = 285.7608
Face-share = 1.8439