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
      2.1778   5.3359
      2.1793   5.3555
      2.1789   5.3492
      2.1771   5.3276
      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
      1106.0000   290.0000   0.0000
      1098.0000   300.0000   0.0000
      1134.0000   286.0000   2.0000
      1116.0000   288.0000   2.0000
      1114.0000   287.0000   2.0000
    ...      ...         ...        ...      

In the file stats.txt:

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