Creating Grain Boundaries#
In this notebook, creation and querying of GBs are discussed. These features are still under active development.
from atomrdf import KnowledgeGraph
import atomrdf.build as build
from ase.visualize import view
kg = KnowledgeGraph()
We start by creating a \(\Sigma 5 (3 \bar{1} 0)\)
struct_gb_1 = build.defect.grain_boundary(axis=[0,0,1],
sigma=5,
gb_plane=[3, -1, 0],
element='Fe',
graph=kg)
---------------------------------------------------------------------------
ModuleNotFoundError Traceback (most recent call last)
File ~/checkouts/readthedocs.org/user_builds/pyscal-rdf/conda/latest/lib/python3.11/site-packages/atomrdf/build/defect.py:373, in grain_boundary(element, axis, sigma, gb_plane, crystalstructure, a, b, c, alpha, covera, overlap, gap, vacuum, delete_layer, tolerance, uc_a, uc_b, repeat, graph, primitive)
372 from pymatgen.io.ase import AseAtomsAdaptor
--> 373 from aimsgb import GrainBoundary as AIMSGrainBoundary
374 from aimsgb import Grain as AIMSGrain
ModuleNotFoundError: No module named 'aimsgb'
During handling of the above exception, another exception occurred:
ImportError Traceback (most recent call last)
Cell In[3], line 1
----> 1 struct_gb_1 = build.defect.grain_boundary(axis=[0,0,1],
2 sigma=5,
3 gb_plane=[3, -1, 0],
4 element='Fe',
File ~/checkouts/readthedocs.org/user_builds/pyscal-rdf/conda/latest/lib/python3.11/site-packages/atomrdf/build/defect.py:376, in grain_boundary(element, axis, sigma, gb_plane, crystalstructure, a, b, c, alpha, covera, overlap, gap, vacuum, delete_layer, tolerance, uc_a, uc_b, repeat, graph, primitive)
374 from aimsgb import Grain as AIMSGrain
375 except ImportError:
--> 376 raise ImportError(
377 "This function requires the aimsgb and pymatgen packages to be installed"
378 )
380 a = _declass(a)
381 b = _declass(b)
ImportError: This function requires the aimsgb and pymatgen packages to be installed
We can visualise the structure
view(struct_gb_1, viewer='x3d')
Some other examples, \(\Sigma 3 (1\bar{-1}0)\) and \(\Sigma 19 (111)\)
struct_gb_2 = build.defect.grain_boundary(axis=[1,1,2],
sigma=3,
gb_plane=[1, -1, 0],
element='Fe',
graph=kg)
struct_gb_3 = build.defect.grain_boundary(axis=[1,1,1],
sigma=19,
gb_plane=[1, 1, 1],
element='Fe',
graph=kg)
What are all the samples with symmetric tilt grain boundaries?
res = kg.query_sample(kg.ontology.terms.pldo.SymmetricalTiltGrainBoundary)
res
| AtomicScaleSample | SymmetricalTiltGrainBoundary | |
|---|---|---|
| 0 | sample:4878c894-b017-4e05-be07-6669c450888f | sample:4878c894-b017-4e05-be07-6669c450888f_Sy... |
We see we have one structure in the database. We can also find what is the sigma value of this structure by modifying our query.
res = kg.query_sample([kg.ontology.terms.pldo.SymmetricalTiltGrainBoundary,
kg.ontology.terms.pldo.hasSigmaValue])
res
| AtomicScaleSample | SymmetricalTiltGrainBoundary | hasSigmaValuevalue | |
|---|---|---|---|
| 0 | sample:4878c894-b017-4e05-be07-6669c450888f | sample:4878c894-b017-4e05-be07-6669c450888f_Sy... | 5 |
We can choose the sample, and save it
sample = res.AtomicScaleSample[0]
sample
rdflib.term.URIRef('sample:4878c894-b017-4e05-be07-6669c450888f')
kg.to_file(sample, filename="POSCAR", format="vasp")
! head -20 POSCAR
Fe
1.0000000000000000
18.1514737693664969 -0.0000000000000006 0.0000000000000000
0.0000000000000000 9.0757368846832485 0.0000000000000000
0.0000000000000011 0.0000000000000006 2.8699999999999997
Fe
40
Cartesian
0.0000000000000000 0.0000000000000000 0.0000000000000000
2.7227210654049743 0.9075736884683246 0.0000000000000002
1.8151473769366497 3.6302947538732990 0.0000000000000003
0.9075736884683242 6.3530158192782737 0.0000000000000004
5.4454421308099485 1.8151473769366493 0.0000000000000004
4.5378684423416242 4.5378684423416233 0.0000000000000006
3.6302947538732995 7.2605895077465981 0.0000000000000007
8.1681631962149215 2.7227210654049738 0.0000000000000007
7.2605895077465972 5.4454421308099477 0.0000000000000008
6.3530158192782693 8.1681631962149215 0.0000000000000009
0.9075736884683249 1.8151473769366495 1.4350000000000001
3.6302947538732990 2.7227210654049743 1.4350000000000003