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pyiron
Potentials Workshop 2021
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b1a4332d
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b1a4332d
authored
Mar 08, 2021
by
Jan Janssen
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Mar 08, 2021
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%% Cell type:markdown id:touched-vocabulary tags:
# [**Workflows for atomistic simulations**](http://potentials.rub.de/)
%% Cell type:markdown id:conceptual-moscow tags:
## **Day 3 - Validation of various potentials**
### **Exercise 1: Validation of generated potentials using pyiron based workflows**
Before the excercise, you should:
*
Have run the notebooks from day 1 and day2
*
Be familiar with working with pyiron and the basics of potential fitting
The aim of this exercise is to make you familiar with:
*
Potential validation workflows
%% Cell type:code id:golden-folks tags:
```
python
import
numpy
as
np
%
matplotlib
inline
import
matplotlib.pylab
as
plt
import
pandas
as
pd
```
%% Cell type:code id:leading-blake tags:
```
python
from
pyiron
import
Project
```
%% Cell type:code id:decreased-latvia tags:
```
python
pr
=
Project
(
"validation"
)
pr
.
remove
(
True
)
```
%% Cell type:code id:empirical-essay tags:
```
python
# The good potentials already added to the pyiron database
potential_list
=
[
'
Cu_
Mendelev
_eam
'
,
'2004--Zhou-X-W--Cu-Ag-Au--LAMMPS--ipr2'
,
'Cu-ace'
,
'Cu-runner-df4'
]
#, 'Cu-runner-df1']
potential_list
=
[
'
2012--
Mendelev
-M-I--Cu--LAMMPS--ipr1
'
,
'2004--Zhou-X-W--Cu-Ag-Au--LAMMPS--ipr2'
,
'Cu-ace'
,
'Cu-runner-df4'
]
#, 'Cu-runner-df1']
# The potentials that were fit yesterday
```
%% Cell type:code id:checked-terminal tags:
```
python
# Do Murnaghan, ElasticMatrix job, vac formation energy, binding energy, surface energies, comparison with dataset forces, energies
```
%% Cell type:code id:residential-diving tags:
```
python
def
clean_project_name
(
name
):
return
name
.
replace
(
"-"
,
"_"
)
```
%% Cell type:code id:conditional-order tags:
```
python
for
pot
in
potential_list
:
group_name
=
clean_project_name
(
pot
)
pr_pot
=
pr
.
create_group
(
pot
)
job_ref
=
pr_pot
.
create_job
(
pr_pot
.
job_type
.
Lammps
,
"ref_job"
)
job_ref
.
structure
=
pr_pot
.
create_ase_bulk
(
"Cu"
)
job_ref
.
potential
=
pot
job_ref
.
calc_minimize
()
murn_job
=
job_ref
.
create_job
(
pr_pot
.
job_type
.
Murnaghan
,
"murn_job"
)
murn_job
.
run
()
print
(
"Potential: "
,
pot
)
murn_job
.
plot
()
```
%%%% Output: stream
The job murn_job was saved and received the ID: 4389
The job strain_0_9 was saved and received the ID: 4390
The job strain_0_92 was saved and received the ID: 4391
The job strain_0_94 was saved and received the ID: 4392
The job strain_0_96 was saved and received the ID: 4393
The job strain_0_98 was saved and received the ID: 4394
The job strain_1_0 was saved and received the ID: 4395
The job strain_1_02 was saved and received the ID: 4396
The job strain_1_04 was saved and received the ID: 4397
The job strain_1_06 was saved and received the ID: 4398
The job strain_1_08 was saved and received the ID: 4399
The job strain_1_1 was saved and received the ID: 4400
job_id: 4390 finished
job_id: 4391 finished
job_id: 4392 finished
job_id: 4393 finished
job_id: 4394 finished
job_id: 4395 finished
job_id: 4396 finished
job_id: 4397 finished
job_id: 4398 finished
job_id: 4399 finished
job_id: 4400 finished
Potential: Cu-ace
%%%% Output: display_data
%%%% Output: stream
The job murn_job was saved and received the ID: 4401
The job strain_0_9 was saved and received the ID: 4402
The job strain_0_92 was saved and received the ID: 4403
The job strain_0_94 was saved and received the ID: 4404
The job strain_0_96 was saved and received the ID: 4405
The job strain_0_98 was saved and received the ID: 4406
The job strain_1_0 was saved and received the ID: 4407
The job strain_1_02 was saved and received the ID: 4408
The job strain_1_04 was saved and received the ID: 4409
The job strain_1_06 was saved and received the ID: 4410
The job strain_1_08 was saved and received the ID: 4411
The job strain_1_1 was saved and received the ID: 4412
job_id: 4402 finished
job_id: 4403 finished
job_id: 4404 finished
job_id: 4405 finished
job_id: 4406 finished
job_id: 4407 finished
job_id: 4408 finished
job_id: 4409 finished
job_id: 4410 finished
job_id: 4411 finished
job_id: 4412 finished
Potential: Cu-runner-df4
%%%% Output: display_data
%% Cell type:code id:leading-sector tags:
```
python
murn_job
[
"output/equilibrium_energy"
]
```
%%%% Output: execute_result
-3.694888787063416
%% Cell type:code id:partial-bulgaria tags:
```
python
def
get_only_murn
(
job_table
):
return
job_table
.
hamilton
==
"Murnaghan"
def
get_eq_vol
(
job_path
):
return
job_path
[
"output/equilibrium_volume"
]
def
get_eq_lp
(
job_path
):
return
np
.
linalg
.
norm
(
job_path
[
"output/structure/cell/cell"
][
0
])
*
np
.
sqrt
(
2
)
def
get_eq_bm
(
job_path
):
return
job_path
[
"output/equilibrium_bulk_modulus"
]
def
get_potential
(
job_path
):
return
job_path
[
"ref_job/input/potential/Name"
]
def
get_eq_energy
(
job_path
):
return
job_path
[
"output/equilibrium_energy"
]
def
get_n_atoms
(
job_path
):
return
len
(
job_path
[
"output/structure/positions"
])
```
%% Cell type:code id:specified-acceptance tags:
```
python
table
=
pr
.
create_table
(
"table_murn"
,
delete_existing_job
=
True
)
table
.
db_filter_function
=
get_only_murn
table
.
add
[
"potential"
]
=
get_potential
table
.
add
[
"a"
]
=
get_eq_lp
table
.
add
[
"eq_vol"
]
=
get_eq_vol
table
.
add
[
"eq_bm"
]
=
get_eq_bm
table
.
add
[
"eq_energy"
]
=
get_eq_energy
table
.
add
[
"n_atoms"
]
=
get_n_atoms
table
.
run
()
data_murn
=
table
.
get_dataframe
()
data_murn
```
%%%% Output: stream
100%|██████████| 2/2 [00:00<00:00, 513.91it/s]
100%|██████████| 2/2 [00:00<00:00, 28.91it/s]
%%%% Output: stream
The job table_murn was saved and received the ID: 4413
CPU times: user 219 ms, sys: 62.5 ms, total: 281 ms
Wall time: 317 ms
%%%% Output: stream
%%%% Output: execute_result
job_id potential a eq_vol eq_bm eq_energy n_atoms
0 4389 Cu-ace 3.629863 11.956678 146.220099 -3.698781 1
1 4401 Cu-runner-df4 3.618770 11.847397 145.857176 -3.694889 1
%% Cell type:code id:automatic-kuwait tags:
```
python
for
pot
in
data_murn
.
potential
.
to_list
():
group_name
=
clean_project_name
(
pot
)
pr_pot
=
pr
.
create_group
(
pot
)
print
(
pot
)
job_id
=
int
(
data_murn
[
data_murn
.
potential
==
pot
].
job_id
)
job_ref
=
pr_pot
.
create_job
(
pr_pot
.
job_type
.
Lammps
,
"ref_job"
)
job_ref
.
structure
=
pr_pot
.
inspect
(
job_id
)[
"output/structure"
].
to_object
()
job_ref
.
potential
=
pot
job_ref
.
calc_minimize
()
elastic_job
=
job_ref
.
create_job
(
pr_pot
.
job_type
.
ElasticMatrixJob
,
"elastic_job"
)
elastic_job
.
input
[
"eps_range"
]
=
0.05
elastic_job
.
run
()
```
%%%% Output: stream
Cu-ace
The job elastic_job was saved and received the ID: 4414
The job s_e_0 was saved and received the ID: 4415
The job s_01_e_m0_05000 was saved and received the ID: 4416
The job s_01_e_m0_02500 was saved and received the ID: 4417
The job s_01_e_0_02500 was saved and received the ID: 4418
The job s_01_e_0_05000 was saved and received the ID: 4419
The job s_08_e_m0_05000 was saved and received the ID: 4420
The job s_08_e_m0_02500 was saved and received the ID: 4421
The job s_08_e_0_02500 was saved and received the ID: 4422
The job s_08_e_0_05000 was saved and received the ID: 4423
The job s_23_e_m0_05000 was saved and received the ID: 4424
The job s_23_e_m0_02500 was saved and received the ID: 4425
The job s_23_e_0_02500 was saved and received the ID: 4426
The job s_23_e_0_05000 was saved and received the ID: 4427
Cu-runner-df4
The job elastic_job was saved and received the ID: 4428
The job s_e_0 was saved and received the ID: 4429
The job s_01_e_m0_05000 was saved and received the ID: 4430
The job s_01_e_m0_02500 was saved and received the ID: 4431
The job s_01_e_0_02500 was saved and received the ID: 4432
The job s_01_e_0_05000 was saved and received the ID: 4433
The job s_08_e_m0_05000 was saved and received the ID: 4434
The job s_08_e_m0_02500 was saved and received the ID: 4435
The job s_08_e_0_02500 was saved and received the ID: 4436
The job s_08_e_0_05000 was saved and received the ID: 4437
The job s_23_e_m0_05000 was saved and received the ID: 4438
The job s_23_e_m0_02500 was saved and received the ID: 4439
The job s_23_e_0_02500 was saved and received the ID: 4440
The job s_23_e_0_05000 was saved and received the ID: 4441
CPU times: user 42 s, sys: 31 s, total: 1min 12s
Wall time: 58.3 s
%% Cell type:code id:dedicated-powder tags:
```
python
plt
.
matshow
(
elastic_job
[
"output/elasticmatrix"
][
"C"
]);
```
%%%% Output: display_data
%% Cell type:code id:joint-shield tags:
```
python
elastic_job
[
"output/elasticmatrix"
][
"C"
].
flatten
()
```
%%%% Output: execute_result
array([143.47389261, 170.02778376, 170.02778376, 0. ,
0. , 0. , 170.02778376, 143.47389261,
170.02778376, 0. , 0. , 0. ,
170.02778376, 170.02778376, 143.47389261, 0. ,
0. , 0. , 0. , 0. ,
0. , 100.95388854, 0. , 0. ,
0. , 0. , 0. , 0. ,
100.95388854, 0. , 0. , 0. ,
0. , 0. , 0. , 100.95388854])
%% Cell type:code id:roman-tenant tags:
```
python
def
filter_elastic
(
job_table
):
return
(
job_table
.
hamilton
==
"ElasticMatrixJob"
)
&
(
job_table
.
status
==
"finished"
)
def
get_c11
(
job_path
):
return
job_path
[
"output/elasticmatrix"
][
"C"
][
0
,
0
]
def
get_c12
(
job_path
):
return
job_path
[
"output/elasticmatrix"
][
"C"
][
0
,
1
]
def
get_c44
(
job_path
):
return
job_path
[
"output/elasticmatrix"
][
"C"
][
3
,
3
]
```
%% Cell type:code id:determined-token tags:
```
python
%%
time
table
=
pr
.
create_table
(
"table_elastic"
,
delete_existing_job
=
True
)
table
.
db_filter_function
=
filter_elastic
table
.
add
[
"potential"
]
=
get_potential
table
.
add
[
"C11"
]
=
get_c11
table
.
add
[
"C12"
]
=
get_c12
table
.
add
[
"C44"
]
=
get_c44
table
.
run
()
data_elastic
=
table
.
get_dataframe
()
data_elastic
```
%%%% Output: stream
100%|██████████| 2/2 [00:00<00:00, 547.17it/s]
0%| | 0/2 [00:00<?, ?it/s]
%%%% Output: stream
The job table_elastic was saved and received the ID: 4442
%%%% Output: stream
100%|██████████| 2/2 [00:00<00:00, 5.13it/s]
%%%% Output: stream
CPU times: user 500 ms, sys: 109 ms, total: 609 ms
Wall time: 669 ms
%%%% Output: execute_result
job_id potential C11 C12 C44
0 4414 Cu-ace 182.054447 132.575877 81.049351
1 4428 Cu-runner-df4 143.473893 170.027784 100.953889
%% Cell type:code id:cooperative-store tags:
```
python
from
structdbrest
import
StructDBLightRester
rest
=
StructDBLightRester
(
token
=
"workshop2021"
)
fhi_calc
=
rest
.
query_calculator_types
(
"FHI%aims%"
)[
0
]
dft_elast_prop
=
rest
.
query_properties
(
rest
.
PropertyTypes
.
ELASTIC_MATRIX
,
composition
=
"Cu-%"
,
strukturbericht
=
"A1"
,
calculator_name
=
fhi_calc
.
NAME
)[
0
]
dft_phon_prop
=
rest
.
query_properties
(
rest
.
PropertyTypes
.
PHONONS
,
composition
=
"Cu-%"
,
strukturbericht
=
"A1"
,
calculator_name
=
fhi_calc
.
NAME
)[
0
]
```
%%%% Output: stream
Querying...done
Response successful, size = 7.20 kB, time = 0.13 s
1 entries received
Querying...done
Response successful, size = 37.78 kB, time = 0.38 s
1 entries received
Querying...done
Response successful, size = 22.50 kB, time = 0.20 s
1 entries received
%% Cell type:code id:planned-cargo tags:
```
python
C_dft
=
dft_elast_prop
.
value
[
"C"
]
print
(
"DFT C11={:.1f} GPa"
.
format
(
C_dft
[
0
][
0
]))
print
(
"DFT C12={:.1f} GPa"
.
format
(
C_dft
[
0
][
1
]))
print
(
"DFT C44={:.1f} GPa"
.
format
(
C_dft
[
3
][
3
]))
```
%%%% Output: stream
DFT C11=176.9 GPa
DFT C12=131.7 GPa
DFT C44=82.5 GPa
%% Cell type:code id:beginning-cheese tags:
```
python
%%
time
surface_type_list
=
[
"fcc111"
,
"fcc110"
,
"fcc100"
]
for
i
,
pot
in
enumerate
(
data_murn
.
potential
.
to_list
()):
group_name
=
clean_project_name
(
pot
)
pr_pot
=
pr
.
create_group
(
group_name
)
a
=
data_murn
.
a
.
to_list
()[
i
]
for
surface_type
in
surface_type_list
:
surface
=
pr
.
create_surface
(
"Cu"
,
surface_type
=
surface_type
,
size
=
(
8
,
8
,
8
),
a
=
a
,
orthogonal
=
True
,
vacuum
=
12
)
job_lammps
=
pr_pot
.
create_job
(
pr_pot
.
job_type
.
Lammps
,
"surf_{}"
.
format
(
surface_type
))
job_lammps
.
structure
=
surface
job_lammps
.
potential
=
pot
job_lammps
.
calc_minimize
()
job_lammps
.
run
()
```
%%%% Output: stream
The job surf_fcc111 was saved and received the ID: 4443
The job surf_fcc110 was saved and received the ID: 4444
The job surf_fcc100 was saved and received the ID: 4445
The job surf_fcc111 was saved and received the ID: 4446
The job surf_fcc110 was saved and received the ID: 4447
The job surf_fcc100 was saved and received the ID: 4448
CPU times: user 7.88 s, sys: 7.86 s, total: 15.7 s
Wall time: 48.4 s
%% Cell type:code id:preceding-fireplace tags:
```
python
``
`
%%
Cell
type
:
code
id
:
interracial
-
lunch
tags
:
```
python
def is_a_surface(job_table):
return (job_table.hamilton == "Lammps") & (job_table.job.str.contains("fcc")) & (job_table.status == "finished")
def get_potential_lammps_job(job_path):
return job_path["input/potential/Name"]
def get_surface_type(job_path):
surf_list = ["fcc111", "fcc110", "fcc100"]
conditions = [val in job_path.job_name for val in surf_list]
return surf_list[np.where(conditions)[0].tolist()[0]]
def get_area(job_path):
cell = job_path["output/structure/cell/cell"]
return np.linalg.norm(np.cross(cell[0], cell[1]))
```
%% Cell type:code id:palestinian-allen tags:
```
python
```
%% Cell type:code id:black-chance tags:
```
python
%%time
table = pr.create_table("table_surface", delete_existing_job=True)
table.db_filter_function = is_a_surface
table.add["potential"] = get_potential_lammps_job
table.add["surface_type"] = get_surface_type
table.add["surface_area"] = get_area
table.add.get_total_number_of_atoms
table.add.get_energy_tot
table.run()
data_surf = table.get_dataframe()
data_surf
```
%%%% Output: stream
100%|██████████| 6/6 [00:00<00:00, 430.05it/s]
0%| | 0/6 [00:00<?, ?it/s]
%%%% Output: stream
The job table_surface was saved and received the ID: 4449
%%%% Output: stream
100%|██████████| 6/6 [00:00<00:00, 13.52it/s]
%%%% Output: stream
CPU times: user 438 ms, sys: 219 ms, total: 656 ms
Wall time: 876 ms
%%%% Output: execute_result
Number_of_atoms job_id energy_tot potential surface_type \
0 512 4443 -1834.286336 Cu-ace fcc111
1 512 4444 -1775.620101 Cu-ace fcc110
2 512 4445 -1814.469585 Cu-ace fcc100
3 512 4446 -1835.853699 Cu-runner-df4 fcc111
4 512 4447 -1786.742960 Cu-runner-df4 fcc110
5 512 4448 -1816.715931 Cu-runner-df4 fcc100
surface_area
0 365.141308
1 596.273259
2 421.628865
3 362.913030
4 592.634496
5 419.055871
%% Cell type:code id:robust-unknown tags:
```
python
```
%% Cell type:code id:painted-taiwan tags:
```
python
data_merged = pd.merge(data_surf, data_murn, on="potential")
data_merged["surface_energy"] = data_merged.energy_tot - (data_merged.eq_energy
*
data_merged.Number_of_atoms)
data_merged["surface_energy_in_mJ_per_sq_m"] = data_merged.surface_energy / data_merged.surface_area / 2
* 16.0219 *
1e3
data_merged[["potential", "surface_type", "surface_energy_in_mJ_per_sq_m"]]
```
%%%% Output: execute_result
potential surface_type surface_energy_in_mJ_per_sq_m
0 Cu-ace fcc111 1305.155196
1 Cu-ace fcc110 1587.423774
2 Cu-ace fcc100 1506.815901
3 Cu-runner-df4 fcc111 1234.585883
4 Cu-runner-df4 fcc110 1419.881876
5 Cu-runner-df4 fcc100 1435.033014
%% Cell type:markdown id:hungarian-benefit tags:
## Finite temperature thermodynamics (Harmonic approximation)
%% Cell type:code id:recovered-warren tags:
```
python
# phonon DOS more analysis (comparison with some datasets)
```
%% Cell type:code id:fiscal-convergence tags:
```
python
%%time
for pot in data_murn.potential.to_list():
group_name = clean_project_name(pot)
pr_pot = pr.create_group(group_name)
job_id = int(data_murn[data_murn.potential==pot].job_id)
job_ref = pr_pot.create_job(pr_pot.job_type.Lammps, "ref_job")
job_ref.structure = pr_pot.inspect(job_id)["output/structure"].to_object()
job_ref.potential = pot
job_ref.calc_static()
phonopy_job = job_ref.create_job(pr_pot.job_type.PhonopyJob, "phonopy_job")
phonopy_job.run()
```
%%%% Output: stream
The job phonopy_job was saved and received the ID: 4450
The job ref_job_0 was saved and received the ID: 4451
The job phonopy_job was saved and received the ID: 4452
The job ref_job_0 was saved and received the ID: 4453
CPU times: user 10.1 s, sys: 6.06 s, total: 16.2 s
Wall time: 13.5 s
%% Cell type:code id:elegant-flashing tags:
```
python
pr
```
%%%% Output: execute_result
{'groups': ['Cu-ace', 'Cu-runner-df4', 'Cu_ace', 'Cu_runner_df4'], 'nodes': ['table_murn', 'table_elastic', 'table_surface']}
%% Cell type:code id:necessary-thomson tags:
```
python
fig, ax_list = plt.subplots(ncols=1, nrows=3, sharex="row")
#fig.set_figwidth(20)
fig.set_figheight(20)
for i, pot in enumerate(potential_list):
group_name = clean_project_name(pot)
phonopy_job = pr[group_name+"/phonopy_job"]
thermo = phonopy_job.get_thermal_properties(t_min=0, t_max=800)
ax = ax_list[0]
ax.plot(thermo.temperatures, thermo.free_energies, label=pot)
ax.set_xlabel("Temperatures [K]")
ax.set_ylabel("Free energies [eV]")
ax = ax_list[1]
ax.plot(thermo.temperatures, thermo.entropy, label=pot)
ax.set_xlabel("Temperatures [K]")
ax.set_ylabel("Entropy [eV/K]")
ax = ax_list[2]
ax.plot(thermo.temperatures, thermo.cv, label=pot)
ax.set_xlabel("Temperatures [K]")
ax.set_ylabel("Heat capacity (C$_\mathrm{V}$) [eV/K]")
ax_list[0].legend()
ax_list[1].legend()
ax_list[2].legend()
fig.subplots_adjust(hspace=0.1);
```
%%%% Output: display_data
