def change_concentration(ge_concentration=0):
# Read in 1728 atom system
atoms = read('structures/1728_atom/aSi.xyz', format='xyz')
# Swap in Ge atoms
if ge_concentration != 0:
symbols = np.array(atoms.get_chemical_symbols())
n_ge_atoms = int(np.round(ge_concentration * len(symbols), 0))
rng = np.random.default_rng(seed=random_seed)
id = rng.choice(len(atoms), size=n_ge_atoms, replace=False)
symbols[id] = 'Ge'
atoms.set_chemical_symbols(symbols.tolist())
ge_concentration = str(int(ge_concentration * 100))
folder_string = 'structures/1728_atom/aSiGe_C' + str(ge_concentration)
if not os.path.exists(folder_string):
os.makedirs(folder_string)
# Minimize structure - LAMMPS + ASE
lammps_inputs = {
'lmpcmds': [
"pair_style tersoff",
"pair_coeff * * forcefields/SiCGe.tersoff Si(D) Ge"
],
"log_file":
"min.log",
"keep_alive":
True
}
calc = LAMMPSlib(**lammps_inputs)
atoms.set_calculator(calc)
atoms.pbc = True
search = LBFGSLineSearch(atoms)
search.run(fmax=.001)
write('structures/1728_atom/aSiGe_C' + str(ge_concentration) +
'/replicated_atoms.xyz',
search.atoms,
format='xyz')
def create_child_from(self, parent):
child = parent.copy()
calc = EMT()
child.set_calculator(calc)
if (random.random() > 0.25):
child.rattle(0.02, random.randint(0, 50))
else:
child.rattle(0.2, random.randint(0, 50))
dyn = LBFGSLineSearch(atoms=child)
dyn.run(steps=20000)
dyn = FIRE(atoms=child)
dyn.run(fmax=0.05)
return child
def test_unitcellfilterpressure():
a0 = bulk('Cu', cubic=True)
# perturb the atoms
s = a0.get_scaled_positions()
s[:, 0] *= 0.995
a0.set_scaled_positions(s)
# perturb the cell
a0.cell[...] += np.random.uniform(-1e-2, 1e-2, size=9).reshape((3, 3))
atoms = a0.copy()
atoms.calc = LennardJones()
ucf = UnitCellFilter(atoms, scalar_pressure=10.0 * GPa)
# test all derivatives
f, fn = gradient_test(ucf)
assert abs(f - fn).max() < 1e-6
opt = FIRE(ucf)
opt.run(1e-3)
# check pressure is within 0.1 GPa of target
sigma = atoms.get_stress() / GPa
pressure = -(sigma[0] + sigma[1] + sigma[2]) / 3.0
assert abs(pressure - 10.0) < 0.1
atoms = a0.copy()
atoms.calc = LennardJones()
ecf = ExpCellFilter(atoms, scalar_pressure=10.0 * GPa)
# test all deritatives
f, fn = gradient_test(ecf)
assert abs(f - fn).max() < 1e-6
opt = LBFGSLineSearch(ecf)
opt.run(1e-3)
# check pressure is within 0.1 GPa of target
sigma = atoms.get_stress() / GPa
pressure = -(sigma[0] + sigma[1] + sigma[2]) / 3.0
assert abs(pressure - 10.0) < 0.1
def genParticle(definingString, number):
"""definingString should be something like " 'Pt80' ", for example.
number should be the number of atoms that will be in the molecule."""
dummyAtom = ase.io.read("InputGeom.vasp", format="vasp")
while len(dummyAtom) > number:
dummyAtom.pop(-1)
coords = dummyAtom.get_positions().tolist()
shuffledCoords = []
while len(coords) > 0: # THIS IS SCREWED UP!
R = random.randint(0, len(coords) - 1)
item = coords.pop(R)
shuffledCoords.append(item)
newAtom = Atoms(definingString, shuffledCoords)
calc = EMT()
newAtom.set_calculator(calc)
newAtom.set_cell(dummyAtom.get_cell() * 10.0)
dyn = LBFGSLineSearch(atoms=newAtom)
dyn.run(steps=20000)
dyn = FIRE(atoms=newAtom)
dyn.run(fmax=0.05)
return newAtom
def nearlySphericalAtom(definingString, inRadius, number):
"""definingString should be something like " 'Pt80' ", for example.
inRadius should be the radius that you wish to have for the atom.
number should be the number of atoms that will be in the molecule."""
positionList = []
for x in range(number):
xDistance = random.uniform(0, inRadius) * plusOrMinus()
remainingX = ((inRadius ** 2) - (xDistance ** 2)) ** 0.5
yDistance = random.uniform(0, remainingX) * plusOrMinus()
zDistance = random.uniform(
0, (((remainingX ** 2) - (yDistance ** 2)) ** 0.5) * plusOrMinus() + random.normal(0, 0.1)
)
coordinates = (xDistance, yDistance, zDistance)
positionList.append(coordinates)
newAtom = Atoms(definingString, positionList)
calc = EMT()
newAtom.set_calculator(calc)
dyn = LBFGSLineSearch(atoms=newAtom)
dyn.run(steps=200000)
dyn = FIRE(atoms=newAtom)
dyn.run(fmax=0.01)
return newAtom
from ase.optimize import LBFGSLineSearch
from ase.constraints import UnitCellFilter
import pyjulip
bulk_at = bulk("Cu", cubic=True)
sigma = (bulk_at * 2).get_distance(0, 1) * (2.**(-1. / 6))
calc = LennardJones(sigma=sigma, epsilon=0.05)
N_cell = 3
at0 = bulk_at * N_cell
del at0[0]
at_ref = at0.copy()
at_ref.set_calculator(calc)
opt = LBFGSLineSearch(at_ref)
opt.run(fmax=1e-6)
at_ref_var_cell = at0.copy()
at_ref_var_cell.set_calculator(calc)
opt = LBFGSLineSearch(UnitCellFilter(at_ref_var_cell))
opt.run(fmax=1e-6)
for variable_cell in [False, True]:
at = at0.copy()
at.set_calculator(calc)
opt = pyjulip.JulipOptimizer(at, variable_cell=variable_cell)
opt.run(fmax=1e-6)
if variable_cell:
assert np.abs(at.positions - at_ref_var_cell.positions).max() < 1e-6
ucf = UnitCellFilter(atoms, scalar_pressure=10.0*GPa) # test all deritatives f, fn = gradient_test(ucf) assert abs(f - fn).max() < 1e-6 opt = FIRE(ucf) opt.run(1e-3) # check pressure is within 0.1 GPa of target sigma = atoms.get_stress()/GPa pressure = -(sigma[0] + sigma[1] + sigma[2])/3.0 assert abs(pressure - 10.0) < 0.1 atoms = a0.copy() atoms.set_calculator(LennardJones()) ecf = ExpCellFilter(atoms, scalar_pressure=10.0*GPa) # test all deritatives f, fn = gradient_test(ecf) assert abs(f - fn).max() < 1e-6 opt = LBFGSLineSearch(ecf) opt.run(1e-3) # check pressure is within 0.1 GPa of target sigma = atoms.get_stress()/GPa pressure = -(sigma[0] + sigma[1] + sigma[2])/3.0 assert abs(pressure - 10.0) < 0.1
