def main():
atoms = atoms_with_calc(50)
# mc = SoluteChainMC(atoms, 350, cluster_elements=["Mg", "Si"],
# cluster_names=["c2_01nn_0"])
T = [10]
snapshot = Snapshot(trajfile="data/solute_chain{}_nostrain.traj".format(T[0]), atoms=atoms)
first = True
nano_part = get_nanoparticle()
for temp in T:
print("Current temperature {}".format(T))
mc = FixedNucleusMC(
atoms, temp, network_name=["c2_01nn_0"],
network_element=["Mg", "Si"],
max_constraint_attempts=1E6)
backup = MCBackup(mc, overwrite_db_row=False, db_name="data/mc_solute_no_strain.db")
mc.attach(backup, interval=20000)
strain = get_strain_observer(mc)
mc.add_bias(strain)
if first:
first = False
#mc.grow_cluster({"Mg": 1000, "Si": 1000})
symbs = insert_nano_particle(atoms.copy(), nano_part)
mc.set_symbols(symbs)
tag_by_layer_type(mc.atoms)
cnst = ConstrainElementByTag(atoms=mc.atoms, element_by_tag=[["Mg", "Al"], ["Si", "Al"]])
mc.add_constraint(cnst)
#mc.build_chain({"Mg": 500, "Si": 500})
fix_layer = FixEdgeLayers(thickness=5.0, atoms=mc.atoms)
mc.add_constraint(fix_layer)
mc.attach(snapshot, interval=20000)
mc.runMC(steps=19000, init_cluster=False)
def run(N, use_bias):
#network_name=["c2_4p050_3", "c2_2p864_2"]
bc = init_bc(N)
mc = FixedNucleusMC(
bc.atoms, T, network_name=["c2_2p864_2"],
network_element=["Mg", "Si"], mpicomm=comm,
max_constraint_attempts=1E6)
#mc.max_allowed_constraint_pass_attempts = 1
nanop = get_nanoparticle()
symbs = insert_nano_particle(bc.atoms.copy(), nanop)
mc.set_symbols(symbs)
mc.init_cluster_info()
formula = "(I1+I2)/(2*I3)" # Needle
#formula = "2*I1/(I2+I3)" # Plate
inert_init = InertiaCrdInitializer(
fixed_nucl_mc=mc, matrix_element="Al", cluster_elements=["Mg", "Si"],
formula=formula)
inert_rng_constraint = InertiaRangeConstraint(
fixed_nuc_mc=mc, inertia_init=inert_init, verbose=True)
if use_bias:
bias = InertiaBiasPotential.load(fname=inertia_bias_file)
bias.inertia_range = inert_rng_constraint
mc.add_bias(bias)
nsteps = 100000
if rank == 0:
snap = Snapshot(atoms=bc.atoms, trajfile="{}/inertia.traj".format(workdir))
mc.attach(snap, interval=100000)
# reac_path = ReactionPathSampler(
# mc_obj=mc, react_crd=[0.05, 0.9], react_crd_init=inert_init,
# react_crd_range_constraint=inert_rng_constraint, n_windows=30,
# n_bins=10, data_file=h5file)
# reac_path.run(nsteps=nsteps)
# reac_path.save()
inert_rng_constraint.range = [0.0, 0.9]
fix_layer = FixEdgeLayers(thickness=5.0, atoms=mc.atoms)
mc.add_constraint(inert_rng_constraint)
mc.add_constraint(fix_layer)
reac_path = AdaptiveBiasReactionPathSampler(
mc_obj=mc, react_crd=[0.0, 0.9], react_crd_init=inert_init,
n_bins=100, data_file="{}/adaptive_bias.h5".format(workdir),
mod_factor=1E-5, delete_db_if_exists=True, mpicomm=None,
db_struct="{}/adaptive_bias_struct.db".format(workdir))
reac_path.run()
reac_path.save()