def strip_eloss(self, strip_int):
if (self.E <= 0.0):
self.E = 0.0
return 0.0
else:
beam_trim = TRIM(target,
Ion(self.title,
energy=self.E * 1.0e6,
mass=self.M),
number_ions=num_ions,
calculation=1)
beam_results = beam_trim.run(srim_executable_directory)
beam_energy = beam_results.ioniz.ions * 100
beam_depth = beam_results.ioniz.depth * 1e-8
f = interp1d(beam_depth, beam_energy, kind='linear')
xnew = np.linspace(0.0157, 1.57, 100)
ynew = f(xnew)
eloss = integrate.quad(f, 0.0157, 1.57)[0]
self.E = self.E - eloss
self.strip[strip_int] = eloss
return eloss
def create_ion_list(
ion_name: Literal['H', 'He', 'Li'],
energy_list: Union[Sequence[int], Set[int]],
units: Literal['ev', 'kev', 'mev'],
) -> List[Ion]:
ion_list = [Ion(f'{ion_name}', energy=x * 1000)
for x in energy_list] # sourcery skip
return ion_list
def plot_bragg(self):
target = Target([setlayer(target_gas, gas_pressure, 2.8e9)])
beam_trim = TRIM(target,
Ion(self.title,
energy=self.E_init * 1.0e6,
mass=self.M),
number_ions=250,
calculation=1)
beam_results = beam_trim.run(srim_executable_directory)
beam_energy = beam_results.ioniz.ions * 100
beam_depth = beam_results.ioniz.depth * 1e-8
f = interp1d(beam_depth, beam_energy, kind='linear')
xnew = np.linspace(0.28, 28.0, 100)
ynew = f(beam_depth)
plt.plot(beam_depth * 0.60714285714, ynew)
def dead_eloss(self):
beam_trim = TRIM(dead,
Ion(self.title,
energy=self.E * 1.0e6,
mass=self.M),
number_ions=num_ions,
calculation=1)
beam_results = beam_trim.run(srim_executable_directory)
beam_energy = beam_results.ioniz.ions * 100
beam_depth = beam_results.ioniz.depth * 1e-8
f = interp1d(beam_depth, beam_energy, kind='linear')
xnew = np.linspace(0.0230251, 2.30251, 100)
ynew = f(xnew)
eloss = integrate.quad(f, 0.0230251, 2.30251)[0]
self.E = self.E - eloss
return eloss
def window_eloss(self):
beam_trim = TRIM(window,
Ion(self.title,
energy=self.E * 1.0e6,
mass=self.M),
number_ions=num_ions,
calculation=1)
beam_results = beam_trim.run(srim_executable_directory)
beam_energy = beam_results.ioniz.ions * 100
beam_depth = beam_results.ioniz.depth * 1e-8
print(beam_depth)
f = interp1d(beam_depth, beam_energy, kind='linear')
xnew = np.linspace(6.00010e-06, 6.00000e-04, 100)
ynew = f(xnew)
eloss = integrate.quad(f, 6.00010e-06, 6.00000e-04)[0]
self.E = self.E - eloss
return eloss
'E_d': Ed_enery_postrior, # Displacement Energy [eV]
'lattice': 0.0,
'surface': 3.0
}}, density=8.9, width=20000.0)
# Construct a target of a single layer of Nickel
target = Target([layer])
return target
#*************************************************************************************
# Simulator Setting
# Construct a 3MeV Nickel ion
# TRIM.copy_output_files('c:/SRIM-Pro', 'c:/SRIM-Pro/SRIM Outputs')
# Specify the directory of SRIM.exe
srim_executable_directory = 'c://SRIM-Pro'
# ION Type and Energy and Mass
ion = Ion('Ni', energy=3.0e6)
# Construct a layer of nick 20um thick with a displacement energy of 30 eV
# Parameters to be optimized
E_d_prior = 30.0 # Displacement Energy [eV]
number_of_IONs = 50
# PRIOR for Parameter to be Optimized
prior = D.Uniform(E_d_prior-3, E_d_prior+3)
# Architecture definitions for Ratio Estimator - Neural Network
activation = torch.nn.ELU
layers = [64, 64, 64]
inputs_shape = (7,)
outputs_shape = (1,)
cmpd_ceo2_dict = {
'Ce': {
'stoich': 1.0,
**elem_ce_dict
},
'O': {
'stoich': 2.0,
**elem_o_dict
},
}
energy__kev_list = [
100, 150, 200, 250, 300, 400, 500, 600, 700, 800, 900, 1000
]
ion_Ni = Ion('Ni', energy=3.0e6)
ions_He_list = [Ion('He', energy=x * 1000) for x in energy__kev_list]
# print(ion.symbol, ion.name)
# print(ion.energy)
# Construct layers
layer_Ni = Layer(
{'Ni': {
'stoich': 1.0,
'E_d': 30.0,
'lattice': 0.0,
'surface': 3.0
}},
density=8.9,
width=20_000.0,
name='Ni')
# use a 0.5 mm sapphire layer as the bottom "substrate"
Al2O3 = Layer(
{"Al": {"stoich": 2.0}, "O": {"stoich": 3.0},},
density=3.95,
width=50000.0,
name="Al2O3",
)
layers.append(Al2O3)
# construct the mulitlayer target using the layers list
target = Target(layers)
# loop over implantation energies
for E_eV in Energy_eV:
# Construct the implanted 8Li ion
ion = Ion("Li", energy=E_eV, mass=m_8Li)
# Initialize a TRIM calculation with the ion & target
trim = TRIM(
target,
ion,
calculation=2,
number_ions=N_Ions,
description="%.0f eV 8Li implanted in heterostructure" % E_eV,
# reminders="",
# autosave=1000,
plot_mode=5,
# plot_xmin=0,
# plot_xmax=0,
ranges=True,
backscattered=True,
transmit=True,