def simSonoraSpc(tAl2O3, e0, det, wkDst=5, lt=100, pc=1, nTraj=1000, xtraParams={}):
"""simSonoraSpc(tAl2O3, e0, det, wkDst=5, lt=100, pc=1, nTraj=1000, xtraParams={})
Simulate a spectrum from tAl2O3 nm of Al2O3 on Al recoreed at
e0 kV using the DTSA detector det and a wkDst mm working distance for
lt sec with a probe current of pc nA. Compute nTraj trajectories."""
tAl = 100 # um
al2o3 = dt2.material("Al2O3",density=3.95)
al = dt2.material("Al", density=2.70)
lAl2O3 = [al2o3, tAl2O3*1.0e-9]
lAl = [al, tAl*1.0e-6]
lay = [lAl2O3, lAl]
sNam = "%g-nm-Al2O3-on-Al-%g-kV" % (tAl2O3, e0)
spc = dt2.wrap(mc3.multiFilm(lay, det, e0, True, nTraj, lt*pc, True, True, xtraParams))
props=spc.getProperties()
props.setTextProperty(epq.SpectrumProperties.SpectrumDisplayName, sNam)
props.setNumericProperty(epq.SpectrumProperties.LiveTime, lt)
props.setNumericProperty(epq.SpectrumProperties.FaradayBegin, pc)
props.setNumericProperty(epq.SpectrumProperties.BeamEnergy, e0)
props.setNumericProperty(epq.SpectrumProperties.WorkingDistance, wkDst)
return(spc)
def simNiCuPetSpc(tNi, tCu, e0, det, wkDst=17, lt=100, pc=1, nTraj=1000):
"""simNiCuPetSpc(tNi, tCu, e0, det, wkDst=17, lt=100, pc=1, nTraj=1000)
Simulate a spectrum from tNi nm of Ni on tCu nm of Cu on PET recoreded at
e0 kV using the DTSA detector det and a wkDst mm working distance for
lt sec with a probe current of pc nA. Compute nTraj trajectories."""
tPET = 76 # um
pet = dt2.material("C10H8O4",density=1.37)
cu = dt2.material("Cu", density=8.96)
ni = dt2.material("Ni", density=8.90)
lNi = [ni, tNi*1.0e-9]
lCu = [cu, tCu*1.0e-9]
lPET = [pet, tPET*1.0e-6]
lay = [lNi, lCu, lPET]
sNam = "%g-nm-Ni-%g-nm-Cu-on-PET-%g-kV" % (tNi, tCu, e0)
spc = dt2.wrap(mc3.multiFilm(lay, det, e0, True, nTraj, lt*pc, True, True))
props=spc.getProperties()
props.setTextProperty(epq.SpectrumProperties.SpectrumDisplayName, sNam)
props.setNumericProperty(epq.SpectrumProperties.LiveTime, lt)
props.setNumericProperty(epq.SpectrumProperties.FaradayBegin, pc)
props.setNumericProperty(epq.SpectrumProperties.BeamEnergy, e0)
props.setNumericProperty(epq.SpectrumProperties.WorkingDistance, wkDst)
return(spc)
def fullSimBulkStd(mat,
ctg,
ctgThickNm,
det,
e0,
nTraj,
outPath,
dim=5.0e-6,
lt=100,
pc=1.0,
emiSize=512,
ctd=False):
"""
fullSimBulkStd(mat, ctg, ctgThickNm, det, e0, nTraj, outPath,
dim=5.0e-6, lt=100, pc=1.0, emiSize=512, ctd=False)
Use mc3 simulation to simulate an uncoated standard specimen
Parameters
----------
mat - a dtsa material.
Note the material must have an associated density. It should
have a useful name.
ctg - a dtsa2 material for the coating
det - a dtsa detector
Here is where we get the detector properties and calibration
e0 - float
The accelerating voltage in kV
nTraj - integer
The number of trajectories to run
outPath - string
The path to the directory for output
dim - float (5.0e-6)
The size of the emission images
lt - integer (100)
The live time (sec)
pc - float (1.0)
The probe current in nA
emiSize - int (default 512)
The width and depth of the emission images.
ctd - Boolean (False) - is C coated
Returns
-------
sim - DTSA scriptable spectrum
The simulated standard spectrum
Example
-------
import dtsa2 as dtsa2
import dtsa2.jmMC3 as jm3
outPath = "path/to/yours/spc"
cu = material("Cu", density=8.92)
det = findDetector("Si(Li)")
a = fullSimBulkStd(cu, det, 15.0, 100, outPath,
dim=5.0e-6, lt=100,
pc=1.0, emiSize=512, ctd=False)
a.display()
"""
start = time.time()
strCtg = ctg.getName()
strMat = mat.getName()
dose = pc * lt # na-sec"
# specify the transitions to generate
xrts = []
trs = mc3.suggestTransitions(mat, e0)
for tr in trs:
xrts.append(tr)
trs = mc3.suggestTransitions(ctg, e0)
for tr in trs:
xrts.append(tr)
# At 20 kV the images are best at 2.0e-6
xtraParams = {}
xtraParams.update(mc3.configureXRayAccumulators(xrts, True, True, True))
# note that the image size on the specimen is in meters...
xtraParams.update(mc3.configureEmissionImages(xrts, 2.0e-6, 512))
xtraParams.update(mc3.configurePhiRhoZ(2.0e-6))
xtraParams.update(mc3.configureTrajectoryImage(2.0e-6, 512))
xtraParams.update(mc3.configureVRML(nElectrons=100))
xtraParams.update(mc3.configureOutput(outPath))
print("Output sent to %s") % (outPath)
layers = [[ctg, ctgThickNm * 1.0e-9], [mat, 1.0e-3]]
sim = mc3.multiFilm(layers,
det,
e0,
withPoisson=True,
nTraj=nTraj,
dose=dose,
sf=True,
bf=True,
xtraParams=xtraParams)
sName = "%g-nm-%s-on-%s-%g-kV" % (ctgThickNm, strCtg, strMat, e0)
sim.rename(sName)
sim.setAsStandard(mat)
sim.display()
end = time.time()
delta = end - start
msg = "This simulation required %.f sec" % (delta)
print(msg)
msg = " %.f min" % (delta / 60.0)
print(msg)
msg = " %.f hr" % (delta / 360.0)
print("")
return (sim)
xtraParams = {}
xtraParams.update(mc3.configurePhiRhoZ(przDepUm * 1.0e-6))
xtraParams.update(mc3.configureXRayAccumulators(xrts, True, True, True))
# note that the image size on the specimen is in meters...
xtraParams.update(mc3.configureEmissionImages(xrts, imgSzUm * 1.0e-6, imgSize))
xtraParams.update(mc3.configureTrajectoryImage(imgSzUm * 1.0e-6, imgSize))
xtraParams.update(mc3.configureVRML(nElectrons=vmrlEl))
xtraParams.update(mc3.configureOutput(simDir))
print(xtraParams)
fmtS = "%g-nm-C-on-EagleXG-at-%g-kV"
print("Starting simulation")
multiLaySim = mc3.multiFilm(layers, det, e0, True, nTraj, dose, True, True,
xtraParams)
sName = fmtS % (tCNm, e0)
multiLaySim.rename(sName)
multiLaySim.setAsStandard(eagleXG)
multiLaySim.display()
fi = spcDir + "/"
fi += sName
fi += "-%g-Traj.msa" % (nTraj)
multiLaySim.save(fi)
# clean up cruft
shutil.rmtree(rptDir)
print "Done!"
end = time.time()
delta = (end - start) / 60
lPISiuc = [] # an array for Si peak integral uncertainty
iCount = 0
for tNmC in lThickC:
if tNmC == 0:
layers = [[si, 50.0e-6]]
else:
layers = [[c, tNmC * 1.0e-9], [si, 50.0e-6]]
spc = mc3.multiFilm(layers,
det,
e0,
withPoisson=True,
nTraj=nTraj,
dose=dose,
sf=True,
bf=True,
xtraParams={})
if tNmC < 1:
sName = "Si-%g-kV" % (e0)
spcNa = "Si"
else:
sName = "%g-nm-C-on-Si-%g-kV" % (tNmC, e0)
spcNa = "%g nm C on Si" % (tNmC)
spc.rename(spcNa)
res = anaCSi(spc, det, digits=2, display=True)
cI = res["C"]
#
# K496 Sim
#
layers = [[c, 2.0e-9], [k496, 50.0e-6]]
# multiFilm(layers, det, e0=20.0, withPoisson=True,
# nTraj=defaultNumTraj, dose=defaultDose,
# sf=defaultCharFluor, bf=defaultBremFluor,
# xtraParams=defaultXtraParams)
k496Sim = mc3.multiFilm(layers,
det,
e0,
withPoisson=True,
nTraj=nTraj,
dose=dose,
sf=True,
bf=True,
xtraParams={})
sName = "%g-nm-C-on-K496" % tNmC
k496Sim.rename(sName)
k496Sim.setAsStandard(k496)
k496Sim.display()
fi = spcDir + "/"
fi += sName
fi += "-%g-Traj.msa" % (nTraj)
k496Sim.save(fi)
# K-497 Sim
layers = [[c, 2.0e-9], [k497, 50.0e-6]]
lPISimu = [] # an array for mean Si peak integral
lPISiuc = [] # an array for Si peak integral uncertainty
iCount = 0
for tNmC in lThickC:
if tNmC == 0:
layers = [ [si, 50.0e-6] ]
else:
layers = [ [c, tNmC*1.0e-9],
[si, 50.0e-6]
]
spc = mc3.multiFilm(layers, det, e0, withPoisson=True, nTraj=nTraj,
dose=dose, sf=True, bf=True, xtraParams={})
if tNmC < 1:
sName = "Si-%g-kV" % (e0)
spcNa = "Si"
else:
sName = "%g-nm-C-on-Si-%g-kV" % (tNmC, e0)
spcNa = "%g nm C on Si" % (tNmC)
spc.rename(spcNa)
res = anaCSi(spc, det, digits=2, display=True)
cI = res["C"]
siI = res["Si"]
lPICmu.append(cI[0])
lPICuc.append(cI[1])
lPISimu.append(siI[0])
epq.Composition([epq.Element.Au, epq.Element.Pd], [0.60, 0.40]),
epq.ToSI.gPerCC(0.6 * 19.30 + 0.4 * 11.9))
ta = material("Ta", density=16.4)
layers = [[sio2, tNmSiO2 * 1.0e-9], [c, 50.0e-6]]
# multiFilm(layers, det, e0=20.0, withPoisson=True,
# nTraj=defaultNumTraj, dose=defaultDose,
# sf=defaultCharFluor, bf=defaultBremFluor,
# xtraParams=defaultXtraParams)
basSim = mc3.multiFilm(layers,
det,
e0,
withPoisson=True,
nTraj=nTraj,
dose=dose,
sf=True,
bf=True,
xtraParams={})
sName = "%g nm SiO2 on C" % tNmSiO2
basSim.rename(sName)
basSim.display()
fi = spcDir + "/%g-nm-SiO2-on-Si-%g-kV-%g-Traj.msa" % (tNmSiO2, e0, nTraj)
basSim.save(fi)
layers = [[aupd, tNmAuPd * 1.0e-9], [sio2, tNmSiO2 * 1.0e-9], [c, 50.0e-6]]
aupdCtd = mc3.multiFilm(layers,
det,
def simCarbonCoatedStd(mat, det, e0, nTraj, lt=100, pc=1.0, tc=20.0):
"""simCarbonCoatedStd(mat, det, e0, nTraj, lt=100, pc=1.0, tc=20.0)
Use mc3 multilayer simulation to simulate a C-ctd standard specimen
Parameters
----------
mat - a dtsa material.
Note the material must have an associated density. It should have a useful name.
det - a dtsa detector
Here is where we get the detector properties and calibration
e0 - float
The accelerating voltage in kV
nTraj - integer
The number of trajectories to run
lt - integer (100)
The live time (sec)
pc - float (1.0)
The probe current in nA
tc - float (20.0)
C thickness in nm
Returns
-------
sim - DTSA scriptable spectrum
The simulated standard spectrum
Example
-------
import dtsa2.jmMC3 as jm3
det = findDetector("Si(Li)")
mgo = material("MgO", density=3.58)
a = jm3.simCarbonCoatedStd(mgo, det, 20.0, 100, 100, 1.0, 20.0)
a.display()
"""
dose = pc * lt # na-sec"
c = dt2.material("C", density=2.1)
layers = [[c, tc * 1.0e-9], [mat, 50.0e-6]]
xrts = []
trs = mc3.suggestTransitions(c, e0)
for tr in trs:
xrts.append(tr)
trs = mc3.suggestTransitions(mat, e0)
for tr in trs:
xrts.append(tr)
xtraParams = {}
xtraParams.update(mc3.configureXRayAccumulators(xrts, True, True, True))
sim = mc3.multiFilm(layers,
det,
e0,
withPoisson=True,
nTraj=nTraj,
dose=dose,
sf=True,
bf=True,
xtraParams=xtraParams)
sName = "%g-nm-C-on-%s-%g-kV-%g-Traj" % (tc, mat, e0, nTraj)
sim.rename(sName)
sim.setAsStandard(mat)
return sim
def sim_amc_coated_mat(mat, det, e0, nTraj, lt=100, pc=1.0, tc=20.0):
"""sim_amc_coated_mat(mat, det, e0, nTraj, lt=100, pc=1.0, tc=20.0)
Use mc3 multilayer simulation to simulate an am-C-ctd specimen
Parameters
----------
mat - a dtsa material.
Note the material must have an associated density. It should have a useful name.
det - a dtsa detector
Here is where we get the detector properties and calibration
e0 - float
The accelerating voltage in kV
nTraj - integer
The number of trajectories to run
lt - integer (100)
The live time (sec)
pc - float (1.0)
The probe current in nA
tc - float (20.0)
C thickness in nm
Returns
-------
sim - DTSA scriptable spectrum
The simulated spectrum
Example
-------
import dtsa2.jmMC3 as jm3
det = findDetector("Oxford p4 05eV 2K")
si = material("Si", density=2.3296)
a = jm3.simCarbonCoatedStd(mgo, det, 20.0, 100, 100, 1.0, 20.0)
a.display()
"""
dose = pc * lt # na-sec"
amc = material("C", density=1.35)
amcThickComment = "amC Thickness = %g nm %g trajectories" % (tc, nTraj)
layers = [ [amc, tc*1.0e-9],
[mat, 50.0e-6]
]
xrts = []
trs = mc3.suggestTransitions(amc, e0)
for tr in trs:
xrts.append(tr)
trs = mc3.suggestTransitions(mat, e0)
for tr in trs:
xrts.append(tr)
xtraParams={}
xtraParams.update(mc3.configureXRayAccumulators(xrts,True, True, True))
sim = mc3.multiFilm(layers, det, e0, withPoisson=True, nTraj=nTraj,
dose=dose, sf=True, bf=True, xtraParams=xtraParams)
sName = "%g-nm-amC-on-%s-%g-kV" % (tc, mat, e0)
sim.rename(sName)
sim.getProperties().setTextProperty(epq.SpectrumProperties.SpectrumComment, amcThickComment)
return sim
xtraParams = {}
xtraParams.update(mc3.configurePhiRhoZ(przDepUm * 1.0e-6, resln))
xtraParams.update(mc3.configureXRayAccumulators(xrts, True, True, True))
# note that the image size on the specimen is in meters...
xtraParams.update(mc3.configureEmissionImages(xrts, imgSzUm * 1.0e-6, imgSize))
xtraParams.update(mc3.configureTrajectoryImage(imgSzUm * 1.0e-6, imgSize))
xtraParams.update(mc3.configureVRML(nElectrons=vmrlEl))
xtraParams.update(mc3.configureOutput(simDir))
print(xtraParams)
k411Sim = mc3.multiFilm(layers,
det,
e0,
withPoisson=True,
nTraj=nTraj,
dose=dose,
sf=True,
bf=True,
xtraParams=xtraParams)
sName = "%g-nm-C-on-K411-%g-kV" % (tNmC, e0)
k411Sim.rename(sName)
k411Sim.setAsStandard(k411)
k411Sim.display()
fi = spcDir + "/" + sName + "-%g-Traj.msa" % (nTraj)
k411Sim.save(fi)
# Now apatite std
layers = [[c, tNmC * 1.0e-9], [apatite, 50.0e-6]]
def simCtdOxOnSi(det, e0, nTraj, lt=100, pc=1.0, tox = 10.0, tc=20.0):
"""
simCtdOxOnSi(det, e0, nTraj, lt=100, pc=1.0, tox = 10.0, tc=20.0)
Use mc3 multilayer simulation to simulate a C-ctd silicon specimen
with a native oxide layer.
det - a dtsa detector
Here is where we get the detector properties and calibration
e0 - float
The accelerating voltage in kV
nTraj - integer
The number of trajectories to run
lt - integer (100)
The live time (sec)
pc - float (1.0)
The probe current in nA
tox - float (10.0)
The thickness of the native oxide in nm
tc - float (20.0)
C thickness in nm
Returns
-------
sim - DTSA scriptable spectrum
The simulated spectrum
Example
-------
import dtsa2.jmMC3 as jm3
det = findDetector("Oxford p4 05eV 2K")
a = jm3.simCtdOxOnSi(det, 3.0, 100, 100, 1.0, 10.0, 20.0)
a.display()
"""
c = dt2.material("C", density=2.1)
si = dt2.material("Si", density=2.329)
sio2 = dt2.material("SiO2", density=2.65)
dose = pc * lt # na-sec"
layers = [ [ c, tc*1.0e-9],
[sio2, tox*1.0e-9],
[si, 50.0e-6] ]
xrts = []
trs = mc3.suggestTransitions(c, e0)
for tr in trs:
xrts.append(tr)
trs = mc3.suggestTransitions(sio2, e0)
for tr in trs:
xrts.append(tr)
xtraParams={}
xtraParams.update(mc3.configureXRayAccumulators(xrts,True, True, True))
sim = mc3.multiFilm(layers, det, e0, withPoisson=True, nTraj=nTraj,
dose=dose, sf=True, bf=True, xtraParams=xtraParams)
sName = "%g-nm-C-on-%g-nm-SiO2-on-Si-%g-kV-%g-Traj" % (tc, tox, e0, nTraj)
sim.rename(sName)
return sim
xrts.append(tr)
xtraParams={}
xtraParams.update(mc3.configurePhiRhoZ(przDepUm*1.0e-6, resln))
xtraParams.update(mc3.configureXRayAccumulators(xrts,True, True, True))
# note that the image size on the specimen is in meters...
xtraParams.update(mc3.configureEmissionImages(xrts, imgSzUm*1.0e-6, imgSize))
xtraParams.update(mc3.configureTrajectoryImage(imgSzUm*1.0e-6, imgSize))
xtraParams.update(mc3.configureVRML(nElectrons = vmrlEl))
xtraParams.update(mc3.configureOutput(simDir))
print(xtraParams)
k411Sim = mc3.multiFilm(layers, det, e0, withPoisson=True, nTraj=nTraj,
dose=dose, sf=True, bf=True, xtraParams=xtraParams)
sName = "%g-nm-C-on-K411-%g-kV" % (tNmC, e0)
k411Sim.rename(sName)
k411Sim.setAsStandard(k411)
k411Sim.display()
fi = spcDir + "/" + sName + "-%g-Traj.msa" % (nTraj)
k411Sim.save(fi)
# Now apatite std
layers = [ [c, tNmC*1.0e-9],
[apatite, 50.0e-6]
]
xrts = []
def simCoatedSubstrate(mat, ctg, thNm, det, e0, nTraj, lt=100, pc=1.0):
"""simCoatedSubstrate(mat, ctg, thNm, det, e0, nTraj, lt=100, pc=1.0)
Use mc3 multilayer simulation to simulate an coated substrate specimen
This ONLY generates a spectrum
Parameters
----------
mat - a dtsa material for the substrate.
Note the material must have an associated density.
It should have a useful name.
ctg - a dtsa material for the coating
thNm - coating thickness in nm
det - a dtsa detector
Here is where we get the detector properties and calibration
e0 - float
The accelerating voltage in kV
nTraj - integer
The number of trajectories to run
lt - integer (100)
The live time (sec)
pc - float (1.0)
The probe current in nA
tc - float (20.0)
C thickness in nm
Returns
-------
sim - DTSA scriptable spectrum
The simulated spectrum
Example
-------
import dtsa2 as dtsa2
import dtsa2.jmMC3 as jm3
det = findDetector("Si(Li)")
sio2 = material("SiO2", 2.65)
si = material("Si", 2.3296)
a = jm3.simCoatedSubstrate(si, sio2, 10.0, det, e0, nTraj, 100, 1.0)
a.display()
"""
dose = pc * lt # na-sec"
layers = [[ctg, thNm * 1.0e-9], [mat, 50.0e-6]]
xrts = []
trs = mc3.suggestTransitions(ctg, e0)
for tr in trs:
xrts.append(tr)
trs = mc3.suggestTransitions(mat, e0)
for tr in trs:
xrts.append(tr)
xtraParams = {}
xtraParams.update(mc3.configureXRayAccumulators(xrts, True, True, True))
sim = mc3.multiFilm(layers, det, e0, True, nTraj, dose, True, True,
xtraParams)
sName = "%g-nm-%s-on-%s-%g-kV" % (thNm, ctg, mat, e0)
sim.rename(sName)
return sim
xtraP = {}
xtraP = {"Characteristic Accumulator":True, "Char Fluor Accumulator":True, "Brem Fluor Accumulator":True}
# outpathoutPath = "/Users/jrminter/Documents/git/dtsa2Scripts/ben-buse/out/"
xtraP.update(mc3.configureOutput(outPath))
xtraP.update(mc3.configurePhiRhoZ(1.5*range))
xtraP.update(mc3.configureEmissionImages(trs, 1.5*range, size = 512))
xtraP.update(mc3.configureTrajectoryImage(1.5*range, size = 512))
resF = {}
for fil in film:
extension = str(film[fil][0])
extension = extension.replace("[","")
extension = extension.replace("]","")
extension = extension.replace(",","")
# pathloc = 'O:\Documents\PFE_Data\Users\Charles_Younes\\041115_CarbonInSteel\\dtsa2repeat7_' + extension # Change to output folder
xtraP.update(mc3.configureOutput(outPath))
print xtraP
resF[fil] = mc3.multiFilm(film[fil], det,e0=e0, nTraj=nE, dose=500.0, sf=True, bf=True,xtraParams=xtraP) # run simulations
tmp = str(resF[fil])
tmpx = extension + tmp
resF[fil].rename(tmpx)
resF[fil].save("%s/%s.msa" % ( outPath, resF[fil] )) # change outPath above to output folder ( location, name) it adds extension
resF[fil].display()
"""
def simCtdOxOnSi(det, e0, nTraj, lt=100, pc=1.0, tox=10.0, tc=20.0):
"""
simCtdOxOnSi(det, e0, nTraj, lt=100, pc=1.0, tox = 10.0, tc=20.0)
Use mc3 multilayer simulation to simulate a C-ctd silicon specimen
with a native oxide layer.
det - a dtsa detector
Here is where we get the detector properties and calibration
e0 - float
The accelerating voltage in kV
nTraj - integer
The number of trajectories to run
lt - integer (100)
The live time (sec)
pc - float (1.0)
The probe current in nA
tox - float (10.0)
The thickness of the native oxide in nm
tc - float (20.0)
C thickness in nm
Returns
-------
sim - DTSA scriptable spectrum
The simulated spectrum
Example
-------
import dtsa2.jmMC3 as jm3
det = findDetector("Si(Li)")
a = jm3.simCtdOxOnSi(det, 3.0, 100, 100, 1.0, 10.0, 20.0)
a.display()
"""
c = dt2.material("C", density=2.1)
si = dt2.material("Si", density=2.329)
sio2 = dt2.material("SiO2", density=2.65)
dose = pc * lt # na-sec"
layers = [[c, tc * 1.0e-9], [sio2, tox * 1.0e-9], [si, 50.0e-6]]
xrts = []
trs = mc3.suggestTransitions(c, e0)
for tr in trs:
xrts.append(tr)
trs = mc3.suggestTransitions(sio2, e0)
for tr in trs:
xrts.append(tr)
xtraParams = {}
xtraParams.update(mc3.configureXRayAccumulators(xrts, True, True, True))
sim = mc3.multiFilm(layers,
det,
e0,
withPoisson=True,
nTraj=nTraj,
dose=dose,
sf=True,
bf=True,
xtraParams=xtraParams)
sName = "%g-nm-C-on-%g-nm-SiO2-on-Si-%g-kV-%g-Traj" % (tc, tox, e0, nTraj)
sim.rename(sName)
return sim
lKAuL = []
# lKAuM=[]
# lists of Cu K-ratios
# lKCuL=[]
lKCuK = []
for i in range(nSteps):
tNmAu = tNmStep * float(i + 1)
print(tNmAu)
lNm.append(tNmAu)
sLay = [[au, tNmAu / 1.0e9], [cu, 100.0]]
sSpc = mc3.multiFilm(sLay,
det,
e0=e0,
withPoisson=True,
nTraj=nTraj,
dose=dose,
sf=charF,
bf=bremF,
xtraParams={})
sp = sSpc.getProperties()
sp.setTextProperty(epq.SpectrumProperties.SpectrumDisplayName,
"%g-nm-Au-on-Cu" % tNmAu)
sp.setNumericProperty(epq.SpectrumProperties.LiveTime, lt)
sp.setNumericProperty(epq.SpectrumProperties.FaradayBegin, dose)
sp.setNumericProperty(epq.SpectrumProperties.FaradayEnd, dose)
display(sSpc)
a = jmg.compKRs(sSpc, stds, trs, det, e0)
print(a[0])
print(a[1])
lKAuL.append(a[0])
def sim_amc_coated_mat(mat, det, e0, nTraj, lt=100, pc=1.0, tc=20.0):
"""sim_amc_coated_mat(mat, det, e0, nTraj, lt=100, pc=1.0, tc=20.0)
Use mc3 multilayer simulation to simulate an am-C-ctd specimen
Parameters
----------
mat - a dtsa material.
Note the material must have an associated density. It should have a useful name.
det - a dtsa detector
Here is where we get the detector properties and calibration
e0 - float
The accelerating voltage in kV
nTraj - integer
The number of trajectories to run
lt - integer (100)
The live time (sec)
pc - float (1.0)
The probe current in nA
tc - float (20.0)
C thickness in nm
Returns
-------
sim - DTSA scriptable spectrum
The simulated spectrum
Example
-------
import dtsa2.jmMC3 as jm3
det = findDetector("Oxford p4 05eV 2K")
si = material("Si", density=2.3296)
a = jm3.simCarbonCoatedStd(mgo, det, 5.0, 100, 100, 1.0, 20.0)
a.display()
"""
dose = pc * lt # na-sec"
amc = material("C", density=1.35)
amcThickComment = "amC Thickness = %g nm %g trajectories" % (tc, nTraj)
layers = [[amc, tc * 1.0e-9], [mat, 50.0e-6]]
xrts = []
trs = mc3.suggestTransitions(amc, e0)
for tr in trs:
xrts.append(tr)
trs = mc3.suggestTransitions(mat, e0)
for tr in trs:
xrts.append(tr)
xtraParams = {}
xtraParams.update(mc3.configureXRayAccumulators(xrts, True, True, True))
sim = mc3.multiFilm(layers,
det,
e0,
withPoisson=True,
nTraj=nTraj,
dose=dose,
sf=True,
bf=True,
xtraParams=xtraParams)
sName = "%g-nm-amC-on-%s-%g-kV" % (tc, mat, e0)
sim.rename(sName)
sim.getProperties().setTextProperty(epq.SpectrumProperties.SpectrumComment,
amcThickComment)
return sim
xtraParams.update(mc3.configurePhiRhoZ(przDepUm*1.0e-6))
xtraParams.update(mc3.configureXRayAccumulators(xrts,True, True, True))
# note that the image size on the specimen is in meters...
xtraParams.update(mc3.configureEmissionImages(xrts, imgSzUm*1.0e-6, imgSize))
xtraParams.update(mc3.configureTrajectoryImage(imgSzUm*1.0e-6, imgSize))
xtraParams.update(mc3.configureVRML(nElectrons = vmrlEl))
xtraParams.update(mc3.configureOutput(spcDir))
print(xtraParams)
layers = [ [raft, tNmRAFT*1.0e-9], # top layer of RAFT
[zno, tNmZnO*1.0e-9], # ZnO layer
[raft, tNmRAFT*1.0e-9], # bottom layer of RAFT
[si, 50.0e-6] # 50 micron (inf. thick Si substrate)
]
spc = mc3.multiFilm(layers, det, e0, True, nTraj,
dose, True, True, xtraParams)
strName = "%g-nm-RAFT-encapsulated-%g-nm-ZnO-on-Si-%g-kV"
spcName = strName % (tNmRAFT, tNmZnO, e0)
spc.rename(spcName)
spc.display()
# only save spectrum with > 500 traj
if nTraj > 500:
fi = spcDir + "/"
fi += spcName
fi += "-%g-Traj.msa" % (nTraj)
spc.save(fi)
sp.setNumericProperty(epq.SpectrumProperties.FaradayEnd, dose)
sp.setNumericProperty(epq.SpectrumProperties.BeamEnergy, e0)
sp.setCompositionProperty(epq.SpectrumProperties.StandardComposition, epq.Composition(epq.Element.Cu))
# display(cuSpc)
cuStd = {"El":element("Cu"), "Spc":cuSpc}
stds = [cStd, cuStd]
lNm=[]
lKCK=[]
lKCuL=[]
for i in range(500):
tNmC = float(i+1)
lNm.append(tNmC)
sLay = [[c, tNmC/1.0e9], [cu, 100.0]]
sSpc = mc3.multiFilm(sLay, det, e0=e0, withPoisson=True, nTraj=nTraj, dose=dose, sf=charF, bf=bremF, xtraParams={})
sp=sSpc.getProperties()
sp.setTextProperty(epq.SpectrumProperties.SpectrumDisplayName,"%g-nm-C-on-Cu"% tNmC)
sp.setNumericProperty(epq.SpectrumProperties.LiveTime, lt)
sp.setNumericProperty(epq.SpectrumProperties.FaradayBegin, dose)
sp.setNumericProperty(epq.SpectrumProperties.FaradayEnd, dose)
# display(sSpc)
a = jmg.compKRs(sSpc, stds, trs, det, e0)
lKCK.append(a[0])
lKCuL.append(a[1])
print (i+1)
# prepare the output file
csvPath = csvDir + "/sim-C-on-Cu-%gkV.csv" % e0
f=open(csvPath, 'w')
strLine = 'tNm, kCKa, kCuLa\n'
[0.60,0.40]),
epq.ToSI.gPerCC(0.6*19.30+0.4*11.9))
ta = material("Ta", density=16.4)
layers = [ [sio2, tNmSiO2*1.0e-9],
[c, 50.0e-6]
]
# multiFilm(layers, det, e0=20.0, withPoisson=True,
# nTraj=defaultNumTraj, dose=defaultDose,
# sf=defaultCharFluor, bf=defaultBremFluor,
# xtraParams=defaultXtraParams)
basSim = mc3.multiFilm(layers, det, e0, withPoisson=True, nTraj=nTraj,
dose=dose, sf=True, bf=True, xtraParams={})
sName = "%g nm SiO2 on C" % tNmSiO2
basSim.rename(sName)
basSim.display()
fi = spcDir + "/%g-nm-SiO2-on-Si-%g-kV-%g-Traj.msa" % (tNmSiO2, e0, nTraj)
basSim.save(fi)
layers = [ [aupd, tNmAuPd*1.0e-9],
[sio2, tNmSiO2*1.0e-9],
[c, 50.0e-6]
]
aupdCtd = mc3.multiFilm(layers, det, e0, withPoisson=True, nTraj=nTraj,
dose=dose, sf=True, bf=True, xtraParams={})
