def test_bet(self):
# Carbon black reference material isotherm (N2 at 77K)
Qads = np.array([
4.39005, 4.67017, 4.79068, 4.9767, 5.14414, 5.31144, 5.47106,
5.63297, 5.80559, 5.96663, 6.13574, 6.31214, 6.49764, 6.67154,
6.85255, 7.04053, 7.22571, 7.40778, 7.59634, 7.7832, 7.96568,
8.1623, 8.34863, 8.54383, 8.74695, 8.94871, 9.16214, 9.38208,
9.61289, 9.8577, 10.12, 10.397, 10.6852, 11.0089, 11.3574, 11.7373,
12.1611, 12.6289, 13.1794, 13.819, 14.57, 15.4858, 16.6535, 18.2409
])
Prel = np.array([
0.0433547, 0.0672921, 0.0796994, 0.0999331, 0.119912, 0.140374,
0.159884, 0.179697, 0.200356, 0.219646, 0.239691, 0.259671,
0.280475, 0.299907, 0.320048, 0.340746, 0.360882, 0.380708,
0.400956, 0.421168, 0.440603, 0.460924, 0.480902, 0.500572,
0.521144, 0.540715, 0.560852, 0.580887, 0.600803, 0.62089, 0.64084,
0.66093, 0.68071, 0.70082, 0.72096, 0.74084, 0.76081, 0.78045,
0.80084, 0.82107, 0.84075, 0.86069, 0.88041, 0.90023
])
pmin = 0.05
pmax = 0.3
r = bet.bet(Prel, Qads, Pmin=pmin, Pmax=pmax, csa=0.162)
np.testing.assert_almost_equal(r.sa, 20.7049, 3)
np.testing.assert_almost_equal(r.sa_err, 0.0289, 4)
np.testing.assert_almost_equal(r.C, 149.959660, 2)
np.testing.assert_almost_equal(r.q_m, 4.7569, 4)
Pfit, Qfit = util.restrict_isotherm(Prel, Qads, pmin, pmax)
roq = bet.Isotherm2RoquerolBET(Pfit, Qfit)
np.testing.assert_almost_equal(roq[0], 4.3559, 4)
np.testing.assert_almost_equal(roq[6], 4.62074, 4)
def test_bet(self):
# Carbon black reference material isotherm (N2 at 77K)
Qads = np.array([4.39005, 4.67017, 4.79068, 4.9767, 5.14414, 5.31144,
5.47106, 5.63297, 5.80559, 5.96663, 6.13574, 6.31214,
6.49764, 6.67154, 6.85255, 7.04053, 7.22571, 7.40778,
7.59634, 7.7832, 7.96568, 8.1623, 8.34863, 8.54383,
8.74695, 8.94871, 9.16214, 9.38208, 9.61289, 9.8577,
10.12, 10.397, 10.6852, 11.0089, 11.3574, 11.7373,
12.1611, 12.6289, 13.1794, 13.819, 14.57, 15.4858,
16.6535, 18.2409])
Prel = np.array([0.0433547, 0.0672921, 0.0796994, 0.0999331, 0.119912,
0.140374, 0.159884, 0.179697, 0.200356, 0.219646,
0.239691, 0.259671, 0.280475, 0.299907, 0.320048,
0.340746, 0.360882, 0.380708, 0.400956, 0.421168,
0.440603, 0.460924, 0.480902, 0.500572, 0.521144,
0.540715, 0.560852, 0.580887, 0.600803, 0.62089,
0.64084, 0.66093, 0.68071, 0.70082, 0.72096, 0.74084,
0.76081, 0.78045, 0.80084, 0.82107, 0.84075, 0.86069,
0.88041, 0.90023])
pmin = 0.05
pmax = 0.3
r = bet.bet(Prel, Qads, Pmin = pmin, Pmax = pmax, csa=0.162)
np.testing.assert_almost_equal( r.sa, 20.7049, 3 )
np.testing.assert_almost_equal( r.sa_err, 0.0289, 4 )
np.testing.assert_almost_equal( r.C, 149.959660, 2 )
np.testing.assert_almost_equal( r.q_m, 4.7569, 4 )
Pfit, Qfit = util.restrict_isotherm(Prel,Qads,pmin,pmax)
roq = bet.Isotherm2RoquerolBET(Pfit,Qfit )
np.testing.assert_almost_equal( roq[0], 4.3559, 4 )
np.testing.assert_almost_equal( roq[6], 4.62074, 4 )
def test_bet(self):
Qads = np.array([4.67017, 4.79068, 4.9767, 5.14414, 5.31144, 5.47106,
5.63297, 5.80559, 5.96663, 6.13574, 6.31214, 6.49764,
6.67154])
Prel = np.array([0.0672921, 0.0796994, 0.0999331, 0.119912, 0.140374,
0.159884, 0.179697, 0.200356, 0.219646, 0.239691,
0.259671, 0.280475, 0.299907])
r = bet.bet(Qads, Prel, csa=0.162)
np.testing.assert_almost_equal( r.sa, 20.7049, 4 )
np.testing.assert_almost_equal( r.sa_err, 0.0289, 4 )
np.testing.assert_almost_equal( r.C, 149.959660, 2 )
np.testing.assert_almost_equal( r.q_m, 4.7569, 4 )
roq = bet.Isotherm2RoquerolBET(Qads, Prel)
np.testing.assert_almost_equal( roq[0], 4.3559, 4 )
np.testing.assert_almost_equal( roq[6], 4.62074, 4 )
from micromeritics import tplot, bet, thickness, util, plots
from micromeritics import isotherm_examples as ex
# Setup the raw data for the calculation.
# using example isotherm data from Silica Alumina analyzed with N2.
s = ex.silica_alumina()
# Compute the BET surface area for this sample
# using the range 0.05 to 0.30, and the Cross-sectional area
# for Nitrogen 0.162
BET_calc = bet.bet(s.Prel, s.Qads, Pmin = 0.05, Pmax = 0.3 , csa = 0.162)
# Do the tplot calculation.
TP_calc = tplot.tplot(s.Prel, s.Qads, thickness.HarkinsJura(),
tmin = 3.0, tmax = 5.0,
dcf = 0.0015468, sacf = 1.0, sa = BET_calc.sa )
plots.plotTPlot( TP_calc )
plots.show()
# Show the results of the tplot calculation.
print("Micropore Volume: %.4f cm^3/g" % TP_calc.mv)
print("Micropore Area: %.4f m^2/g" % TP_calc.ma)
print("External surface area: %.4f" % TP_calc.ext_sa)
print("Total surface area (BET): %.4f" % TP_calc.tot_sa)
from micromeritics import tplot, bet, thickness, util, plots
from micromeritics import isotherm_examples as ex
# Setup the raw data for the calculation.
# using example isotherm data from Silica Alumina analyzed with N2.
s = ex.silica_alumina()
# Compute the BET surface area for this sample
# using the range 0.05 to 0.30, and the Cross-sectional area
# for Nitrogen 0.162
BET_calc = bet.bet(s.Prel, s.Qads, Pmin=0.05, Pmax=0.3, csa=0.162)
# Do the tplot calculation.
TP_calc = tplot.tplot(s.Prel,
s.Qads,
thickness.HarkinsJura(),
tmin=3.0,
tmax=5.0,
dcf=0.0015468,
sacf=1.0,
sa=BET_calc.sa)
plots.plotTPlot(TP_calc)
plots.show()
# Show the results of the tplot calculation.
print("Micropore Volume: %.4f cm^3/g" % TP_calc.mv)
print("Micropore Area: %.4f m^2/g" % TP_calc.ma)
print("External surface area: %.4f" % TP_calc.ext_sa)
print("Total surface area (BET): %.4f" % TP_calc.tot_sa)