In [1]:
from models import TwoComponentBindingModel
from pylab import *
import numpy
In [9]:
# Compound 8 [082213b11.itc]
# Our measured enthalpy parameters from ITC
DeltaH = -14.02 # kcal/mol
DeltaH_0 = 0.30e-6; # cal/mol/uL
# Lyle's measured DeltaG from NMR
DeltaG = -11.96 # kcal/mol
L_purity = 0.975;
P_purity = 0.975;
Ls = 0.808e-3 # titrant concentration (M) - guest - uncorrected for purity
P0 = 0.801e-3 # sample cell concentration (M) - host - uncorrected for purity
DeltaVn = numpy.array([0.1, 0.2, 0.4, 0.8, 1.6, 3.2, 6.4, 12.8]) * 1.0e-6 # injection volumes (L)
q_n_observed = numpy.array([
0.79295,
1.89536,
3.99292,
7.84439,
15.89120,
31.98229,
63.71221,
125.13223]) * 1.0e-6 # calories, 082213b11 integrated heats from exponential baseline fit
N = DeltaVn.size # number of injections
temperature = 298 # temperature (K)
V0 = 0.2028e-3 # volume of sample cell (L)
model = TwoComponentBindingModel(Ls, P0, q_n_observed, DeltaVn, temperature, V0)
In [10]:
q_n = model.expected_injection_heats(P0, Ls, DeltaG, DeltaH, DeltaH_0, q_n_observed)
In [11]:
plot(q_n_observed * 1e6, 'ko', q_n * 1e6, 'ro');
xlabel('injection');
ylabel('injection heat ($\mu$cal)');
legend(['observed', 'model'], 'upper left')
axis([-0.5, 8, -10, 200]);
In [5]:
# Use our measured enthalpy with both our DeltaG and Lyle's
DeltaH = -14.02 # kcal/mol - DeltaH from JDC Bayesian analysis
q_n_1 = model.expected_injection_heats(P0, Ls, -5.68, DeltaH, DeltaH_0, q_n_observed)
q_n_2 = model.expected_injection_heats(P0, Ls, -11.97, DeltaH, DeltaH_0, q_n_observed)
plot(q_n_observed * 1e6, 'ko', q_n_1 * 1e6, 'ro', q_n_2 * 1e6, 'bo');
legend(['observed', 'JDC', 'LI with JDC $\Delta H$'], 'upper left');
xlabel('injection');
ylabel('injection heat ($\mu$cal)');
axis([-0.5, 8, -10, 200]);
In [6]:
DeltaH = -10.80 # kcal/mol
q_n_1 = model.expected_injection_heats(P0, Ls, -5.68, DeltaH, DeltaH_0, q_n_observed)
q_n_2 = model.expected_injection_heats(P0, Ls, -11.97, DeltaH, DeltaH_0, q_n_observed)
plot(q_n_observed * 1e6, 'ko', q_n_1 * 1e6, 'ro', q_n_2 * 1e6, 'bo');
legend(['observed', 'JDC', 'LI with JDC $\Delta H$'], 'upper left');
xlabel('injection');
ylabel('injection heat ($\mu$cal)');
axis([-0.5, 8, -10, 200]);
In [7]:
# Try to see if we can get the Lyle Isaacs data to fit by tweaking the enthalpy
DeltaH = -10.00 # kcal/mol
q_n_2 = model.expected_injection_heats(P0, Ls, -11.97, DeltaH, DeltaH_0, q_n_observed)
plot(q_n_observed * 1e6, 'ko', q_n_2 * 1e6, 'rs');
legend(['observed', 'LI with JDC $\Delta H$'], 'upper left');
xlabel('injection');
ylabel('injection heat ($\mu$cal)');
axis([-0.5, 8, -10, 200]);
In [8]:
(q_n_observed + q_n_2) * 1e6
Out[8]:
In [8]: