Hi y’all, I am trying to do a BH3NH3 potential energy surface scan using a zmat of fixed symmetry, and I am running into problems. Here is the input file with no symmetry:
molecule bh3nh3 {
0 1
N
B 1 R
H 1 hn3 2 hnb3
H 2 hb4 1 hbn4 3 dih4
H 1 hn5 2 hnb5 4 dih5
H 2 hb6 1 hbn6 3 dih6
H 1 hn7 2 hnb7 4 dih7
H 2 hb8 1 hbn8 3 dih8
hn3 = 1.004382
hnb3 = 110.832
hb4 = 1.217824
hbn4 = 104.478
dih4 = -59.966
hn5 = 1.004489
hnb5 = 110.744
dih5 = 59.986
hb6 = 1.217435
hbn6 = 104.504
dih6 = -179.955
hn7 = 1.004416
hnb7 = 110.900
dih7 = 179.970
hb8 = 1.217541
hbn8 = 104.533
dih8 = 60.022
}
set {
basis cc-pvdz
}
Rval = [1.5, 2.0, 2.5, 3.0, 3.5]
PES =
for d in Rval:
bh3nh3.R = d
r_idx = "1 2 "
set optking frozen_distance = $r_idx
E = optimize(‘scf’)
PES.append((d, E))
print “\n\tcc-pVDZ SCF energy as a function of R\n”
for point in PES:
print “\t%5.1f%20.10f” % (point[0], point[1])
And this is for the one with fixed symmetry:
molecule bh3nh3 {
0 1
B
N 1 R
X 1 1.0 2 90.0
H 2 Rn 1 An 3 dih4
H 2 Rn 1 An 3 dih5
H 2 Rn 1 An 3 dih6
H 1 Rb 2 Ab 3 dih7
H 1 Rb 2 Ab 3 dih8
H 1 Rb 2 Ab 3 dih9
R = 1.5002
Rn = 1.217541
Rb = 1.004446
An = 104.501526
Ab = 110.819753
dih4 = 120.000
dih5 = 240.000
dih6 = 0.000
dih7 = 180.000
dih8 = 300.000
dih9 = 60.000
}
set {
basis cc-pvdz
}
Rval = [1.5, 2.0, 2.5, 3.0, 3.5]
PES =
for d in Rval:
bh3nh3.R = d
r_idx = "1 2 "
set optking frozen_distance = $r_idx
E = optimize(‘scf’)
PES.append((d, E))
print “\n\tcc-pVDZ SCF energy as a function of R\n”
for point in PES:
print “\t%5.1f%20.10f” % (point[0], point[1])
Which is essentially the same as the one before, with a symmetric zmat input.
The problem is that in the symmetric one, the distance R remains as 1.5 A for all the optimizations.
Even though the output explicitly states:
Setting geometry variable R to 2.000000
A noticed a difference between the two output files. The symmetric one that repeats the optimization
for R = 1.5 prints the optimized geom in cartesian coordinates while the one without symmetry prints it
in z-mat format.
Writing optimization data to binary file.
Final energy is -82.6156165478973
Final (previous) structure:
Cartesian Geometry (in Angstrom)
N -0.0000030307 0.0000001213 -0.8886031343
B -0.0000030307 0.0000001213 1.1113968657
H -0.0000030307 0.9405698114 -1.2466722075
H 1.0324255989 0.5960925854 1.3152637417
H 0.8145938560 -0.4702636032 -1.2466099041
H 0.0000213569 -1.1921509487 1.3152872650
H -0.8145224186 -0.4703089845 -1.2467263196
H -1.0324401473 0.5960581299 1.3153145147
Saving final (previous) structure.
--------------------------
OPTKING Finished Execution
--------------------------
Final optimized geometry and variables:
Molecular point group: c1
Full point group: C1
Geometry (in Angstrom), charge = 0, multiplicity = 1:
N
B 1 R
H 1 hn3 2 hnb3
H 2 hb4 1 hbn4 3 dih4
H 1 hn5 2 hnb5 4 dih5
H 2 hb6 1 hbn6 3 dih6
H 1 hn7 2 hnb7 4 dih7
H 2 hb8 1 hbn8 3 dih8
R = 2.0000000000
dih4 = -59.9991876724
dih5 = 59.9984907880
dih6 = -179.9988279123
dih7 = 179.9983793358
dih8 = 60.0008257225
hb4 = 1.2094613694
hb6 = 1.2094608176
hb8 = 1.2094601925
hbn4 = 99.7041082120
hbn6 = 99.7052432317
hbn8 = 99.7065579430
hn3 = 1.0064217820
hn5 = 1.0064218328
hn7 = 1.0064217327
hnb3 = 110.8415202118
hnb5 = 110.8377238811
hnb7 = 110.8448176060
Cleaning optimization helper files.
Setting geometry variable R to 2.500000
gradient() will perform analytic gradient computation.
And this is the output for the computation with the symmetric z-mat:
Writing optimization data to binary file.
Final energy is -82.6158751587106
Final (previous) structure:
Cartesian Geometry (in Angstrom)
B 0.0000000532 0.8238656988 0.0000000000
N -0.0000000436 -0.6761343012 0.0000000000
H 0.4674733216 -1.0541925521 -0.8096876617
H 0.4674733216 -1.0541925521 0.8096876617
H -0.9349468486 -1.0541924624 0.0000000000
H 1.1705866699 1.1857528375 0.0000000000
H -0.5852932200 1.1857529507 -1.0137577271
H -0.5852932200 1.1857529507 1.0137577271
Saving final (previous) structure.
--------------------------
OPTKING Finished Execution
--------------------------
Final optimized geometry and variables:
Molecular point group: cs
Full point group: C1
Geometry (in Angstrom), charge = 0, multiplicity = 1:
B 0.000000053217 0.823865698805 0.000000000000
N -0.000000043604 -0.676134301195 0.000000000000
H 0.467473321634 -1.054192552071 -0.809687661705
H 0.467473321634 -1.054192552071 0.809687661705
H -0.934946848585 -1.054192462415 0.000000000000
H 1.170586669865 1.185752837539 0.000000000000
H -0.585293220018 1.185752950665 -1.013757727063
H -0.585293220018 1.185752950665 1.013757727063
R = 2.0000000000
Cleaning optimization helper files.
Setting geometry variable R to 2.500000
gradient() will perform analytic gradient computation.
The energy however is the same for all the points
cc-pVDZ SCF energy as a function of R
1.5 -82.6158751587
2.0 -82.6158751587
2.5 -82.6158751587
3.0 -82.6158751587
3.5 -82.6158751587
Meaning that the R distance is not increasing during the for loop. I don’t know what is
going on so any help is greatly appreciated.