Hey everyone!
I’m using Avogadro for building Gaussian Input Files. However, I have not yet found a way to obtain a connectivity table as it is required for geometry optimisations under “geom=connectivity”, in order to prevent bond dissociation. Can anyone help me who might have had the same trouble? Would be annoying writing this table anytime by hand…
This would be amazing. Do you know when it would be released? I am searching for a quite fast solution…Btw: I am using Avogadro on Mac. Don’t know whether this makes a difference in any way. Please find an example input below, the lower table is the corresponding connectivity table:
#n B3LYP/6-31G(d) Opt geom=connectivity
Avogadro_exp
0 1
C 1.71843 -2.01080 0.49606
C 0.53954 -2.70258 1.16776
C -0.55890 -1.73938 1.60234
H 2.13761 -1.29863 1.24132
H 0.13478 -3.51941 0.54179
H 2.49448 -2.78571 0.30588
H 0.91862 -3.19156 2.09129
H -1.29521 -2.36848 2.15714
H -0.11303 -1.01849 2.32446
C 0.73510 -2.20771 -1.74672
H 0.92623 -3.27758 -1.51041
H 1.16387 -2.06167 -2.76304
C -0.78840 -1.92127 -1.84622
H -0.89982 -0.95306 -2.34745
H -1.21511 -2.65121 -2.56836
N 1.37893 -1.30420 -0.76989
N -1.24420 -0.97661 0.52275
C 2.59403 -0.58348 -1.22306
H 2.48424 -0.22406 -2.26792
H 3.48627 -1.25187 -1.19212
C 2.78827 0.65102 -0.34295
C 4.02731 1.28462 -0.20083
C 1.73447 2.30285 1.02611
C 4.10791 2.44333 0.57941
H 4.91071 0.89623 -0.69352
C 2.95942 2.95741 1.19660
H 0.82805 2.70662 1.45463
H 5.05681 2.95289 0.69118
H 3.01611 3.86748 1.77873
N 1.68919 1.17350 0.27750
C -1.70078 -1.90701 -0.56782
H -1.86582 -2.93739 -0.18868
H -2.69342 -1.60194 -0.95831
C -2.38738 -0.32507 1.24216
Cu 0.17866 0.14284 -0.34316
N -0.40758 1.25012 -1.87248
N 0.14041 2.31860 -2.04211
N 0.69651 3.39517 -2.21367
C -3.22817 0.68268 0.47546
H -2.00984 0.22401 2.13573
H -3.09601 -1.10940 1.60537
H -2.61309 1.53146 0.12184
H -3.98887 1.07953 1.19020
H -3.78516 0.20483 -0.35125
Thanks - I’ll take a look at this. It doesn’t matter about the platform - the new input generators in Avo2 are written in Python, so it runs the same on everything.