Help: Suggestion for gaussian calculation setup involving nanoparticles and DNA

rpestana94

Greetings, I want to use gaussian to see the interaction between DNA and nanoparticles(NPs) of gold and silver, for these, I was thinking on calculate the binding energy between the DNA and the NPs and also make a cytosine(C)-guanine(G) and put one NPs in different places and measure the binding energy between C-G. For this, the cluster of gold and silver were made by putting some atoms and do an optimization using Lanl2dz, the C-G was optimized using B3LYP.

I'm not pretty sure how to calculate the energy between the C-G and the NPs, maybe using Gen keyword or even if this kind of approximation makes sense, so I open to suggestions, changes in calculation, improvement, advice, etc.

Thanks in advance.

rpestana94

wzkchem5 发表于 2021-7-23 12:15
RI is for pure functionals, while RIJCOSX is for hybrid functionals. However in ORCA 5 there is re ...

I see, so in orca 5 I can leave out that keyword and by defaults orca decided the best things to do

wzkchem5

rpestana94 发表于 2021-7-23 17:52
Professor I running the system with this configuration using orca 5, I'm reading about RI and auxi ...

RI is for pure functionals, while RIJCOSX is for hybrid functionals. However in ORCA 5 there is relatively little need to worry about this, since the correct one is turned on by default. This is different from ORCA 4 where RI is turned on by default for pure functionals, but hybrid functionals by default do not use any approximation.
Besides, please note that RI only speeds up individual SCF iterations, but does not reduce the number of iterations, so they cannot be said to "help to converge".

rpestana94

sobereva 发表于 2021-3-29 23:52
Your keywords are incorrect.

If your nanoparticle is very large, due to consideration of comput ...

Professor I running the system with this configuration using orca 5, I'm reading about RI and auxiliary basis sets to speed up the calculation and help to converge, but I'm kind of lost of which one I should use, I think RI or RIJCOSX can be worth using but not sure which one I should choose or there are a better one to consider

rpestana94

sobereva 发表于 2021-6-25 10:20
If gridx setting is not quite small (i.e. the grid for COSX part is not too coarse), the numerical ...

Thanks professor Sob

sobereva

rpestana94 发表于 2021-6-25 20:50
Three questions, about the basis sets in gaussian how it would be? I have your recommendation in O ...

If gridx setting is not quite small (i.e. the grid for COSX part is not too coarse), the numerical error caused by RIJCOSX is fully negligible. So you do not need to worry about this.

I have a blog article about choice of basis set, see http://sobereva.com/336 (in Chinese). The recommendations in this article are very suitable for Gaussian users.

GPU acceleration performance in G16 is quite poor, simply ignore it. ORCA currently doesn't support GPU acceleration.

rpestana94

sobereva 发表于 2021-6-25 05:09
ORCA is significantly faster than Gaussian for single point and optimization tasks when RIJ (for p ...

Three questions, about the basis sets in gaussian how it would be? I have your recommendation in ORCA but I don't know exactly how to translate this to gaussian, is there a way to do this automatically?

If I'm right gaussian16 have some GPU acelleration for some process, ORCA have something like this?

The RIJCOSX and this kind of keywords actually accelerate the calculation but I understand that this also give some error in the measurement, It will be better to do a calculation with RIJCOSX activate and then a new calculation deactivating RIJCOSX or the error is too low

wzkchem5

sobereva 发表于 2021-6-25 11:09
ORCA is significantly faster than Gaussian for single point and optimization tasks when RIJ (for p ...

As a side note: ORCA 5.0 will be released on next Thursday. The frequency calculation of ORCA 5.0 will be noticeably faster than in ORCA 4.2.1. But due to some (in)famous reasons I cannot comment on whether ORCA 5.0 will become faster than Gaussian in this aspect.

sobereva

rpestana94 发表于 2021-6-25 11:36
orca is significantly faster than gaussian for general purposes or just with the dispersion?

ORCA is significantly faster than Gaussian for single point and optimization tasks when RIJ (for pure DFT functionals) or RIJCOSX/RIJK (for hybrid DFT functionals) or RI (MP2 and double-hybrid functionals) is enabled for medium and large-sized systems.

However, speed of frequency analysis of current version of ORCA (4.2.1) doesn't outperform Gaussian even if RI related techniques is enabled.

Gaussian also has RIJ for pure DFT functionals, however it significantly speeds up calculation only when you use relatively large basis sets (e.g. def2-TZVP) or in frequency analysis process.

Overall, you can benefit from RI related techniques in ORCA much more than Gaussian.

rpestana94

zjxitcc 发表于 2021-6-24 22:43
ORCA is much faster than Gaussian for RI (or density fitting) related computations. If RI is turne ...

Thanks

zjxitcc

rpestana94 发表于 2021-6-25 11:36
orca is significantly faster than gaussian for general purposes or just with the dispersion?

ORCA is much faster than Gaussian for RI (or density fitting) related computations. If RI is turned off, ORCA may be slower than Gaussian (but it also depends on which method you use).

By the way, the dispersion correction keyword in Gaussian is em=GD3 or em=GD3BJ, where 'BJ' means with Becke-Johnson damping. The dispersion correction is not default, and you should add it explicitly. You can find this on http://gaussian.com/dft. Dispersion correction costs little time (less than 1s, or only several seconds) in any quantum chemistry software.

rpestana94

zjxitcc 发表于 2021-6-24 22:29
These keywords will not provide any meaningful result.

For practical computation, a double-zeta ...

orca is significantly faster than gaussian for general purposes or just with the dispersion?

zjxitcc

rpestana94 发表于 2021-6-25 11:20
Professor Sob thanks for this recommendation for this basis set in gaussian16 how it would be? Her ...

These keywords will not provide any meaningful result.

For practical computation, a double-zeta basis set is at least required, such as def2SVP, 6-31G(d,p), 6-31G(d), etc. So 3-21+g is useless.

For RI (or density fitting), you should use ORCA instead of Gaussian, since density fitting in Gaussian does not accelerate the computation (or acceleration is little). But this is significant in ORCA.

rpestana94

sobereva 发表于 2021-3-29 23:52
Your keywords are incorrect.

If your nanoparticle is very large, due to consideration of comput ...

Professor Sob thanks for this recommendation for this basis set in gaussian16 how it would be? Here I will try to guess the correct keywords but let me know if I'm wrong:

For opt
opt pbepbe/3-21+g/def2sv geom=connectivity

For single point
pbepbe/3-21+g/def2tzv geom=connectivity

I don't know if the dispersion correction is already added by default in gaussian

Thanks in advance

rpestana94

sobereva 发表于 2021-4-6 12:20
I can't give you answer because I know nothing about character of your practical system.

Thanks for the advice I solve the problem