[CP2K-user] GEO_OPT a molecular is 10000 time longer then gaussian

[Linfeng Gan]

Thank you for your advice, Travis.

I had tested EPS_SCF from 1e-5 to 1e-14. I posted the 1e-5 one only because 
it took the shortest time to get the final structure. And I will try 
convergence criteria with 1e-4 as you suggest. 

 

Linfeng


On Sunday, May 17, 2020 at 12:36:33 PM UTC+8, Travis wrote:
>
> Hi,
>
> I see you have EPS_SCF commented out in your input file. The default 
> convergence threshold is 1e-5 au which is usually not tight enough for 
> accurate forces (and certainly not for vibrational analysis, which is 
> computed numerically - hence it will take ages over Gaussian). The value 
> you commented out is actually better and may take less steps to converge. 
> Your criteria for convergence are also extremely tight, 1e-4 au is 
> typically enough. Also, just to be clear, CP2K when setup appropriately 
> will reproduce Gaussian output for the total energies for non-periodic 
> calculations. So you CAN use Gaussian for the gas phase reaction and CP2K 
> for the surface reaction.
>
> -T
>
>
> On Saturday, May 16, 2020 at 10:47:56 PM UTC-4, Linfeng Gan wrote:
>>
>>
>> Thank you very much Vladimir,
>>
>> 1) I know CP2K is not a choice for small molecules. But I am 
>> investigating an organic reaction which could take place in gas phase and 
>> on C3N4 surface. I have to compare the data between the gas phase and the 
>> surface. So, I can’t use gaussian or orca to that. DMol3 or CASTEP maybe is 
>> best choice for me, but I think we should give open source software a 
>> chance. So, CP2K is my choice right now. I am not very familiar with CP2K 
>> that it’s why I go to this forum and ask for some help. 
>>
>> 2) Agree. 
>>
>> 3) Yes, it was. 
>>
>> 4) 10000 times is an exaggeration, I apologize for that. Form the same 
>> initial structure, it took gaussian 41 seconds with a single Xeon 2680v2 
>> CPU to finish the geometry optimization, but it took CP2k 40 minutes with 
>> 20 CPU to do the same thing. If we include the frequencies calculation the 
>> time is 4 minutes vs 71 minutesX20CPU. A single SCF calculation of CP2K was 
>> pretty fast, but most of time was wasting in locating the minimize. 
>> This efficiency issue only happened in this 1-butene molecular. Another 
>> molecular I tested, cyclobutene, seemed much batter than 1-butene. 
>>
>> I attach all the input and the output file. So, you guy can help me to 
>> improve this. Thanks all.
>>
>>
>> Best,
>> LInfeng
>>
>>
>> On Friday, May 15, 2020 at 7:41:12 PM UTC+8, Vladimir Rybkin wrote:
>>>
>>> Dear Linfeng,
>>>
>>> a few general remarks:
>>> 1) CP2K is not the most efficient tool for small molecules. For 
>>> instance, it does a lot of integrations over cells in real and reciprocal 
>>> space, and for a small molecule the cell is almost everywhere empty.
>>> 2) CP2K does not use internal coordinates for optimisation. This has to 
>>> do with the fact that it's mostly meant for large periodic systems. 
>>> Gaussians' Berny algorithm does use internal coordinates and is very 
>>> efficient for small systems.
>>> 3) It's very likely that you 150 steps have not change the geometry 
>>> significantly. 
>>> 4) It's not completely clear where this 10000 times come from. It may 
>>> have to do with how you compile and run your applications.
>>>
>>> That said, there's no specific problems with optimisers and efficiency. 
>>> It's about applicability of tools for specific purposes. If you going to 
>>> work with small molecules, you'd better stick to programs made for them, 
>>> i.e. Gaussian. CP2K is meant for large and/or periodic systems.
>>>
>>> Yours,
>>>
>>> Vladimir
>>>
>>> пятница, 15 мая 2020 г., 2:51:51 UTC+2 пользователь Linfeng Gan написал:
>>>>
>>>> Hi all,
>>>>
>>>> When I optimized 1-butene molecular at B3lYP/6-311G** level, it took 
>>>> much much longer than gaussian16 did.  I had test optimizer CG, BDGS 
>>>> and LBFGD, nothing better. It seems the optimizers have some efficiency 
>>>> issues. All three optimizer had taken at least 150 optimization steps to 
>>>> get the final structure, but the initial structure had been optimized by 
>>>> gaussian.   How could I improve that?
>>>>
>>>>  
>>>>
>>>> Best
>>>>
>>>> Linfeng
>>>>
>>>
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