exercises:2021_uzh_acpc2:ex03
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exercises:2021_uzh_acpc2:ex03 [2021/05/21 07:50] – [NEB activation barrier] Some improvements mrossmannek | exercises:2021_uzh_acpc2:ex03 [2021/05/21 10:13] (current) – [Free energy surface] Add tip about RuntimeWarning mrossmannek | ||
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Sampling the free energy surface (FES) of a chemical system is a convenient method to explore various stable conformations and possible reaction pathways. To calculate the FES for complicated systems, advanced sampling methods (such as umbrella sampling, metadynamics, | Sampling the free energy surface (FES) of a chemical system is a convenient method to explore various stable conformations and possible reaction pathways. To calculate the FES for complicated systems, advanced sampling methods (such as umbrella sampling, metadynamics, | ||
- | The FES is a projection of the high-dimensional free energy landscape | + | The FES is a projection of the high-dimensional free energy landscape |
- | To help the calculation | + | To help the simulation |
The following CP2K input script runs our MD calculation and prints out the CV values for every step: | The following CP2K input script runs our MD calculation and prints out the CV values for every step: | ||
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&GLOBAL | &GLOBAL | ||
PRINT_LEVEL LOW | PRINT_LEVEL LOW | ||
- | PROJECT | + | PROJECT |
RUN_TYPE MD # Molecular Dynamics | RUN_TYPE MD # Molecular Dynamics | ||
&END GLOBAL | &END GLOBAL | ||
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$$ F(s) = -k T \log(P(s)), | $$ F(s) = -k T \log(P(s)), | ||
- | where $s$ is the set CVs and $P(s)$ is the probability that the system has the set of CV values $s$. | + | where $s$ is the set of CVs and $P(s)$ is the probability that the system has the set of CV values $s$. |
- | The following Python script can be used to calculate the FES from the '' | + | The following Python script can be used to calculate the FES from the '' |
< | < | ||
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kb = 8.6173303e-5 # eV * K^-1 | kb = 8.6173303e-5 # eV * K^-1 | ||
- | temperature = 1000.0 | + | temperature = 1000.0 |
colvar_path = " | colvar_path = " | ||
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</ | </ | ||
- | Here is an example output for temperature 1000K. We clearly see the two local minima corresponding to the one of the chlorine atoms being covalently bonded (distance 1.8 Å) while the other one is around distance 2.5 Å. | + | Here is an example output for a temperature |
{{ : | {{ : | ||
< | < | ||
- | * Run the MD calculation for 400K, 800K, 1200K and 1600K. (The calculations can a take a while.) | + | * Run the MD calculation for 400K, 800K, 1200K and 1600K. (These calculations can a take a while.) |
* Create the corresponding FES plots and discuss the temperature dependence. | * Create the corresponding FES plots and discuss the temperature dependence. | ||
* In general, how does potential energy differ from free energy? For our reaction, what are the activation barriers from the different free energy surfaces? How and why do they differ from the NEB barrier? | * In general, how does potential energy differ from free energy? For our reaction, what are the activation barriers from the different free energy surfaces? How and why do they differ from the NEB barrier? | ||
+ | </ | ||
+ | |||
+ | <note tip> | ||
+ | You may encounter a warning like the following: | ||
+ | < | ||
+ | plot.py:24: RuntimeWarning: | ||
+ | fes = -kb * temperature * np.log(prob) | ||
+ | </ | ||
+ | Don't worry about this, the script still works as expected and produces the plot in the file '' | ||
</ | </ |
exercises/2021_uzh_acpc2/ex03.1621583435.txt.gz · Last modified: 2021/05/21 07:50 by mrossmannek