Skip to main content
Join the official 2019 Python Developers SurveyStart the survey!

A python program to compute corrections to thermochemical data from frequency calculations

Project description

GoodVibes

Build Status PyPI version Anaconda-Server Badge Anaconda-Server Badge DOI

A Python program to compute corrections to thermochemical data from frequency calculations at a given temperature/concentration, corrected for the effects of vibrational scaling-factors and available free space in solvent. Developed by Robert Paton, Ignacio Funes-Ardoiz, and members of the Paton Research Group, Colorado State: Guilian Luchini, Juan V. Alegre-Requena, and Yanfei Guan . Integration with Travis CI testing by Jaime Rodríguez-Guerra with additions from Guilian Luchini.

All (electronic, translational, rotational and vibrational) partition functions are recomputed and will be adjusted to any temperature or concentration. These default to 298.15 Kelvin and 1 atmosphere.

The program will attempt to parse the level of theory and basis set used in the calculations and then try to apply the appropriate vibrational (zpe) scaling factor. Scaling factors are taken from the Truhlar group database.

Quasi-Harmonic Approximation

Two types of quasi-harmonic approximation are readily applied. The first is vibrational entropy: below a given cut-off value vibrational normal modes are not well described by the rigid-rotor-harmonic-oscillator (RRHO) approximation and an alternative expression is instead used to compute the associated entropy. The quasi-harmonic vibrational entropy is always less than or equal to the standard (RRHO) value obtained using Gaussian. Two literature approaches have been implemented. In the simplest approach, from Cramer and Truhlar,1 all frequencies below the cut-off are uniformly shifted up to the cut-off value before entropy calculation in the RRHO approximation. Alternatively, as proposed by Grimme,2 entropic terms for frequencies below the cut-off are obtained from the free-rotor approximation; for those above the RRHO expression is retained. A damping function is used to interpolate between these two expressions close to the cut-off frequency.

The second type of quasi-harmonic approximation available is applied to the vibrational energy used in enthalpy calculations. Similar to the entropy corrections, the enthalpy correction implements a quasi-harmonic correction to the RRHO vibrational energy computed in DFT methods. The quasi-harmonic enthalpy value as specified by Head-Gordon3 will be less than or equal to the uncorrected value using the RRHO approach, as the quasi-RRHO value of the vibrational energy used to compute the enthalpy is damped to approach a value of 0.5RT, opposed to the RRHO value of RT. Because of this, the quasi-harmonic enthalpy correction is appropriate for use in systems and reactions resulting in a loss of a rotational or translational degree of freedom.

Symmetry

GoodVibes is able to detect a probable symmetry point group for each species and apply a symmetry correction to the entropy (Ssym) by finding a molecule's internal symmetry number using atom connectivity, and external symmetry with the help of the external open source C program, "Brute Force Symmetry Analyzer" developed by S. Patchkovskii. These numbers are combined to give a symmetry number, n, and Ssym is then defined as -Rln(n), which is applied to the GoodVibes calculated entropy. Note: this option may not function properly on some versions of Windows.

Checks

A computational workflow can become less effective without consistency throughout the process. By using the --check option, GoodVibes will enforce a number of pass/fail checks on the input files given to make sure uniform options were used. Checks employed are:

Gaussian Output Checks
  • Same version of Gaussian used across all output files
  • Same solvation state/gas phase used across all output files
  • Same level of theory and basis set used
  • Same charge and multiplicity used
  • Check if standard concenctration of 1 atm was used in calculation
  • Check for duplicate structures or enantiomeric conformers based on E, H, qh_T.S and qh_G with a cutoff of 0.1 kcal/mol
  • Check for potential calculation error in linear molecules by Gaussian
  • Check for transition states (one imaginary frequency in output file)
  • Check if empirical dispersion is used and consistent across all output files
Single Point Calculation Checks
  • Same version and program used for all single point calculations
  • Same solvation model used across output files
  • Same level of theory used across all output files
  • Same charge and multiplicity used
  • Same geometry coordinates for SPC and associated geometry optimized and frequency calculation output file
  • Check if empirical dispersion is used and consistent across all output files

Installation

  • With pypi: pip install goodvibes
  • With conda: conda install -c patonlab goodvibes
  • Manually Cloning the repository https://github.com/bobbypaton/GoodVibes.git and then adding the location of the GoodVibes directory to the PYTHONPATH environment variable.
  • Run the script with your Gaussian output files (the program expects .log or .out extensions). It has been tested with Python 2 and 3 on Linux, macOS and Windows

Correct Usage

python -m goodvibes [-q] [--qs grimme/truhlar] [--qh] [-f cutoff_freq] [--fs S_cutoff_freq] [--fh H_cutoff_freq] 
[--check] [-t temperature] [-c concentration] [--ti 't_initial, t_final, step'] [--ee] 
[--cosmo cosmo_filename] [--cosmoint cosmo_filename,initial_temp,final_temp] [-v frequency_scale_factor] 
[--vmm mm_freq_scale_factor][--ssymm] [--spc link/filename] [--boltz] [--dup][--pes pes_yaml] [--nogconf] 
[--graph graph_yaml] [--cpu] [--imag] [--invertifreq] [--freespace solvent_name] [--output output_name] 
[--media solvent_name] [--xyz] [--csv] [--custom_ext file_extension] <output_file(s)>
  • The -h option gives help by listing all available options, default values and units, and proper usage.
  • The -q option turns on quasi-harmonic corrections to both entropy and enthalpy, defaulting to the Grimme method for entropy and the Head-Gordon enthalpy correction.
  • The --qs option selects the approximation for the quasi-harmonic entropic correction: --qs truhlar or --qs grimme request the options explained above. Both avoid the tendency of RRHO vibrational entropies towards infinite values for low frequencies. If not specified this defaults to Grimme's expression.
  • The --qh option selects the approximation for the quasi-harmonic enthalpy correction. Calling this argument requests the enthalpy correction option explained above. This replaces harmonic energy contributions with a quasi-RRHO vibrational energy term. If not specified the Head-Gordon expression is defaulted.
  • The -f option specifies the frequency cut-off for both entropy and enthalpy calculations (in wavenumbers) i.e. -f 10 would use 10 cm-1 when calculating thermochemical values. The default value is 100 cm-1. N.B. when set to zero all thermochemical values match standard (i.e. harmonic) Gaussian quantities.
  • The --fs option specifies the frequency cut-off for only entropy calculations(in wavenumbers). --fs 40 would use 40 cm-1 when calculating entropies. The default value is 100 cm-1.
  • The --fh option specifies the frequency cut-off for only enthalpy calculations (in wavenumbers).--fh 200 would use 200 cm-1 when calculating enthalpies. The default value is 100 cm-1.
  • The --check option applies the checks specified above to the calculation output files and displays a pass or fail message to the user.
  • The -t option specifies temperature (in Kelvin). N.B. This does not have to correspond to the temperature used in the Gaussian calculation since all thermal quantities are reevalulated by GoodVibes at the requested temperature. The default value is 298.15 K.
  • The -c option specifies concentration (in mol/l). It is important to notice that the ideal gas approximation is used to relate the concentration with the pressure, so this option is the same as the Gaussian Pressure route line specification. The correction is applied to the Sackur-Tetrode equation of the translational entropy e.g. -c 1 corrects to a solution-phase standard state of 1 mol/l. The default is 1 atmosphere.
  • The --ti option specifies a temperature interval (for example to see how a free energy barrier changes with the temperature). Usage is --ti 'initial_temperature, final_temperature, step_size'. The step_size is optional, the default is set by the relationship (final_temp-initial_temp) / 10
  • The --ee option takes a file naming pattern (such as *_R*,*_S*) with files named as structure_R.log, structure_S.log, and will calculate and display values for stereoisomer excess (in %), ratio, major isomer present, and ddG.
  • The --cosmo option can be used to read Gibbs Free Energy of Solvation data from a COSMO-RS .out formatted file.
  • The --cosmo_int option allows for Gibbs Free Energy of Solvation calculated using COSMO-RS with a temperature interval to be applied at a range of temperatures. Since temperature gaps may not be consistent, the interval is automatically detected. Usage is --cosmo_int cosmo_gsolv.out,initial_temp,final_temp. GoodVibes will detect temperatures within the range provided.
  • The -v option is a scaling factor for vibrational frequencies. DFT-computed harmonic frequencies tend to overestimate experimentally measured IR and Raman absorptions. Empirical scaling factors have been determined for several functional/basis set combinations, and these are applied automatically using values from the Truhlar group4 based on detection of the level of theory and basis set in the output files. This correction scales the ZPE by the same factor, and also affects vibrational entropies. The default value when no scaling factor is available is 1 (no scale factor). The automated scaling can also be suppressed by -v 1.0
  • The --vmm option is a second scaling factor for vibrational frequencies when performing QM/MM calculations with ONIOM. The correction is applied using the additional information in the output file, %ModelSys and %RealSys. This correction is only applied when requested with ONIOM calculation files. The option is activated with the command -vmm scale_factor
  • The --ssymm option will apply a symmetry correction to the entropy by detecting a molecule's internal and external symmetry.
  • The --spc option can be used to obtain single point energy corrected values. For multi-step jobs in which a frequency calculation is followed by an additional (e.g. single point energy) calculation, the energy is taken from the final job and all thermal corrections are taken from the frequency calculation. Alternatively, the energy can be taken from an additional file.
  • The --boltz option will display the Boltzmann weighted factors based on free energy of each specified output file.
  • The --dup option will check multiple output files for duplicate structures based on energy, rotational constants and calculated frequencies. Cutoffs are currently specified as: energy cutoff = 1 microHartree; RMS Rotational Constant cutoff = 100kHz; RMS Freq cutoff = 1 wavenumber.
  • The --pes option takes a .yaml file input (see template below) along with calculation output files to allow for the construction of a potential energy surface from relative computed Gibbs free-energy values.
  • The --nogconf option will turn off a correction to the Gibbs free-energy due to multiple conformations when constructing a potential energy surface (use only with --pes option). Default is to calculate Gconf correction.
  • The --graph option takes a .yaml file input (see template below) along with calculation output files and will compute and graph relative Gibbs free-energy values along a reaction path (requires matplotlib library to be installed)
  • The --cpu option will add up all of the CPU time across all files (including single point calculations if requested).
  • The --imag option will print any imaginary frequencies (in wavenumbers) for each structure. Presently, all are reported. The hard-coded variable im_freq_cutoff can be edited to change this. To generate new input files (i.e. if this is an undesirable imaginary frequency) see pyQRC
  • The --invertifreq option will convert any low lying imaginary frequencies lying in a certain range to positive values (in wavenumbers). The default cutoff is to make imaginary frequencies above -50 cm-1 positive.
  • The --freespace option specifies the solvent. The amount of free space accessible to the solute is computed based on the solvent's molecular and bulk densities. This is then used to correct the volume available to each molecule from the ideal gas approximation used in the Sackur-Tetrode calculation of translational entropy, as proposed by Shakhnovich and Whitesides.5 The keywords H2O, toluene, DMF (N,N-dimethylformamide), AcOH (acetic acid) and chloroform are recognized.
  • The --output option is used to change the default output file name to a specified name instead. Use as --output NAME to change the name of the output file of thermochemical data from "GoodVibes.dat" to "GoodVibes_NAME.dat"
  • The --media option applies an entropy correction to calculations done on solvent molecules calculated from their standard concentration.
  • The --xyz option will write all molecular Cartesian coordinates to a .xyz output file.
  • The --csv option will write GoodVibes calculated thermochemical data to a .csv output file.
  • The --custom_ext option allows for custom file extensions to be used. Current default calculation output files accepted are .log or .out file extensions. New extensions can be detected by using GoodVibes with the option --custom_ext file_extension.

Example 1: Grimme-type quasi-harmonic correction with a (Grimme type) cut-off of 150 cm-1

python -m goodvibes examples/methylaniline.out -f 150

   Structure                    E        ZPE             H        T.S     T.qh-S          G(T)       qh-G(T)
   *********************************************************************************************************
o  methylaniline      -326.664901   0.142118   -326.514489   0.039668   0.039465   -326.554157   -326.553955
   *********************************************************************************************************

The output shows both standard harmonic and quasi-harmonic corrected thermochemical data (in Hartree). The corrected enthalpy and entropy values are always less than or equal to the harmonic value.

Example 2: Quasi-harmonic thermochemistry with a larger basis set single point energy correction link job

python -m goodvibes examples/ethane_spc.out --spc link

   Structure                E_SPC             E        ZPE         H_SPC        T.S     T.qh-S      G(T)_SPC   qh-G(T)_SPC
   ***********************************************************************************************************************
o  ethane_spc          -79.858399    -79.830421   0.075238    -79.778748   0.027523   0.027525    -79.806271    -79.806273
   ***********************************************************************************************************************

This calculation contains a multi-step job: an optimization and frequency calculation with a small basis set followed by (--Link1--) a larger basis set single point energy. Note the use of the --spc link option. The standard harmonic and quasi-harmonic corrected thermochemical data are obtained from the small basis set partition function combined with the larger basis set single point electronic energy. In this example, GoodVibes automatically recognizes the level of theory used in the frequency calculation, B3LYP/6-31G(d), and applies the appropriate scaling factor of 0.977 (this can be suppressed to apply no scaling with -v 1.0)

Alternatively, if a single point energy calculation has been performed separately, provided both file names share a common root e.g. ethane.out and ethane_TZ.out then use of the --spc TZ option is appropriate. This will give identical results as above.

python -m goodvibes examples/ethane.out --spc TZ

   Structure                E_SPC             E        ZPE         H_SPC        T.S     T.qh-S      G(T)_SPC   qh-G(T)_SPC
   ***********************************************************************************************************************
o  ethane              -79.858399    -79.830421   0.075238    -79.778748   0.027523   0.027525    -79.806271    -79.806273
   ***********************************************************************************************************************

Example 3: Changing the temperature (from standard 298.15 K to 1000 K) and concentration (from standard state in gas phase, 1 atm, to standard state in solution, 1 mol/l)

python -m goodvibes examples/methylaniline.out t 1000 c 1.0

   Structure                    E        ZPE             H        T.S     T.qh-S          G(T)       qh-G(T)
   *********************************************************************************************************
o  methylaniline      -326.664901   0.142118   -326.514489   0.039668   0.039535   -326.554157   -326.554024
   *********************************************************************************************************

This correction from 1 atm to 1 mol/l is responsible for the addition 1.89 kcal/mol to the Gibbs energy of each species (at 298K). It affects the translational entropy, which is the only component of the molecular partition function to show concentration dependence. In the example above the correction is larger due to the increase in temperature.

Example 4: Analyzing the Gibbs energy across an interval of temperatures 300-1000 K with a stepsize of 100 K, applying a (Truhlar type) cut-off of 100 cm-1

python -m goodvibes examples/methylaniline.out --ti '300,1000,100' --qs truhlar -f 120

   Structure               Temp/K                        H        T.S     T.qh-S          G(T)       qh-G(T)
   ******************************************************************************************************
o  methylaniline            300.0              -326.514399   0.040005   0.039842   -326.554404   -326.554241
o  methylaniline            400.0              -326.508735   0.059816   0.059596   -326.568551   -326.568331
o  methylaniline            500.0              -326.501670   0.082625   0.082349   -326.584296   -326.584020
o  methylaniline            600.0              -326.493429   0.108148   0.107816   -326.601577   -326.601245
o  methylaniline            700.0              -326.484222   0.136095   0.135707   -326.620317   -326.619930
o  methylaniline            800.0              -326.474218   0.166216   0.165772   -326.640434   -326.639990
o  methylaniline            900.0              -326.463545   0.198300   0.197800   -326.661845   -326.661346
o  methylaniline           1000.0              -326.452307   0.232169   0.231614   -326.684476   -326.683921
   ******************************************************************************************************

Note that the energy and ZPE are not printed in this instance since they are temperature-independent. The Truhlar-type quasi-harmonic correction sets all frequencies below than 120 cm-1 to a value of 100. Constant pressure is assumed, so that the concentration is recomputed at each temperature.

Example 5: Analyzing the Gibbs Energy using scaled vibrational frequencies

python -m goodvibes examples/methylaniline.out -v 0.95

   Structure                    E        ZPE             H        T.S     T.qh-S          G(T)       qh-G(T)
   *********************************************************************************************************
o  methylaniline      -326.664901   0.135012   -326.521265   0.040238   0.040091   -326.561503   -326.561356
   *********************************************************************************************************

The frequencies are scaled by a factor of 0.95 before they are used in the computation of the vibrational energies (including ZPE) and entropies.

Example 6: Writing Cartesian coordinates

python -m goodvibes examples/HCN*.out --xyz

Optimized cartesian-coordinates found in files HCN_singlet.out and HCN_triplet.out are written to Goodvibes_output.xyz

Example 7: Analyzing multiple files at once

python -m goodvibes examples/*.out --cpu

   Structure                    E        ZPE             H        T.S     T.qh-S          G(T)       qh-G(T)
   *********************************************************************************************************
o  Al_298K            -242.328708   0.000000   -242.326347   0.017670   0.017670   -242.344018   -242.344018
o  Al_400K            -242.328708   0.000000   -242.326347   0.017670   0.017670   -242.344018   -242.344018
o  H2O                 -76.368128   0.020772    -76.343577   0.021458   0.021458    -76.365035    -76.365035
o  HCN_singlet         -93.358851   0.015978    -93.339373   0.022896   0.022896    -93.362269    -93.362269
o  HCN_triplet         -93.153787   0.012567    -93.137780   0.024070   0.024070    -93.161850    -93.161850
o  allene             -116.569605   0.053913   -116.510916   0.027618   0.027621   -116.538534   -116.538537
o  benzene            -232.227201   0.101377   -232.120521   0.032742   0.032745   -232.153263   -232.153265
o  ethane              -79.830421   0.075238    -79.750770   0.027523   0.027525    -79.778293    -79.778295
o  isobutane          -158.458811   0.132380   -158.319804   0.034241   0.034252   -158.354046   -158.354056
o  methylaniline      -326.664901   0.142118   -326.514489   0.039668   0.039535   -326.554157   -326.554024
o  neopentane         -197.772980   0.160311   -197.604824   0.036952   0.036966   -197.641776   -197.641791
   *********************************************************************************************************
TOTAL CPU      0 days  2 hrs 37 mins  5 secs

The program will detect several different levels of theory and give a warning that any vibrational scaling factor other than 1 would be inappropriate in this case. Wildcard characters (*) can be used to represent any character or string of characters.

Example 8: Entropic Symmetry Correction

python -m goodvibes examples/allene.out examples/benzene.out examples/ethane.out examples/isobutane.out examples/neopentane.out --ssymm

   Structure                    E        ZPE             H        T.S     T.qh-S          G(T)       qh-G(T)  Point Group
   **********************************************************************************************************************
o  allene             -116.569605   0.053913   -116.510916   0.024235   0.024237   -116.535150   -116.535153          D2d
o  benzene            -232.227201   0.101377   -232.120521   0.030396   0.030399   -232.150917   -232.150919          D6h
o  ethane              -79.830421   0.075238    -79.750770   0.023757   0.023759    -79.774527    -79.774529          D3d
o  isobutane          -158.458811   0.132380   -158.319804   0.030092   0.030103   -158.349896   -158.349907          C3v
o  neopentane         -197.772980   0.160311   -197.604824   0.030456   0.030471   -197.635281   -197.635295           Td
   *********************************************************************************************************************************************

GoodVibes will apply a symmetry correction described above to the entropy term of each molecule after determining the symmetry number. It is always a good idea to double-check that the point group GoodVibes returns is the correct group.

Example 9: Potential Energy Surface (PES) Comparison with Accessible Conformer Correction

python -m goodvibes examples/gconf_ee_boltz/*.log --pes gconf_aminox_cat.yaml 

   Structure                       E        ZPE             H        T.S     T.qh-S          G(T)       qh-G(T)
   ************************************************************************************************************
o  Aminoxylation_TS1_R   -879.405138   0.304487   -879.082686   0.062861   0.060665   -879.145547   -879.143351
o  Aminoxylation_TS2_S   -879.404445   0.304434   -879.081872   0.063479   0.061076   -879.145351   -879.142948
o  aminox_cat_conf212_S  -517.875165   0.206534   -517.656256   0.051294   0.049337   -517.707550   -517.705593
o  aminox_cat_conf280_R  -517.877308   0.207081   -517.658218   0.049481   0.048300   -517.707700   -517.706519
o  aminox_cat_conf65_S   -517.877161   0.206999   -517.658210   0.049276   0.048179   -517.707487   -517.706389
o  aminox_subs_conf713   -361.535757   0.098285   -361.430368   0.037571   0.037450   -361.467939   -361.467818
   ************************************************************************************************************

   Gconf correction requested to be applied to below relative values using quasi-harmonic Boltzmann factors

   RXN: Reaction (kcal/mol)       DE       DZPE            DH       T.DS    T.qh-DS         DG(T)      qh-DG(T)
   ************************************************************************************************************
o  Cat+Subs                     0.00       0.00          0.00       0.00       0.00          0.00          0.00
o  TS                           4.71      -0.47          3.49     -15.93     -16.43         19.42         19.92
   ************************************************************************************************************

A .yaml file is given to the --pes argument which specifies the reaction: Catalyst + Substrate -> TS. Because multiple conformers for the catalysts and transition states have been provided, GoodVibes will calculate a correction to the free energy based on the number of accessible conformations based on the Boltzmann-weighted energies of the conformers. To turn this correction off, --nogconf should be specified. An example .yaml file is shown below to show how these files should be formatted.

Example 10: Stereoselectivity and Boltzmann populations

python -m goodvibes examples/gconf_ee_boltz/Aminoxylation_TS1_R.log examples/gconf_ee_boltz/Aminoxylation_TS2_S.log --boltz --ee *_R*,*_S* 

   Structure                       E        ZPE             H        T.S     T.qh-S          G(T)       qh-G(T)  Boltz
   *******************************************************************************************************************
o  Aminoxylation_TS1_R   -879.405138   0.304487   -879.082686   0.062861   0.060665   -879.145547   -879.143351  0.605
o  Aminoxylation_TS2_S   -879.404445   0.304434   -879.081872   0.063479   0.061076   -879.145351   -879.142948  0.395
   *******************************************************************************************************************

   Selectivity            Excess (%)     Ratio (%)         Ratio     Major Iso           ddG
   *****************************************************************************************
o                              21.00         60:40         1.5:1             R          0.25
   *****************************************************************************************

The --boltz option will provide Boltzmann probabilities to the right of energy results under the boltz tab. With the --ee option, %ee, er and a reduced ratio are shown along with the dominant isomer and a calculated transition state energy value, ddG or ΔG‡.

File Naming Conventions

Some options (--pes, --graph, --spc, -ee, --media) require the calculation output files to be named in a certain way for GoodVibes to recognize them and perform extra calculations properly.

  • PES & Graph

    PES and graphing file names need correlate with the file names specified in the # SPECIES block of the .yaml file (see below for .yaml formatting).

  • SPC

    To link a frequency output file to a separately performed single point energy calculation file, the single point calculation file should have the same common root as the frequency file, with an additional underscore and descriptor at the end, such as ethane.out and ethane_TZ.out shown above, where ethane_TZ.out is the separate single point calculation file. When running GoodVibes in this case, the descriptor TZ should be passed as an argument, as --spc TZ.

  • Selectivity

    To calculate enantiomeric excess, enantiomeric ratio, or diastereomeric ratios, file names should begin or end with a pattern identifier, such as _R and _S. The argument then passed to GoodVibes should be --ee *_R*,*_S*.

  • Media

    To apply the media correction to calculations performed on solvent molecules, the calculation output file should match the name passed in the media argument, for example, if performing the correction on water, the output file should be named H2O.log and the command line option should be --media H2O. GoodVibes will recognize the following solvent molecule names:

      meco2h / aceticacid, acetone, mecn / acetonitrile, benzene, 1buoh / 1butanol, 2buoh / 2butanol, 2butanone, tbuoh / tbutylalcohol, ccl4 / carbontetrachloride,
      phcl / chlorobenzene, chcl3 / chloroform, cyclohexane, 12dce  / 12dichloroethane, diethyleneglycol, et2o / diethylether, diglyme, dme / 12dimethoxyethane, 
      dmf / dimethylformamide, dmso / dimethylsulfoxide, 14dioxane, etoh / ethanol, etoac / acoet / ethylacetate, ethyleneglycol, glycerin, hmpa / hexamethylphosphoramide,
      hmpt / hexamethylphosphoroustriamide, hexane, meoh / methanol, mtbe / methyltbutylether, ch2cl2 / methylenechloride, dcm / dichloromethane, nmp / nmethyl2pyrrolidinone,
      meno2 / nitromethane, pentane, 1propanol, 2propanol, pyridine, thf / tetrahydrofuran, toluene, et3n / triethylamine, h2o / water, oxylene, mxylene, pxylene
    

.yaml File Formatting

When using the --pes or --graph options in GoodVibes, a .yaml file must be provided to the program to specify qualities like reaction pathways, provided conformers, and other formatting options. The same .yaml may be used for both --pes and --graphing options. An example .yaml file is shown below:

--- # PES
# Double S addition
   Reaction: [Int-I+TolS+TolSH, Int-II+TolSH, Int-III] 

--- # SPECIES
   Int-I     : Int-I_*
   TolS      : TolS
   TolSH     : TolSH
   Int-II    : Int-II_*
   Int-III   : Int-III_*

--- # FORMAT
   dec : 1
   units: kcal|mol

options in the # FORMAT block are not necessary, but allow for stylistic choices to be employed, especially when graphing. All current options that can be specified for either --pes or --graph options are:

    dec : 1 or 2 (decimal points in output)
    units : kcal/mol or kJ/mol
    legend : True or False (puts legend on graph)
    ylim : y_min,y_max (y axis limits on graph)
    color : Color (color of line for a reaction pathway, multiple pathways can have different colors i.e. color1,color2,color3 etc., this follows rules for matplotlib standard colors)
    pointlabel : True or False (labels relative energy on graph at point)
    xlabel : True or False (displays structure labels at pathway points on x axis)
    title : Title (title displayed on graph)
    gridlines: True or False (displays gridlines on graph)
    dpi : number (specify dpi (dots per inch) of an image, will automatically save output image at specified dpi)
    show_conformers : True or False (displays a point for each conformer of a certain compound at its relative energy on graph)
    show_gconf : True or False (displays the effect of multiple accessible conformers correction if applied)

Tips and Troubleshooting

  • The python file doesn’t need to be in the same folder as the Gaussian files. Just set the location of GoodVibes.py in the $PATH variable of your system (this is not necessary if installed with pip or conda)
  • It is possible to run on any number of files at once using wildcards to specify all of the Gaussian files in a directory (specify *.out or *.log)
  • File names not in the form of filename.log or filename.out are not read, however more file extensions can be added with the option --custom_ext
  • The script will not work if terse output was requested in the Gaussian job
  • Problems may occur with Restart Gaussian jobs due to missing information in the output file.

Papers citing GoodVibes

  1. Li, Y.; Du, S. RSC Adv. 2016, 6, 84177-84186 DOI: 10.1039/C6RA16321A
  2. Myllys, N.; Elm, J.; Kurtén, T. Comp. Theor. Chem. 2016, 1098, 1–12 DOI: 10.1016/j.comptc.2016.10.015
  3. Kiss, E.; Campbell, C. D.; Driver, R. W.; Jolliffe, J. D.; Lang, R.; Sergeieva, T.; Okovytyy, S.; Paton, R. S.; Smith, M. D. Angew. Chem. Int. Ed. 2016, 128 14017-14021 DOI: 10.1002/ange.201608534
  4. Mohamed, S.; Krenske, E. H.; Ferro, V. Org. Biomol. Chem. 2016, 14, 2950-2960 DOI: 10.1039/c6ob00283h
  5. Deb, A.; Hazra, A.; Peng, Q.; Paton, R. S.; Maiti, D. J. Am. Chem. Soc. 2017, 139, 763–775 DOI: 10.1021/jacs.6b10309
  6. Simón, L.; Paton, R. S. J. Org. Chem. 2017, 82, 3855-3863 DOI: 10.1021/acs.joc.7b00540
  7. Grayson, M. N. J. Org. Chem. 2017, 82, 4396–4401 DOI: 10.1021/acs.joc.7b00521
  8. Duarte, F.; Paton, R. S. J. Am. Chem. Soc. 2017, 139, 8886-8896 DOI: 10.1021/jacs.7b02468
  9. Elm, J. J. Phys. Chem. A 2017, 121, 8288−8295 DOI: 10.1021/acs.jpca.7b08962
  10. Münster, N.; Parker, N. A.; van Dijk, L.; Paton, R. S.; Smith, M. D. Angew. Chem. Int. Ed. 2017, 56, 9468-9472 DOI: 10.1002/anie.201705333
  11. Mekareeya, A.; Walker, P. R.; Couce-Rios, A.; Campbell, C. D.; Steven, A.; Paton, R. S.; Anderson, E. A. J. Am. Chem. Soc. 2017, 139, 10104–10114 DOI 10.1021/jacs.7b05436
  12. Alegre-Requena, J. V.; Marqués-López, E.; Herrera, R. P. ACS Catal. 2017, 7, 6430–6439 DOI: 10.1021/acscatal.7b02446
  13. Elm, J. J. Phys. Chem. A 2017, 121, 8288–8295 DOI: 10.1021/acs.jpca.7b08962
  14. Li, Y.; Jackson, K. E.; Charlton, A.; Le Neve-Foster, B.; Khurshid, A.; Rudy, H.-K. A.; Thompson, A. L.; Paton, R. S.; Hodgson, D. M. J. Org. Chem. 2017, 82, 10479-10488 DOI: 10.1021/acs.joc.7b01954
  15. Alegre-Requena, J. V.; Marqués-López, E.; Herrera, R. P. Chem. Eur. J. 2017, 23, 15336–15347DOI: 10.1002/chem.201702841
  16. Funes‐Ardoiz, I.; Nelson, D. J.; Maseras, F. Chem. Eur. J. 2017, 23, 16728–16733 DOI: 10.1002/chem.201702331
  17. Morris, D. S.; van Rees, K.; Curcio, M.; Cokoja, M.; Kühn, F. E.; Duarte, F.; Love, J. B. Catal. Sci. Technol. 2017, 5644–5649 DOI: 10.1039/C7CY01728F
  18. Elm, J.; Passananti, M.; Kurtén, T.; Vehkamäki, H. J. Phys. Chem. A 2017, 121, 6155–6164 DOI: 10.1021/acs.jpca.7b05658
  19. De Silvestro, I.; Drew, S. L.; Nichol, G. S.; Duarte, F.; Lawrence, A. L. Angew. Chem. Int. Ed. 2017, 56, 6813–6817 DOI: 10.1002.anie.201701481
  20. Funes‐Ardoiz, I.; Nelson, D. J.; Maseras, F. Chem. Eur. J. 2017 DOI: 10.1002/chem.201702331
  21. Besora, M.; Vidossich, P.; Lledos, A.; Ujaque, G.; Maseras, F. J. Phys. Chem. A 2018, 122, 1392–1399 DOI: 10.1021/acs.jpca.7b11580
  22. Harada, T. J. Org. Chem. 2018, 83, 7825–7835 DOI: 10.1021/acs.joc.8b00712
  23. Lewis, R. D.; Garcia-Borràs, M.; Chalkley, M. J.; Buller, A. R.; Houk, K. N.; Kan, S. B. J.; Arnold, F. H. Proc. Natl. Acad. Sci. 2018, 115, 7308-7313 DOI: 10.1073/pnas.1807027115
  24. Hojoon Park, Nikita Chekshin, Peng-Xiang Shen, Jin-Quan Yu, ACS Catalysis 2018, 8, 9292–9297 DOI: 10.1021/acscatal.8b03014
  25. Pupo, G.; Ibba, F.; Ascough, D. M. H.; Vicini, A. C.; Ricci, P.; Christensen, K.; Morphy, J. R.; Brown, J. M.; Paton, R. S.; Gouverneur, V. Science 2018, 360, 638–642 DOI: 10.1126/science.aar7941
  26. Ye, J.; Kalvet, I.; Schoenebeck, F.; Rovis, T. Nature Chem. 2018, 10, 1037–1041 DOI: 10.1038/s41557-018-0085-9
  27. Green, N. J.; Connolly, C. A.; Rietdijk, K. P. W.; Nichol, G. S.; Duarte, F.; Lawrence, A. L. Angew. Chem. Int. Ed. 2018, 57, 6198–6202. DOI: 10.1002/anie.201802125
  28. dos Passos Gomes, G.; Loginova, Y.; Vatsadze, S. Z.; Alabugin, I. V. J. Am. Chem. Soc. 2018, 140, 14272-14288 DOI: 10.1021.jacs.8b08513
  29. Wodrich, M. D.; Busch, M.; Corminboeuf, C. Helv. Chim. Acta 2018, 101, e1800107 DOI: 10.1002/hlca.201800107
  30. Hilton, M. C.; Zhang, X.; Boyle, B. T.; Alegre-Requena, J. V.; Paton, R. S.; McNally, A. Science 2018, 362, 799-804 DOI: 10.1126/science.aas8961
  31. Simon, L. Org. Biomol. Chem. 2018, 16, 2225–2238 DOI: 10.1039/c7ob02875j
  32. Audic, B.; Wodrich, M. D.; Cramer, N. Chem. Sci. 2019, 10, 781-787 DOI: 10.1039/C8SC04385J
  33. Tuguldurova, V. P.; Fateev, A. V.; Poleshchuk, O. K.; Vodyankina, O. V. Phys. Chem. Chem. Phys. 2019, 21, 9326--9334 DOI: 10.1039/c8cp07270a
  34. Fischer, T.; Bamberger, J.; Gomez‐Martinez, M.; Piekarski, D. G.; Garcia Mancheño, O. Angew Chem. Int. Ed. 2019, 58, 3217–3221 DOI: 10.1002/anie.201812031
  35. Svatunek, D.; Houszka, N.; Hamlin, T. A.; Bickelhaupt, F. M.; Mikula, H. Chem. Eur. J. 2019, 25, 754–758 DOI: 10.1002/chem.201805215
  36. Green, S.; Montgomery, H.; Benton, T. R.; Chan, N.; Nelson, H. DOI: doi.org/10.26434/chemrxiv.7824755.v1
  37. Putatunda, S.; Alegre-Requena, J. V.; Meazza, M.; Franc, M.; Rohal'ova, D.; Vemuri, P.; Cısarova, I.; Herrera, R. P.; Rios, R.; Vesely, J.Chem. Sci. 2019, 10, 4107–4115 DOI: doi.org/10.1039/c8sc05258a

References for the underlying theory

  1. Ribeiro, R. F.; Marenich, A. V.; Cramer, C. J.; Truhlar, D. G. J. Phys. Chem. B 2011, 115, 14556-14562 DOI: 10.1021/jp205508z
  2. Grimme, S. Chem. Eur. J. 2012, 18, 9955–9964 DOI: 10.1021/jp509921r
  3. Li, Y.; Gomes, J.; Sharada, S. M.; Bell, A. T.; Head-Gordon, M. J. Phys. Chem. C 2015, 119, 1840-1850 DOI: 10.1002/chem.201200497
  4. Alecu, I. M.; Zheng, J.; Zhao, Y.; Truhlar, D. G.; J. Chem. Theory Comput. 2010, 6, 2872-2887 DOI: 10.1021/ct100326h
  5. Mammen, M.; Shakhnovich, E. I.; Deutch, J. M.; Whitesides, G. M. J. Org. Chem. 1998, 63, 3821-3830 DOI: 10.1021/jo970944f

License: CC-BY

Project details


Download files

Download the file for your platform. If you're not sure which to choose, learn more about installing packages.

Files for goodvibes, version 3.0.1
Filename, size File type Python version Upload date Hashes
Filename, size goodvibes-3.0.1-py2.py3-none-any.whl (6.4 MB) File type Wheel Python version py2.py3 Upload date Hashes View hashes
Filename, size goodvibes-3.0.1.tar.gz (6.3 MB) File type Source Python version None Upload date Hashes View hashes

Supported by

Elastic Elastic Search Pingdom Pingdom Monitoring Google Google BigQuery Sentry Sentry Error logging AWS AWS Cloud computing DataDog DataDog Monitoring Fastly Fastly CDN SignalFx SignalFx Supporter DigiCert DigiCert EV certificate StatusPage StatusPage Status page