12.4. Database Modification

Note that the RMG-Py database is written in Python code where line indentions determine the scope. When modifying the database, be sure to preserve all line indentions shown in the examples.

12.4.1. Modifying the Thermo Database

12.4.1.1. Creating Thermo Libraries

12.4.1.2. Adding Thermo Groups

12.4.1.3. Adding Thermo to the Depository

12.4.2. Modifying the Kinetics Database

For the casual user, it is recommended to use either a kinetic library or add to the training set instead of modifying the kinetic groups.

Put kinetic parameters into a kinetic library when:

  • A set of reaction rates were optimized together
  • You know the reaction rate is not generalizable to similar species (perhaps due to catalysis or aromatic structures)
  • No family exists for the class of reaction
  • You are not confident about the accuracy of kinetic parameters

Put kinetic parameters into the training set when:

  • You are confident on the accurcy of the kinetic parameter
  • You wish for the reaction to be generalized to similar reactions in your mechanism

12.4.2.1. Adding Reaction Family

There are several places in the RMG-database and RMG-Py source code where reaction family details are hard-coded. You should check all these when you create a new reaction family. Here are some of the places:

  • RMG-database/input/kinetics/families/[family name]
    • add folder for your family name
    • create groups.py, rules.py and a template folder with species dictionary and reactions.py.
    • fill the files with rate data that you plan to use.
    • Many tools exist to help with the conversion process:
      • convertKineticsLibraryToTrainingReactions.ipynb in RMG-database/scripts
      • importChemkinLibrary.py in RMG-database/scripts
  • rmgpy.data.kinetics.family
    • applyRecipe: swapping the atom labels (eg. *1 and *2) around
    • getReactionPairs: figuring out which species becomes which for flux analyses
    • __generateReactions: correcting degeneracy eg. dividing by 2 for radical recombination
  • rmgpy.data.kinetics.rules
    • processOldLibraryEntry: determining units when importing RMG-Java database
    • getAllRules: for radical recombination add reverse templates
  • rmgpy.data.kinetics.groups
    • getReactionTemplate: for radical recombination duplicate the template
  • RMG-database/input/kinetics/families/recommended.py
    • allows the usage of the database with the recommended families.

12.4.2.2. Creating Kinetics Libraries

To add a reaction library, simply create a folder bearing the library’s name under RMG-database/input/kinetics/libraries. You’ll need to create two files: dictionary.txt and reactions.py. The dictionary file contains the Adjacency lists for all relevant species (can be generated using the Molecule Search function of the rmg website, while the reactions file specifies the kinetics. To conform to RMG’s format, simply copy and modify an existing library.

At the top of the reactions file fill in the name and short (one line) and long descriptions. The name must be identical to the folder’s name. Then list the kinetics entries, each with a unique index number. The following formats are accepted as kinetics entries:

Arrhenius of the form \(k(T) = A \left( \frac{T}{T_0} \right)^n \exp \left( -\frac{E_\mathrm{a}}{RT} \right)\) (see Arrhenius Class for details):

entry(
index = 1,
label = "H + O2 <=> O + OH",
degeneracy = 1,
kinetics = Arrhenius(A=(9.841e+13, 'cm^3/(mol*s)'), n=0, Ea=(15310, 'cal/mol'), T0=(1, 'K')),
shortDesc = u"This is a short description limited to one line, e.g. 'CBS-QB3'",
longDesc = u"""This is a long description, unlimited by number of lines.
These descriptions can be added to every kinetics type.""")

MultiArrhenius is the sum of multiple Arrhenius expressions (all apply to the same temperature range) (see MultiArrhenius Class for details):

entry(
index = 2,
label = "O + H2 <=> H + OH",
degeneracy = 1,
        duplicate = True,
kinetics = MultiArrhenius(
        arrhenius = [Arrhenius(A=(3.848e+12, 'cm^3/(mol*s)'), n=0, Ea=(7950, 'cal/mol'), T0=(1, 'K')),
        Arrhenius(A=(6.687e+14, 'cm^3/(mol*s)'), n=0, Ea=(19180, 'cal/mol'), T0=(1, 'K'))]))

ThirdBody for pressure dependent reactions of the sort H2 + M <=> H + H + M. efficiencies are optional and specify the factor by which the rate is multiplies if the mentioned species is the third body collider. Note that for complex efficiency behaviour, an efficiency of 0 can be set, and a seperate specific reaction can be defined (see ThirdBody Class for details):

entry(
index = 3,
label = "H2 <=> H + H",
degeneracy = 1,
kinetics = ThirdBody(
        arrheniusLow = Arrhenius(A=(4.58e+19, 'cm^3/(mol*s)'), n=-1.4, Ea=(104390, 'cal/mol'), T0=(1, 'K')),
        efficiencies = {'[Ar]': 0, 'N#N': 1.01, '[H][H]': 2.55, 'O': 12.02, '[C-]#[O+]': 1.95, 'O=C=O': 3.83, 'C': 2.00, 'C=O': 2.50, 'CO': 3.00, 'CC': 3.00}))

entry(
index = 4,
label = "H2 + Ar <=> H + H + Ar",
degeneracy = 1,
kinetics = Arrhenius(A=(5.176e+18, 'cm^3/(mol*s)'), n= 1.1, Ea=(104390, 'cal/mol'), T0=(1, 'K')))

Troe for pressure dependent reactions (see Troe Class for details):

entry(
index = 5,
label = "H + O2 <=> HO2",
degeneracy = 1,
kinetics = Troe(
        arrheniusHigh = Arrhenius(A=(4.565e+12, 'cm^3/(mol*s)'), n=0.44, Ea=(0, 'cal/mol'), T0=(1, 'K')),
        arrheniusLow = Arrhenius( A=(6.37e+20, 'cm^6/(mol^2*s)'), n = -1.72, Ea = (525, 'cal/mol'), T0 = (1, 'K')),
        alpha=0.5, T3=(30, 'K'), T1=(90000, 'K'), T2=(90000, 'K'),
        efficiencies = {'[Ar]': 0.6, '[He]': 0.71, 'N#N': 0.96, '[H][H]': 1.87, '[O][O]': 0.75, 'O': 15.81, '[C-]#[O+]': 1.90, 'O=C=O': 3.45, 'C': 2.00, 'C=O': 2.50, 'CO': 3.00, 'CC': 3.00}))

Lindemann (see Lindemann Class for details):

entry(
    index = 6,
    label = "CO + O <=> CO2",
    degeneracy = 1,
    kinetics = Lindemann(
        arrheniusHigh = Arrhenius(A=(1.88e+11, 'cm^3/(mol*s)'), n=0, Ea=(2430, 'cal/mol'), T0=(1, 'K')),
        arrheniusLow = Arrhenius(A = (1.4e+21, 'cm^6/(mol^2*s)'), n = -2.1, Ea = (5500, 'cal/mol'), T0 = (1, 'K')),
        efficiencies = {'[Ar]': 0.87, '[He]': 2.50, 'O': 12.00, '[C-]#[O+]': 1.90, 'O=C=O': 3.80, 'C': 2.00, 'C=O': 2.50, 'CO': 3.00, 'CC': 3.00}))

PDepArrhenius where each Arrhenius expression corresponds to a different pressure, as specified. Allowed pressure units are Pa, bar, atm, torr, psi, mbar (see PDepArrhenius Class for details):

entry(
    index = 7,
    label = "HCO <=> H + CO",
    degeneracy = 1,
    kinetics = PDepArrhenius(
        pressures = ([1, 10, 20, 50, 100], 'atm'),
        arrhenius = [
            Arrhenius(A=(9.9e+11, 's^-1'), n=-0.865, Ea=(16755, 'cal/mol'), T0=(1, 'K')),
            Arrhenius(A=(7.2e+12, 's^-1'), n=-0.865, Ea=(16755, 'cal/mol'), T0=(1, 'K')),
            Arrhenius(A=(1.3e+13, 's^-1'), n=-0.865, Ea=(16755, 'cal/mol'), T0=(1, 'K')),
            Arrhenius(A=(2.9e+13, 's^-1'), n=-0.865, Ea=(16755, 'cal/mol'), T0=(1, 'K')),
            Arrhenius(A=(5.3e+13, 's^-1'), n=-0.865, Ea=(16755, 'cal/mol'), T0=(1, 'K'))]))

MultiPDepArrhenius (see MultiPDepArrhenius Class for details):

entry(
    index = 8,
    label = "N2H2 <=> NNH + H",
    degeneracy = 1,
    duplicate = True,
    kinetics = MultiPDepArrhenius(
        arrhenius = [
            PDepArrhenius(
                pressures = ([0.1, 1, 10], 'atm'),
                arrhenius = [
                    Arrhenius(A=(5.6e+36, '1/s'), n=-7.75, Ea=(70250.4, 'cal/mol'), T0=(1, 'K')),
                    Arrhenius(A=(1.8e+40, '1/s'), n=-8.41, Ea=(73390, 'cal/mol'), T0=(1, 'K')),
                    Arrhenius(A=(3.1e+41, '1/s'), n=-8.42, Ea=(76043, 'cal/mol'), T0=(1, 'K'))]),
            PDepArrhenius(
                pressures = ([0.1, 1, 10], 'atm'),
                arrhenius = [
                    Arrhenius(A=(1.6e+37, '1/s'), n=-7.94, Ea=(70757, 'cal/mol'), T0=(1, 'K')),
                    Arrhenius(A=(2.6e+40, '1/s'), n=-8.53, Ea=(72923, 'cal/mol'), T0=(1, 'K')),
                    Arrhenius(A=(1.3e+44, '1/s'), n=-9.22, Ea=(77076, 'cal/mol'), T0=(1, 'K'))])]))

Chebyshev (see Chebyshev Class for details):

entry(
    index = 9,
    label = "CH3 + OH <=> CH2(S) + H2O",
    degeneracy = 1,
    kinetics = Chebyshev(
        coeffs = [
            [12.4209, -0.799241, -0.299133, -0.0143012],
            [0.236291, 0.856853, 0.246313, -0.0463755],
            [-0.0827561, 0.0457236, 0.105699, 0.057531],
            [-0.049145, -0.0760609, -0.0214574, 0.0247001],
            [-0.00664556, -0.0412733, -0.0308561, -0.00959838],
            [0.0111919, -0.00649914, -0.0106088, -0.0137528],
        ],
        kunits='cm^3/(mol*s)', Tmin=(300, 'K'), Tmax=(3000, 'K'), Pmin=(0.0013156, 'atm'), Pmax=(131.56, 'atm')))

12.4.2.3. Adding a specific collider

Only the Troe and Lindemann pressure dependent formats could be defined with a specific species as a third body collider, if needed. For example:

entry(
    index = 10,
    label = "SO2 + O <=> SO3",
    degeneracy = 1,
    kinetics = Troe(
        arrheniusHigh = Arrhenius(A=(3.7e+11, 'cm^3/(mol*s)'), n=0, Ea=(1689, 'cal/mol'), T0=(1, 'K')),
        arrheniusLow = Arrhenius(A=(2.4e+27, 'cm^6/(mol^2*s)'), n=-3.6, Ea=(5186, 'cal/mol'), T0=(1, 'K')),
        alpha = 0.442, T3=(316, 'K'), T1=(7442, 'K'), efficiencies={'O=S=O': 10, 'O': 10, 'O=C=O': 2.5, 'N#N': 0}))

entry(
    index = 11,
    label = "SO2 + O (+N2) <=> SO3 (+N2)",
    degeneracy = 1,
    kinetics = Troe(
        arrheniusHigh = Arrhenius(A=(3.7e+11, 'cm^6/(mol^2*s)'), n=0, Ea=(1689, 'cal/mol'), T0=(1, 'K')),
        arrheniusLow = Arrhenius(A=(2.9e+27, 'cm^9/(mol^3*s)'), n=-3.58, Ea=(5206, 'cal/mol'), T0=(1, 'K')),
        alpha=0.43, T3=(371, 'K'), T1=(7442, 'K'), efficiencies={}))

12.4.2.4. Adding New Kinetic Groups and Rate Rules

12.4.2.5. Decide on a Template

First you need to know the template for your reaction to decide whether or not to create new groups:

  1. Type your reaction into the kinetics search at http://rmg.mit.edu/database/kinetics/search/
  2. Select the correct reaction
  3. In the results search for “(RMG-Py rate rules)” and select that link. The kinetic family listed is the family of interest.
  4. Scroll to the bottom and look at the end of the long description. There may be very long description of the averaging scheme, but the template for the reaction is the very last one listed:
../../../_images/GroupSearch.png

Now you must determine whether the chosen template is appropriate. A good rule of thumb is to see if the all neighbours of the reacting atoms are as specified as possible. For example, assume your species is ethanol

../../../_images/ethanol.png

and RMG suggests the group:

label = "C_sec",
group =
"""
1 *1 Cs  0 {2,S} {3,S} {4,S}
2 *2 H   0 {1,S}
3    R!H 0 {1,S}
4    R!H 0 {1,S}
""",

If you use the suggested groups you will not capture the effect of the alcohol group. Therefore it is better to make a new group.

label = "C/H2/CsO",
group =
"""
1 *1 Cs  0 {2,S} {3,S} {4,S} {5,S}
2 *2 H  0 {1,S}
3    H  0 {1,S}
4    O  0 {1,S}
5    Cs 0 {1,S}
""",

If you have determined the suggested groups is appropriate, skip to Adding Training Reactions or Adding Kinetic Rules. Otherwise proceed to the next section for instructions on creating the new group.

12.4.2.6. Creating a New Group

In the family’s groups.py, you will need to add an entry of the format:

entry(
        index = 61,
        label = "C_sec",
        group =
"""
1 *1 Cs   0 {2,S} {3,S} {4,S} {5,S}
2 *2 H   0 {1,S}
3    C   0 {1,S}
4    H   0 {1,S}
5    R!H 0 {1,S}
""",
        kinetics = None,
        reference = None,
        referenceType = "",
        shortDesc = u"""""",
        longDesc = u"""""",
)
  • The index can be any number not already present in the set
  • The label is the name of the group.
  • The group is the group adjacency list with the starred reacting atoms.
  • The other attributes do not need to be filled for a group

Next, you must enter your new group into the tree. At the bottom of groups.py you will find the trees. Place your group in the appropriate position. In the example given in the previous section, the new group would be added under the C_sec.

L1: X_H
        L2: H2
        L2: Cs_H
                L3: C_pri
                L3: C_sec
                        L4: C/H2/CsO
                L3: C_ter

12.4.2.7. Adding Kinetic Rules

Rules give generalized kinetic parameters for a specific node template. In most cases, your kinetic parameters describe a specific reaction in which case you will want to add your reaction to the training set.

The rule must be added into rules.py in the form:

entry(
        index = 150,
        label = "C/H/Cs3;O_rad/NonDeO",
        group1 =
"""
1 *1 Cs  0 {2,S} {3,S} {4,S} {5,S}
2 *2 H  0 {1,S}
3    Cs 0 {1,S}
4    Cs 0 {1,S}
5    Cs 0 {1,S}
""",
        group2 =
"""
1 *3 O 1 {2,S}
2    O 0 {1,S}
""",
        kinetics = ArrheniusEP(
                A = (2800000000000.0, 'cm^3/(mol*s)', '*|/', 5),
                n = 0,
                alpha = 0,
                E0 = (16.013, 'kcal/mol', '+|-', 1),
                Tmin = (300, 'K'),
                Tmax = (1500, 'K'),
        ),
        reference = None,
        referenceType = "",
        rank = 5,
        shortDesc = u"""Curran et al. [8] Rate expressions for H atom abstraction from fuels.""",
        longDesc =
u"""
[8] Curran, H.J.; Gaffuri, P.; Pit z, W.J.; Westbrook, C.K. Combust. Flame 2002, 129, 253.
Rate expressions for H atom abstraction from fuels.

pg 257 A Comprehensive Modelling Study of iso-Octane Oxidation, Table 1. Radical:HO2, Site: tertiary (c)

Verified by Karma James
""",
)
  • The index can be any number not already used in rules.py.
  • The label is the name of the rule.
  • The groups must have the adjacency list of the respective groups. Between them they should have all starred atoms from the recipe.
  • The value and units of kinetic parameters must be given.
    • Multiplicative uncertainty is given as '*\|/,' 5 meaning within a factor of 5
    • Additive uncertainty is given as '+\|/-', 2 meaning plus or minus 2.
  • Rank determines the priority of the rule when compared with other rules.
  • The short description will appear in the annotated chemkin file.
  • The long description only appears in the database.

12.4.2.8. Adding Training Reactions

If you know the kinetics of a specific reaction, rather than a rate rule for a template, you can add the kinetics to the database training set. By default, RMG creates new rate rules from this training set, which in turn benefits the kinetics of similar reactions. The new rate rules are formed by matching the reaction to the most most specific template nodes within the reaction’s respective family. If you do not want the training depository reactions to create new rate rules in the database, set the option for kineticsDepositories within the database field in your input file to

kineticsDepositories = ['!training'],

Currently, RMG’s rate rule estimates overrides all kinetics depository kinetics, including training reactions. Unless the training reaction’s rate rule ranks higher than the existing node, it will not be used. If you want the training reaction to override the rate rule estimates, you should put the reaction into a reaction library or seed mechanism.

The easiest way to add training reactions to the database is via the RMG website. First, search for the reaction using http://rmg.mit.edu/database/kinetics/search/ . This will automatically search the existing RMG database for the reaction, as well as identify the reaction family template that this reaction matches. If the reaction does not match any family, then it cannot be added to the training reactions. Click the ‘Create training rate from average’ button underneath the kinetics plot for the reaction and edit the kinetics and reference descriptions for the reaction. The atom labels marking the reaction recipe actions (lose bond, add radical, etc.) will already be automatically labeled for you. After editing the reaction data, write a short message for the reaction added under the ‘Summary of changes’ field, then click ‘Save.’ You will need an account for the RMG website to make an entry.

Note

If you are entering the reaction in the reverse direction of the family, you must still label the reactants and products with the atomLabels of the original reaction template. Otherwise, RMG will not be able to locate the nodes in the group tree to match the reaction.

Entries added in the reverse direction of the original template will use the current RMG job’s thermo database to estimate the kinetics in the forward direction. Therefore this value can differ depending on the order of thermo libraries used when running a job.

If adding the training reaction manually, first identify the reaction family of the reaction, then go to the family’s folder in RMG-database/input/kinetics/families/. Create a new kinetics entry in the training.py file. Make sure to apply the reaction recipe labels properly for the reactants and products.

12.4.2.9. Pitfalls

Be careful with the specificity when naming neighbouring atoms. On upper nodes, you should try to be general so that you do not exclude reactions.

Sibling nodes must be exclusive from one another so that there is no question which group a molecule qualifies as. However, you do not need to be exhaustive and list out every possibility.

Be sure to give errors whenever adding rules. If you don’t know the uncertainty, why do you trust the kinetics?

After you are done always check via populate reactions or the website, that your modifications are behaving the way you expect.

Caveat regarding how rate rules are used by RMG and the rate parameters you input: because tunneling is important for many chemical reactions, the rate of a reaction may not be easily represented by a bi-Arrhenius fit. 3-parameter fits are more common. However, the resulting fit may report an ‘activation energy’ that is much different (possibly by 10+ kcals) than the the true barrier height. When RMG is assembling pressure-dependent networks, it will use barrier heights from rate rules. This can lead to very inaccurate rate calculations. To avoid this issue, try to ensure that your fitted arrhenius activation energy truly does reflect the reaction barrier height.