# -*- coding: utf-8 -*-
'''Chemical Engineering Design Library (ChEDL). Utilities for process modeling.
Copyright (C) 2017, Caleb Bell <Caleb.Andrew.Bell@gmail.com>
Permission is hereby granted, free of charge, to any person obtaining a copy
of this software and associated documentation files (the "Software"), to deal
in the Software without restriction, including without limitation the rights
to use, copy, modify, merge, publish, distribute, sublicense, and/or sell
copies of the Software, and to permit persons to whom the Software is
furnished to do so, subject to the following conditions:
The above copyright notice and this permission notice shall be included in all
copies or substantial portions of the Software.
THE SOFTWARE IS PROVIDED "AS IS", WITHOUT WARRANTY OF ANY KIND, EXPRESS OR
IMPLIED, INCLUDING BUT NOT LIMITED TO THE WARRANTIES OF MERCHANTABILITY,
FITNESS FOR A PARTICULAR PURPOSE AND NONINFRINGEMENT. IN NO EVENT SHALL THE
AUTHORS OR COPYRIGHT HOLDERS BE LIABLE FOR ANY CLAIM, DAMAGES OR OTHER
LIABILITY, WHETHER IN AN ACTION OF CONTRACT, TORT OR OTHERWISE, ARISING FROM,
OUT OF OR IN CONNECTION WITH THE SOFTWARE OR THE USE OR OTHER DEALINGS IN THE
SOFTWARE.'''
from __future__ import division
__all__ = ['smarts_fragment', 'Joback', 'J_BIGGS_JOBACK_SMARTS',
'J_BIGGS_JOBACK_SMARTS_id_dict']
from collections import namedtuple, Counter
from pprint import pprint
from thermo.utils import to_num, horner, exp
try:
from rdkit import Chem
from rdkit.Chem import Descriptors
from rdkit.Chem import AllChem
from rdkit.Chem import rdMolDescriptors
hasRDKit = True
except:
# pragma: no cover
hasRDKit = False
rdkit_missing = 'RDKit is not installed; it is required to use this functionality'
J_BIGGS_JOBACK_SMARTS = [["Methyl","-CH3", "[CX4H3]"],
["Secondary acyclic", "-CH2-", "[!R;CX4H2]"],
["Tertiary acyclic",">CH-", "[!R;CX4H]"],
["Quaternary acyclic", ">C<", "[!R;CX4H0]"],
["Primary alkene", "=CH2", "[CX3H2]"],
["Secondary alkene acyclic", "=CH-", "[!R;CX3H1;!$([CX3H1](=O))]"],
["Tertiary alkene acyclic", "=C<", "[$([!R;#6X3H0]);!$([!R;#6X3H0]=[#8])]"],
["Cumulative alkene", "=C=", "[$([CX2H0](=*)=*)]"],
["Terminal alkyne", u"≡CH","[$([CX2H1]#[!#7])]"],
["Internal alkyne",u"≡C-","[$([CX2H0]#[!#7])]"],
["Secondary cyclic", "-CH2- (ring)", "[R;CX4H2]"],
["Tertiary cyclic", ">CH- (ring)", "[R;CX4H]"],
["Quaternary cyclic", ">C< (ring)", "[R;CX4H0]"],
["Secondary alkene cyclic", "=CH- (ring)", "[R;CX3H1,cX3H1]"],
["Tertiary alkene cyclic", "=C< (ring)","[$([R;#6X3H0]);!$([R;#6X3H0]=[#8])]"],
["Fluoro", "-F", "[F]"],
["Chloro", "-Cl", "[Cl]"],
["Bromo", "-Br", "[Br]"],
["Iodo", "-I", "[I]"],
["Alcohol","-OH (alcohol)", "[OX2H;!$([OX2H]-[#6]=[O]);!$([OX2H]-a)]"],
["Phenol","-OH (phenol)", "[$([OX2H]-a)]"],
["Ether acyclic", "-O- (nonring)", "[OX2H0;!R;!$([OX2H0]-[#6]=[#8])]"],
["Ether cyclic", "-O- (ring)", "[#8X2H0;R;!$([#8X2H0]~[#6]=[#8])]"],
["Carbonyl acyclic", ">C=O (nonring)","[$([CX3H0](=[OX1]));!$([CX3](=[OX1])-[OX2]);!R]=O"],
["Carbonyl cyclic", ">C=O (ring)","[$([#6X3H0](=[OX1]));!$([#6X3](=[#8X1])~[#8X2]);R]=O"],
["Aldehyde","O=CH- (aldehyde)","[CX3H1](=O)"],
["Carboxylic acid", "-COOH (acid)", "[OX2H]-[C]=O"],
["Ester", "-COO- (ester)", "[#6X3H0;!$([#6X3H0](~O)(~O)(~O))](=[#8X1])[#8X2H0]"],
["Oxygen double bond other", "=O (other than above)","[OX1H0;!$([OX1H0]~[#6X3]);!$([OX1H0]~[#7X3]~[#8])]"],
["Primary amino","-NH2", "[NX3H2]"],
["Secondary amino acyclic",">NH (nonring)", "[NX3H1;!R]"],
["Secondary amino cyclic",">NH (ring)", "[#7X3H1;R]"],
["Tertiary amino", ">N- (nonring)","[#7X3H0;!$([#7](~O)~O)]"],
["Imine acyclic","-N= (nonring)","[#7X2H0;!R]"],
["Imine cyclic","-N= (ring)","[#7X2H0;R]"],
["Aldimine", "=NH", "[#7X2H1]"],
["Cyano", "-CN","[#6X2]#[#7X1H0]"],
["Nitro", "-NO2", "[$([#7X3,#7X3+][!#8])](=[O])~[O-]"],
["Thiol", "-SH", "[SX2H]"],
["Thioether acyclic", "-S- (nonring)", "[#16X2H0;!R]"],
["Thioether cyclic", "-S- (ring)", "[#16X2H0;R]"]]
J_BIGGS_JOBACK_SMARTS_id_dict = {i+1: j[2] for i, j in enumerate(J_BIGGS_JOBACK_SMARTS)}
J_BIGGS_JOBACK_SMARTS_str_dict = {i[1]: i[2] for i in J_BIGGS_JOBACK_SMARTS}
# Shi Chenyang's JRGUI code indicates he left the following list of smarts in
# favor of those above by J Biggs
SHI_CHENYANG_JOBACK_SMARTS = [
("-CH3", "[CH3;A;X4;!R]"),
("-CH2-", "[CH2;A;X4;!R]"),
(">CH-", "[CH1;A;X4;!R]"),
(">C<", "[CH0;A;X4;!R]"),
("=CH2", "[CH2;A;X3;!R]"),
("=CH-", "[CH1;A;X3;!R]"),
("=C<", "[CH0;A;X3;!R]"),
("=C=", "[$([CH0;A;X2;!R](=*)=*)]"),
("≡CH", "[$([CH1;A;X2;!R]#*)]"),
("≡C-", "[$([CH0;A;X2;!R]#*)]"),
("-CH2- (ring)", "[CH2;A;X4;R]"),
(">CH- (ring)", "[CH1;A;X4;R]"),
(">C< (ring)", "[CH0;A;X4;R]"),
("=CH- (ring)", "[CH1;X3;R]"),
("=C< (ring)", "[CH0;X3;R]"),
("-F", "[F]"),
("-Cl", "[Cl]"),
("-Br", "[Br]"),
("-I", "[I]"),
("-OH (alcohol)", "[O;H1;$(O-!@[C;!$(C=!@[O,N,S])])]"),
("-OH (phenol)", "[O;H1;$(O-!@c)]"),
("-O- (nonring)", "[OH0;X2;!R]"),
("-O- (ring)", "[OH0;X2;R]"),
(">C=O (nonring)", "[CH0;A;X3;!R]=O"),
(">C=O (ring)", "[CH0;A;X3;R]=O"),
("O=CH- (aldehyde)", "[CH;D2;$(C-!@C)](=O)"),
("-COOH (acid)", "[$(C-!@[A;!O])](=O)([O;H,-])"),
("-COO- (ester)", "C(=O)[OH0]"),
("=O (other than above)", "[OX1]"),
("-NH2", "[NH2;X3]"),
(">NH (nonring)", "[NH1;X3;!R]"),
(">NH (ring)", "[NH1;X3;R]"),
(">N- (nonring)", "[NH0;X3;!R]"),
("-N= (nonring)", "[NH0;X2;!R]"),
("-N= (ring)", "[NH0;X2;R]"),
("=NH", "[NH1;X2]"),
("-CN", "C#N"),
("-NO2", "N(=O)=O"),
("-SH", "[SH1]"),
("-S- (nonring)", "[SH0;!R]"),
("-S- (ring)", "[SH0;R]")]
SHI_CHENYANG_JOBACK_SMARTS_id_dict = {i+1: j[1] for i, j in enumerate(SHI_CHENYANG_JOBACK_SMARTS)}
SHI_CHENYANG_JOBACK_SMARTS_str_dict = {i[0]: i[1] for i in SHI_CHENYANG_JOBACK_SMARTS}
joback_data_txt = u'''-CH3 0.0141 -0.0012 65 23.58 -5.10 -76.45 -43.96 1.95E+1 -8.08E-3 1.53E-4 -9.67E-8 0.908 2.373 548.29 -1.719
-CH2- 0.0189 0.0000 56 22.88 11.27 -20.64 8.42 -9.09E-1 9.50E-2 -5.44E-5 1.19E-8 2.590 2.226 94.16 -0.199
>CH- 0.0164 0.0020 41 21.74 12.64 29.89 58.36 -2.30E+1 2.04E-1 -2.65E-4 1.20E-7 0.749 1.691 -322.15 1.187
>C< 0.0067 0.0043 27 18.25 46.43 82.23 116.02 -6.62E+1 4.27E-1 -6.41E-4 3.01E-7 -1.460 0.636 -573.56 2.307
=CH2 0.0113 -0.0028 56 18.18 -4.32 -9.630 3.77 2.36E+1 -3.81E-2 1.72E-4 -1.03E-7 -0.473 1.724 495.01 -1.539
=CH- 0.0129 -0.0006 46 24.96 8.73 37.97 48.53 -8.00 1.05E-1 -9.63E-5 3.56E-8 2.691 2.205 82.28 -0.242
=C< 0.0117 0.0011 38 24.14 11.14 83.99 92.36 -2.81E+1 2.08E-1 -3.06E-4 1.46E-7 3.063 2.138 n. a. n. a.
=C= 0.0026 0.0028 36 26.15 17.78 142.14 136.70 2.74E+1 -5.57E-2 1.01E-4 -5.02E-8 4.720 2.661 n. a. n. a.
≡CH 0.0027 -0.0008 46 9.20 -11.18 79.30 77.71 2.45E+1 -2.71E-2 1.11E-4 -6.78E-8 2.322 1.155 n. a. n. a.
≡C- 0.0020 0.0016 37 27.38 64.32 115.51 109.82 7.87 2.01E-2 -8.33E-6 1.39E-9 4.151 3.302 n. a. n. a.
-CH2- (ring) 0.0100 0.0025 48 27.15 7.75 -26.80 -3.68 -6.03 8.54E-2 -8.00E-6 -1.80E-8 0.490 2.398 307.53 -0.798
>CH- (ring) 0.0122 0.0004 38 21.78 19.88 8.67 40.99 -2.05E+1 1.62E-1 -1.60E-4 6.24E-8 3.243 1.942 -394.29 1.251
>C< (ring) 0.0042 0.0061 27 21.32 60.15 79.72 87.88 -9.09E+1 5.57E-1 -9.00E-4 4.69E-7 -1.373 0.644 n. a. n. a.
=CH- (ring) 0.0082 0.0011 41 26.73 8.13 2.09 11.30 -2.14 5.74E-2 -1.64E-6 -1.59E-8 1.101 2.544 259.65 -0.702
=C< (ring) 0.0143 0.0008 32 31.01 37.02 46.43 54.05 -8.25 1.01E-1 -1.42E-4 6.78E-8 2.394 3.059 -245.74 0.912
-F 0.0111 -0.0057 27 -0.03 -15.78 -251.92 -247.19 2.65E+1 -9.13E-2 1.91E-4 -1.03E-7 1.398 -0.670 n. a. n. a.
-Cl 0.0105 -0.0049 58 38.13 13.55 -71.55 -64.31 3.33E+1 -9.63E-2 1.87E-4 -9.96E-8 2.515 4.532 625.45 -1.814
-Br 0.0133 0.0057 71 66.86 43.43 -29.48 -38.06 2.86E+1 -6.49E-2 1.36E-4 -7.45E-8 3.603 6.582 738.91 -2.038
-I 0.0068 -0.0034 97 93.84 41.69 21.06 5.74 3.21E+1 -6.41E-2 1.26E-4 -6.87E-8 2.724 9.520 809.55 -2.224
-OH (alcohol) 0.0741 0.0112 28 92.88 44.45 -208.04 -189.20 2.57E+1 -6.91E-2 1.77E-4 -9.88E-8 2.406 16.826 2173.72 -5.057
-OH (phenol) 0.0240 0.0184 -25 76.34 82.83 -221.65 -197.37 -2.81 1.11E-1 -1.16E-4 4.94E-8 4.490 12.499 3018.17 -7.314
-O- (nonring) 0.0168 0.0015 18 22.42 22.23 -132.22 -105.00 2.55E+1 -6.32E-2 1.11E-4 -5.48E-8 1.188 2.410 122.09 -0.386
-O- (ring) 0.0098 0.0048 13 31.22 23.05 -138.16 -98.22 1.22E+1 -1.26E-2 6.03E-5 -3.86E-8 5.879 4.682 440.24 -0.953
>C=O (nonring) 0.0380 0.0031 62 76.75 61.20 -133.22 -120.50 6.45 6.70E-2 -3.57E-5 2.86E-9 4.189 8.972 340.35 -0.350
>C=O (ring) 0.0284 0.0028 55 94.97 75.97 -164.50 -126.27 3.04E+1 -8.29E-2 2.36E-4 -1.31E-7 0. 6.645 n. a. n. a.
O=CH- (aldehyde) 0.0379 0.0030 82 72.24 36.90 -162.03 -143.48 3.09E+1 -3.36E-2 1.60E-4 -9.88E-8 3.197 9.093 740.92 -1.713
-COOH (acid) 0.0791 0.0077 89 169.09 155.50 -426.72 -387.87 2.41E+1 4.27E-2 8.04E-5 -6.87E-8 11.051 19.537 1317.23 -2.578
-COO- (ester) 0.0481 0.0005 82 81.10 53.60 -337.92 -301.95 2.45E+1 4.02E-2 4.02E-5 -4.52E-8 6.959 9.633 483.88 -0.966
=O (other than above) 0.0143 0.0101 36 -10.50 2.08 -247.61 -250.83 6.82 1.96E-2 1.27E-5 -1.78E-8 3.624 5.909 675.24 -1.340
-NH2 0.0243 0.0109 38 73.23 66.89 -22.02 14.07 2.69E+1 -4.12E-2 1.64E-4 -9.76E-8 3.515 10.788 n. a. n. a.
>NH (nonring) 0.0295 0.0077 35 50.17 52.66 53.47 89.39 -1.21 7.62E-2 -4.86E-5 1.05E-8 5.099 6.436 n. a. n. a.
>NH (ring) 0.0130 0.0114 29 52.82 101.51 31.65 75.61 1.18E+1 -2.30E-2 1.07E-4 -6.28E-8 7.490 6.930 n. a. n. a.
>N- (nonring) 0.0169 0.0074 9 11.74 48.84 123.34 163.16 -3.11E+1 2.27E-1 -3.20E-4 1.46E-7 4.703 1.896 n. a. n. a.
-N= (nonring) 0.0255 -0.0099 n. a. 74.60 n. a. 23.61 n. a. n. a. n. a. n. a. n. a. n. a. 3.335 n. a. n. a.
-N= (ring) 0.0085 0.0076 34 57.55 68.40 55.52 79.93 8.83 -3.84E-3 4.35E-5 -2.60E-8 3.649 6.528 n. a. n. a.
=NH n. a. n. a. n. a. 83.08 68.91 93.70 119.66 5.69 -4.12E-3 1.28E-4 -8.88E-8 n. a. 12.169 n. a. n. a.
-CN 0.0496 -0.0101 91 125.66 59.89 88.43 89.22 3.65E+1 -7.33E-2 1.84E-4 -1.03E-7 2.414 12.851 n. a. n. a.
-NO2 0.0437 0.0064 91 152.54 127.24 -66.57 -16.83 2.59E+1 -3.74E-3 1.29E-4 -8.88E-8 9.679 16.738 n. a. n. a.
-SH 0.0031 0.0084 63 63.56 20.09 -17.33 -22.99 3.53E+1 -7.58E-2 1.85E-4 -1.03E-7 2.360 6.884 n. a. n. a.
-S- (nonring) 0.0119 0.0049 54 68.78 34.40 41.87 33.12 1.96E+1 -5.61E-3 4.02E-5 -2.76E-8 4.130 6.817 n. a. n. a.
-S- (ring) 0.0019 0.0051 38 52.10 79.93 39.10 27.76 1.67E+1 4.81E-3 2.77E-5 -2.11E-8 1.557 5.984 n. a. n. a.'''
joback_groups_str_dict = {}
joback_groups_id_dict = {}
JOBACK = namedtuple('JOBACK', 'i, name, Tc, Pc, Vc, Tb, Tm, Hform, Gform, Cpa, Cpb, Cpc, Cpd, Hfus, Hvap, mua, mub')
for i, line in enumerate(joback_data_txt.split('\n')):
parsed = to_num(line.split('\t'))
j = JOBACK(i+1, *parsed)
joback_groups_str_dict[parsed[0]] = j
joback_groups_id_dict[i+1] = j
def smarts_fragment(catalog, rdkitmol=None, smi=None):
r'''Fragments a molecule into a set of unique groups and counts as
specified by the `catalog`. The molecule can either be an rdkit
molecule object, or a smiles string which will be parsed by rdkit.
Returns a dictionary of groups and their counts according to the
indexes of the catalog provided.
Parameters
----------
catalog : dict
Dictionary indexed by keys pointing to smarts strings, [-]
rdkitmol : mol, optional
Molecule as rdkit object, [-]
smi : str, optional
Smiles string representing a chemical, [-]
Returns
-------
counts : dict
Dictionaty of integer counts of the found groups only, indexed by
the same keys used by the catalog [-]
success : bool
Whether or not molecule was fully and uniquely fragmented, [-]
status : str
A string holding an explanation of why the molecule failed to be
fragmented, if it fails; 'OK' if it suceeds.
Notes
-----
Raises an exception if rdkit is not installed, or `smi` or `rdkitmol` is
not defined.
Examples
--------
Acetone:
>>> smarts_fragment(catalog=J_BIGGS_JOBACK_SMARTS_id_dict, smi='CC(=O)C')
({24: 1, 1: 2}, True, 'OK')
Sodium sulfate, (Na2O4S):
>>> smarts_fragment(catalog=J_BIGGS_JOBACK_SMARTS_id_dict, smi='[O-]S(=O)(=O)[O-].[Na+].[Na+]')
({29: 4}, False, 'Did not match all atoms present')
Propionic anhydride (C6H10O3):
>>> smarts_fragment(catalog=J_BIGGS_JOBACK_SMARTS_id_dict, smi='CCC(=O)OC(=O)CC')
({1: 2, 2: 2, 28: 2}, False, 'Matched some atoms repeatedly: [4]')
'''
if not hasRDKit: # pragma: no cover
raise Exception(rdkit_missing)
if rdkitmol is None and smi is None:
raise Exception('Either an rdkit mol or a smiles string is required')
if smi is not None:
rdkitmol = Chem.MolFromSmiles(smi)
if rdkitmol is None:
status = 'Failed to construct mol'
success = False
return {}, success, status
atom_count = len(rdkitmol.GetAtoms())
status = 'OK'
success = True
counts = {}
all_matches = {}
for key, smart in catalog.items():
patt = Chem.MolFromSmarts(smart)
hits = rdkitmol.GetSubstructMatches(patt)
if hits:
all_matches[smart] = hits
counts[key] = len(hits)
matched_atoms = set()
for i in all_matches.values():
for j in i:
matched_atoms.update(j)
if len(matched_atoms) != atom_count:
status = 'Did not match all atoms present'
success = False
# Check the atom aount again, this time looking for duplicate matches (only if have yet to fail)
if success:
matched_atoms = []
for i in all_matches.values():
for j in i:
matched_atoms.extend(j)
if len(matched_atoms) < atom_count:
status = 'Matched %d of %d atoms only' %(len(matched_atoms), atom_count)
success = False
elif len(matched_atoms) > atom_count:
status = 'Matched some atoms repeatedly: %s' %( [i for i, c in Counter(matched_atoms).items() if c > 1])
success = False
return counts, success, status
class Joback(object):
r'''Class for performing chemical property estimations with the Joback
group contribution method as described in [1]_ and [2]_. This is a very
common method with low accuracy but wide applicability. This routine can be
used with either its own automatic fragmentation routine, or user specified
groups. It is applicable to organic compounds only, and has only 41 groups
with no interactions between them. Each method's documentation describes
its accuracy. The automatic fragmentation routine is possible only because
of the development of SMARTS expressions to match the Joback groups by
Dr. Jason Biggs. The list of SMARTS expressions
was posted publically on the
`RDKit mailing list <https://www.mail-archive.com/rdkit-discuss@lists.sourceforge.net/msg07446.html>`_.
Parameters
----------
mol : rdkitmol or smiles str
Input molecule for the analysis, [-]
atom_count : int, optional
The total number of atoms including hydrogen in the molecule; this will
be counted by rdkit if it not provided, [-]
MW : float, optional
Molecular weight of the molecule; this will be calculated by rdkit if
not provided, [g/mol]
Tb : float, optional
An experimentally known boiling temperature for the chemical; this
increases the accuracy of the calculated critical point if provided.
[K]
Notes
-----
Be sure to check the status of the automatic fragmentation; not all
chemicals with the Joback method are applicable.
Approximately 68% of chemcials in the thermo database seem to be able to
be estimated with the Joback method.
Examples
--------
Analysis of Acetone:
>>> J = Joback('CC(=O)C')
>>> J.Hfus(J.counts)
5125.0
>>> J.Cpig(350)
84.69109750000001
>>> J.status
'OK'
All properties can be obtained in one go with the `estimate` method:
>>> pprint(J.estimate()) # doctest: +ELLIPSIS
{'Cpig': <bound method Joback.Cpig of <thermo.joback.Joback object at 0x...>>,
'Cpig_coeffs': [7.520000000000003,
0.26084,
-0.0001207,
1.545999999999998e-08],
'Gf': -154540.00000000003,
'Hf': -217829.99999999997,
'Hfus': 5125.0,
'Hvap': 29018.0,
'Pc': 4802499.604994407,
'Tb': 322.11,
'Tc': 500.5590049525365,
'Tm': 173.5,
'Vc': 0.0002095,
'mul': <bound method Joback.mul of <thermo.joback.Joback object at 0x...>>,
'mul_coeffs': [839.1099999999998, -14.99]}
The results for propionic anhydride (if the status is not OK) should not be
used.
>>> J = Joback('CCC(=O)OC(=O)CC')
>>> J.status
'Matched some atoms repeatedly: [4]'
>>> J.Cpig(300)
175.85999999999999
None of the routines need to use the automatic routine; they can be used
manually too:
>>> Joback.Tb({1: 2, 24: 1})
322.11
References
----------
.. [1] Joback, Kevin G. "A Unified Approach to Physical Property Estimation
Using Multivariate Statistical Techniques." Thesis, Massachusetts
Institute of Technology, 1984.
.. [2] Joback, K.G., and R.C. Reid. "Estimation of Pure-Component
Properties from Group-Contributions." Chemical Engineering
Communications 57, no. 1-6 (July 1, 1987): 233-43.
doi:10.1080/00986448708960487.
'''
calculated_Cpig_coeffs = None
calculated_mul_coeffs = None
def __init__(self, mol, atom_count=None, MW=None, Tb=None):
if type(mol) == Chem.rdchem.Mol:
self.rdkitmol = mol
else:
self.rdkitmol = Chem.MolFromSmiles(mol)
if atom_count is None:
self.rdkitmol_Hs = Chem.AddHs(self.rdkitmol)
self.atom_count = len(self.rdkitmol_Hs.GetAtoms())
else:
self.atom_count = atom_count
if MW is None:
self.MW = rdMolDescriptors.CalcExactMolWt(self.rdkitmol_Hs)
else:
self.MW = MW
self.counts, self.success, self.status = smarts_fragment(J_BIGGS_JOBACK_SMARTS_id_dict, rdkitmol=self.rdkitmol)
if Tb is not None:
self.Tb_estimated = self.Tb(self.counts)
else:
self.Tb_estimated = Tb
def estimate(self):
'''Method to compute all available properties with the Joback method;
returns their results as a dict. For the tempearture dependent values
Cpig and mul, both the coefficients and objects to perform calculations
are returned.
'''
# Pre-generate the coefficients or they will not be returned
self.mul(300)
self.Cpig(300)
estimates = {'Tb': self.Tb(self.counts),
'Tm': self.Tm(self.counts),
'Tc': self.Tc(self.counts, self.Tb_estimated),
'Pc': self.Pc(self.counts, self.atom_count),
'Vc': self.Vc(self.counts),
'Hf': self.Hf(self.counts),
'Gf': self.Gf(self.counts),
'Hfus': self.Hfus(self.counts),
'Hvap': self.Hvap(self.counts),
'mul': self.mul,
'mul_coeffs': self.calculated_mul_coeffs,
'Cpig': self.Cpig,
'Cpig_coeffs': self.calculated_Cpig_coeffs}
return estimates
@staticmethod
def Tb(counts):
r'''Estimates the normal boiling temperature of an organic compound
using the Joback method as a function of chemical structure only.
.. math::
T_b = 198.2 + \sum_i {T_{b,i}}
For 438 compounds tested by Joback, the absolute average error was
12.91 K and standard deviation was 17.85 K; the average relative error
was 3.6%.
Parameters
----------
counts : dict
Dictionary of Joback groups present (numerically indexed) and their
counts, [-]
Returns
-------
Tb : float
Estimated normal boiling temperature, [K]
Examples
--------
>>> Joback.Tb({1: 2, 24: 1})
322.11
'''
tot = 0.0
for group, count in counts.items():
tot += joback_groups_id_dict[group].Tb*count
Tb = 198.2 + tot
return Tb
@staticmethod
def Tm(counts):
r'''Estimates the melting temperature of an organic compound using the
Joback method as a function of chemical structure only.
.. math::
T_m = 122.5 + \sum_i {T_{m,i}}
For 388 compounds tested by Joback, the absolute average error was
22.6 K and standard deviation was 24.68 K; the average relative error
was 11.2%.
Parameters
----------
counts : dict
Dictionary of Joback groups present (numerically indexed) and their
counts, [-]
Returns
-------
Tm : float
Estimated melting temperature, [K]
Examples
--------
>>> Joback.Tm({1: 2, 24: 1})
173.5
'''
tot = 0.0
for group, count in counts.items():
tot += joback_groups_id_dict[group].Tm*count
Tm = 122.5 + tot
return Tm
@staticmethod
def Tc(counts, Tb=None):
r'''Estimates the critcal temperature of an organic compound using the
Joback method as a function of chemical structure only, or optionally
improved by using an experimental boiling point. If the experimental
boiling point is not provided it will be estimated with the Joback
method as well.
.. math::
T_c = T_b \left[0.584 + 0.965 \sum_i {T_{c,i}}
- \left(\sum_i {T_{c,i}}\right)^2 \right]^{-1}
For 409 compounds tested by Joback, the absolute average error was
4.76 K and standard deviation was 6.94 K; the average relative error
was 0.81%.
Appendix BI of Joback's work lists 409 estimated critical temperatures.
Parameters
----------
counts : dict
Dictionary of Joback groups present (numerically indexed) and their
counts, [-]
Tb : float, optional
Experimental normal boiling temperature, [K]
Returns
-------
Tc : float
Estimated critical temperature, [K]
Examples
--------
>>> Joback.Tc({1: 2, 24: 1}, Tb=322.11)
500.5590049525365
'''
if Tb is None:
Tb = Joback.Tb(counts)
tot = 0.0
for group, count in counts.items():
tot += joback_groups_id_dict[group].Tc*count
Tc = Tb/(0.584 + 0.965*tot - tot*tot)
return Tc
@staticmethod
def Pc(counts, atom_count):
r'''Estimates the critcal pressure of an organic compound using the
Joback method as a function of chemical structure only. This
correlation was developed using the actual number of atoms forming
the molecule as well.
.. math::
P_c = \left [0.113 + 0.0032N_A - \sum_i {P_{c,i}}\right ]^{-2}
In the above equation, critical pressure is calculated in bar; it is
converted to Pa here.
392 compounds were used by Joback in this determination, with an
absolute average error of 2.06 bar, standard devaition 3.2 bar, and
AARE of 5.2%.
Parameters
----------
counts : dict
Dictionary of Joback groups present (numerically indexed) and their
counts, [-]
atom_count : int
Total number of atoms (including hydrogens) in the molecule, [-]
Returns
-------
Pc : float
Estimated critical pressure, [Pa]
Examples
--------
>>> Joback.Pc({1: 2, 24: 1}, 10)
4802499.604994407
'''
tot = 0.0
for group, count in counts.items():
tot += joback_groups_id_dict[group].Pc*count
Pc = (0.113 + 0.0032*atom_count - tot)**-2
return Pc*1E5 # bar to Pa
@staticmethod
def Vc(counts):
r'''Estimates the critcal volume of an organic compound using the
Joback method as a function of chemical structure only.
.. math::
V_c = 17.5 + \sum_i {V_{c,i}}
In the above equation, critical volume is calculated in cm^3/mol; it
is converted to m^3/mol here.
310 compounds were used by Joback in this determination, with an
absolute average error of 7.54 cm^3/mol, standard devaition 13.16
cm^3/mol, and AARE of 2.27%.
Parameters
----------
counts : dict
Dictionary of Joback groups present (numerically indexed) and their
counts, [-]
Returns
-------
Vc : float
Estimated critical volume, [m^3/mol]
Examples
--------
>>> Joback.Vc({1: 2, 24: 1})
0.0002095
'''
tot = 0.0
for group, count in counts.items():
tot += joback_groups_id_dict[group].Vc*count
Vc = 17.5 + tot
return Vc*1E-6 # cm^3/mol to m^3/mol
@staticmethod
def Hf(counts):
r'''Estimates the ideal-gas enthalpy of formation at 298.15 K of an
organic compound using the Joback method as a function of chemical
structure only.
.. math::
H_{formation} = 68.29 + \sum_i {H_{f,i}}
In the above equation, enthalpy of formation is calculated in kJ/mol;
it is converted to J/mol here.
370 compounds were used by Joback in this determination, with an
absolute average error of 2.2 kcal/mol, standard devaition 2.0
kcal/mol, and AARE of 15.2%.
Parameters
----------
counts : dict
Dictionary of Joback groups present (numerically indexed) and their
counts, [-]
Returns
-------
Hf : float
Estimated ideal-gas enthalpy of formation at 298.15 K, [J/mol]
Examples
--------
>>> Joback.Hf({1: 2, 24: 1})
-217829.99999999997
'''
tot = 0.0
for group, count in counts.items():
tot += joback_groups_id_dict[group].Hform*count
Hf = 68.29 + tot
return Hf*1000 # kJ/mol to J/mol
@staticmethod
def Gf(counts):
r'''Estimates the ideal-gas Gibbs energy of formation at 298.15 K of an
organic compound using the Joback method as a function of chemical
structure only.
.. math::
G_{formation} = 53.88 + \sum {G_{f,i}}
In the above equation, Gibbs energy of formation is calculated in
kJ/mol; it is converted to J/mol here.
328 compounds were used by Joback in this determination, with an
absolute average error of 2.0 kcal/mol, standard devaition 4.37
kcal/mol, and AARE of 15.7%.
Parameters
----------
counts : dict
Dictionary of Joback groups present (numerically indexed) and their
counts, [-]
Returns
-------
Gf : float
Estimated ideal-gas Gibbs energy of formation at 298.15 K, [J/mol]
Examples
--------
>>> Joback.Gf({1: 2, 24: 1})
-154540.00000000003
'''
tot = 0.0
for group, count in counts.items():
tot += joback_groups_id_dict[group].Gform*count
Gf = 53.88 + tot
return Gf*1000 # kJ/mol to J/mol
@staticmethod
def Hfus(counts):
r'''Estimates the enthalpy of fusion of an organic compound at its
melting point using the Joback method as a function of chemical
structure only.
.. math::
\Delta H_{fus} = -0.88 + \sum_i H_{fus,i}
In the above equation, enthalpy of fusion is calculated in
kJ/mol; it is converted to J/mol here.
For 155 compounds tested by Joback, the absolute average error was
485.2 cal/mol and standard deviation was 661.4 cal/mol; the average
relative error was 38.7%.
Parameters
----------
counts : dict
Dictionary of Joback groups present (numerically indexed) and their
counts, [-]
Returns
-------
Hfus : float
Estimated enthalpy of fusion of the compound at its melting point,
[J/mol]
Examples
--------
>>> Joback.Hfus({1: 2, 24: 1})
5125.0
'''
tot = 0.0
for group, count in counts.items():
tot += joback_groups_id_dict[group].Hfus*count
Hfus = -0.88 + tot
return Hfus*1000 # kJ/mol to J/mol
@staticmethod
def Hvap(counts):
r'''Estimates the enthalpy of vaporization of an organic compound at
its normal boiling point using the Joback method as a function of
chemical structure only.
.. math::
\Delta H_{vap} = 15.30 + \sum_i H_{vap,i}
In the above equation, enthalpy of fusion is calculated in
kJ/mol; it is converted to J/mol here.
For 368 compounds tested by Joback, the absolute average error was
303.5 cal/mol and standard deviation was 429 cal/mol; the average
relative error was 3.88%.
Parameters
----------
counts : dict
Dictionary of Joback groups present (numerically indexed) and their
counts, [-]
Returns
-------
Hvap : float
Estimated enthalpy of vaporization of the compound at its normal
boiling point, [J/mol]
Examples
--------
>>> Joback.Hvap({1: 2, 24: 1})
29018.0
'''
tot = 0.0
for group, count in counts.items():
tot += joback_groups_id_dict[group].Hvap*count
Hvap = 15.3 + tot
return Hvap*1000 # kJ/mol to J/mol
@staticmethod
def Cpig_coeffs(counts):
r'''Computes the ideal-gas polynomial heat capacity coefficients
of an organic compound using the Joback method as a function of
chemical structure only.
.. math::
C_p^{ig} = \sum_i a_i - 37.93 + \left[ \sum_i b_i + 0.210 \right] T
+ \left[ \sum_i c_i - 3.91 \cdot 10^{-4} \right] T^2
+ \left[\sum_i d_i + 2.06 \cdot 10^{-7}\right] T^3
288 compounds were used by Joback in this determination. No overall
error was reported.
The ideal gas heat capacity values used in developing the heat
capacity polynomials used 9 data points between 298 K and 1000 K.
Parameters
----------
counts : dict
Dictionary of Joback groups present (numerically indexed) and their
counts, [-]
Returns
-------
coefficients : list[float]
Coefficients which will result in a calculated heat capacity in
in units of J/mol/K, [-]
Examples
--------
>>> c = Joback.Cpig_coeffs({1: 2, 24: 1})
>>> c
[7.520000000000003, 0.26084, -0.0001207, 1.545999999999998e-08]
>>> Cp = lambda T : c[0] + c[1]*T + c[2]*T**2 + c[3]*T**3
>>> Cp(300)
75.32642000000001
'''
a, b, c, d = 0.0, 0.0, 0.0, 0.0
for group, count in counts.items():
a += joback_groups_id_dict[group].Cpa*count
b += joback_groups_id_dict[group].Cpb*count
c += joback_groups_id_dict[group].Cpc*count
d += joback_groups_id_dict[group].Cpd*count
a -= 37.93
b += 0.210
c -= 3.91E-4
d += 2.06E-7
return [a, b, c, d]
@staticmethod
def mul_coeffs(counts):
r'''Computes the liquid phase viscosity Joback coefficients
of an organic compound using the Joback method as a function of
chemical structure only.
.. math::
\mu_{liq} = \text{MW} \exp\left( \frac{ \sum_i \mu_a - 597.82}{T}
+ \sum_i \mu_b - 11.202 \right)
288 compounds were used by Joback in this determination. No overall
error was reported.
The liquid viscosity data used was specified to be at "several
temperatures for each compound" only. A small and unspecified number
of compounds were used in this estimation.
Parameters
----------
counts : dict
Dictionary of Joback groups present (numerically indexed) and their
counts, [-]
Returns
-------
coefficients : list[float]
Coefficients which will result in a liquid viscosity in
in units of Pa*s, [-]
Examples
--------
>>> mu_ab = Joback.mul_coeffs({1: 2, 24: 1})
>>> mu_ab
[839.1099999999998, -14.99]
>>> MW = 58.041864812
>>> mul = lambda T : MW*exp(mu_ab[0]/T + mu_ab[1])
>>> mul(300)
0.0002940378347162687
'''
a, b = 0.0, 0.0
for group, count in counts.items():
a += joback_groups_id_dict[group].mua*count
b += joback_groups_id_dict[group].mub*count
a -= 597.82
b -= 11.202
return [a, b]
def Cpig(self, T):
r'''Computes ideal-gas heat capacity at a specified temperature
of an organic compound using the Joback method as a function of
chemical structure only.
.. math::
C_p^{ig} = \sum_i a_i - 37.93 + \left[ \sum_i b_i + 0.210 \right] T
+ \left[ \sum_i c_i - 3.91 \cdot 10^{-4} \right] T^2
+ \left[\sum_i d_i + 2.06 \cdot 10^{-7}\right] T^3
Parameters
----------
T : float
Temperature, [K]
Returns
-------
Cpig : float
Ideal-gas heat capacity, [J/mol/K]
Examples
--------
>>> J = Joback('CC(=O)C')
>>> J.Cpig(300)
75.32642000000001
'''
if self.calculated_Cpig_coeffs is None:
self.calculated_Cpig_coeffs = Joback.Cpig_coeffs(self.counts)
return horner(reversed(self.calculated_Cpig_coeffs), T)
def mul(self, T):
r'''Computes liquid viscosity at a specified temperature
of an organic compound using the Joback method as a function of
chemical structure only.
.. math::
\mu_{liq} = \text{MW} \exp\left( \frac{ \sum_i \mu_a - 597.82}{T}
+ \sum_i \mu_b - 11.202 \right)
Parameters
----------
T : float
Temperature, [K]
Returns
-------
mul : float
Liquid viscosity, [Pa*s]
Examples
--------
>>> J = Joback('CC(=O)C')
>>> J.mul(300)
0.0002940378347162687
'''
if self.calculated_mul_coeffs is None:
self.calculated_mul_coeffs = Joback.mul_coeffs(self.counts)
a, b = self.calculated_mul_coeffs
return self.MW*exp(a/T + b)
