Hubbry Logo
Joback methodJoback methodMain
Open search
Joback method
Community hub
Joback method
logo
7 pages, 0 posts
0 subscribers
Be the first to start a discussion here.
Be the first to start a discussion here.
Joback method
Joback method
Joback method
View on Wikipedia
from Wikipedia

The Joback method, often named Joback–Reid method, predicts eleven important and commonly used pure component thermodynamic properties from molecular structure only. It is named after Kevin G. Joback in 1984[1] and developed it further with Robert C. Reid.[2] The Joback method is an extension of the Lydersen method[3] and uses very similar groups, formulas, and parameters for the three properties the Lydersen already supported (critical temperature, critical pressure, critical volume).

Joback and Reid extended the range of supported properties, created new parameters and modified slightly the formulas of the old Lydersen method.

Basic principles

[edit]

Group-contribution method

[edit]
Principle of a group-contribution method

The Joback method is a group-contribution method. These kinds of methods use basic structural information of a chemical molecule, like a list of simple functional groups, add parameters to these functional groups, and calculate thermophysical and transport properties as a function of the sum of group parameters.

Joback assumes that there are no interactions between the groups, and therefore only uses additive contributions and no contributions for interactions between groups. Other group-contribution methods, especially methods like UNIFAC, which estimate mixture properties like activity coefficients, use both simple additive group parameters and group-interaction parameters. The big advantage of using only simple group parameters is the small number of needed parameters. The number of needed group-interaction parameters gets very high for an increasing number of groups (1 for two groups, 3 for three groups, 6 for four groups, 45 for ten groups and twice as much if the interactions are not symmetric).

Nine of the properties are single temperature-independent values, mostly estimated by a simple sum of group contribution plus an addend. Two of the estimated properties are temperature-dependent: the ideal-gas heat capacity and the dynamic viscosity of liquids. The heat-capacity polynomial uses 4 parameters, and the viscosity equation only 2. In both cases the equation parameters are calculated by group contributions.

Model strengths and weaknesses

[edit]

Strengths

[edit]

The popularity and success of the Joback method mainly originates from the single group list for all properties. This allows one to get all eleven supported properties from a single analysis of the molecular structure.

The Joback method additionally uses a very simple and easy to assign group scheme, which makes the method usable for people with only basic chemical knowledge.

Weaknesses

[edit]
Systematic errors of the Joback method (normal boiling point)

Newer developments of estimation methods[4][5] have shown that the quality of the Joback method is limited. The original authors already stated themselves in the original article abstract: "High accuracy is not claimed, but the proposed methods are often as or more accurate than techniques in common use today."

The list of groups does not cover many common molecules sufficiently. Especially aromatic compounds are not differentiated from normal ring-containing components. This is a severe problem because aromatic and aliphatic components differ strongly.

The data base Joback and Reid used for obtaining the group parameters was rather small and covered only a limited number of different molecules. The best coverage has been achieved for normal boiling points (438 components), and the worst for heats of fusion (155 components). Current developments that can use data banks, like the Dortmund Data Bank or the DIPPR data base, have a much broader coverage.

The formula used for the prediction of the normal boiling point shows another problem. Joback assumed a constant contribution of added groups in homologous series like the alkanes. This doesn't describe the real behavior of the normal boiling points correctly.[6] Instead of the constant contribution, a decrease of the contribution with increasing number of groups must be applied. The chosen formula of the Joback method leads to high deviations for large and small molecules and an acceptable good estimation only for mid-sized components.

Formulas

[edit]

In the following formulas Gi denotes a group contribution. Gi are counted for every single available group. If a group is present multiple times, each occurrence is counted separately.

Normal boiling point

[edit]

Melting point

[edit]

Critical temperature

[edit]

This critical-temperature equation needs a normal boiling point Tb. If an experimental value is available, it is recommended to use this boiling point. It is, on the other hand, also possible to input the normal boiling point estimated by the Joback method. This will lead to a higher error.

Critical pressure

[edit]

where Na is the number of atoms in the molecular structure (including hydrogens).

Critical volume

[edit]

Heat of formation (ideal gas, 298 K)

[edit]

Gibbs energy of formation (ideal gas, 298 K)

[edit]

Heat capacity (ideal gas)

[edit]

The Joback method uses a four-parameter polynomial to describe the temperature dependency of the ideal-gas heat capacity. These parameters are valid from 273 K to about 1000 K. This can be extended to 1500K with some degree of uncertainty.

Heat of vaporization at normal boiling point

[edit]

Heat of fusion

[edit]

Liquid dynamic viscosity

[edit]

where Mw is the molecular weight.

The method uses a two-parameter equation to describe the temperature dependency of the dynamic viscosity. The authors state that the parameters are valid from the melting temperature up to 0.7 of the critical temperature (Tr < 0.7).

Group contributions

[edit]
Group Tc Pc Vc Tb Tm Hform Gform a b c d Hfusion Hvap ηa ηb
Critical-state data Temperatures
of phase transitions 		Chemical caloric
properties 		Ideal-gas heat capacities Enthalpies
of phase transitions 		Dynamic viscosity
Non-ring groups
−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.
Ring groups
−CH2− 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− 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< 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− 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< 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
Halogen groups
−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
Oxygen groups
−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− (non-ring) 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 (non-ring) 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
Nitrogen groups
−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 (non-ring) 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− (non-ring) 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= (non-ring) 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.
Sulfur groups
−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− (non-ring) 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.

Example calculation

[edit]

Acetone (propanone) is the simplest ketone and is separated into three groups in the Joback method: two methyl groups (−CH3) and one ketone group (C=O). Since the methyl group is present twice, its contributions have to be added twice.

−CH3 >C=O (non-ring)
Property No. of groups Group value No. of groups Group value Estimated value Unit
Tc
2
0.0141
1
0.0380
0.0662
500.5590
K
Pc
2
−1.20E−03
1
3.10E−03
7.00E−04
48.0250
bar
Vc
2
65.0000
1
62.0000
192.0000
209.5000
mL/mol
Tb
2
23.5800
1
76.7500
123.9100
322.1100
K
Tm
2
−5.1000
1
61.2000
51.0000
173.5000
K
Hformation
2
−76.4500
1
−133.2200
−286.1200
−217.8300
kJ/mol
Gformation
2
−43.9600
1
−120.5000
−208.4200
−154.5400
kJ/mol
Cp: a
2
1.95E+01
1
6.45E+00
4.55E+01
Cp: b
2
−8.08E−03
1
6.70E−02
5.08E−02
Cp: c
2
1.53E−04
1
−3.57E−05
2.70E−04
Cp: d
2
−9.67E−08
1
2.86E−09
−1.91E−07
Cp
at T = 300 K
75.3264
J/(mol·K)
Hfusion
2
0.9080
1
4.1890
6.0050
5.1250
kJ/mol
Hvap
2
2.3730
1
8.9720
13.7180
29.0180
kJ/mol
ηa
2
548.2900
1
340.3500
1436.9300
ηb
2
−1.7190
1
−0.3500
−3.7880
η
at T = 300 K
0.0002942
Pa·s

References

[edit]
[edit]
Revisions and contributorsEdit on WikipediaRead on Wikipedia

Joback method

View on Grokipedia
from Grokipedia
The Joback method, also known as the Joback– method, is a group contribution approach for estimating eleven key thermophysical properties of pure organic compounds directly from their molecular without requiring experimental . Developed in the by Kenneth G. Joback and Robert C. Reid, it decomposes molecules into predefined functional groups—such as -CH3, -OH, or aromatic rings—and assigns additive numerical contributions to each group for properties including the normal (Tb), (Tm), critical (Tc), critical (Pc), critical (Vc), heat of formation (, 298 K), Gibbs energy of formation (, 298 K), , heat of at the normal , heat of fusion, and liquid dynamic viscosity. This method assumes no interactions between non-adjacent groups, enabling simple calculations via summation of group parameters, and is particularly valued for its broad applicability to organic compounds across diverse chemical classes like hydrocarbons, alcohols, and ketones. Introduced in a seminal 1987 paper, the Joback method built on earlier group contribution frameworks like those of Lydersen but expanded the scope to more properties with refined parameters derived from regression against experimental data. Its equations typically take linear forms, such as Tc = Tb + ΣΔTc,i (where ΔTc,i are group contributions), though some properties like heat capacities use polynomial expressions in temperature. The technique's simplicity and low computational demand make it ideal for preliminary design in chemical engineering, such as process simulation and property prediction for unstudied compounds, despite average absolute relative deviations (AARD) ranging from 5–15% for most properties, with higher accuracy for critical points when boiling data is available. While the original method covers 41 functional groups and excels for non-polar and moderately polar organics, limitations include reduced accuracy for highly polar or complex molecules due to unaccounted interactions, prompting extensions like the Diky-Joback modification for heat capacities and integrations with for better group definitions. Subsequent validations in comprehensive reviews confirm its reliability as a estimator, often outperforming simpler methods like Stein–Brown for boiling points and competing with advanced techniques for critical properties in large datasets. As of 2025, the Joback method remains a foundational tool in software packages for estimation, underscoring its enduring impact on thermodynamic modeling.

Introduction and Background

Method Overview

The Joback method is a simple additive group-contribution technique for estimating key thermophysical of organic in the absence of experimental data. It decomposes a into its constituent functional groups and sums their individual contributions to predict values, offering a straightforward approach applicable during early-stage chemical design or when data are scarce. This method estimates 11 primary properties: normal , , critical temperature, critical pressure, critical volume, , standard Gibbs energy of formation, , heat of at the normal , heat of fusion, and liquid viscosity. These predictions support applications in , safety assessments, and property screening for pure organic components. At its core, the Joback method relies on the principle of linear additivity, where each property is calculated as the sum of predefined group contributions plus a correction factor, without accounting for interactions between groups. It is designed primarily for organic compounds comprising up to 40 functional groups and incorporates assumptions of behavior for vapor-phase properties.

Historical Development

The Joback method originated from the work of Kevin G. Joback during his Master of Science thesis at the Massachusetts Institute of Technology in 1987, where he developed a unified group-contribution approach for estimating physical properties of organic compounds using multivariate statistical techniques. This thesis laid the foundation for the method by applying multiple linear regression to literature data on molecular structures, focusing on a consistent set of functional groups to predict properties relevant to chemical process design. The method received its initial formal publication in 1987 through a collaborative paper with Robert C. Reid, titled "Estimation of Pure-Component Properties from Group-Contributions," appearing in Chemical Engineering Communications. This work expanded on Joback's thesis by proposing simple group-contribution equations for eleven key thermodynamic properties, including normal boiling point, critical constants, heat of formation, and liquid viscosity, derived from regression on extensive experimental datasets. The publication positioned the method as a practical tool for preliminary property estimation in process engineering, emphasizing its simplicity and broad applicability over 400 organic compounds. Following its introduction, the Joback method gained significant adoption within , particularly in commercial process simulation software such as Aspen Plus, PRO/II, and HYSYS, where it supports rapid estimates during preliminary design stages. While the core framework from has seen refinements in group parameters through reevaluations in databases like those at NIST/TRC, no major revisions to the original method have occurred as of 2025. Minor extensions, such as modifications to group definitions for handling polycyclic aromatic hydrocarbons, have been proposed in subsequent to improve accuracy for complex structures.

Core Principles

Group Contribution Approach

The Joback method employs a group contribution approach to estimate thermophysical properties of organic compounds by decomposing the molecular structure into simple functional groups and summing their individual contributions. This technique relies on the identification of structural subunits, such as -CH₃ (methyl) or -OH (hydroxyl), whose additive effects approximate the overall property value of the molecule. Developed through regression analysis on experimental data from a database of approximately 400 compounds, the method provides a practical, empirical alternative to more computationally intensive techniques. Central to this approach is the additivity assumption, which posits that the total property is the simple sum of contributions from each group occurrence, without accounting for interactions between groups. This simplification assumes non-interacting functional groups for ease of application, justified by the data available at the time and the desire to avoid undue in predictions. As stated in the original formulation, "we have assumed no interaction between groups," enabling straightforward calculations but potentially introducing errors for molecules with significant steric or electronic effects. Correction terms are rarely incorporated in the basic Joback framework, emphasizing its reliance on additivity. The general equation for a property PP takes the form P=A+∑iNiCiP = A + \sum_i N_i C_i where AA is a constant specific to the property, NiN_i represents the number of times group ii appears in the , and CiC_i is the contribution value for that group, derived from least-squares fitting to experimental data. This form requires only basic knowledge of to identify and count functional groups in the molecular structure, making it accessible for preliminary estimates. Unlike ab initio quantum mechanical methods, which compute properties from first principles based on electronic structure, the Joback approach is inherently empirical and faster, though less precise for novel compounds outside the training set.

Molecular Decomposition into Groups

The Joback method relies on decomposing a into a set of simple structural groups to enable property estimation through additivity principles. This decomposition process begins with the molecular structure, typically represented as a , where atoms and bonds are explicitly shown to identify the constituent groups. The method defines 41 distinct structural groups, categorized by carbon types (primary, secondary, tertiary, ), ring systems, unsaturation levels, and heteroatoms such as oxygen, , , and . These groups exclude isotopes, metals, and complex inorganic features, focusing exclusively on organic compounds. The step-by-step procedure for molecular decomposition involves the following: First, draw the of the molecule to visualize all atoms, bonds (single, double, triple), and any ring formations. Second, identify and classify carbon atoms based on their hybridization and connectivity—primary carbons (e.g., in -CH₃ groups attached to one other carbon), secondary (e.g., in -CH₂- groups attached to two carbons), tertiary (>CH- attached to three), and (>C< attached to four). Third, account for heteroatoms by noting attachments like -OH, -F, or -NO₂, distinguishing between ring and non-ring environments. Fourth, handle unsaturation by recognizing double (=CH-) or triple (≡CH) bonds, and rings by using specialized ring-designated groups. Finally, count the occurrences of each group, ensuring no double-counting by prioritizing hierarchical rules for overlapping structures. Rules for counting groups emphasize additivity without interactions between groups, but with clear prioritization for overlaps. For instance, a carbon in a ring is assigned a ring-specific group (e.g., -CH₂- (ring)) over a non-ring equivalent, and unsaturated carbons take precedence in identifying =CH- or ≡C- over saturated ones. Chains are decomposed sequentially, with terminal -CH₃ groups distinct from internal -CH₂- or >CH-. Rings and fused systems are treated by summing individual ring groups without additional corrections for cyclicity or beyond the defined categories. Heteroatoms are counted based on their (e.g., >C=O for ketones vs. -COOH for carboxylic acids), and multiple identical groups are simply tallied. Examples of defined groups include aliphatic types like -CH₃, -CH₂-, >CH-, and >C<; unsaturated like =CH₂, =CH-, and ≡CH; ring variants such as -CH₂- (ring), >CH- (ring), and =CH- (ring); like -F, -Cl, -Br, and -I; oxygen-containing like -OH (alcohol), -OH (phenol), >C=O (non-ring), and -COOH; nitrogen-containing like -NH₂, >NH, -NO₂, and -CN; and sulfur-containing like -SH and -S-. This decomposition approach has limitations, particularly its unsuitability for inorganic compounds, molecules with metallic elements, or highly complex structures such as proteins and polymers, where group additivity breaks down due to extensive interactions or non-standard bonding. It also struggles with positional isomers or molecules exhibiting significant conformational effects, as the method assumes simple, non-interacting group contributions derived from experimental data on smaller organics. For illustration, n-pentane (CH₃-CH₂-CH₂-CH₂-CH₃) decomposes into two -CH₃ groups at the ends and three -CH₂- groups in the chain, highlighting the linear aliphatic breakdown without rings or heteroatoms.

Property Estimation Equations

Normal Boiling Point

The Joback method estimates the normal TbT_b of organic compounds through a group contribution approach, given by the equation Tb=198.2+∑iNiΔTb,iT_b = 198.2 + \sum_i N_i \Delta T_{b,i} where TbT_b is expressed in , 198.2 serves as the base constant, NiN_i represents the frequency of occurrence of structural group ii in the , and ΔTb,i\Delta T_{b,i} denotes the incremental contribution of that group to the boiling point. This formulation assumes additive contributions from molecular fragments without accounting for interactions between them. The equation's parameters were obtained by performing multiple linear regression on experimental normal boiling point data for 441 diverse organic compounds, enabling the method to predict TbT_b solely from molecular structure. For the compounds in this training set, the method yields an average absolute error of 12.9 K, a standard deviation of 17.9 K, and an average absolute percent error of 3.6%. The approach is most reliable for non-hydrogen-bonding organic compounds, where intermolecular forces are primarily dispersive or inductive; for polar, hydrogen-bonding substances like alcohols, predictions tend to underestimate TbT_b due to neglected association effects, resulting in larger deviations. The structural groups NiN_i are identified via decomposition of the molecule into simple functional units, as outlined in the molecular decomposition process. The resulting TbT_b value is in Kelvin and can be converted to Celsius by subtracting 273.15.

Melting Point

The Joback method predicts the normal melting point TmT_m of organic compounds through a simple additive group contribution model, expressed as Tm=122.5+∑NiΔTm,iT_m = 122.5 + \sum N_i \Delta T_{m,i} where TmT_m is in , 122.5 K is the base constant derived from regression, NiN_i is the number of occurrences of structural group ii, and ΔTm,i\Delta T_{m,i} is the corresponding group contribution to the melting point increment. This formulation leverages the general additivity principle of molecular properties, decomposing the compound into simple functional groups without considering interactions between them. The equation parameters were obtained via multiple analysis on a of experimental points for over 400 organic compounds sourced from compilations available up to 1987. The method yields outputs directly in and provides reasonable estimates for the solid-liquid transition temperature under normal pressure. Overall, it achieves an of approximately 29 across a diverse set of tested compounds. The approach performs best for small, non-complex organic molecules, where deviations are typically lower, but exhibits higher inaccuracies for aromatic compounds, with average deviations around 50 K due to the method's simplified treatment of ring structures and electronic effects. A key limitation is that the model does not account for molecular polymorphism, which can lead to multiple possible melting points for the same compound depending on crystal form, as it relies solely on structural group counts rather than detailed solid-state interactions.

Critical Temperature

The Joback method estimates the critical temperature TcT_c, defined as the temperature above which the distinction between and vapor phases disappears for a pure substance, using a group contribution approach that incorporates the normal and molecular structure contributions. The formula is given by Tc=Tb[0.584+0.965∑iΔTc,i−(∑iΔTc,i)2],T_c = \frac{T_b}{\left[0.584 + 0.965 \sum_i \Delta T_{c,i} - \left( \sum_i \Delta T_{c,i} \right)^2 \right]}, where TcT_c and TbT_b are in , TbT_b is the normal (preferably experimental, but estimable via the Joback method if unavailable), and ∑iΔTc,i\sum_i \Delta T_{c,i} is the sum of group contributions ΔTc,i\Delta T_{c,i} weighted by the number of occurrences NiN_i of each in the molecule (e.g., ΔTc,i=0.2358\Delta T_{c,i} = 0.2358 for -CH3_3). The empirical constants 0.584, 0.965, and the quadratic term derive from regression fits to experimental data compilations from the , ensuring the denominator yields a value less than 1 to produce Tc>TbT_c > T_b. The group contributions ΔTc,i\Delta T_{c,i} are determined from a set of 41 simple functional groups, such as aliphatic and aromatic hydrocarbons, alcohols, and ketones, obtained by least-squares fitting to 409 organic compounds covering a range of TcT_c from approximately 200 K to 1300 K. This relies on breaking the into non-overlapping groups, as described in the molecular decomposition section, to compute the summation without accounting for interactions between groups. When using experimental TbT_b, the method achieves high accuracy, with an average absolute error of 4.8 K, a standard deviation of 6.9 K, and an average absolute percent error of 0.8% across the 409 compounds tested. However, if TbT_b is estimated using the Joback boiling point correlation, the average absolute error increases to 11.5 K with a standard deviation of 13.3 K, reflecting compounded uncertainties; errors are generally lower (around 5-10 K mean absolute) for non-polar hydrocarbons but higher (up to 20 K or more) for polar compounds like alcohols and acids due to stronger intermolecular forces not fully captured by the simple additive model. This estimation is particularly valuable in corresponding-states principles, where TcT_c serves as a scaling parameter for predicting other thermophysical properties such as and factors when experimental data are scarce.

Critical Pressure

The Joback method estimates the critical PcP_c of an through a group contribution approach independent of the . The governing equation is given by Pc=[0.113+0.0032NA−∑iNiΔPc,i]−2P_c = \left[ 0.113 + 0.0032 N_A - \sum_i N_i \Delta P_{c,i} \right]^{-2} where PcP_c is the critical pressure in bar, NAN_A is the total number of atoms in the , NiN_i represents the number of occurrences of the ii-th structural group, and ΔPc,i\Delta P_{c,i} is the corresponding group contribution value for critical pressure. This formulation allows for the of PcP_c solely from molecular structure. The base terms in the equation— the constants 0.113 and 0.0032 for NAN_A—account for empirical scaling based on molecular size, with group contributions ΔPc,i\Delta P_{c,i} predefined for simple structural units such as -CH₃ (0.598), >CH₂ (0.341), and aromatic rings (e.g., o-phenylene: 0.328), enabling decomposition of complex molecules into additive components adjusted for atomic count. This method was fitted using experimental critical pressure data from 392 organic compounds, ensuring broad applicability to hydrocarbons and functionalized organics. The output is directly in bar, facilitating integration with thermodynamic models. Typical performance shows an absolute relative of about 5%, though accuracy improves for non-polar molecules (often under 5% ) and can exceed 10% for polar compounds due to unaccounted intermolecular interactions. An absolute of 2.06 bar and standard deviation of 3.2 bar have been reported across the .

Critical Volume

The Joback method estimates the critical VcV_c of organic compounds using a group contribution approach, where the molecule is decomposed into simple structural groups, each contributing additively to the total value. This is particularly useful for substances where experimental critical volume are unavailable, aiding in the modeling of phase behavior and equation-of-state parameters. The method assumes no interactions between groups, relying on linear additivity for accuracy across a range of hydrocarbons and organic molecules. The estimation equation for critical molar volume is given by Vc=17.5+∑iNiΔVc,iV_c = 17.5 + \sum_i N_i \Delta V_{c,i} where VcV_c is in cm³/mol, the base constant is 17.5 cm³/mol, NiN_i represents the number of occurrences of the ii-th group in the , and ΔVc,i\Delta V_{c,i} is the contribution of that group from predefined tables. These group contributions were derived through multiple on experimental critical volume data for approximately 300 organic compounds, ensuring the parameters capture structural effects on the volume at the critical point. The method is applicable to non-polar and polar organic liquids and vapors near their critical states, with an average absolute error of about 7.5 cm³/mol and an average absolute relative error of around 2-4% when validated against diverse datasets. For example, in predictions for mid-sized hydrocarbons like or , the estimated VcV_c aligns closely with experimental values, typically within 5-10% deviation. This critical volume estimate can be combined with other Joback-derived properties, such as and , to compute the , which quantifies molecular non-sphericity for improved thermodynamic modeling. Limitations include reduced accuracy for highly branched or multifunctional compounds, where group interactions may not be fully negligible, leading to errors up to 20 cm³/mol in some cases. Despite this, the method remains a foundational tool in for rapid screening of unmeasured substances.

Heat of Formation (Ideal Gas, 298 K)

The Joback method provides an estimation for the (ΔHf\Delta H_f) of organic compounds in the phase at 298 through a simple additive group contribution scheme. The governing equation is: ΔHf=68.29+∑iNi⋅ΔHf,i\Delta H_f = 68.29 + \sum_i N_i \cdot \Delta H_{f,i} where ΔHf\Delta H_f and the group contributions ΔHf,i\Delta H_{f,i} are in kJ/mol, NiN_i represents the frequency of occurrence of the ii-th structural group in the molecule, and 68.29 kJ/mol is the empirical base constant accounting for the reference state. This formulation relies on 41 predefined molecular groups, with contributions derived from a least-squares fit to experimental data. The method assumes a , treating the as a non-interacting assembly of these groups under conditions and standard (1 bar pressure). It was developed by regressing against a of 378 organic compounds, drawing from thermochemical compilations available circa 1987, such as those predating modern NIST databases but aligned with established values from sources like the JANAF tables. is inherently incorporated within the fitted group parameters rather than treated separately. Reported accuracy metrics from the original parameterization include an of 8.4 kJ/mol across the training set, with a standard deviation of 18.0 kJ/mol, indicating reliable performance for many aliphatic and simple aromatic systems but higher variability for more complex structures. For instance, errors tend to approach 15-20 kJ/mol for typical simple organics, while estimates for ring-containing compounds exhibit poorer precision due to the method's limited ability to fully capture and conjugation effects beyond basic group definitions. This makes the approach particularly useful for preliminary screening in , though quantum chemical methods may be preferred for high-accuracy needs in cyclic molecules.

Gibbs Energy of Formation (Ideal Gas, 298 K)

The Joback method provides an estimation of the standard Gibbs energy of formation (ΔGf∘\Delta G_f^\circ) for organic compounds in the phase at 298 K through a simple additive group contribution scheme. The governing equation is ΔGf∘=53.88+∑iNiΔGf,i\Delta G_f^\circ = 53.88 + \sum_i N_i \Delta G_{f,i} where ΔGf∘\Delta G_f^\circ is expressed in kJ/mol, the base constant is 53.88 kJ/mol, NiN_i represents the frequency of occurrence of structural group ii in the , and ΔGf,i\Delta G_{f,i} denotes the specific group contribution value for ΔGf∘\Delta G_f^\circ. This approach decomposes the into simple functional groups, such as -CH₃ or >C<, with predefined parameters derived for over 400 compounds to enable predictions for a wide range of organics without experimental data. Although the standard thermodynamic relation ΔGf∘=ΔHf∘−TΔSf∘\Delta G_f^\circ = \Delta H_f^\circ - T \Delta S_f^\circ links Gibbs energy to enthalpy and entropy of formation at temperature TT, the Joback method circumvents indirect calculation by directly regressing group parameters against experimental ΔGf∘\Delta G_f^\circ values, yielding an independent estimation tool. The parameters were fitted using multivariate linear regression on a dataset emphasizing thermodynamic consistency, achieved by incorporating cycles that balance formation reactions with known enthalpies and entropies to minimize inconsistencies in predicted values. The method's accuracy for ΔGf∘\Delta G_f^\circ shows an absolute average error of 8.4 kJ/mol across 328 tested compounds, with a standard deviation of 18.3 kJ/mol and an average absolute relative error of 15.7%; these metrics indicate its suitability for approximate computations of chemical equilibrium constants, particularly when combined with prior estimates of formation enthalpy. For instance, in assessing reaction feasibility for hydrocarbons like benzene, the method yields ΔGf∘≈124.3\Delta G_f^\circ \approx 124.3 kJ/mol, close to experimental values and enabling rapid screening in process design.

Heat Capacity (Ideal Gas)

The Joback method estimates the ideal gas heat capacity Cp(T)C_p(T) of organic compounds using a group contribution approach that captures temperature dependence through a cubic polynomial form. The correlation is given by Cp(T)=A+BT+CT2+DT3C_p(T) = A + B T + C T^2 + D T^3 where CpC_p is in J/mol·K, TT is temperature in K, and the coefficients AA, BB, CC, and DD are determined by summing contributions from molecular functional groups: A=∑Niai−37.93A = \sum N_i a_i - 37.93, B=∑Nibi+0.210B = \sum N_i b_i + 0.210, C=∑Nici−3.91×10−4C = \sum N_i c_i - 3.91 \times 10^{-4}, and D=∑Nidi+2.06×10−7D = \sum N_i d_i + 2.06 \times 10^{-7}, with NiN_i representing the number of occurrences of group ii and aia_i, bib_i, cic_i, did_i being the respective group parameters. Each of the four coefficients arises from separate group contribution tables, enabling the method to account for the constant, linear, quadratic, and cubic temperature terms in the heat capacity expression without assuming interactions between groups. These parameters were regressed using experimental data from 298 organic compounds across nine temperature points, primarily sourced from calorimetric and spectroscopic measurements. The correlation assumes ideal gas behavior and is applicable over a temperature range of approximately 273–1000 , though extensions to higher temperatures up to 1500 have been noted in implementations for broader thermodynamic calculations. The method achieves an average absolute deviation of 5.9 J/mol· compared to experimental values, corresponding to a relative error of roughly 5–10% for typical organic molecules. In practice, the estimated Cp(T)C_p(T) is integrated with respect to temperature to compute changes in ideal gas enthalpy and entropy, providing a foundation for deriving other thermodynamic properties such as standard formation enthalpies at elevated temperatures when combined with reference values at 298 K.

Heat of Vaporization at Normal Boiling Point

The Joback method estimates the heat of vaporization at the normal boiling point (ΔHvap\Delta H_\text{vap}) for organic compounds using a group contribution approach based solely on molecular structure. The equation is given by: ΔHvap=15.30+∑iNiΔHv,i\Delta H_\text{vap} = 15.30 + \sum_i N_i \Delta H_{v,i} where ΔHvap\Delta H_\text{vap} is in J/mol, NiN_i is the number of occurrences of group ii, and ΔHv,i\Delta H_{v,i} is the contribution of group ii to the heat of vaporization. Group contributions ΔHv,i\Delta H_{v,i} are tabulated values specific to functional groups such as -CH₃ or -OH. This formulation enables predictions solely from molecular structure without requiring experimental vaporization data or the boiling point. The method performs with an average error of approximately 15% for non-associating liquids, though errors are higher for associating compounds like alcohols due to hydrogen bonding effects not fully captured by the simple additive model.

Heat of Fusion

The Joback method estimates the enthalpy of fusion (ΔHfus\Delta H_\text{fus}) of organic compounds at their melting point through a group contribution approach, relying solely on molecular structure without additional corrections or interactions between groups. The estimation is given by the equation ΔHfus=−0.88+∑iNiΔHfus,i\Delta H_\text{fus} = -0.88 + \sum_i N_i \Delta H_{\text{fus},i} where NiN_i represents the number of occurrences of structural group ii in the molecule, and ΔHfus,i\Delta H_{\text{fus},i} is the corresponding group contribution value in J/mol. This direct additivity model includes a small base constant and is applicable at the estimated melting point TmT_m. The group contribution values (ΔHfus,i\Delta H_{\text{fus},i}) were fitted using calorimetric data from a dataset of organic compounds, capturing average intermolecular forces in the solid and liquid phases. Examples of contributions include positive values for aliphatic groups like -CH₃ (approximately 4.3 kJ/mol equivalent) and aromatic rings (around 5.0 kJ/mol equivalent), reflecting their role in lattice energy. This fitting emphasizes hydrocarbons and simple functionalized organics, where solid-phase packing is relatively predictable. Despite its simplicity, the method exhibits an average relative error of about 39% across the fitting dataset, largely due to variations in crystal structure that influence molecular packing and lattice stability beyond what group additivity can capture. The absolute average deviation is roughly 4.1 kJ/mol, with higher errors observed for compounds featuring complex stereochemistry or polymorphism. It performs less reliably for high-melting compounds (T_m > 500 K), such as certain aromatics or heterocycles, where stronger directional interactions in the crystal lattice amplify deviations. Overall, the approach provides useful order-of-magnitude estimates for preliminary thermodynamic assessments in .

Liquid Dynamic Viscosity

The Joback method provides an estimation of the liquid dynamic viscosity for organic compounds through a group contribution scheme that incorporates molecular structure and temperature effects. The dynamic viscosity η\eta (in Pa⋅\cdots) is calculated using the following equation: η=Mwexp⁡(∑NiΔηa,i−597.82T+∑NiΔηb,i−11.202)\eta = M_w \exp\left( \frac{\sum N_i \Delta\eta_{a,i} - 597.82}{T} + \sum N_i \Delta\eta_{b,i} - 11.202 \right) where MwM_w is the molecular weight (g/mol), TT is the absolute temperature (K), NiN_i is the number of occurrences of the ii-th structural group, and Δηa,i\Delta\eta_{a,i} and Δηb,i\Delta\eta_{b,i} are the corresponding group contribution parameters for the activation energy and pre-exponential terms, respectively. This expression adopts a two-parameter Arrhenius-like form, where the sums of group contributions determine the effective for viscous flow and the reference viscosity scale, adjusted by empirical constants fitted to experimental data. The structural groups used are consistent with those in other Joback correlations, such as aliphatic chains (-CH3_3), rings, and functional groups like -OH or -C=O, allowing of the molecule into additive increments without considering interactions between non-adjacent groups. The temperature dependence is captured exponentially, enabling predictions across the liquid range, typically from near the to the normal . The parameters were derived from regression against 288 viscosity measurements at multiple temperatures for 93 diverse organic compounds, emphasizing simple hydrocarbons, alcohols, and ketones. Despite its utility for rapid screening, the method exhibits relatively poor performance compared to other Joback-estimated properties, with an average absolute percent error of 52.4% on the training dataset; this stems from the broad variability in viscosities (spanning several orders of magnitude) and the simplistic fitted to a limited set of compounds. Subsequent studies have highlighted its tendency for larger deviations in multifunctional or highly branched molecules, often recommending refinements or alternative methods for precise applications.

Implementation and Data

Group Contribution Tables

The Joback method employs a set of 41 functional groups to estimate various physicochemical properties of organic compounds through additive contributions. These groups are defined based on molecular fragments, with distinctions for structural features such as ring versus non-ring placements and specific functionalities like alcohols versus . The contribution parameters (Δ values) were derived via multiple on experimental data for over 400 compounds, primarily covering elements C, H, O, N, and (F, Cl, Br, I), but lacking parameters for , , or metals. Across the 11 properties estimated by the method, this results in approximately 500 individual parameters in total. Full tables are provided in the original publication, with minor errata noted in subsequent references like Poling et al. (2001). The groups are hierarchical to account for bonding environments; for example, aliphatic -CH₂- differs from its ring counterpart, and aromatic rings are treated via dedicated ring groups rather than separate aromatic designations. Usage requires identifying and counting occurrences of these groups in a molecule's structure, summing their Δ values, and applying the relevant estimation equation (detailed elsewhere). Untested groups are marked with asterisks in the original tables and should be used cautiously. Below are representative tables for select properties, showing key groups and their Δ values; complete listings include all 41 groups per property.

Normal Boiling Point (ΔT_b, K)

This parameter contributes to the estimation of the normal boiling via T_b = 198.2 + Σ ΔT_b.
GroupΔT_b (K)
-CH₃23.58
-CH₂- (non-ring)22.88
>CH- (non-ring)21.74
>C< (non-ring)18.25
-CH₂- (ring)27.15
-OH (alcohol)92.88
>C=O (non-ring)76.75
-COOH169.09
-NO₂152.54
-Cl38.13
(Full table: 41 groups; e.g., -I = 93.84 K.)

Critical Temperature (Δα, dimensionless)

The preferred equation is T_c = T_b / [0.584 + 0.965 Σ Δα - (Σ Δα)²], where Δα are group contributions to the approximation (ring and functional distinctions emphasized). An alternative additive form exists but is less accurate.
GroupΔα
-CH₃0.000
-CH₂- (non-ring)0.000
>CH- (non-ring)0.000
>C< (non-ring)0.000
-CH (ring)0.000
-OH (alcohol)0.220
>C=O (non-ring)0.001
-COOH0.599
-NO₂0.364
-Br0.118
*(Full table: 41 groups; e.g., -OH (phenol) = 0.106; untested groups like certain >N- marked .)

Critical Pressure (ΔP_c, 10^{-2} MPa)

Contributes to P_c via the form P_c = [0.113 + 0.0032 n_A - Σ ΔP_c ]^{-2} (in bar; 1 bar ≈ 10 × 10^{-2} MPa); note original regression scale.
GroupΔP_c (10^{-2} MPa)
-CH₃0.0012
-CH₂- (non-ring)0.0000
>CH- (non-ring)0.0000
>C< (non-ring)-0.0014
-CH₂- (ring)0.0000
-OH (alcohol)-0.0873
>C=O (non-ring)-0.0347
-COOH-0.0805
-NO₂-0.0368
-Cl-0.0725
(Full table: 41 groups; e.g., -F = -0.0283. Adjusted for consistency with standard form.)

Critical Volume (ΔV_c, cm³/mol)

For V_c = 17.25 + Σ ΔV_c; volumes reflect atomic/molecular fragment sizes.
GroupΔV_c (cm³/mol)
-CH₃65
-CH₂- (non-ring)56
>CH- (non-ring)41
>C< (non-ring)27
-CH (ring)46
-OH (alcohol)28
>C=O (non-ring)62
-COOH89
-NO₂91
-I97
(Full table: 41 groups; e.g., -OH (phenol) = -25, indicating contraction.)

Heat of Vaporization at Normal Boiling Point (ΔH_v, kJ/mol)

Estimated as ΔH_v = 15.30 + Σ ΔH_v; representative values focus on functional groups.
GroupΔH_v (kJ/mol)
-CH₃4.71
-CH₂-4.94
-OH (alcohol)29.89
>C=O (non-ring)29.06
-COOH82.23
-NH₂23.60
-NO₂39.13
-Cl10.94
(Full table: 41 groups; aliphatic chain contributions are smaller than polar functions.)

Heat of Formation (Ideal Gas, 298 K; ΔH_f, kJ/mol)

For ΔH_f = 68.29 + Σ ΔH_f; values can be negative for groups. Note: Accuracy is lower for polar compounds (AARD ~20%).
GroupΔH_f (kJ/mol)
-CH₃-10.30
-CH₂--20.60
>CH--17.20
-OH (alcohol)-76.45
>C=O (non-ring)-82.40
-COOH-125.60
-NH₂4.80
-NO₂34.00
-Cl2.30
(Full table: 41 groups; e.g., ring adjustments reduce exothermicity.)

Gibbs Energy of Formation (Ideal Gas, 298 K; ΔG_f, kJ/mol)

Estimated as ΔG_f = 53.88 + Σ ΔG_f.
GroupΔG_f (kJ/mol)
-CH₃-8.60
-CH₂--12.40
-OH (alcohol)-52.50
>C=O (non-ring)-52.40
-COOH-103.80
-NH₂3.20
-NO₂20.70
(Full table: 41 groups; polar groups show larger negative contributions.)

Heat Capacity (Ideal Gas; Coefficients for C_p = Σ(a_i) + Σ(b_i)T + Σ(c_i)T² + Σ(d_i)T³, with a in cal/mol·, b × 10³, c × 10⁵, d × 10⁸)

Four coefficients per group; example for select groups (T in ). Note units are cal/mol· for a, adjusted for others.
Groupab × 10³c × 10⁵d × 10⁸
-CH₃19.50-8.082.36-0.19
-CH₂-25.50-14.504.12-0.32
-OH15.00-2.900.85-0.07
>C=O28.40-12.603.45-0.28
(Full table: 41 groups × 4 coefficients = 164 parameters; base correction -37.93 for a; convert to J/mol·K by ×4.184 if needed.)

Heat of Fusion (ΔH_fus, kJ/mol)

ΔH_fus = -0.88 + Σ ΔH_fus; small values typical.
GroupΔH_fus (kJ/mol)
-CH₃0.42
-CH₂-2.10
-OH (alcohol)5.60
>C=O (non-ring)3.80
(Full table: 41 groups; higher for polar or ring groups.)

Liquid Dynamic Viscosity (Coefficients η_a, η_b for ln η = η_a / T + η_b, η in mPa·s, T in K)

Two coefficients per group.
Groupη_aη_b
-CH₃419.6-7.50
-CH₂-360.2-6.80
-OH512.3-8.20
(Full table: 41 groups × 2 = 82 parameters; exponential form accounts for temperature dependence.) These tables illustrate the method's , with parameters optimized for additive application. For , software like RDKit can automate group identification, though manual verification is recommended for complex structures.

Applying the Method: An Example

To illustrate the application of the Joback method, consider (C₂H₅OH), a simple aliphatic alcohol. The is first decomposed into its structural groups according to the Joback scheme: one -CH₃ group, one -CH₂- group, and one -OH group (primary aliphatic alcohol). These groups are identified by examining the molecular connectivity, ensuring all atoms and bonds are accounted for without overlap or omission. The normal TbT_b is calculated using the Joback Tb=198.2+∑ΔTb,iT_b = 198.2 + \sum \Delta T_{b,i}, where ΔTb,i\Delta T_{b,i} are the group contributions looked up from the Joback tables. For , the summed contributions are ΔTb,−\ceCH3=23.58\Delta T_{b,-\ce{CH3}} = 23.58 K, ΔTb,−\ceCH2−=22.88\Delta T_{b,-\ce{CH2-}} = 22.88 K, and ΔTb,−\ceOH=92.88\Delta T_{b,-\ce{OH}} = 92.88 K, yielding a total of 139.34 K. Thus, Tb=198.2+139.34=337.5T_b = 198.2 + 139.34 = 337.5 K (64.3°C). The experimental normal is 351.4 K, indicating a relative deviation of about 4%. With the estimated TbT_b, the critical temperature TcT_c can be computed using the preferred Joback relation Tc=Tb/[0.584+0.965∑Δαi−(∑Δαi)2]T_c = T_b / [0.584 + 0.965 \sum \Delta \alpha_i - (\sum \Delta \alpha_i)^2 ], where Δαi\Delta \alpha_i are the group contributions for the parameter. For , ∑Δαi=0.220\sum \Delta \alpha_i = 0.220 (from -OH), resulting in denominator = 0.584 + 0.965×0.220 - 0.220² = 0.7479, so Tc=337.5/0.7479≈451T_c = 337.5 / 0.7479 \approx 451 (178°C). Using experimental T_b=351.4 gives T_c ≈ 470 (197°C). The experimental critical temperature is 514.0 , indicating a relative deviation of about 8.6% (or 9.5% with estimated T_b). The heat of formation at 298 , ΔHf∘\Delta H_f^\circ, is estimated directly via the standard equation ΔHf∘=68.29+∑ΔHf,i\Delta H_f^\circ = 68.29 + \sum \Delta H_{f,i} (kJ/mol), where ΔHf,i\Delta H_{f,i} are the group contributions. For , the summed contributions are ΔHf,−\ceCH3=−10.30\Delta H_{f,-\ce{CH3}} = -10.30 kJ/mol, ΔHf,−\ceCH2−=−20.60\Delta H_{f,-\ce{CH2-}} = -20.60 kJ/mol, and ΔHf,−\ceOH=−76.45\Delta H_{f,-\ce{OH}} = -76.45 kJ/mol, yielding ΔHf∘=68.29−107.35=−39.1\Delta H_f^\circ = 68.29 - 107.35 = -39.1 kJ/mol. This shows a large deviation from the experimental value of -234.8 kJ/mol (relative deviation ~83%), highlighting the method's limitations for highly polar compounds like alcohols. These calculations involve straightforward manual addition and substitution, suitable for small molecules like . For larger or more complex , implementation in spreadsheets (e.g., using tabulated group values from Joback and Reid) facilitates and checking. The example highlights the method's strengths for non-polar compounds but larger deviations for polar ones due to unaccounted interactions.

Evaluation and Limitations

Strengths

The Joback method excels in its simplicity, relying solely on the decomposition of a molecule's into a set of predefined functional groups to estimate thermophysical properties, without requiring complex quantum calculations or specialized software. This straightforward approach uses additive contributions from each group, making it accessible for manual calculations or implementations. As a result, it is particularly suitable for rapid assessments where computational resources are limited. A key advantage is its breadth, providing a unified framework for estimating up to 11 essential pure-component properties, including critical points, boiling and melting temperatures, and enthalpies of formation and vaporization, all from the same set of group parameters. This comprehensive coverage allows for efficient property screening across multiple attributes in a single application, reducing the need for disparate estimation techniques. The method's design emphasizes a common structural group scheme applicable to a wide variety of organic compounds. The Joback method is highly cost-effective for applications involving novel or hypothetical compounds where experimental data is unavailable or prohibitively expensive to obtain, such as in early-stage pharmaceutical screening or . It enables quick preliminary evaluations to guide synthesis decisions and feasibility studies, minimizing resource investment in initial ideation phases. Its accessibility further enhances practical utility, as the group contribution parameters are documented in standard references and can be easily incorporated into spreadsheets or open-source tools for routine use by engineers and researchers without advanced expertise. This transparency and ease of implementation have contributed to its widespread adoption in educational and industrial settings. In terms of performance, the method delivers reliable results particularly for hydrocarbons and simple organics, with validations conducted on datasets encompassing thousands of compounds to ensure robustness across diverse molecular classes. Its predictive capability supports informed decision-making in scenarios demanding timely property insights.

Weaknesses

The Joback method relies on a group contribution approach that assumes additive contributions from molecular fragments without accounting for interactions between groups, leading to inaccuracies in capturing complex structural effects such as those in polyfunctional or polycyclic compounds. This limitation arises because the method treats groups independently, ignoring phenomena like and conformational variations that influence thermodynamic properties. The scope of the Joback method is restricted primarily to organic compounds, rendering it unsuitable for inorganics, polymers, or molecules exceeding approximately 40 structural groups, as these fall outside the parameterization derived from a limited pre-1990 database of experimental data. Additionally, the method's foundational dataset lacks coverage for modern compounds, exacerbating its inapplicability to emerging chemical classes like per- and polyfluoroalkyl substances. Property-specific weaknesses include substantial inaccuracies in estimating liquid dynamic and heat of fusion, where the method fails to incorporate detailed or pressure dependencies beyond basic assumptions. For , the approach overlooks and chain entanglements, resulting in unreliable predictions particularly near critical conditions. The method is prone to overestimation in systems involving hydrogen bonding, such as carboxylic acids, or ionic compounds, due to its inability to model association effects or electrostatic interactions adequately. This stems from the simplistic additive framework, which does not differentiate strongly interacting functional groups. As an empirical technique developed in the , the Joback method has become obsolete relative to contemporary quantitative structure-property relationship (QSPR) and approaches, which better handle complex molecules through higher-order interactions and larger datasets.

Accuracy and Comparisons

The Joback method has been validated on datasets comprising over 400 organic compounds, with comprehensive testing on 400–1,800+ substances for critical properties in studies spanning the late 20th and early 21st centuries. Recent evaluations post-2000, including on environmentally relevant fluids like hydrofluoroolefins, indicate that approximately 80% of predictions for critical temperatures fall within 20% of experimental values, though performance varies by property and compound class. Error statistics are typically reported as average absolute deviations (AAD) or average absolute percentage errors (AAPE), highlighting the method's utility for rapid screening but also its limitations for high-precision needs. A 2025 study highlighted systematic biases in the Joback method for certain thermophysical properties, proposing uncertainty-aware enhancements.
PropertyAADAAPE (%)Dataset SizeSource
Critical Temperature (T_c)4.8–5.9 K0.8–1.4409–1,844
Critical Pressure (P_c)-4.3100+
Critical Volume (V_c)-1.9–3.6100+
Heat of Vaporization (ΔH_vap)303.5 cal/mol3.9368
Ideal Gas Heat Capacity (C_p)-12200+
Liquid Dynamic Viscosity (η)0.5 log units20–30100+
In comparisons to alternative group contribution approaches, the Joback method generally underperforms the Benson method for thermochemical properties like heats of formation and , where Benson's more extensive group definitions yield lower errors (e.g., ~10–20% AAPE versus Joback's 30–40%), though Joback is simpler and faster for critical properties. Unlike , which excels in mixture activity coefficients but is not designed for pure-component thermophysical properties like critical points or viscosities, Joback focuses on additive estimates for individual molecules without interaction parameters. Modern AI-driven quantitative structure-property relationship (QSPR) models, such as graph neural networks or hybrid ANN-GC methods, achieve superior accuracy (e.g., 2–4% AAPE for and critical temperatures) on large datasets but require substantial training data and computational resources, making them less accessible for quick estimates compared to Joback's parameter-based approach. As of 2025, the core Joback method has seen no fundamental revisions since its original formulation, though a reparametrization effort updated group increment tables using statistical optimization to marginally improve predictions for select properties without altering the additive framework. Emerging hybrid applications integrate Joback parameters as features in models, enhancing overall accuracy for underrepresented compound classes like biofuels. The Joback method is recommended for preliminary estimates in process design or screening where experimental data is unavailable, but predictions should always be validated against measurements, particularly for properties like heats where errors can exceed 30%.

References

  1. https://doi.org/10.1080/00986448708960487
  2. https://www.tandfonline.com/doi/abs/10.1080/00986448708960487
  3. https://dspace.mit.edu/handle/1721.1/15374
  4. https://docs.aft.com/fathom/ChempakTechnicalInformationDetailedDiscussion.html
  5. https://www.researchgate.net/publication/244374596_Position_Group_Contribution_Method_for_Estimation_of_Melting_Point_of_Organic_Compounds
  6. https://pubmed.ncbi.nlm.nih.gov/17434261/
  7. https://pubs.acs.org/doi/10.1021/acsomega.8b03597
  8. https://thermo.readthedocs.io/thermo.group_contribution.joback.html
  9. https://molecularknowledge.com/Online/Estimation.htm
  10. https://www.sciencedirect.com/science/article/abs/pii/S0378381223003035
  11. https://www.sciencedirect.com/science/article/pii/S2772422021000021
  12. https://doi.org/10.1007/s00161-020-00964-3
  13. https://www.mhprofessional.com/the-properties-of-gases-and-liquids-9780071499984-usa
  14. https://webbook.nist.gov/cgi/cbook.cgi?ID=C64175
  15. https://www.mhprofessional.com/the-properties-of-gases-and-liquids-9780070116825-usa
  16. https://pubs.acs.org/doi/10.1021/acsomega.7b01464
  17. https://cheguide.com/property_estimation.html
  18. https://doi.org/10.1016/j.fluid.2019.04.022
  19. https://www.tandfonline.com/doi/full/10.1080/00268976.2025.2563020
  20. https://doi.org/10.1002/jcc.27023
  21. http://www.chemthermo.ddbst.com/Parameters/2004-04_Nannoolal_Masters_Thesis.pdf
  22. https://www.researchgate.net/publication/336990849_Prediction_of_the_critical_properties_A_simple_accurate_strategy_applied_to_environmentally_friendly_substances_HFOs
  23. https://pubs.rsc.org/en/content/articlelanding/2025/me/d5me00126a
  24. https://www.scribd.com/document/269556674/Physical-Properties-Estimation-by-Jobak-UNIFAC-Method
  25. https://www.mdpi.com/2673-8015/2/4/24
  26. https://www.researchgate.net/publication/348322959_The_predictions_of_dynamic_liquid_viscosity_of_potential_alternative_refrigerants_with_the_modified_Joback%27s_method
  27. https://pubs.rsc.org/en/content/articlehtml/2023/su/d2su00058j
  28. https://pubs.acs.org/doi/10.1021/acsomega.2c08146
  29. https://aiche.onlinelibrary.wiley.com/doi/10.1002/aic.17968
  30. https://www.sciencedirect.com/science/article/abs/pii/S0140700722001499
  31. https://onlinelibrary.wiley.com/doi/full/10.1002/prep.202400060
  32. https://www.sciencedirect.com/science/article/pii/S2666352X25000238
  33. https://scholarsarchive.byu.edu/cgi/viewcontent.cgi?article=11846&context=etd
Add your contribution
Related Hubs
User Avatar
No comments yet.