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Article

Computational Models for Analyzing the Thermodynamic Properties of Linear Triatomic Molecules

1
Department of Physics, Faculty of Physical Sciences, Modibbo Adama University, P.M.B. 2076, Yola 640231, Adamawa State, Nigeria
2
Physics Program, College of Agriculture, Engineering and Science, Bowen University, P.M.B. 284, Iwo 232102, Osun State, Nigeria
3
Department of Physics, University of Agriculture and Environmental Sciences, P.M.B. 1038, Umuagwo 511101, Imo State, Nigeria
4
Department of Physics, National Open University of Nigeria, P.M.B. 581, Jabi-Abuja 900108, Nigeria
5
Department of Natural Sciences, School of Sciences, College of Education, P.M.B. 011, Billiri 771102, Gombe State, Nigeria
6
Department of Physics, Faculty of Natural Sciences, University of Jos, P.M.B. 2084, Jos 930105, Plateau State, Nigeria
*
Author to whom correspondence should be addressed.
Chemistry 2025, 7(2), 35; https://doi.org/10.3390/chemistry7020035
Submission received: 23 December 2024 / Revised: 27 February 2025 / Accepted: 4 March 2025 / Published: 5 March 2025
(This article belongs to the Section Physical Chemistry and Chemical Physics)

Abstract

:
This study presents analytical models for simulating the thermal properties of linear triatomic systems, using the modified Rosen–Morse oscillator and harmonic oscillator potential to represent vibrational modes. The models employ existing partition functions to derive the thermodynamic functions for the symmetric, asymmetric, and 2-fold degenerate bending modes. These thermodynamic functions are applied to gaseous triatomic molecules such as BO2, HCN, N3, and Si2N. The results demonstrate high accuracy, with mean percentage absolute deviations (MPAD) of less than 0.17% for molar entropy and Gibbs free energy. For enthalpy and heat capacity, MPAD values are below 2% compared to National Institute of Standards and Technology (NIST) data. The findings are in strong agreement with the existing literature on gaseous triatomic molecules, confirming the reliability of the proposed models.

1. Introduction

Thermodynamics is a branch of physical science focused on the study of heat, work, energy, and how these quantities interact with matter. It provides insights into energy conversion processes and the transformation of energy between systems. Thermodynamic processes are governed by key state variables, such as temperature, pressure, volume, and energy, and are described by the following four fundamental laws: the Zeroth, First (energy conservation), Second (entropy), and Third (Nernst heat theorem) laws [1].
A deep understanding of thermodynamics is essential for advancing technologies such as fuel cells, enhanced oil recovery techniques, carbon capture and storage systems, and battery management systems. It also plays a critical role in manufacturing heat exchangers, which are widely used in industries like nuclear power, dyeing and printing, and steel production [2,3,4,5]. Furthermore, thermodynamics aids in determining equilibrium constants in chemical reactions [6,7,8], with applications in hydrogen production, carbon emission control, water treatment, material selection, and corrosion prevention [9].
Quantum mechanical methods, particularly non-fitting models, are increasingly embraced for analyzing the thermodynamic properties of molecular systems. These models offer a computationally efficient alternative for studying diatomic and polyatomic molecules. Fitted models, while supported by experimental data to improve accuracy, rely on data availability and are system-specific. They also require new data for different systems or conditions and are sensitive to temperature and pressure, limiting their broader use. In contrast, non-fitting models, based on fundamental physical principles, do not rely on experimental data and are valuable when such data are unavailable, offering a simplified approach to predicting thermal properties.
In polyatomic molecule analysis, both the number of atoms (atomicity) and the molecular shape are fundamental to identifying the vibrational modes. Each of these modes is associated with an oscillator similar to that of a diatomic molecule. The energy levels and partition function can then be calculated to explore different thermodynamic models. For a linear polyatomic molecule with N atoms, the number of vibrational modes is determined by the formula 3N–5.
A diatomic molecule (N = 2) has only one vibrational mode—the symmetric stretching mode. Different oscillator models, such as exponential-type and hyperbolic-type models, have been used to represent these vibrational modes [10,11,12,13,14,15]. Thermodynamic models derived from these oscillators, such as Helmholtz free energy, Gibbs free energy, mean thermal energy, heat capacities, enthalpy, and entropy, have been applied to various diatomic molecules [16,17,18,19,20,21,22,23,24,25,26,27,28,29,30,31].
Despite these successes, the thermodynamic properties of triatomic molecules remain underexplored, particularly when analyzed using non-fitting computational models. Analytical expressions for Gibbs free energy, entropy, heat capacity, and enthalpy have been derived by using appropriate representations of the vibrational, rotational, and translational partition functions, and by being applied to molecules such as MgCl2, Si2N, BeF2, CNC, BO2, and N3 [32]. Non-fitting models have also been employed to study the thermodynamic properties of nonlinear triatomic molecules, such as NO2, BF2, and AlCl2 [33]. However, the exploration of thermodynamic properties using these non-fitting models remains limited. Further studies on polyatomic molecules using non-fitting models are listed in [34,35,36,37,38,39,40].
Unlike diatomic molecules, which have a single vibrational mode, triatomic molecules are more complex. A linear triatomic molecule has the following four vibrational modes: symmetric, asymmetric, and two bending modes (degenerate). Thus, accurately formulating the thermodynamic functions for these molecules requires incorporating all four vibrational modes. Previous models for both linear and nonlinear polyatomic systems have used the improved Tietz (IMTZ) oscillator [10] to approximate the internal stretching vibrations. These models are based on three molecular constants (equilibrium dissociation energy, chemical bond length, and harmonic frequency of vibration) and two oscillator parameters (screening parameter α and dimensionless parameter q). A key limitation of the IMTZ model is the need to adjust the dimensionless parameter for each molecular system.
To address this issue, this study employs the modified Rosen–Morse (MRM) oscillator [11], which has proven effective in modeling the internuclear potential energy curve of diatomic molecules and handling anharmonicity in molecular systems. The MRM oscillator is widely used in fields such as solid-state physics, chemical physics, computational chemistry, and material science. Despite its versatility, the MRM oscillator has yet to be applied to study the thermodynamic properties of linear triatomic molecules. This study is the first to employ the MRM oscillator to derive computational models for the thermodynamic properties of these molecules, providing novel insights into the thermodynamics of triatomic systems.
The paper is organized as follows: Section 2 derives the thermodynamic functions; Section 3 uses these functions to generate numerical data for linear triatomic molecules such as BO2 (boron oxide), HCN (hydrogen cyanide), N3 (azide), and Si2N (silicon nitride); and Section 4 provides a brief conclusion.

2. Computational Method

This section outlines the computational models that do not rely on fitting parameters for determining the thermodynamic properties of linear triatomic molecules. The non-fitting computational method uses quantum mechanics to develop model equations that analyze the physical properties of substances. Unlike the fitting functional approach, which is restricted to systems or conditions similar to those used for parameter calibration, the non-fitting method is more adaptable and can be applied to a variety of chemical and physical systems. In this approach, the thermal properties of a linear triatomic molecule are predicted through analytical formulations that start with the canonical partition function, given by Q = Q vib Q rot Q tra , where Q vib , Q rot , and Q tra correspond to the vibrational, rotational, and translational partition functions, respectively [30].

2.1. Formulating the Vibrational Partition Function

In a linear triatomic molecule of the form XZY, where X, Y, and Z represent atoms, the system exhibits the following three distinct vibrational modes: symmetric stretching, asymmetric stretching, and two degenerate bending modes. The vibrational partition function Q vib is expressed as Q vib = Q s Q a Q b 2 , where Q s , Q a , and Q b represent the partition functions for the symmetric, asymmetric, and bending vibrations, respectively. The square in Q b 2 accounts for the two-fold degeneracy of the bending modes. If the molecule consists of more than three atoms while remaining linear, additional vibrational modes emerge, requiring an adjustment to the vibrational partition function to include these modes.
In a linear triatomic molecule XZY, where atoms X, Y, and Z are bonded in a straight line, symmetric stretching occurs when both the X-Z and Z-Y bonds stretch and compress in unison. If atoms X and Y are identical, the central atom Z shifts along the molecular axis, and both X and Y move symmetrically toward or away from Z. Since X and Y are the same, their movements are identical, resulting in equal changes in bond lengths and preserving the molecule’s symmetry.
In an asymmetric linear triatomic molecule, where X, Y, and Z are all different, the central atom Z moves along the molecular axis, and atoms X and Y move in phase. However, due to differences in atomic size, mass, and electronegativity, the displacements of X and Y are unequal. This leads to one bond (X-Z or Z-Y) stretching more than the other, causing an asymmetric vibration despite the motion occurring in phase.
However, anharmonicity causes deviations from perfect harmonic motion, particularly at higher energy levels, leading to the uneven spacing of vibrational energy levels. While previous studies modeled anharmonicity using the IMTZ potential, the present work employs the simpler MRM oscillator, which avoids the need for an adjustable dimensionless parameter that varies across molecules. The energy–distance relationship for a system modeled by the MRM oscillator is given by [11]
U r = D e 1 exp α r e r ij + 1 exp α r r ij + 1 2
where
α = k es 2 D e + 1 r e r ij W r e r ij k es 2 D e exp r e r ij k es 2 D e
is the potential screening parameter; D e is the equilibrium dissociation energy; k es = μ XY ( 2 π c ω es ) 2 is the equilibrium force constant for symmetric vibrations; μ XY is the reduced mass of atoms X and Y; c is the speed of light; ω es is the symmetric harmonic vibrational frequency; and the parameters r ij and r e are defined as r ij = r e 2 k es 1 D e and r e = r eZX + r eZY , where r eZX is the equilibrium bond length between atoms Z and X, r eZY is the equilibrium bond length between atoms Z and Y, W is the Lambert W function, and r is the internuclear separation between atoms X and Y.
Deng and Jia previously derived the vibrational partition function for a diatomic molecule using the MRM oscillator. Their expression for the symmetric stretching vibrations is adopted here, given by [41]
Q s = 1 2 exp ω 1 2 ω 2 λ 1 2 exp ω 2 2 ω 2 λ + π 4 ω 3 Erfi ω 1 + Erfi ω 2 exp ω 2 + λ Erfi ω ¯ 1 + Erfi ω ¯ 2 exp ω 2 + λ + 4 ω 3 2 ω 4 ,
ω 1 = ω 3 ω 5 ω 4 ω 5 1 ,
ω 2 = ω 3 ν max + 1 ω 5 ω 4 ν max + 1 ω 5 1 ,
ω ¯ 1 = ω 3 ω 5 + ω 4 ω 5 1 ,
ω ¯ 2 = ω 3 ν max + 1 ω 5 + ω 4 ν max + 1 ω 5 1 ,
ω 3 = α 1 8 β μ XY 1
ω 4 = 2 μ XY D e α 2 2 exp 2 α r e r ij 1 ,
ω 5 = 1 2 + 1 2 + 2 μ XY D e α 2 2 exp α r e r ij + 1 2 ,
In Equation (3), ω = β D e 1 2 , where β−1 = kBT (with T representing the temperature and kB the Boltzmann constant); Erfi(z) denotes the imaginary error function evaluated at z. ν max = ω 5 + ω 4 1 2 refers to the number of excited bonded molecular states, which can be deduced by applying E ν ν ν max = 0 , where ν = 0, 1, 2, … is the vibrational quantum number, Eν represents the vibrational energy eigenvalues, ℏ is the reduced Planck constant, and λ is an optimization parameter. As noted in Ref. [42], exp 4 ω 3 2 ω 4 is negligibly small for the molecular system. By neglecting the terms involving this factor, the partition function simplifies to
Q s = 1 2 exp ω 1 2 ω 2 λ 1 2 exp ω 2 2 ω 2 λ + π 4 ω 3 Erfi ω 1 + Erfi ω 2 exp ω 2 + λ .
In the asymmetric stretching vibration, the bonds (X-Z and Z-Y) stretch and compress in opposite directions, causing unequal changes in bond lengths. During this vibration, atom Z moves along the molecular axis, while atoms X and Y move in opposite directions. This mode is termed “asymmetric” because the two sides of Z behave differently. The bending vibration, on the other hand, changes the angle between the bonds (X-Z and Z-Y), rather than the bond lengths. In this mode, atoms X and Y move perpendicular to the molecular axis, causing the bond angle to increase or decrease. There are two degenerate bending modes with the same frequency but different atomic motion directions, typically referred to as in-plane and out-of-plane bending. These bending vibrations occur at lower frequencies than the stretching modes.
Anharmonicity plays an important role in selecting oscillator models to represent the internal motion of molecular systems. It refers to how molecular vibrations deviate from the idealized harmonic oscillator behavior. In simpler systems, deviations are typically less pronounced in asymmetric and bending modes than in symmetric stretching modes. At typical temperatures, these deviations are smaller in asymmetric and bending vibrations compared to symmetric stretching vibrations, likely due to the lower vibrational frequencies of the atoms involved. Therefore, at standard temperatures, these vibrations can often be accurately modeled using harmonic oscillator potentials. As a result, the partition functions for the asymmetric and bending modes are given in compact form as [43]
Q A = 1 2 csch 2 π c ω e A β , A a , b ,
where ω e a and ω e b are the equilibrium frequencies for the asymmetric and bending vibrations, respectively.

2.2. Formulating the Rotational and Translational Partition Functions

Using the rigid rotor approximation for molecular systems and neglecting molecular interactions, the rotational and translational partition functions can be expressed as [43]
Q rot =   1 3 + Ω 1 β 1 + 1 15 Ω β + 4 315 Ω 2 β 2 ,
Q tra = 1 p m 2 π 2 3 2 β 5 2 .
In these expressions, Ω =   1 2 μ r e 2 1 2 , m denotes the molar mass, and p represents the pressure exerted by the system in a container of volume V.

2.3. Formulating the Thermodynamic Functions

In this work, analytical equations for assessing the thermal properties of a linear triatomic molecule are derived from the following expressions [43]
S = R ln Q γ 1 ,
H = N A γ 1 ,
G = R T ln Q ,
C p = R γ 1 2 + γ 2 .
In these equations, γ 1 = β Q Q β , γ 2 = β 2 Q 2 Q β 2 , and the Avogadro number, N A , with R denotes the universal gas constant. Additionally, S represents the molar entropy, H the molar enthalpy, G the molar Gibbs free energy, and C p is the constant-pressure (or isobaric) molar heat capacity. The thermodynamic functions are computed by substituting Q = Q vib Q rot Q tra and Q vib = Q s Q a Q b 2 into Equations (8)–(11). The first- and second-order derivatives required for these evaluations are derived from Equations (4)–(7), with the corresponding expressions for the first and second derivatives provided in (12) and (13), respectively.
β Q s Q s β = ω 2 1 2 + 2 ω 1 2 + ω 1 ω 3 1 + 1 4 Q s exp ω 2 ω 1 2 + λ 2 ω 2 2 ω 2 ω 3 1 + 1 4 Q s exp ω 2 ω 2 2 + λ ,
β Q A Q A β = 2 π c ω e A β 1 + 4 Q A 2 , A a , b ,
β Q rot Q rot β = β Q rot Ω 1 β 2 1 15 Ω 8 315 Ω 2 β ,
β Q tra Q tra β = 5 2 ,
β 2 Q s 2 Q s β 2 = ω 4 + ω 2 + 3 4 + 4 ω 1 2 ω 2 2 2 ω 2 + 1 2 + ω 1 ω 3 1 2 ω 1 2 4 ω 2 3 2 8 Q s exp ω 2 ω 1 2 + λ ,
β 2 Q A 2 Q A β 2 = 4 π 2 2 c 2 ω eA 2 β 1 + 8 Q A 2 , A a , b ,
β 2 Q rot 2 Q rot β 2 = β 2 Q rot 2 Ω 1 β 3 + 8 315 Ω 2 ,
β 2 Q tra 2 Q tra β 2 = 35 4 .
This work introduces the application of these equations specifically to the thermal properties of linear triatomic molecules, providing new insights into the calculation of thermodynamic properties. The use of the MRM oscillator, a tool previously underexplored in this context, represents a significant advancement in computational thermodynamics.

3. Results and Discussion

The accuracy of the new model equations for analyzing the thermal properties of linear triatomic molecules is assessed using data on equilibrium dissociation energy ( D e ), harmonic vibrational frequencies ( ω e s , ω e a , ω e b ), and bond lengths ( r e ZX , r e ZY ). The molecules considered, including boron oxide (BO2), hydrogen cyanide (HCN), azide (N3), and silicon nitride (Si2N), are selected for their relevance to computational and theoretical chemistry, atomic and molecular physics, materials science, and chemical physics. The equilibrium dissociation energy represents the energy required to break a molecule XZY into X and ZY. For these molecules, the dissociation reactions are as follows: BO2 dissociates into O and BO [44], HCN dissociates into H and CN [45], N3 dissociates into N and N2 [46], and Si2N dissociates into Si and NSi [47]. Model parameters, along with experimental values for D e , r e ZX , r e ZY , ω e s , ω e a , and ω e b , are provided in Table 1, with data drawn from Refs. [32,34,44,45,46,47].

3.1. Significance of the Optimization Parameter

Before exploring the applicability of the model equations, it is important to consider the role of the optimization parameter, λ, introduced into the partition function. By expressing the symmetric partition function as Q s = F β e λ , where F(β) is solely a function of temperature, the combined partition function Q = Q vib Q rot Q tra , where Q vib = Q s Q a Q b 2 , can also be expressed as
lnQ = ln F β + lnQ a + 2 lnQ b + lnQ rot + lnQ tra λ .
The first derivative of this equation is given by
β lnQ = β ln F β + β lnQ a + 2 β lnQ b + β lnQ rot + β lnQ tra .
Equation (14) clearly depends on λ, which in turn affects the molar entropy and Gibbs free energy (Equations (8) and (10)). However, Equation (15) is independent of λ, meaning the molar enthalpy (Equation (9)) and heat capacity (Equation (11)) are unaffected by changes in the optimization parameter. Setting λ = 0 effectively disables the optimization parameter, which, in turn, recovers the original model equations. This recovery ensures that the system returns to the unoptimized form, where the entropy and Gibbs free energy models are no longer adjusted by λ, but the enthalpy and heat capacity remain unchanged. The optimization parameter, λ, is varied manually until optimized data for molar entropy and reduced Gibbs free energy are achieved.

3.2. Validating the Thermodynamic Models

This section explores the use of model equations to evaluate the thermodynamic properties of linear triatomic molecules, as listed in Table 1. The model equations generate numerical data, which are then compared to available experimental data. The accuracy of the model is assessed based on Lippincott’s specifications, which dictate that the mean percentage absolute deviation (MPAD) between observed and experimental values should not exceed 1%.
To calculate the MPAD, the following equation is applied: MPAD = N p 1 j PAD j , where Np denotes the total number of experimental data points and PAD j = 100 1 A j B j 1 represents the percentage absolute deviation [25]. The terms Aj and Bj refer to the predicted and experimental values at data point j, respectively. One source of experimental data for comparison is the NIST database [48]. NIST employs a fitting functional approach, using various fitting parameters to model the thermal properties of a substance, though its applicability is limited to certain temperature and pressure ranges.
The approach presented here offers a more efficient alternative by reducing the need for extensive experimental setups and the large number of fitting parameters used in the NIST method. Instead, only a few key molecular constants—such as equilibrium dissociation energy, vibrational frequencies, and bond lengths—are required to predict the thermal properties of linear triatomic systems. Since NIST results for molar enthalpy and Gibbs free energy are standardized to molar enthalpy at T = 298.15 K and p = 0.1 MPa, this study introduces theoretical adjustments to calibrate enthalpy and Gibbs free energy using the following equations
H STA = H H 0 ,
G STA = T 1 H 0 G ,
Here, H0 represents the enthalpy calculated from Equation (9) at T = 298.15 K and p = 0.1 MPa. The thermodynamic functions from Equations (8), (11), (16) and (17) are applied to the data in Table 1, where pressure is held constant at 0.1 MPa and temperature varies from 300 to 6000 K. MATLAB (version 2016a) is utilized for numerical computations and to generate graphical plots. The program includes molecular constants and other necessary parameters, such as those defining the canonical partition function.
The computational procedure is illustrated using data for the HCN molecule. When T = 298.15 K, p = 0.1 MPa, and λ is set to zero, the dimensionless parameters γ1 and γ2 are calculated as −20.3332 and 10.2903, respectively. These values are substituted into Equation (9), yielding H0 = 51.48 kJmol−1. This value of H0 is required for the calculation of HSTA and GSTA at other temperatures.
When T = 300 K, p = 0.1 MPa, and λ set to 2.3, the dimensionless parameters are γ1 = −20.2361 and γ2 = 8.9915. These values are inserted into Equations (8), (11), (16) and (17), resulting in S = 200.095 Jmol−1K−1, Cp = 38.146 Jmol−1K−1, HSTA = 0.070 kJmol−1, and GSTA = 199.860 Jmol−1K−1. The same procedure is repeated for the other temperature values.
The program algorithm also calculates the MPAD values, enabling λ to be adjusted gradually to optimize S and GSTA. The numerical results for BO2, HCN, N3, and Si2N, along with the NIST data and MPAD values, are summarized in Table 2, Table 3, Table 4 and Table 5. A MATLAB script for computing the thermodynamic properties of nonlinear triatomic molecules is available upon request.
The results show that the MPAD values for all molecules fall within the acceptable range. However, the models for enthalpy and heat capacity slightly deviate from the NIST data for the HCN molecule, with the MPAD exceeding the Lippincott error threshold. These discrepancies may result from the exclusion of quantum correction terms in the partition function for the MRM oscillator [41]. Nevertheless, the models for molar enthalpy and heat capacity provide accurate predictions for most molecules.
Figure 1, Figure 2, Figure 3 and Figure 4 present the temperature dependence of the thermal functions, with the corresponding NIST data shown for comparison. The alignment of the predicted thermal functions with the NIST data further supports the validity of the proposed thermodynamic models in predicting the thermal properties of the selected triatomic molecules.
Finally, Table 6 compares the performance of the MRM models (developed in the present work) with the existing IMTZ models from the literature. The MPAD values for the MRM models are smaller than those for the IMTZ models, indicating that the MRM models offer improved accuracy in predicting the thermal properties of BO2, HCN, N3, and Si2N. Both the MRM and IMTZ models incorporate optimization parameters for efficiency and rely on the same input data. However, the simplicity of the MRM models lies in their ability to predict thermal properties without requiring a dimensionless parameter.

4. Conclusions

In this study, computational models are developed to estimate the thermodynamic properties of linear triatomic molecules, including molar enthalpy, molar Gibbs free energy, constant pressure molar heat capacity, and molar entropy. These models are derived from the partition functions of the modified Rosen–Morse (MRM) potential, which simulates symmetric vibrational modes, and the harmonic oscillator, which represents asymmetric and 2-fold degenerate bending vibrational modes. The models incorporate key parameters such as equilibrium dissociation energy (De), vibrational frequencies (ωes, ωea, ωeb), and bond lengths (reZX, reZY). Additionally, an optimization parameter (λ) is introduced to refine the expressions for molar entropy and Gibbs free energy. The models are then applied to determine the thermodynamic properties of linear triatomic molecules, including BO2, HCN, N3, and Si2N. The determined values are compared to experimental data from the National Institute of Standards and Technology (NIST) database. When assessed using the mean percentage absolute deviation (MPAD), the models show strong accuracy, as follows: the MPAD for molar entropy and Gibbs free energy is no greater than 0.17%, while the MPAD for molar enthalpy and isobaric heat capacity does not exceed 2%. The determined thermodynamic properties agree with values found in the literature for triatomic molecules. These computational models provide an efficient and straightforward approach for estimating thermodynamic properties, making them highly relevant for applications in the chemical industry, environmental chemistry, materials science, and chemical engineering.

Author Contributions

E.S.E.: Conceptualization; Supervision; Data curation; Writing—Original draft; Writing—Review and editing; Methodology; Validation; Formal analysis; Resources; and Software. A.D.A.: Data curation; Writing—Original draft; Writing—Review and editing; Methodology; Formal analysis; Resources; and Software. C.A.O.: Writing—Original draft; Writing—Review and editing; Methodology; Data curation; and Formal analysis. E.O.: Writing—Original draft; Writing—Review and editing; Methodology; Data curation; Formal analysis; Investigation; Validation; and Visualization. E.P.I.: Data curation; Formal analysis; Investigation; Resources; Software; Visualization; Writing—Original draft; Writing—Review and editing; and Methodology. S.A.: Formal analysis; Investigation; Resources; Software; Visualization; Writing—Original draft; Writing—Review and editing; and Methodology. E.K.M.: Supervision; Writing—Original draft; Writing—Review and editing; Methodology; Project administration; Resources; and Validation. All authors have read and agreed to the published version of the manuscript.

Funding

This research received no external funding.

Data Availability Statement

The original contributions presented in this study are included in the article. Further inquiries can be directed to the corresponding author.

Conflicts of Interest

We have no known competing financial interest or personal relationships that could have appeared to influence the work reported in this paper.

Glossary

NISTNational Institute of Standards and Technology
NAtomicity or number of atoms in a molecule
IMTZImproved Tietz
MRMModified Rosen–Morse
QCanonical partition function
Q vib Vibrational partition function
Q rot Rotational partition function
Q tra Translational partition function
Q s Partition function for symmetric vibration
Q a Partition function for asymmetric vibration
Q b Partition function for bending vibration
XZYLinear triatomic molecule with atoms X, Y, and Z
D e Equilibrium dissociation energy
k es Equilibrium force constant for the symmetric vibration
μ XY Reduced mass of atoms X and Y
cSpeed of light
ω es Symmetric harmonic vibrational frequency
ω ea Asymmetric harmonic vibrational frequency
ω eb Bending vibration harmonic frequency
r eZX Equilibrium bond length between atoms Z and X
r eZY Equilibrium bond length between atoms Z and Y
WLambert W function
rInternuclear separation between atoms X and Y
TTemperature and kB the Boltzmann constant
k B Boltzmann constant
Erfi(z)Imaginary error function evaluated at z
ν max Number of excited bonded molecular states
νVibrational quantum number
E ν Vibrational energy eigenvalues
Reduced Planck constant
λOptimization parameter
mMolar mass of molecule
pPressure exerted by gaseous molecules
VVolume of gaseous molecules
N A Avogadro number
RUniversal gas constant
SMolar entropy
HMolar enthalpy
H STA Calibrated molar enthalpy
GMolar Gibbs free energy
G STA Calibrated molar Gibbs free energy
C p Constant-pressure (or isobaric) molar heat capacity
PADPercentage absolute deviation
MPADMean percentage absolute deviation

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Figure 1. Characterization of molar thermodynamic functions for the BO2 molecule, with comparison to NIST data.
Figure 1. Characterization of molar thermodynamic functions for the BO2 molecule, with comparison to NIST data.
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Figure 2. Characterization of molar thermodynamic functions for the HCN molecule, with comparison to NIST data.
Figure 2. Characterization of molar thermodynamic functions for the HCN molecule, with comparison to NIST data.
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Figure 3. Characterization of molar thermodynamic functions for the N3 molecule, with comparison to NIST data.
Figure 3. Characterization of molar thermodynamic functions for the N3 molecule, with comparison to NIST data.
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Figure 4. Characterization of molar thermodynamic functions for the Si2N molecule, with comparison to NIST data.
Figure 4. Characterization of molar thermodynamic functions for the Si2N molecule, with comparison to NIST data.
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Table 1. Equilibrium dissociation energy, bond lengths, vibrational frequencies, and screening and optimization parameters for linear triatomic molecules in this study.
Table 1. Equilibrium dissociation energy, bond lengths, vibrational frequencies, and screening and optimization parameters for linear triatomic molecules in this study.
MoleculeAtoms in MoleculeMolecular Parameter [32,34,44,45,46,47]α−1)λ
XZYDe (kcalmol−1)reZX (Å)reZY (Å)ωes (cm−1)ωea (cm−1)ωeb (cm−1)
BO2OBO68.331.2631.26310561321.74542.79170.913
HCNHCN130.0184 #1.0661.1532096.33311.5713.51.37752.300
N3NNN219.61.181151.18115132016454571.82161.130
Si2NSiNSi1231.701.7060010002401.56660.812
130.0184 # kcalmol−1 = 544 kJmol−1.
Table 2. Comparison of thermodynamic properties of the BO2 molecule at 0.1 MPa: NIST data vs. MRM model predictions.
Table 2. Comparison of thermodynamic properties of the BO2 molecule at 0.1 MPa: NIST data vs. MRM model predictions.
T [48]S (J mol−1K−1)H (kJ mol−1)G (J mol−1K−1)Cp (J mol−1K−1)
Equation (8)NIST [48]Equation (16)NIST [48]Equation (17)NIST [48]Equation (11)NIST [48]
300229.618230.0820.0830.080229.342229.81544.76343.359
350236.676236.9312.3732.303229.895230.35146.80545.527
400243.042243.1414.7584.630231.147231.56748.54847.495
450248.849248.8387.2247.049232.796233.17450.05249.246
500254.192254.1089.7609.550234.672235.00751.35650.780
2900356.949356.752153.495152.949304.020304.01162.66461.904
3000359.076358.852159.768159.142305.820305.80462.78161.961
3100361.136360.884166.052165.341307.571307.54862.89762.019
3200363.135362.854172.347171.546309.276309.24663.01262.078
3300365.076364.765178.654177.757310.938310.90063.12662.138
5600398.976398.069326.275322.804340.713340.42564.83664.169
5700400.124399.206332.759329.226341.745341.44764.84564.273
5800401.252400.324339.244335.658342.762342.45264.84864.377
5900402.360401.426345.729342.101343.762343.44364.84564.480
6000403.450402.510352.213348.554344.748344.41864.83664.582
MPAD (%)0.1030.8220.0501.190
Table 3. Comparison of thermodynamic properties of the HCN molecule at 0.1 MPa: NIST data vs. MRM model predictions.
Table 3. Comparison of thermodynamic properties of the HCN molecule at 0.1 MPa: NIST data vs. MRM model predictions.
T [48]S (J mol−1K−1)H (kJ mol−1)G (J mol−1K−1)Cp (J mol−1K−1)
Equation (8)NIST [48]Equation (16)NIST [48]Equation (17)NIST [48]Equation (11)NIST [48]
300200.095202.0500.0700.066199.860201.82938.14635.928
400211.600212.8634.0793.833201.403203.28141.78839.229
500221.210221.8948.3907.885204.430206.12544.29141.731
600229.454229.69012.91412.164207.930209.41746.11643.806
700236.676236.58317.60116.638211.531212.81547.57745.643
3100317.712317.718151.976152.072268.687268.66360.11661.347
3200319.623319.669157.995158.215270.249270.22660.27061.513
3300321.479321.564164.030164.374271.774271.75460.41561.669
3400323.285323.407170.078170.548273.262273.24660.55161.814
3500325.042325.201176.140176.736274.717274.70560.68061.948
5600354.002354.707305.679308.689299.416299.58462.50563.358
5700355.108355.829311.933315.026300.383300.56162.57363.378
5800356.197356.931318.194321.364301.336301.52462.64063.395
5900357.269358.015324.461327.705302.275302.47262.70763.407
6000358.323359.081330.735334.046303.201303.40762.77363.417
MPAD (%)0.1621.6660.1311.980
Table 4. Comparison of thermodynamic properties of the N3 molecule at 0.1 MPa: NIST data vs. MRM model predictions.
Table 4. Comparison of thermodynamic properties of the N3 molecule at 0.1 MPa: NIST data vs. MRM model predictions.
T [48]S (J mol−1K−1)H (kJ mol−1)G (J mol−1K−1)Cp (J mol−1K−1)
Equation (8)NIST [48]Equation (16)NIST [48]Equation (17)NIST [48]Equation (11)NIST [48]
300225.361226.7210.0810.075225.092226.47043.75540.842
350232.244233.1722.3142.169225.631226.97445.53442.864
400238.425239.0164.6304.359226.851228.12047.04444.686
450244.044244.3777.0166.635228.454229.63348.37146.339
500249.203249.3389.4658.990230.274231.35849.55647.838
2900349.441349.221150.092149.614297.686297.63061.43261.503
3000351.525351.307156.239155.767299.446299.38561.50561.558
3100353.543353.327162.393161.926301.159301.09361.57461.607
3200355.499355.283168.553168.089302.826302.75661.63861.652
3300357.397357.181174.720174.256304.451304.37661.69761.693
5600390.254389.944317.700316.788333.522333.37462.51362.153
5700391.360391.044323.952323.004334.527334.37762.53762.165
5800392.448392.125330.207329.222335.516335.36362.56162.177
5900393.518393.188336.464335.440336.490336.33462.58462.189
6000394.570394.234342.724341.659337.449337.29062.60762.202
MPAD (%)0.0981.1990.0970.793
Table 5. Comparison of thermodynamic properties of the Si2N molecule at 0.1 MPa: NIST data vs. MRM model predictions.
Table 5. Comparison of thermodynamic properties of the Si2N molecule at 0.1 MPa: NIST data vs. MRM model predictions.
T [48]S (J mol−1K−1)H (kJ mol−1)G (J mol−1K−1)Cp (J mol−1K−1)
Equation (8)NIST [48]Equation (16)NIST [48]Equation (17)NIST [48]Equation (11)NIST [48]
300256.930256.7950.0940.092256.618256.48850.66349.965
350264.863264.6522.6682.642257.241257.10452.25151.951
400271.930271.6995.3155.281258.643258.49553.59853.570
450278.311278.0878.0247.994260.480260.32354.73254.886
500284.128283.92710.78510.766262.558262.39555.68755.958
2800387.749387.821150.997151.094333.822333.85962.41762.097
2900389.940390.000157.241157.305335.719335.75762.46362.118
3000392.058392.106163.489163.517337.562337.60162.50762.137
3100394.109394.144169.742169.732339.353339.39262.54962.156
3200396.095396.118175.999175.949341.096341.13462.59062.175
5600431.355431.093327.320326.046372.905372.87163.53863.112
5700432.480432.211333.676332.361373.940373.90263.58363.179
5800433.586433.310340.037338.682374.959374.91763.62963.248
5900434.674434.392346.402345.010375.962375.91663.67563.318
6000435.745435.457352.771351.346376.950376.89963.72163.391
MPAD (%)0.0360.2990.0160.583
Table 6. Benchmarking APAD (%) data for MRM thermodynamic models against the literature-based IMTZ models.
Table 6. Benchmarking APAD (%) data for MRM thermodynamic models against the literature-based IMTZ models.
ModelBO2HCNN3Si2N
MRMIMTZ [32]MRMIMTZ [34]MRMIMTZ [32]MRMIMTZ [32]
Entropy0.1030.1320.1620.1760.0980.1060.0360.044
Enthalpy0.8221.1181.6661.7051.1991.3780.2990.323
Gibbs free energy0.0500.0530.1310.0980.0970.0470.0160.014
Heat capacity1.1901.3341.9801.8990.7930.8810.5830.640
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Eyube, E.S.; Ahmed, A.D.; Onate, C.A.; Omugbe, E.; Inyang, E.P.; Amasuwa, S.; Makama, E.K. Computational Models for Analyzing the Thermodynamic Properties of Linear Triatomic Molecules. Chemistry 2025, 7, 35. https://doi.org/10.3390/chemistry7020035

AMA Style

Eyube ES, Ahmed AD, Onate CA, Omugbe E, Inyang EP, Amasuwa S, Makama EK. Computational Models for Analyzing the Thermodynamic Properties of Linear Triatomic Molecules. Chemistry. 2025; 7(2):35. https://doi.org/10.3390/chemistry7020035

Chicago/Turabian Style

Eyube, Edwin S., Abubakar D. Ahmed, Clement A. Onate, Ekwevugbe Omugbe, Etido P. Inyang, Sanda Amasuwa, and Ezekiel K. Makama. 2025. "Computational Models for Analyzing the Thermodynamic Properties of Linear Triatomic Molecules" Chemistry 7, no. 2: 35. https://doi.org/10.3390/chemistry7020035

APA Style

Eyube, E. S., Ahmed, A. D., Onate, C. A., Omugbe, E., Inyang, E. P., Amasuwa, S., & Makama, E. K. (2025). Computational Models for Analyzing the Thermodynamic Properties of Linear Triatomic Molecules. Chemistry, 7(2), 35. https://doi.org/10.3390/chemistry7020035

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