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A Systematic Exploration of B-F Bond Dissociation Enthalpies of Fluoroborane-Type Molecules at the CCSD(T)/CBS Level.

ABSTRACT: Fluoroborane-type molecules (R¹R²B-F) are of interest in synthetic chemistry, but to date, apart from a handful of small species (such as H₂BF, HBF₂, and BF₃), little is known concerning the effect of substituents in governing the strength of the B-F bonds of such species toward homolytic dissociation in the gas phase. In this study, we have calculated the bond dissociation enthalpies (BDEs) of thirty unique B-F bonds at the CCSD(T)/CBS level using the high-level W1w thermochemical protocol. The B-F bonds in all species considered are very strong, ranging from 545.9 kJ mol^-1 in (H₂B)₂B-F to 729.2 kJ mol^-1 HBF₂. Nevertheless, these BDEs still vary over a wide range of 183.3 kJ mol^-1. The structural properties that affect the BDEs are examined in detail, and the homolytic BDEs are rationalized based on molecule stabilization enthalpies and radical stabilization enthalpies. Since polar B-F bonds may represent a challenging test case for density functional theory (DFT) methods, we proceed to examine the performance of a wide range of DFT methods across the rungs of Jacob's Ladder for their ability to compute B-F BDEs. We find that only a handful of DFT methods can reproduce the CCSD(T)/CBS BDEs with mean absolute deviations (MADs) below the threshold of chemical accuracy (i.e., with average deviations below 4.2 kJ mol^-1). The only functionals capable of achieving this feat were (MADs given in parentheses): ωB97M-V (4.0), BMK (3.5), DSD-BLYP (3.8), and DSD-PBEB95 (1.8 kJ mol^-1).

SUBMITTER: O'Reilly RJ

PROVIDER: S-EPMC10420309 | biostudies-literature | 2023 Jul

REPOSITORIES: biostudies-literature

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A Systematic Exploration of B-F Bond Dissociation Enthalpies of Fluoroborane-Type Molecules at the CCSD(T)/CBS Level.

O'Reilly Robert J RJ Karton Amir A

Molecules (Basel, Switzerland) 20230728 15

Fluoroborane-type molecules (R1R2B-F) are of interest in synthetic chemistry, but to date, apart from a handful of small species (such as H2BF, HBF2, and BF3), little is known concerning the effect of substituents in governing the strength of the B-F bonds of such species toward homolytic dissociation in the gas phase. In this study, we have calculated the bond dissociation enthalpies (BDEs) of thirty unique B-F bonds at the CCSD(T)/CBS leve ...[more]

PMID: 37570677

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Project description:A broad collection of technologies, including e.g. drug metabolism, biofuel combustion, photochemical decontamination of water, and interfacial passivation in energy production/storage systems rely on chemical processes that involve bond-breaking molecular reactions. In this context, a fundamental thermodynamic property of interest is the bond dissociation energy (BDE) which measures the strength of a chemical bond. Fast and accurate prediction of BDEs for arbitrary molecules would lay the groundwork for data-driven projections of complex reaction cascades and hence a deeper understanding of these critical chemical processes and, ultimately, how to reverse design them. In this paper, we propose a chemically inspired graph neural network machine learning model, BonDNet, for the rapid and accurate prediction of BDEs. BonDNet maps the difference between the molecular representations of the reactants and products to the reaction BDE. Because of the use of this difference representation and the introduction of global features, including molecular charge, it is the first machine learning model capable of predicting both homolytic and heterolytic BDEs for molecules of any charge. To test the model, we have constructed a dataset of both homolytic and heterolytic BDEs for neutral and charged (-1 and +1) molecules. BonDNet achieves a mean absolute error (MAE) of 0.022 eV for unseen test data, significantly below chemical accuracy (0.043 eV). Besides the ability to handle complex bond dissociation reactions that no previous model could consider, BonDNet distinguishes itself even in only predicting homolytic BDEs for neutral molecules; it achieves an MAE of 0.020 eV on the PubChem BDE dataset, a 20% improvement over the previous best performing model. We gain additional insight into the model's predictions by analyzing the patterns in the features representing the molecules and the bond dissociation reactions, which are qualitatively consistent with chemical rules and intuition. BonDNet is just one application of our general approach to representing and learning chemical reactivity, and it could be easily extended to the prediction of other reaction properties in the future.

Project description:The concept of a bond energy between a pair of atoms is well-established in chemistry and physics. In materials science, it is a fundamental parameter in the development of thermodynamic models such as the regular, quasi-chemical and sub-regular solution models, as well as the central atoms model. Accurate bond dissociation enthalpies are available for gaseous molecular compounds, but these values are likely to differ significantly from single bond strengths between atoms in liquids and solids. While interatomic potential functions have been developed for atomic pairs by fitting to observed quantities, these functions often contain invariant transformations that yield bond energies that differ by up to a factor of four from values provided by other potentials for the same system, even though both may produce the same physical properties. Moreover, there is presently no widely used approach to determine bond enthalpies in condensed phases. An approach has been developed earlier to calculate bond enthalpies in solid and liquid phases using classical thermodynamic concepts, measured enthalpies for compound formation and elemental sublimation, and by counting bonds in the thermodynamically stable product and reactant phases (Miracle et al., 2011). That work reported bond enthalpies for essentially all stable solid and liquid elements, as well as bond strengths between unlike atoms for 71 different intermetallic compounds in 15 binary systems. This earlier work was validated by estimating elemental fusion enthalpies and surface energies, as well as formation enthalpies for ternary intermetallic compounds. Given the utility of this approach, the present dataset applies this earlier methodology to produce bond enthalpies between unlike atom pairs in an additional 904 binary intermetallic compounds from 443 systems, giving a total dataset of 975 bond enthalpies from 458 binary systems. Typical errors in the values reported here (from enthalpy measurements) are ±4%, and larger errors of about ±10-30% occur for a small subset of values where the number of bonds in the structure are difficult to establish. Used appropriately, these bond enthalpies enable classical approximations that-to first order-can capture critical material properties. A wide range of such estimates are possible, including the energies of vacancies and other atomic defects, solution enthalpies for complex, concentrated solid solution alloys (CCAs), formation enthalpies of higher-order compounds, and metallic glass stability. These bond enthalpies may also be useful for establishing trends in systematic studies that cover many systems, thus narrowing the scope of subsequent experimental measurements or computations which are more accurate, but are also more difficult and time consuming.

Dataset Information

A Systematic Exploration of B-F Bond Dissociation Enthalpies of Fluoroborane-Type Molecules at the CCSD(T)/CBS Level.

Publications

A Systematic Exploration of B-F Bond Dissociation Enthalpies of Fluoroborane-Type Molecules at the CCSD(T)/CBS Level.

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