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Halocarbon Thermochemistry: A Challenge for Density Functional Theory

Dorian Armando Acevedo-Castro1, Jhon Faber Zapata1, Ricardo Urrego-Ortiz2,3, Santiago Builes1,*, and Federico Calle-Vallejo3,4,†

  • 1Escuela de Ciencias Aplicadas e Ingeniería, Universidad EAFIT, Carrera 49 # 7 sur – 50, Medellín 050022, Colombia
  • 2Department of Materials Science and Chemical Physics and Institute of Theoretical and Computational Chemistry, University of Barcelona, Barcelona, Spain
  • 3Nano-Bio Spectroscopy Group and European Theoretical Spectroscopy Facility, Department of Advanced Materials and Polymers: Physics, Chemistry and Technology, University of the Basque Country (EHU), Avenida Tolosa 72, 20018 San Sebastián, Spain
  • 4IKERBASQUE, Basque Foundation for Science, Plaza de Euskadi 5, 48009 Bilbao, Spain

  • *Contact author: sbuiles@eafit.edu.co
  • †Contact author: federico.calle@ehu.es
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PRX Energy 5, 023001 – Published 9 April, 2026

DOI: https://doi.org/10.1103/xg4n-6mfg

Abstract

Halocarbons have a vast array of industrial applications and non-negligible environmental impact. Their structures, properties, and thermochemistry are often modeled with the use of density functional theory (DFT) calculations. Here we analyze the DFT-calculated gas-phase formation enthalpies of 56 halocarbons containing various amounts of F, Cl, Br, and I using a group-additivity approach and seven exchange-correlation functionals (Perdew-Burke-Ernzerhof, Perdew-Wang 91, revised Perdew-Burke-Ernzerhof, Bayesian error estimation functional with van der Waals corrections, Tao-Perdew-Staroverov-Scuseria, Becke 3-parameter Lee-Yang-Parr, and Heyd-Scuseria-Ernzerhof 2006). Carbon—halogen bonds are found to introduce significant errors in the formation enthalpies, which are proportional to the electronegativity of the elements. We devised two correction methods based on the number and type of functional groups in each molecule in the reactants and products of the formation reactions. Both methods lower the mean absolute errors from approximately 0.35 eV to approximately 0.05 eV. Finally, the corrections were tested in an independent set of more than 150 reactions, and high accuracy was found without relying on error cancellation.

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Halocarbons are organic compounds with bonds between carbon, hydrogen, and halogen atoms (fluorine, chlorine, bromine, and iodine). They have numerous applications in industry and technology and often have a harmful environmental impact. Their structures, physicochemical properties, and chemical reactions are generally modeled using density functional theory (DFT) calculations. In this work, the authors show that DFT calculations exhibit sizable errors when predicting the energies of chemical reactions involving halocarbons because carbon-halogen bonds are not well described. Interestingly, the errors are proportional to the electronegativity of the elements forming the bonds. The authors devised two correction methods to lower these errors to the scale of “chemical accuracy.” They verified the benefit of the corrections in an independent set of halocarbon reactions and high accuracy was found without relying on error cancellation. The enhanced halocarbon energetics calculated with these methods can be used to improve DFT-based models for a number of applications including atmospheric modeling and catalysis.

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References (86)

  1. P. M. D. F. Forster and M. Joshi, The role of halocarbons in the climate change of the troposphere and stratosphere, Clim. Change 71, 249 (2005).
  2. S. Hu, L. F. Cabeza, and D. Yan, Review and estimation of global halocarbon emissions in the buildings sector, Energy Build. 225, 110311 (2020).
  3. W.-Y. Fang, L. Ravindar, K. P. Rakesh, H. M. Manukumar, C. S. Shantharam, N. S. Alharbi, and H.-L. Qin, Synthetic approaches and pharmaceutical applications of chloro-containing molecules for drug discovery: A critical review, Eur. J. Med. Chem. 173, 117 (2019).
  4. J. M. Calm, The next generation of refrigerants—Historical review, considerations, and outlook, Int. J. Refrig. 31, 1123 (2008).
  5. A. Ghosh and S. Berg, Arrow Pushing in Inorganic Chemistry (John Wiley & Sons, Inc. (Wiley), Hoboken, New Jersey, 2014), p. 252.
  6. R. Kampes, S. Zechel, M. D. Hager, and U. S. Schubert, Halogen bonding in polymer science: Towards new smart materials, Chem. Sci. 12, 9275 (2021).
  7. P. Jeschke, The unique role of halogen substituents in the design of modern agrochemicals, Pest Manage. Sci. 66, 10 (2010).
  8. J. Villamayor, F. Iglesias-Suarez, C. A. Cuevas, R. P. Fernandez, Q. Li, M. Abalos, R. Hossaini, M. P. Chipperfield, D. E. Kinnison, S. Tilmes, et al., Very short-lived halogens amplify ozone depletion trends in the tropical lower stratosphere, Nat. Clim. Change 13, 554 (2023).
  9. W. D. Rhodes, V. I. Kovalchuk, and M. A. McDonald, Reaction pathways of halocarbon catalytic oligomerization, Catal. Commun. 18, 98 (2012).
  10. C. Fernandez-Ruiz, S. Liu, J. Bedia, J. J. Rodriguez, and L. M. Gómez-Sainero, Enhanced selectivity to olefins in the hydrodechlorination of trichloromethane using Ag—Pd on activated carbon catalysts, J. Environ. Chem. Eng. 9, 104744 (2021).
  11. G. Meißner, M. Feist, T. Braun, and E. Kemnitz, Selective reduction of a C—Cl bond in halomethanes with Et3GeH at nanoscopic Lewis acidic aluminium fluoride, J. Organomet. Chem. 847, 234 (2017).
  12. W. Ma, T. Liu, C. Xu, C. Lei, P. Jiang, X. He, and X. Liang, A twelve-electron conversion iodine cathode enabled by interhalogen chemistry in aqueous solution, Nat. Commun. 14, 5508 (2023).
  13. L. She, H. Cheng, Z. Yuan, Z. Shen, Q. Wu, W. Zhong, S. Zhang, B. Zhang, C. Liu, M. Zhang, et al., Rechargeable aqueous zinc–halogen batteries: Fundamental mechanisms, research issues, and future perspectives, Adv. Sci. 11, 2305061 (2024).
  14. B. He, F. Zhang, Y. Xin, C. Xu, X. Hu, X. Wu, Y. Yang, and H. Tian, Halogen chemistry of solid electrolytes in all-solid-state batteries, Nat. Rev. Chem. 7, 826 (2023).
  15. M. K. Wilsey, T. Taseska, Z. Meng, W. Yu, and A. M. Müller, Advanced electrocatalytic redox processes for environmental remediation of halogenated organic water pollutants, Chem. Commun. 59, 11895 (2023).
  16. K.-H. Kim, Z.-H. Shon, H. T. Nguyen, and E.-C. Jeon, A review of major chlorofluorocarbons and their halocarbon alternatives in the air, Atmos. Environ. 45, 1369 (2011).
  17. R. F. Howe, Handbook of Heterogeneous Catalysis (Wiley-VCH (Wiley-VCH Verlag GmbH & Co. KGaA), Weinheim, Germany, 2008), p. 2385.
  18. J. Liu, R. Burciaga, S. Tang, S. Ding, H. Ran, W. Zhao, G. Wang, Z. Zhuang, L. Xie, Z. Lyu, et al., Heterogeneous catalysis for the environment, Innov. Mater. 2, 100090 (2024).
  19. A. Cavallini, The state-of-the-art on refrigerants, J. Phys.: Conf. Ser. 1599, 012001 (2020).
  20. P. Li, S. Hou, Q. Wu, Y. Chen, B. Wang, H. Ren, J. Wang, Z. Zhai, Z. Yu, C. J. Lambert, et al., The role of halogens in Au–S bond cleavage for energy-differentiated catalysis at the single-bond limit, Nat. Commun. 14, 7695 (2023).
  21. W. J. Teh, E. Romeo, S. Xi, B. Rowley, F. Illas, F. Calle-Vallejo, and B. S. Yeo, Selective electroreduction of acetylene to 1,3-butadiene on iodide-induced Cuδ+–Cu0 sites, Nat. Catal. 7, 1382 (2024).
  22. A. S. Varela, W. Ju, T. Reier, and P. Strasser, Tuning the catalytic activity and selectivity of Cu for CO2 electroreduction in the presence of halides, ACS Catal. 6, 2136 (2016).
  23. W. R. Leow, Y. Lum, A. Ozden, Y. Wang, D.-H. Nam, B. Chen, J. Wicks, T.-T. Zhuang, F. Li, D. Sinton, et al., Chloride-mediated selective electrosynthesis of ethylene and propylene oxides at high current density, Science 368, 1228 (2020).
  24. H. Zhu, Z. Liang, S. Xue, X. Ren, X. Liang, W. Xiong, L. Gao, and A. Liu, DFT practice in MXene-based materials for electrocatalysis and energy storage: From basics to applications, Ceram. Int. 48, 27217 (2022).
  25. R. Haunschild, A. Barth, and B. French, A comprehensive analysis of the history of DFT based on the bibliometric method RPYS, J. Cheminf. 11, 72 (2019).
  26. R. Urrego-Ortiz, S. Builes, F. Illas, and F. Calle-Vallejo, Gas-phase errors in computational electrocatalysis: a review, EES Catal. 2, 157 (2024).
  27. Y. Yang, J. Wang, Y. Shu, Y. Ji, H. Dong, and Y. Li, Significance of density functional theory (DFT) calculations for electrocatalysis of N2 and CO2 reduction reactions, Phys. Chem. Chem. Phys. 24, 8591 (2022).
  28. J. I. Martínez, H. A. Hansen, J. Rossmeisl, and J. K. Nørskov, Formation energies of rutile metal dioxides using density functional theory, Phys. Rev. B 79, 045120 (2009).
  29. F. Calle-Vallejo, J. I. Martínez, J. M. García-Lastra, M. Mogensen, and J. Rossmeisl, Trends in stability of perovskite oxides, Angew. Chem., Int. Ed. Engl. 49, 7699 (2010).
  30. F. Calle-Vallejo, O. A. Díaz-Morales, M. J. Kolb, and M. T. M. Koper, Why is bulk thermochemistry a good descriptor for the electrocatalytic activity of transition metal oxides?, ACS Catal. 5, 869 (2015).
  31. J. Wellendorff, T. L. Silbaugh, D. Garcia-Pintos, J. K. Nørskov, T. Bligaard, F. Studt, and C. T. Campbell, A benchmark database for adsorption bond energies to transition metal surfaces and comparison to selected DFT functionals, Surf. Sci. 640, 36 (2015).
  32. J. F. Zapata, R. Urrego-Ortiz, S. Builes, and F. Calle-Vallejo, Halogen thermochemistry assessed with density functional theory: Systematic errors, swift corrections and effects on electrochemistry, ChemSusChem 18, e202402189 (2025).
  33. C. F. Cloud and M. Schwartz, Systematic errors in DFT calculations of haloalkane heats of formation, J. Comput. Chem. 24, 640 (2003).
  34. K. R. Jorgensen and M. Cadena, Theoretical study of bromine halocarbons: Accurate enthalpies of formation, Comput. Theor. Chem. 1141, 66 (2018).
  35. R. Urrego-Ortiz, S. Builes, and F. Calle-Vallejo, Impact of intrinsic density functional theory errors on the predictive power of nitrogen cycle electrocatalysis models, ACS Catal. 12, 4784 (2022).
  36. E. Sargeant, F. Illas, P. Rodríguez, and F. Calle-Vallejo, On the shifting peak of volcano plots for oxygen reduction and evolution, Electrochim. Acta 426, 140799 (2022).
  37. R. Urrego-Ortiz, M. O. Almeida, and F. Calle-Vallejo, Error awareness in the volcano plots of oxygen electroreduction to hydrogen peroxide, ChemSusChem 17, e202400873 (2024).
  38. R. Urrego-Ortiz, S. Builes, and F. Calle-Vallejo, Fast correction of errors in the DFT-calculated energies of gaseous nitrogen-containing species, ChemCatChem 13, 2508 (2021).
  39. J. Zhang, T. H. M. Pham, S. Xi, L. Zhong, D. Liem, F. You, B. Rowley, R. Ganganahalli, F. Calle-Vallejo, and B. S. Yeo, Low CO2 mass transfer promotes methanol and formaldehyde electrosynthesis on cobalt phthalocyanine, J. Mater. Chem. A 12, 31547 (2024).
  40. E. Romeo, F. You, H. Ma, F. Illas, B. S. Yeo, and F. Calle-Vallejo, Improving the description of adsorbed hydroxyl to make predictive catalytic activity models, ACS Catal. 15, 18004 (2025).
  41. R. Christensen, H. A. Hansen, C. F. Dickens, J. K. Nørskov, and T. Vegge, Functional independent scaling relation for ORR/OER catalysts, J. Phys. Chem. C 120, 24910 (2016).
  42. D. Bond, Computational methods in organic chemistry. 3. Correction of computed enthalpies for multiple conformations, J. Phys. Chem. A 112, 1656 (2008).
  43. L. P. Granda-Marulanda, A. Rendón-Calle, S. Builes, F. Illas, M. T. M. Koper, and F. Calle-Vallejo, A semiempirical method to detect and correct DFT-based gas-phase errors and its application in electrocatalysis, ACS Catal. 10, 6900 (2020).
  44. A. A. Peterson, F. Abild-Pedersen, F. Studt, J. Rossmeisl, and J. K. Nørskov, How copper catalyzes the electroreduction of carbon dioxide into hydrocarbon fuels, Energy Environ. Sci. 3, 1311 (2010).
  45. R. Christensen, H. A. Hansen, and T. Vegge, Identifying systematic DFT errors in catalytic reactions, Catal. Sci. Technol. 5, 4946 (2015).
  46. R. Urrego-Ortiz, S. Builes, and F. Calle-Vallejo, Automated versus chemically intuitive deconvolution of density functional theory (DFT)-based gas-phase errors in nitrogen compounds, Ind. Eng. Chem. Res. 61, 13375 (2022).
  47. I. Aguado-Ruiz, R. Urrego-Ortiz, and F. Calle-Vallejo, A computational view on the thermochemical and electrochemical stability of ruthenium oxides, J. Mater. Chem. A 13, 12482 (2025).
  48. See Supplemental Material at http://link.aps.org/supplemental/10.1103/xg4n-6mfg for the list of validation reactions and statistics, error decomposition and enthalpy comparisons, the results of bootstrapping and Akaike information criterion, and structure-property and error correlations (dipole moment, substituent, electronegativity, PBE error, and van der Waals radius) for CX and X2 systems.
  49. E. J. Bylaska, K. R. Glaesemann, A. R. Felmy, M. Vasiliu, D. A. Dixon, and P. G. Tratnyek, Free energies for degradation reactions of 1,2,3-trichloropropane from ab initio electronic structure theory, J. Phys. Chem. A 114, 12269 (2010).
  50. A. S. Carson, P. G. Laye, J. B. Pedley, A. M. Welsby, J. S. Chickos, and S. Hosseini, The enthalpies of formation of iodoethane, 1,2-diiodoethane, 1,3-diiodopropane, and 1,4-diiodobutane, J. Chem. Thermodyn. 26, 1103 (1994).
  51. J. L. Holmes and C. Aubry, Group additivity values for estimating the enthalpy of formation of organic compounds: An update and reappraisal. 2. C, H, N, O, S, and halogens, J. Phys. Chem. A 116, 7196 (2012).
  52. E. Paulechka and A. Kazakov, Critical evaluation of the enthalpies of formation for fluorinated compounds using experimental data and high-level ab initio calculations, J. Chem. Eng. Data 64, 4863 (2019).
  53. E. Paulechka and A. Kazakov, Formation enthalpies of C3 and C4 brominated hydrocarbons: Bringing together classical thermodynamics, modern mass spectrometry, and high-level ab initio calculations, J. Phys. Chem. A 128, 1339 (2024).
  54. G. Stridh and S. Sunner, Enthalpies of formation of some 1-chloroalkanes and the CH2-increment in the 1-chloroalkane series, J. Chem. Thermodyn. 7, 161 (1975).
  55. H. Y. Afeefy, J. F. Liebman, and S. E. Stein, in NIST Chemistry WebBook, NIST Standard Reference Database Number 69, edited by P. J. Linstrom, and W. G. Mallard (National Institute of Standards and Technology, Gaithersburg MD, 2025).
  56. B. Ruscic, Uncertainty quantification in thermochemistry, benchmarking electronic structure computations, and active thermochemical tables, Int. J. Quantum Chem. 114, 1097 (2014).
  57. B. Ruscic and D. Bross, Active Thermochemical Tables (ATcT) values based on ver. 1.220 of the Thermochemical Network (2025).
  58. G. Kresse and J. Furthmüller, Efficient iterative schemes for ab initio total-energy calculations using a plane-wave basis set, Phys. Rev. B 54, 11169 (1996).
  59. J. P. Perdew, K. Burke, and M. Ernzerhof, Generalized gradient approximation made simple, Phys. Rev. Lett. 77, 3865 (1996).
  60. J. P. Perdew and Y. Wang, Accurate and simple analytic representation of the electron-gas correlation energy, Phys. Rev. B 45, 13244 (1992).
  61. B. Hammer, L. B. Hansen, and J. K. Nørskov, Improved adsorption energetics within density-functional theory using revised Perdew–Burke–Ernzerhof functionals, Phys. Rev. B 59, 7413 (1999).
  62. J. Wellendorff, K. T. Lundgaard, A. Møgelhøj, V. Petzold, D. D. Landis, J. K. Nørskov, T. Bligaard, and K. W. Jacobsen, Density functionals for surface science: Exchange-correlation model development with Bayesian error estimation, Phys. Rev. B 85, 235149 (2012).
  63. J. Tao, J. P. Perdew, V. N. Staroverov, and G. E. Scuseria, Climbing the density functional ladder: Nonempirical meta–generalized gradient approximation designed for molecules and solids, Phys. Rev. Lett. 91, 146401 (2003).
  64. A. D. Becke, Density-functional thermochemistry. III. The role of exact exchange, J. Chem. Phys. 98, 5648 (1993).
  65. J. Heyd, G. E. Scuseria, and M. Ernzerhof, Hybrid functionals based on a screened Coulomb potential, J. Chem. Phys. 118, 8207 (2003).
  66. G. Kresse and D. Joubert, From ultrasoft pseudopotentials to the projector augmented-wave method, Phys. Rev. B 59, 1758 (1999).
  67. W. Wang, S. Dai, X. Li, J. Yang, D. J. Srolovitz, and Q. Zheng, Measurement of the cleavage energy of graphite, Nat. Commun. 6, 7853 (2015).
  68. L. A. Girifalco and R. A. Lad, Energy of cohesion, compressibility, and the potential energy functions of the graphite system, J. Chem. Phys. 25, 693 (1956).
  69. R. Zacharia, H. Ulbricht, and T. Hertel, Interlayer cohesive energy of graphite from thermal desorption of polyaromatic hydrocarbons, Phys. Rev. B 69, 155406 (2004).
  70. L. X. Benedict, N. G. Chopra, M. L. Cohen, A. Zettl, S. G. Louie, and V. H. Crespi, Microscopic determination of the interlayer binding energy in graphite, Chem. Phys. Lett. 286, 490 (1998).
  71. M. Xia, C. Liang, Z. Cheng, R. Hu, and S. Liu, The adhesion energy measured by a stress accumulation-peeling mechanism in the exfoliation of graphite, Phys. Chem. Chem. Phys. 21, 1217 (2019).
  72. Z. Liu, J. Z. Liu, Y. Cheng, Z. Li, L. Wang, and Q. Zheng, Interlayer binding energy of graphite: A mesoscopic determination from deformation, Phys. Rev. B 85, 205418 (2012).
  73. S. I. Sandler, Chemical, Biochemical, and Engineering Thermodynamics (John Wiley & Sons, Hoboken, NJ, 2017).
  74. R. Urrego-Ortiz, S. Builes, F. Illas, S. T. Bromley, M. C. Figueiredo, and F. Calle-Vallejo, Minimum conditions for accurate modeling of urea production via co-electrolysis, Commun. Chem. 6, 196 (2023).
  75. S. Kurth, J. P. Perdew, and P. Blaha, Molecular and solid-state tests of density functional approximations: LSD, GGAs, and meta-GGAs, Int. J. Quantum Chem. 75, 889 (1999).
  76. J. Harl, L. Schimka, and G. Kresse, Assessing the quality of the random phase approximation for lattice constants and atomization energies of solids, Phys. Rev. B 81, 115126 (2010).
  77. J. Yan, J. S. Hummelshøj, and J. K. Nørskov, Formation energies of group I and II metal oxides using random phase approximation, Phys. Rev. B 87, 075207 (2013).
  78. L. Schimka, J. Harl, A. Stroppa, A. Grüneis, M. Marsman, F. Mittendorfer, and G. Kresse, Accurate surface and adsorption energies from many-body perturbation theory, Nat. Mater. 9, 741 (2010).
  79. Z. Wei and P. Sautet, Improving the accuracy of modelling CO2 electroreduction on copper using many-body perturbation theory, Angew. Chem., Int. Ed. Engl. 61, e202210060 (2022).
  80. J. A. Pople, L. Radom, and W. J. Hehre, Molecular orbital theory of the electronic structure of organic compounds. VII. Systematic study of energies, conformations, and bond interactions, J. Am. Chem. Soc. 93, 289 (1971).
  81. B. Kreitz, G. S. Gusmão, D. Nai, S. J. Sahoo, A. A. Peterson, D. H. Bross, C. F. Goldsmith, and A. J. Medford, Unifying thermochemistry concepts in computational heterogeneous catalysis, Chem. Soc. Rev. 54, 560 (2025).
  82. S. E. Wheeler, Homodesmotic reactions for thermochemistry, WIREs Comput. Mol. Sci. 2, 204 (2012).
  83. R. O. Ramabhadran and K. Raghavachari, The successful merger of theoretical thermochemistry with fragment-based methods in quantum chemistry, Acc. Chem. Res. 47, 3596 (2014).
  84. S. E. Wheeler, K. N. Houk, P. v, R. Schleyer, and W. D. Allen, A hierarchy of homodesmotic reactions for thermochemistry, J. Am. Chem. Soc. 131, 2547 (2009).
  85. R. Urrego-Ortiz, C. S. Zhong, W. J. Teh, S. Builes, B. S. Yeo, and F. Calle-Vallejo, Correcting errors in the adsorbed intermediates of CO2 electroreduction, Carbon Energy 8, e70128 (2026).
  86. I. Dattner, A model-based initial guess for estimating parameters in systems of ordinary differential equations, Biometrics 71, 1176 (2015).

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PRX Energy 5, 023001– Published 9 April, 2026
  • Received 27 November 2025
  • Revised 5 February 2026
  • Accepted 2 March 2026
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