For citation:
Glukhova O. E., Kolesnichenko P. A. Improving the efficiency of the SCC DFTB method in describing interatomic interactions and predicting electronic properties. Izvestiya of Saratov University. Physics , 2026, vol. 26, iss. 1, pp. 53-61. DOI: 10.18500/1817-3020-2026-26-1-53-61, EDN: KMNROY
Improving the efficiency of the SCC DFTB method in describing interatomic interactions and predicting electronic properties
Background and Objectives: Thin films of copper oxide are one of the most effective materials for gas sensors. Expanding the sensor capabilities of this material requires predictive modeling. In this work, to provide a physically correct description of the interaction of the Cu2O film surface with analytes and its chemoresistive response, a modification of the parameterization for pairs of Cu, O, C, H atoms were carried out within the SCC DFTB method (O–, C–, H– atoms are part of the detected alcohol and water molecules). The created parameters set of functions demonstrates: more accurate reproduction of the metric parameters of the crystal lattice (lengths of interatomic bonds and lengths of translation vectors) – based on a comparison with metric and electrical conductivity data from experimental studies. Materials and Methods: The Tango software package was used to create the repulsive part of the parameter set, and the atomistic modeling was carried out using the DFTB SCC method in the DFTB+ software model. Results: A comparison has been made for eleven different supercells of Cu–C, Cu–O, Cu–H and Cu– Cu atom pairs. As a result, it has been shown that in all the studied cases, the improved parameterization gives a multiple smaller error relative to the DFT method, which was taken as a standard. For the Cu2O supercell with a cubic crystal lattice, the DOS calculation has been performed, which has shown a band gap width of ∼2 eV, which is close to the experimental value. The resistance has also been calculated, which differs from the experimentally determined value by no more than 10%. Conclusion: Thus, the parameters obtained in this work can be used to study electronic and electrophysical properties.
- Steinhauer S. Gas sensors based on copper oxide nanomaterials: A review. Chemosensors, 2021, vol. 9, iss. 3, art. 51. https://doi.org/10.3390/chemosensors9030051
- Nunes D., Pimentel A., Gonçalves A., Pereira S., Branquinho R., Barquinha P., Fortunato E., Martins R. Metal oxide nanostructures for sensor applications. Semicond. Sci. Technol., 2019, vol. 34, iss. 4, art. 43001. https://doi.org/10.1088/1361–6641/ab011e
- Zhang Z., Zhang S., Liu S., Wang M., Fu G., He L., Yang Y., Fang S. Electrochemical aptasensor based on one-step synthesis of Cu2O@aptamer nanospheres for sensitive thrombin detection. Sens. Actuators B Chem., 2015, vol. 220, pp. 184–191. https://doi.org/10.1016/j.snb.2015.05.089
- Moseley P. T. Progress in the development of semiconducting metal oxide gas sensors: A review. Meas. Sci. Technol., 2017, vol. 28, art. 082001. https://doi.org/10.1088/1361-6501/aa7443
- Kim H. J., Lee J. H. Highly sensitive and selective gas sensors using p-type oxide semiconductors: Overview. Sens. Actuators B Chem., 2014, vol. 192, pp. 607–627. https://doi.org/10.1016/j.snb.2013.11.005
- Zoolfakar A. S., Rani R. A., Morfa A. J., O’Mullane A. P., Kalantar-zadeh K. Nanostructured copper oxide semiconductors: A perspective on materials, synthesis methods and applications. J. Mater. Chem. C, 2014, vol. 2, pp. 5247–5270. https://doi.org/10.1039/C4tc00345d
- Zhang Q., Zhang K., Xu D., Yang G., Huang H., Nie F., Liu C., Yang S. CuO nanostructures: Synthesis, characterization, growth mechanisms, fundamental properties, and applications. Prog. Mater. Sci., 2014, vol. 60, pp. 208–337. https://doi.org/10.1016/j.pmatsci.2013.09.003
- Vequizo J. J. M., Zhang C., Ichimura M. Fabrication of Cu2O/Fe–O heterojunction solar cells by electrodeposition. Thin Solid Films, 2015, vol. 597, pp. 83–87. https://doi.org/10.1016/j.tsf.2015.11.034
- Izaki M., Saito T., Ohata T., Murata K., Fariza B. M., Sasano J., Shinagawa T., Watase S. Hybrid Cu2O diode with orientation-controlled C60 polycrystal. ACS Appl. Mater. Interfaces, 2012, vol. 4, iss. 7, pp. 3558–3565. https://doi.org/10.1021/am3006093
- Hsu C.-L., Tsai J.-Y., Hsueh T.-J. Ethanol gas and humidity sensors of CuO/Cu2O composite nanowires based on a Cu through-silicon via approach. Sens. Actuators B Chem., 2016, vol. 224, pp. 95–102. https://doi.org/10.1016/j.snb.2015.10.018
- Al-Jawhari H. A. A review of recent advances in transparent p-type Cu2O-based thin film transistors. Mater. Sci. Semicond. Process., 2015, vol. 40, pp. 241–252. https://doi.org/10.1016/j.mssp.2015.06.063
- Valvo M., Rehnlund D., Lafont U., Hahlin M., Edström K., Nyholm L. The impact of size effects on the electrochemical behaviour of Cu2O-coated Cu nanopillars for advanced Li-ion microbatteries. J. Mater. Chem. A, 2014, vol. 2, pp. 9574–9586. https://doi.org/10.1039/C4TA01361A
- Kresse G., Joubert D. From ultrasoft pseudopotentials to the projector augmented-wave method. Phys. Rev. B, 1999, vol. 59, pp. 1758–1775. https://doi.org/10.1103/PhysRevB.59.1758
- Giannozzi P., Andreussi O., Brumme T., Bunau O., Buongiorno Nardelli M., Calandra M., Car R., Cavazzoni C., Ceresoli D., Cococcioni M., Colonna N., Carnimeo I., Dal Corso A., de Gironcoli S., Delugas P., DiStasio R. A. Jr., Ferretti A., Floris A., Fratesi G., Fugallo G. et al. Advanced capabilities for materials modelling with Quantum ESPRESSO. J. Phys.: Condens. Matter, 2017, vol. 29, no. 46, art. 465901. https://doi.org/10.1088/1361-648X/aa8f79
- Soler J. M., Artacho E., Gale J. D., García A., Junquera J., Ordejón P., Sánchez-Portal D. The SIESTA method for ab initio order-N materials simulation. J. Phys.: Condens. Matter., 2002, vol. 14, pp. 2745–2779. https://doi.org/10.1088/0953-8984/14/11/302
- Liu H., Seifert G., Di Valentin C. An efficient way to model complex magnetite: Assessment of SCC-DFTB against DFT. J. Chem. Phys., 2019, vol. 150, art. 094703. https://doi.org/10.1063/1.5085190
- Zheng G., Irle S., Morokuma K. Performance of the DFTB method in comparison to DFT and semiempirical methods for geometries and energies of C20–C60 fullerene isomers. Chem. Phys. Lett., 2005, vol. 412, pp. 210–216. https://doi.org/10.1016/j.cplett.2005.06.105
- Manzhos S. Comparative density functional theory and density functional tight binding study of 2-anthroic acid on TiO2. Chem. Phys. Lett., 2016, vol. 643, pp. 16–20. https://doi.org/10.1016/j.cplett.2015.11.007
- Hourahine B., Aradi B., Blum V., Bonafé F., Buccheri A., Camacho C., Cevallos C., Deshaye M. Y., Dumitrică T., Dominguez A., Ehlert S., Elstner M., van der Heide T., Hermann J., Irle S., Kranz J. J., Köhler C., Kowalczyk T., Kubař T., Lee I. S. et al. DFTB+, a software package for efficient approximate density functional theory based atomistic simulations. J. Chem. Phys., 2020, vol. 152, iss. 12, art. 124101. https://doi.org/10.1063/1.5143190
- Cui M., Reuter K., Margraf J. T. Obtaining Robust Density Functional Tight Binding Parameters for Solids Across the Periodic Table (Version 0.1) [Data set]. Zenodo. Available at: https://zenodo.org/records/10677796 (accessed December 26, 2025). https://doi.org/10.5281/zenodo.10677796
- Cui M., Reuter K., Margraf J. T. Obtaining Robust Density Functional Tight Binding Parameters for Solids Across the Periodic Table. J. Chem. Theory Comput., 2024, vol. 20, iss. 12, pp. 5276–5290. https://doi.org/10.1021/acs.jctc.4c00228
- DFTB. Available at: https://dftb.org/parameters/ (accessed August 10, 2025)
- Van den Bossche M., Grönbeck H., Hammer B. Tight-binding approximation-enhanced global optimization. J. Chem. Theory Comput., 2018, vol. 14, iss. 5, pp. 2797–2807. https://doi.org/10.1021/acs.jctc.8b00039
- Koskinen P., Makinen V. Density-functional tight-binding for beginners. Comput. Mater. Sci., 2009, vol. 47, iss. 1, pp. 237–253. https://doi.org/10.1016/j.commatsci.2009.07.013
- Frauenheim T., Seifert G., Elstner M., Hajnal Z., Jungnickel G., Porezag D., Suhai S., Scholz R. A self-consistent charge density-functional based tight-binding method for predictive materials simulations in physics, chemistry and biology. Phys. Status Solidi B, 2000, vol. 217, pp. 41–62. https://doi.org/10.1002/(SICI)1521-3951(200001)217:1{%}3C41::AID-PSSB41{%}3E3.0.CO;2-V
- Slater J. C., Koster G. F. Simplified LCAO method for the periodic potential problem. Phys. Rev., 1954, vol. 94, no. 6, pp. 1498–1524. https://doi.org/10.1103/physrev.94.1498
- Jain A., Ong S. P., Hautier G., Chen W., Richards W. D., Dacek S., Cholia S., Gunter D., Skinner D., Ceder G., Persson K. A. Commentary: The Materials Project: A materials genome approach to accelerating materials innovation. APL Mater., 2013, vol. 1, iss. 1, art. 011002. https://doi.org/10.1063/1.4812323
- Kjeldsen M. K., Enkovaara J., Rostgaard C., Olsen J., Thygesen K. S. Implementation of the projector augmented-wave method in the real-space grid-based electronic structure code GPAW. Phys. Rev. B, 2006, vol. 74, art. 235102. https://doi.org/10.1103/PhysRevB.74.235102
- Larsen A. H., Mortensen J. J., Blomqvist J., Castelli I. E., Christensen R., Dułak M., Friis J., Groves M. N., Hammer B., Hargus C., Hermes E. D., Jennings P. C., Jensen P. B., Kermode J., Kitchin J. R., Kolsbjerg E. L., Kubal J., Kaasbjerg K., Lysgaard S., Maronsson J. B. et al. The Atomic Simulation Environment – A Python library for working with atoms. J. Phys.: Condens. Matter, 2017, vol. 29, iss. 27, art. 273002. https://doi.org/10.1088/1361-648X/aa680e
- Materials Project for CuC6 (mp-1213653) from database version v2025.09.25. Available: https://next-gen.materialsproject.org/materials/mp-1213653 (accessed December 26, 2025).
- Ribbing C. G., Roos A. Copper oxides (Cu2O, CuO). In: Palik E. D., ed. Handbook of Optical Constants of Solids: in 3 vols. New York, Academic Press, 1998, vol. 3, pp. 875–882. https://doi.org/10.1016/B978-0-08-055630-7.50054-7
- Mei L.-P., Feng J.-J., Wu L., Chen J.-R., Shen L., Xie Y., Wang A.-J. A glassy carbon electrode modified with porous Cu2O nanospheres on reduced graphene oxide support for simultaneous sensing of uric acid and dopamine with high selectivity over ascorbic acid. Microchim. Acta, 2016, vol. 183, pp. 2039–2046. https://doi.org/10.1007/s00604-016-1845-0
- Materials Project for Cu2O (mp-361) from database version v2025.09.25. Available: https://next-gen.materialsproject.org/materials/mp-361 (accessed December 26, 2025). https://doi.org/10.17188/1207131
- Materials Project for CuH (mp-24093) from database version v2025.06.09. Available at: https://next-gen.materialsproject.org/materials/mp-24093 (accessed December 26, 2025). https://doi.org/10.17188/1199906
- Padyath R., Seth J., Babu S. V. Deposition of copper oxide films by reactive laser – Ablation of copper formate in an Rf oxygen plasma ambient. Thin Solid Films, 1994, vol. 239, pp. 8–15. https://doi.org/10.1016/0040-6090(94)90101-5
- Li F. M., Waddingham R., Milne W. I., Flewitt A. J., Speakman S., Dutson J., Thwaites M. Low temperature (<100°C) deposited p-type cuprous oxide thin films: Importance of controlled oxygen and deposition energy. Thin Solid Films, 2011, vol. 520, pp. 1278–1284. https://doi.org/10.1016/j.tsf.2011.04.192
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