Overview of the VASP Software and Its Applications in Materials Research
Abstract:
The rapid advancement of computational materials science has significantly accelerated the discovery and design of advanced materials at the atomicscale. Among the various first-principles simulation packages, the Vienna Ab initio Simulation Package (VASP) has become one of the most powerful and widely used computational tools in modern materials research. This review presents a comprehensive overview of the theoretical foundations, main functionalities, and applications of VASP in computational materials science. The fundamental principles underlying VASP, including Density Functional Theory (DFT), plane-wave basis sets, and the Projector Augmented Wave (PAW) method, are discussed in detail. In addition, the major computational capabilities of VASP, such as geometry optimization, electronic structure calculations, magnetic property analysis, optical property simulations, and ab initio molecular dynamics (AIMD), are systematically summarized. Particular attention is devoted to the applications of VASP in the investigation of two-dimensional materials, semiconductors, catalytic systems,gas adsorption, and energy-related materials, including lithium-ion batteries, photocatalysts, and perovskite solarcells. The advantages and current limitations of VASP are also analyzed, together with recent development trends involving machine learning, high-throughput calculations, workflow automation, and AI-assisted materials discovery. Owing to its high computational accuracy, scalability on high-performance computing platforms, and extensive methodological support, VASP continues to play a crucial role in advancing modern computational materials research and the development of next-generation functional materials.
KeyWords:
VASP; Density Functional Theory; First-principles calculations; Electronic properties; Two-dimensional materials; Computational materials science
References:
- Kresse, G., & Furthmüller, J. (1996). Efficientiterative schemes for ab initio total-energy calculations using a plane-wave basis set. Physical Review B, 54(16), 11169–11186. https://doi.org/10.1103/PhysRevB.54.11169
- Kresse, G., & Furthmüller, J. (1996). Efficiency of ab initio total energy calculations for metals and semiconductors using a plane-wave basis set. Computational Materials Science, 6(1), 15–50. https://doi.org/10.1016/0927-0256(96)00008-0
- Blöchl, P. E. (1994).Projector augmented-wave method.Physical Review B, 50(24), 17953–17979. https://doi.org/10.1103/PhysRevB.50.17953
- Kresse, G., & Joubert,D. (1999). From ultrasoft pseudopotentials to the projector augmented-wave method. Physical Review B, 59(3), 1758–1775. https://doi.org/10.1103/PhysRevB.59.1758
- Hohenberg, P., & Kohn, W. (1964).Inhomogeneous electron gas. PhysicalReview, 136(3B), B864–B871. https://doi.org/10.1103/PhysRev.136.B864
- Kohn, W., & Sham, L. J. (1965). Self-consistent equations including exchangeand correlation effects. Physical Review, 140(4A), A1133–A1138. https://doi.org/10.1103/PhysRev.140.A1133
- Kresse, G., & Furthmüller, J. (1996). Efficiency of ab initio total energy calculations for metals and semiconductors using a plane-wave basis set. Computational Materials Science, 6(1), 15–50. https://doi.org/10.1016/0927-0256(96)00008-0
- Kresse, G., & Furthmüller, J. (1996). Efficientiterative schemes for ab initio total-energy calculations using a plane-wave basis set. Physical Review B, 54(16), 11169–11186. https://doi.org/10.1103/PhysRevB.54.11169
- Kresse, G., & Hafner,J. (1993). Ab initiomolecular dynamics for liquid metals.Physical Review B, 47(1), 558–561. https://doi.org/10.1103/PhysRevB.47.558
- Hohenberg, P., & Kohn, W. (1964).Inhomogeneous electron gas. PhysicalReview, 136(3B), B864–B871. https://doi.org/10.1103/PhysRev.136.B864
- Kohn, W., & Sham, L. J. (1965). Self-consistent equations including exchangeand correlation effects. Physical Review, 140(4A), A1133–A1138. https://doi.org/10.1103/PhysRev.140.A1133
- Jones, R. O. (2015).Density functional theory:Its origins, rise to prominence, and future. Reviews of Modern Physics, 87(3), 897–923. https://doi.org/10.1103/RevModPhys.87.897
- Hohenberg, P., & Kohn, W. (1964).Inhomogeneous electron gas. PhysicalReview, 136(3B), B864–B871. https://doi.org/10.1103/PhysRev.136.B864
- Kohn, W., & Sham, L. J. (1965). Self-consistent equations including exchangeand correlation effects. Physical Review, 140(4A), A1133–A1138. https://doi.org/10.1103/PhysRev.140.A1133
- Blöchl, P. E. (1994).Projector augmented-wave method.Physical Review B, 50(24), 17953–17979. https://doi.org/10.1103/PhysRevB.50.17953
- Kresse, G., & Joubert,D. (1999). From ultrasoft pseudopotentials to the projector augmented-wave method. Physical Review B, 59(3), 1758–1775. https://doi.org/10.1103/PhysRevB.59.1758
- Novoselov, K. S., Geim,A. K., Morozov, S. V., et al. (2004). Electricfield effect in atomically thin carbon films. Science, 306(5696), 666–669. https://doi.org/10.1126/science.1102896
- Vogt, P., De Padova,P., Quaresima, C., et al. (2012). Silicene:Compelling experimental evidence for graphenelike two-dimensional silicon. Physical Review Letters, 108(15), 155501. https://doi.org/10.1103/PhysRevLett.108.155501
- Zhu,F.-f., Chen, W.-j., Xu, Y., et al. (2015). Epitaxialgrowth of two-dimensional stanene. Nature Materials, 14(10), 1020–1025. https://doi.org/10.1038/nmat4384
- Naguib, M., Kurtoglu, M., Presser, V., et al. (2011). Two-dimensional nanocrystals produced by exfoliation of Ti3AlC2. Advanced Materials, 23(37), 4248–4253. https://doi.org/10.1002/adma.201102306
- Henkelman, G., Arnaldsson, A., & Jónsson, H. (2006). A fast and robust algorithm for Bader decomposition of charge density.Computational Materials Science, 36(3), 354–360. https://doi.org/10.1016/j.commatsci.2005.04.010
- Silvi, B., & Savin,A. (1994). Classification of chemical bondsbased on topological analysis of electron localization functions. Nature, 371(6499), 683–686. https://doi.org/10.1038/371683a0
- Zhu,F.-f., Chen, W.-j., Xu, Y., et al. (2015). Epitaxialgrowth of two-dimensional stanene. Nature Materials, 14(10), 1020–1025. https://doi.org/10.1038/nmat4384
- Son,Y.-W., Cohen, M. L.,& Louie, S. G.(2006). Half-metallic graphenenanoribbons. Nature, 444(7117), 347–349. https://doi.org/10.1038/nature05180
- Žutić, I., Fabian, J., & Das Sarma, S. (2004). Spintronics: Fundamentals and applications. Reviews of Modern Physics, 76(2), 323–410. https://doi.org/10.1103/RevModPhys.76.323
- Ding, Y., & Wang,Y. (2012). Electronic structures of silicenematerials: The effectsof dimensionality and external fields. Applied Physics Letters, 100(8), 083102. https://doi.org/10.1063/1.3688047
- Gajdoš, M., Hummer, K., Kresse, G., Furthmüller, J., & Bechstedt, F. (2006). Linear optical properties in the projector-augmented wave methodology. Physical ReviewB, 73(4), 045112. https://doi.org/10.1103/PhysRevB.73.045112
- Fox,M. (2010). Optical properties of solids (2nded.). Oxford University Press. https://doi.org/10.1093/acprof:oso/9780199573370.001.0001
- Marx, D., & Hutter,J. (2000). Ab initiomolecular dynamics: Theoryand implementation. In Modern methods and algorithms of quantum chemistry. https://doi.org/10.1002/9780470141731.ch2
- Car,R., & Parrinello, M. (1985). Unifiedapproach for molecular dynamics and density- functional theory. Physical Review Letters, 55(22), 2471–2474. https://doi.org/10.1103/PhysRevLett.55.2471
- Novoselov, K. S., Geim,A. K., Morozov, S. V., et al. (2004). Electricfield effect in atomically thin carbon films. Science, 306(5696), 666–669. https://doi.org/10.1126/science.1102896
- Li,L., Yu, Y., Ye, G. J., et al. (2014).Black phosphorus field-effect transistors. Nature Nanotechnology, 9(5), 372–377. https://doi.org/10.1038/nnano.2014.35
- Naguib, M., Kurtoglu, M., Presser, V., et al. (2011). Two-dimensional nanocrystals produced by exfoliation of Ti3AlC2. Advanced Materials, 23(37), 4248–4253. https://doi.org/10.1002/adma.201102306
- Liu,C.-C., Feng, W., & Yao, Y. (2011).Quantum spin Hall effect in silicene and two- dimensional germanium. Physical Review Letters, 107(7), 076802. https://doi.org/10.1103/PhysRevLett.107.076802
- Heyd, J., Scuseria, G. E., & Ernzerhof, M. (2003). Hybrid functionals based on a screened Coulombpotential. The Journal of Chemical Physics,118(18), 8207–8215. https://doi.org/10.1063/1.1564060
- Heyd, J., Scuseria, G. E., & Ernzerhof, M. (2006). Erratum:“Hybrid functionals based on a screened Coulomb potential”. The Journal of Chemical Physics, 124(21), 219906. https://doi.org/10.1063/1.2204597
- Paier, J., Marsman, M., Hummer, K., Kresse, G., Gerber, I. C., & Ángyán, J. G. (2006). Screened hybrid densityfunctionals applied to solids. The Journalof Chemical Physics, 124(15), 154709. https://doi.org/10.1063/1.2187006
- Perdew, J. P., Burke, K., & Ernzerhof, M. (1996). Generalized gradient approximation made simple. Physical Review Letters, 77(18), 3865–3868. https://doi.org/10.1103/PhysRevLett.77.3865
- Nørskov, J. K., Bligaard,T., Logadottir, A., et al. (2005). Trendsin the exchange current for hydrogen evolution. Journal of the Electrochemical Society, 152(3), J23–J26. https://doi.org/10.1149/1.1856988
- Man,I. C., Su, H.-Y., Calle-Vallejo, F., et al. (2011). Universality in oxygen evolution electrocatalysis on oxide surfaces. ChemCatChem, 3(7), 1159–1165. https://doi.org/10.1002/cctc.201000397
- Henkelman, G., Arnaldsson, A., & Jónsson, H. (2006). A fast and robust algorithm for Bader decomposition of charge density.Computational Materials Science, 36(3), 354–360. https://doi.org/10.1016/j.commatsci.2005.04.010
- Tang, Q., & Zhou,Z. (2013). Graphene-analogous low-dimensional materials. Progress in Materials Science, 58(8), 1244–1315. https://doi.org/10.1016/j.pmatsci.2013.04.003
- Goodenough, J. B., & Park, K.-S. (2013). The Li-ion rechargeable battery: A perspective. Journal of the American Chemical Society, 135(4), 1167–1176. https://doi.org/10.1021/ja3091438
- Slater, M. D., Kim, D., Lee, E., &Johnson, C. S. (2013). Sodium-ion batteries. Advanced Functional Materials, 23(8), 947–958. https://doi.org/10.1002/adfm.201200691
- Simon, P., & Gogotsi,Y. (2008). Materialsfor electrochemical capacitors. Nature Materials, 7(11), 845–854. https://doi.org/10.1038/nmat2297
- Fujishima, A., & Honda, K. (1972). Electrochemical photolysis of water at a semiconductor electrode. Nature, 238(5358), 37–38. https://doi.org/10.1038/238037a0
- Kojima, A., Teshima, K., Shirai, Y., & Miyasaka, T. (2009). Organometal halide perovskites as visible-light sensitizers for photovoltaic cells.Journal of the American Chemical Society, 131(17), 6050–6051. https://doi.org/10.1021/ja809598r
- Blöchl, P. E. (1994).Projector augmented-wave method.Physical Review B, 50(24), 17953–17979. https://doi.org/10.1103/PhysRevB.50.17953
- Hafner, J. (2008). Materialssimulations using VASP—Aquantum perspective to materials science. Computational Materials Science, 43(1), 4–15. https://doi.org/10.1016/j.commatsci.2007.11.007
- Anisimov, V. I., Zaanen,J., & Andersen, O. K. (1991).Band theory and Mott insulators: Hubbard U instead of Stoner I. Physical Review B, 44(3), 943–954. https://doi.org/10.1103/PhysRevB.44.943
- Aryasetiawan, F., Imada, M., Georges,A., Kotliar, G., Biermann, S., & Lichtenstein, A.I. (2004). Frequency-dependent localinteractions and low-energy effective models from electronic structure calculations. Physical Review B, 70(19), 195104. https://doi.org/10.1103/PhysRevB.70.195104
- Jain, A., Ong, S. P., Hautier, G., et al. (2013). Commentary: The Materials Project: A materials genomeapproach to accelerating materials innovation. APL Materials, 1(1), 011002. https://doi.org/10.1063/1.4812323
- Ong, S. P., Richards, W. D., Jain, A., et al. (2013). Python Materials Genomics (pymatgen): A robust, open-source python library for materials analysis. Computational Materials Science, 68, 314–319. https://doi.org/10.1016/j.commatsci.2012.10.028
- Larsen, A. H., Mortensen, J. J., Blomqvist, J., et al. (2017). The Atomic Simulation Environment—A Pythonlibrary for workingwith atoms. Journal of Physics: Condensed Matter, 29(27), 273002. https://doi.org/10.1088/1361-648X/aa680e
- Wang, V., Xu, N., Liu,J.-C., Tang, G., & Geng, W.-T. (2021).VASPKIT: A user-friendly interface facilitating high-throughput computing and analysisusing VASP code. Computer Physics Communications, 267, 108033. https://doi.org/10.1016/j.cpc.2021.108033
- Mathew, K., Montoya, J. H., Faghaninia, A., et al. (2017). Atomate: A high-level interface to generate, execute,and analyze computational materials science workflows. Computational Materials Science, 139, 140–152. https://doi.org/10.1016/j.commatsci.2017.07.030