The DOI matches its Crossref record; 6 of the 6 references it cites were found in a registry or an index.
Nuclear quantum effects enter the mainstream
Open accessAbstract
Atomistic simulations of chemical, biological and materials systems have become increasingly precise and predictive owing to the development of accurate and efficient techniques that describe the quantum mechanical behaviour of electrons. Nevertheless, the overwhelming majority of such simulations still assumes that the nuclei behave as classical particles. Historically, this approximation could sometimes be justified owing to the complexity and computational overhead. However, neglecting nuclear quantum effects has become one of the largest sources of error, especially when systems containing light atoms are treated using current state-of-the-art descriptions of chemical interactions. Over the past decade, this realization has spurred a series of methodological advances that have dramatically reduced the cost of including these important physical effects in the structure and dynamics of chemical systems. Here, we discuss how these developments are now allowing nuclear quantum effects to become a mainstream feature of molecular simulations. These advances have led to new insights into phenomena that are relevant to different areas of science — from biochemistry to condensed matter — and open the door to many exciting future opportunities. The approximation underlying most atomistic simulations to treat nuclei classically can lead to large errors and the failure to capture important physical effects. This Review reports on recent developments that enable modelling of quantum nuclei at a computational cost comparable with that of a classical simulation.
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Cites
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Cited by
Unke, O. T., Chmiela, S., Sauceda, H. E., Gastegger, M., Poltavsky, I., Schütt, K. T., Tkatchenko, A., & Müller, K.-R. (2021) · Chemical Reviews · doi:10.1021/acs.chemrev.0c01111 · Cited by 1,647
Quantum Chemistry in the Age of Quantum Computing
Cao, Y., Romero, J., Olson, J. P., Degroote, M., Johnson, P. D., Kieferová, M., Kivlichan, I. D., Menke, T., Peropadre, B., Sawaya, N. P. D., et al. (2019) · Chemical Reviews · doi:10.1021/acs.chemrev.8b00803 · Cited by 1,560
Physics-Inspired Structural Representations for Molecules and Materials
Musil, F., Grisafi, A., Bartók, A. P., Ortner, C., Csányi, G., & Ceriotti, M. (2021) · Chemical Reviews · doi:10.1021/acs.chemrev.1c00021 · Cited by 523
Self-citationZheng, Q., Chu, W., Zhao, C., Zhang, L., Guo, H., Wang, Y., Jiang, X., & Zhao, J. (2019) · WIREs Computational Molecular Science · doi:10.1002/wcms.1411 · Cited by 452
i-PI 2.0: A universal force engine for advanced molecular simulations
Kapil, V., Rossi, M., Marsalek, O., Petraglia, R., Litman, Y., Spura, T., Cheng, B., Cuzzocrea, A., Meißner, R. H., Wilkins, D. M., et al. (2019) · Computer Physics Communications · doi:10.1016/j.cpc.2018.09.020 · Cited by 357
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Metadata
- Authors
- Markland, T. E., & Ceriotti, M.
- Venue
- Nature Reviews Chemistry
- Published
- 2018-02-28
- Volume
- 2
- Issue
- 3
- ISSN
- 2397-3358 (ISSN-L)
- OpenAlex
- W2789857314
- Cited by
- 491
- References
- 6
- FWCI
- 2.54
- Type
- journal article
- Language
- en
- Open access
- green
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