Cite the Following Article
Correlation effects and many-body interactions in water clusters
Andreas Heßelmann
Beilstein J. Org. Chem. 2018, 14, 979–991.
https://doi.org/10.3762/bjoc.14.83
How to Cite
Heßelmann, A. Beilstein J. Org. Chem. 2018, 14, 979–991. doi:10.3762/bjoc.14.83
Download Citation
Citation data can be downloaded as file using the "Download" button or used for copy/paste from the text window
below.
Citation data in RIS format can be imported by all major citation management software, including EndNote,
ProCite, RefWorks, and Zotero.
Presentation Graphic
Picture with graphical abstract, title and authors for social media postings and presentations. | ||
Format: PNG | Size: 392.8 KB | Download |
Citations to This Article
Up to 20 of the most recent references are displayed here.
Scholarly Works
- Altun, A.; Schiavo, E.; Mehring, M.; Schulz, S.; Bistoni, G.; Auer, A. A. Rationalizing polymorphism with local correlation-based methods: a case study of pnictogen molecular crystals. Physical chemistry chemical physics : PCCP 2024, 26, 28733–28745. doi:10.1039/d4cp03697b
- Shi, B.; Li, H.; Fu, X.; Zhao, C.; Wang, A. H.; Tan, W.; Rao, Y.; Li, M.; Komarneni, S.; Yang, H. Insight into the key role of imine groups in polyaniline for adsorbing heavy metal ions: Density functional theory and experimental study. Separation and Purification Technology 2024, 335, 125866. doi:10.1016/j.seppur.2023.125866
- Shi, B.; Li, H.; Fu, X.; Zhao, C.; Wang, A. H.; Tan, W.; Rao, Y.; Li, M.; Komarneni, S.; Yang, H. Insight into the Key Role of Imine Groups in Polyaniline for Adsorbing Heavy Metal Ions: Density Functional Theory and Experimental Study. Elsevier BV 2023. doi:10.2139/ssrn.4607829
- Speake, B. T.; Irons, T. J. P.; Wibowo, M.; Johnson, A. G.; David, G.; Teale, A. M. An Embedded Fragment Method for Molecules in Strong Magnetic Fields. Journal of chemical theory and computation 2022, 18, 7412–7427. doi:10.1021/acs.jctc.2c00865
- Kwon, T.; Song, H. W.; Woo, S. Y.; Kim, J.; Sung, B. J. The accurate estimation of the third virial coefficients for helium using three‐body neural network potentials. Bulletin of the Korean Chemical Society 2022, 43, 612–619. doi:10.1002/bkcs.12497
- James, A.; John, C.; Melekamburath, A.; Rajeevan, M.; Swathi, R. S. A journey toward the heaven of chemical fidelity of intermolecular force fields. WIREs Computational Molecular Science 2022, 12. doi:10.1002/wcms.1599
- Shiranirad, M.; Burnham, C. J.; English, N. J. Machine-Learning-based Many-body Energy Analysis of Argon Clusters: fit for size?. Chemical Physics 2022, 552, 111347. doi:10.1016/j.chemphys.2021.111347
- Hellmers, J.; König, C. A unified and flexible formulation of molecular fragmentation schemes. The Journal of chemical physics 2021, 155, 164105. doi:10.1063/5.0059598
- Konrad, M.; Wenzel, W. CONI-Net: Machine Learning of Separable Intermolecular Force Fields. Journal of chemical theory and computation 2021, 17, 4996–5006. doi:10.1021/acs.jctc.1c00328
- Modrzejewski, M.; Yourdkhani, S.; Śmiga, S.; Klimeš, J. Random-Phase Approximation in Many-Body Noncovalent Systems: Methane in a Dodecahedral Water Cage. Journal of chemical theory and computation 2021, 17, 804–817. doi:10.1021/acs.jctc.0c00966
- Shyama, M.; Lakshmipathi, S. Water confined (H2O) n=1–10 amino acid-based ionic liquids – A DFT study on the bonding, energetics and IR spectra. Journal of Molecular Liquids 2020, 304, 112720. doi:10.1016/j.molliq.2020.112720
- Liu, K.-Y.; Herbert, J. M. Energy-Screened Many-Body Expansion: A Practical Yet Accurate Fragmentation Method for Quantum Chemistry. Journal of chemical theory and computation 2019, 16, 475–487. doi:10.1021/acs.jctc.9b01095
- Herbert, J. M. Fantasy versus reality in fragment-based quantum chemistry. The Journal of chemical physics 2019, 151, 170901. doi:10.1063/1.5126216