DESRES Data Sets (DESS66 and S66x8) ========================================= Please see the original paper at https://doi.org/10.1038/s41597-021-00833-x for more information about this dataset. This package contains two datasets described by Donchev et al. [1]: DESS66 and DESS66x8, they are presented as CSVs (.../DESS66.csv and .../DESS66x8.csv) and .mol files (.../geometries/<system_id>/DESS66[x8]_<geom_id>.mol). Also included is for each is a metadata file DESS66[x8]_meta.csv, which contains a set of long-form column descriptions replicating those in [1], as well as data types and units (when applicable) for each column. Manifest -------- - DESS66.csv : S66 geometries computed in the same style as DES370K, containing interaction energies calculated using CCSD(T), MP2, HF, and SAPT0, as well as dimer geometries, and silver-standard [3] reference values. - DESS66_meta.csv : Long-form descriptions of the columns in DESS66, as well as datatypes and units (when applicable) for each column - DESS66x8.csv : S66x8 geometries computed in the same style as DES370K, containing interaction energies calculated using CCSD(T), MP2, HF, and SAPT0, as well as dimer geometries, and bronze-standard [3] reference values. - DESS66x8_meta.csv : Long-form descriptions of the columns in DESS66x8, as well as datatypes and units (when applicable) for each column - LICENSE.txt : License for using and redistributing the datasets provided. - README.md : This file. Loading the Datset ------------------ The datasets are presented as CSVs as a compromise between human-readability, format uniformity, and parsing speed. While an almost uncountable number of packages exist to read CSV files, we recommend using the python data analysis References ---------- [1] A. G. Donchev, A. G. Taube, E. Decolvenaere, C. Hargus, R. T. McGibbon, K.-H. Law, B. A. Gregersen, J.-L. Li, K. Palmo, K. Siva, M. Bergdorf, J. L. Klepeis, and D. E. Shaw. "Quantum chemical benchmark database of dimer interaction energies at a “gold standard” level of accuracy" [2] R. T. McGibbon, A. G. Taube, A. G. Donchev, K. Siva, F. Fernandez, C. Hargus, K.-H. Law, J.L. Klepeis, and D. E. Shaw. "Improving the accuracy of Moller-Plesset perturbation theory with neural networks" [3] M. K. Kesharwani, A. Karton, N. Sylvetsky, J. M. L. Nitai. "The S66 non-covalent interactions benchmark reconsidered using explicitly correlated methods near the basis set limit." License ------- ``` DESRES DATA SETS LICENSE AGREEMENT Copyright 2020, D. E. Shaw Research. All rights reserved. Redistribution and use of electronic structure data released in the DESRES Data Sets (DES370K, DES15K, DES5M, DESS66, and DESS66x8) with or without modification, is permitted provided that the following conditions are met: * Redistributions of the data must retain the above copyright notice, this list of conditions, and the following disclaimer. * Redistributions in binary form must reproduce the above copyright notice, this list of conditions, and the following disclaimer in the documentation and/or other materials provided with the distribution. Neither the name of D. E. Shaw Research nor the names of its contributors may be used to endorse or promote products derived from this software without specific prior written permission. THIS SOFTWARE AND DATA ARE PROVIDED BY THE COPYRIGHT HOLDERS AND CONTRIBUTORS "AS IS" AND ANY EXPRESS OR IMPLIED WARRANTIES, INCLUDING, BUT NOT LIMITED TO, THE IMPLIED WARRANTIES OF MERCHANTABILITY AND FITNESS FOR A PARTICULAR PURPOSE ARE DISCLAIMED. IN NO EVENT SHALL THE COPYRIGHT OWNER OR CONTRIBUTORS BE LIABLE FOR ANY DIRECT, INDIRECT, INCIDENTAL, SPECIAL, EXEMPLARY, OR CONSEQUENTIAL DAMAGES (INCLUDING, BUT NOT LIMITED TO, PROCUREMENT OF SUBSTITUTE GOODS OR SERVICES; LOSS OF USE, DATA, OR PROFITS; OR BUSINESS INTERRUPTION) HOWEVER CAUSED AND ON ANY THEORY OF LIABILITY, WHETHER IN CONTRACT, STRICT LIABILITY, OR TORT (INCLUDINGNEGLIGENCE OR OTHERWISE) ARISING IN ANY WAY OUT OF THE USE OF THIS SOFTWARE AND/OR DATA, EVEN IF ADVISED OF THE POSSIBILITY OF SUCH DAMAGE.