标题/作者	年份
CP2K: An electronic structure and molecular dynamics software package-Quickstep: Efficient and accurate electronic structure calculations TD Kühne, M Iannuzzi, M Del Ben, VV Rybkin, P Seewald, F Stein, ... The Journal of Chemical Physics 152 (19)	2020
Automated exploration of the low-energy chemical space with fast quantum chemical methods P Pracht, F Bohle, S Grimme Physical Chemistry Chemical Physics 22 (14), 7169-7192	2020
Towards the online computer-aided design of catalytic pockets L Falivene, Z Cao, A Petta, L Serra, A Poater, R Oliva, V Scarano, ... Nature Chemistry 11 (10), 872-879	2019
A generally applicable atomic-charge dependent London dispersion correction E Caldeweyher, S Ehlert, A Hansen, H Neugebauer, S Spicher, ... The Journal of chemical physics 150 (15)	2019
Extended tight‐binding quantum chemistry methods C Bannwarth, E Caldeweyher, S Ehlert, A Hansen, P Pracht, J Seibert, ... Wiley Interdisciplinary Reviews: Computational Molecular Science 11 (2), e1493	2021
TURBOMOLE: Modular program suite for ab initio quantum-chemical and condensed-matter simulations SG Balasubramani, GP Chen, S Coriani, M Diedenhofen, MS Frank, ... The Journal of chemical physics 152 (18)	2020
DFTB+, a software package for efficient approximate density functional theory based atomistic simulations B Hourahine, B Aradi, V Blum, F Bonafé, A Buccheri, C Camacho, ... The Journal of chemical physics 152 (12)	2020
Exploration of chemical compound, conformer, and reaction space with meta-dynamics simulations based on tight-binding quantum chemical calculations S Grimme Journal of chemical theory and computation 15 (5), 2847-2862	2019
Independent gradient model based on Hirshfeld partition: A new method for visual study of interactions in chemical systems T Lu, Q Chen Journal of Computational Chemistry 43 (8), 539-555	2022
Efficient evaluation of electrostatic potential with computerized optimized code J Zhang, T Lu Physical Chemistry Chemical Physics 23 (36), 20323-20328	2021
Combining machine learning and computational chemistry for predictive insights into chemical systems JA Keith, V Vassilev-Galindo, B Cheng, S Chmiela, M Gastegger, ... Chemical reviews 121 (16), 9816-9872	2021
Robust atomistic modeling of materials, organometallic, and biochemical systems S Spicher, S Grimme Angewandte Chemie International Edition 59 (36), 15665-15673	2020
Equivariant message passing for the prediction of tensorial properties and molecular spectra K Schütt, O Unke, M Gastegger International Conference on Machine Learning, 9377-9388	2021
OrbNet: Deep learning for quantum chemistry using symmetry-adapted atomic-orbital features Z Qiao, M Welborn, A Anandkumar, FR Manby, TF Miller The Journal of chemical physics 153 (12)	2020
Fast and uncertainty-aware directional message passing for non-equilibrium molecules J Gasteiger, S Giri, JT Margraf, S Günnemann arXiv preprint arXiv:2011.14115	2020
Machine-learned potentials for next-generation matter simulations P Friederich, F Häse, J Proppe, A Aspuru-Guzik Nature Materials 20 (6), 750-761	2021
Equivariant diffusion for molecule generation in 3d E Hoogeboom, VG Satorras, C Vignac, M Welling International conference on machine learning, 8867-8887	2022
Understanding chemical reactivity using the activation strain model P Vermeeren, SCC van der Lubbe, C Fonseca Guerra, FM Bickelhaupt, ... Nature protocols 15 (2), 649-667	2020
TeraChem: A graphical processing unit‐accelerated electronic structure package for large‐scale ab initio molecular dynamics S Seritan, C Bannwarth, BS Fales, EG Hohenstein, CM Isborn, ... Wiley Interdisciplinary Reviews: Computational Molecular Science 11 (2), e1494	2021
Machine learning the quantum-chemical properties of metal–organic frameworks for accelerated materials discovery AS Rosen, SM Iyer, D Ray, Z Yao, A Aspuru-Guzik, L Gagliardi, ... Matter 4 (5), 1578-1597	2021

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