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• Hancock Amy C., Giudici Erica, Goerigk Lars: How do spin‐scaled double hybrids designed for excitation energies perform for noncovalent excited‐state interactions? An investigation on aromatic excimer models. J Comput Chem 2024. <https://doi.org/10.1002/jcc.27351>
• Wilson Cameron J. G., Plesniar Jan, Kuhn Heike, Armstrong Jeff, Wood Peter A., Parsons Simon: The Advantages of Flexibility: The Role of Entropy in Crystal Structures Containing C–H···F Interactions. Crystal Growth & Design 2024, 24, 2217. <https://doi.org/10.1021/acs.cgd.4c00042>
• Dasgupta Saswata, Palos Etienne, Pan Yuanhui, Paesani Francesco: Balance between Physical Interpretability and Energetic Predictability in Widely Used Dispersion-Corrected Density Functionals. J. Chem. Theory Comput. 2024, 20, 49. <https://doi.org/10.1021/acs.jctc.3c00903>
• Stewart James J. P., Stewart Anna C.: A semiempirical method optimized for modeling proteins. J Mol Model 2023, 29. <https://doi.org/10.1007/s00894-023-05695-1>
• Pierce Karl, Valeev Edward F.: Efficient Construction of Canonical Polyadic Approximations of Tensor Networks. J. Chem. Theory Comput. 2023, 19, 71. <https://doi.org/10.1021/acs.jctc.2c00861>
• Yourdkhani Sirous, Klimeš Jiří: Using Noncovalent Interactions to Test the Precision of Projector-Augmented Wave Data Sets. J. Chem. Theory Comput. 2023, 19, 8871. <https://doi.org/10.1021/acs.jctc.3c00930>
• Kim Shinae, Conrad Justin A., Tow Garrett M., Maginn Edward J., Boatz Jerry A., Gordon Mark S.: Intermolecular interactions in clusters of ethylammonium nitrate and 1-amino-1,2,3-triazole. Phys. Chem. Chem. Phys. 2023, 25, 30428. <https://doi.org/10.1039/D3CP02407E>
• Palos Etienne, Dasgupta Saswata, Lambros Eleftherios, Paesani Francesco: Data-driven many-body potentials from density functional theory for aqueous phase chemistry. Chemical Physics Reviews 2023, 4. <https://doi.org/10.1063/5.0129613>
• Cabaleiro-Lago Enrique M., Fernández Berta, Rodríguez-Fernández Roberto, Rodríguez-Otero Jesús, Vázquez Saulo A.: Functional group corrections to the GFN2-xTB and PM6 semiempirical methods for noncovalent interactions in alkanes and alkenes. The Journal of Chemical Physics 2023, 158. <https://doi.org/10.1063/5.0140668>
• Nakano Kousuke, Kohulák Oto, Raghav Abhishek, Casula Michele, Sorella Sandro: TurboGenius: Python suite for high-throughput calculations of ab initio quantum Monte Carlo methods. The Journal of Chemical Physics 2023, 159. <https://doi.org/10.1063/5.0179003>
• Seijas Luis E., Zambrano Cesar H., Almeida Rafael, Alí-Torres Jorge, Rincón Luis, Torres Fernando Javier: Exploring the Non-Covalent Bonding in Water Clusters. IJMS 2023, 24, 5271. <https://doi.org/10.3390/ijms24065271>
• Matveeva Regina, Falck Erichsen Merete, Koch Henrik, Høyvik Ida‐Marie: The effect of midbond functions on interaction energies computed using MP2 and CCSD(T). J Comput Chem 2022, 43, 121. <https://doi.org/10.1002/jcc.26777>
• Palos Etienne, Lambros Eleftherios, Swee Steven, Hu Jie, Dasgupta Saswata, Paesani Francesco: Assessing the Interplay between Functional-Driven and Density-Driven Errors in DFT Models of Water. J. Chem. Theory Comput. 2022, 18, 3410. <https://doi.org/10.1021/acs.jctc.2c00050>
• Dasgupta Saswata, Shahi Chandra, Bhetwal Pradeep, Perdew John P., Paesani Francesco: How Good Is the Density-Corrected SCAN Functional for Neutral and Ionic Aqueous Systems, and What Is So Right about the Hartree–Fock Density?. J. Chem. Theory Comput. 2022, 18, 4745. <https://doi.org/10.1021/acs.jctc.2c00313>
• Tahir Muhammad N., Zhu Tong, Shang Honghui, Li Jia, Blum Volker, Ren Xinguo: Localized Resolution of Identity Approach to the Analytical Gradients of Random-Phase Approximation Ground-State Energy: Algorithm and Benchmarks. J. Chem. Theory Comput. 2022, 18, 5297. <https://doi.org/10.1021/acs.jctc.2c00512>
• Brémond Eric, Li Hanwei, Sancho-García Juan Carlos, Adamo Carlo: Double Hybrids and Noncovalent Interactions: How Far Can We Go?. J. Phys. Chem. A 2022, 126, 2590. <https://doi.org/10.1021/acs.jpca.2c01193>
• Chakraborty Anish, Tribedi Soumi, Maitra Rahul: A double exponential coupled cluster theory in the fragment molecular orbital framework. The Journal of Chemical Physics 2022, 156. <https://doi.org/10.1063/5.0090115>
• Palos Etienne, Lambros Eleftherios, Dasgupta Saswata, Paesani Francesco: Density functional theory of water with the machine-learned DM21 functional. The Journal of Chemical Physics 2022, 156. <https://doi.org/10.1063/5.0090862>
• Ramos Chloe, Muehlbrad Jeremiah, Janesko Benjamin G.: Density functionals with full nonlocal exchange, nonlocal rung‐3.5 correlation, and D3 dispersion: Combined accuracy for general main‐group thermochemistry, kinetics, and noncovalent interactions. J Comput Chem 2021, 42, 1974. <https://doi.org/10.1002/jcc.26728>
• Takaya Daisuke, Watanabe Chiduru, Nagase Shunpei, Kamisaka Kikuko, Okiyama Yoshio, Moriwaki Hirotomo, Yuki Hitomi, Sato Tomohiro, Kurita Noriyuki, Yagi Yoichiro, Takagi Tatsuya, Kawashita Norihito, Takaba Kenichiro, Ozawa Tomonaga, Takimoto-Kamimura Midori, Tanaka Shigenori, Fukuzawa Kaori, Honma Teruki: FMODB: The World’s First Database of Quantum Mechanical Calculations for Biomacromolecules Based on the Fragment Molecular Orbital Method. J. Chem. Inf. Model. 2021, 61, 777. <https://doi.org/10.1021/acs.jcim.0c01062>
• Tölle Johannes, Deilmann Thorsten, Rohlfing Michael, Neugebauer Johannes: Subsystem-Based GW/Bethe–Salpeter Equation. J. Chem. Theory Comput. 2021, 17, 2186. <https://doi.org/10.1021/acs.jctc.0c01307>
• Pierce Karl, Rishi Varun, Valeev Edward F.: Robust Approximation of Tensor Networks: Application to Grid-Free Tensor Factorization of the Coulomb Interaction. J. Chem. Theory Comput. 2021, 17, 2217. <https://doi.org/10.1021/acs.jctc.0c01310>
• Pérez-Tabero Sergio, Fernández Berta, Cabaleiro-Lago Enrique M., Martínez-Núñez Emilio, Vázquez Saulo A.: New Approach for Correcting Noncovalent Interactions in Semiempirical Quantum Mechanical Methods: The Importance of Multiple-Orientation Sampling. J. Chem. Theory Comput. 2021, 17, 5556. <https://doi.org/10.1021/acs.jctc.1c00365>
• Al-Hamdani Yasmine S., Nagy Péter R., Zen Andrea, Barton Dennis, Kállay Mihály, Brandenburg Jan Gerit, Tkatchenko Alexandre: Interactions between large molecules pose a puzzle for reference quantum mechanical methods. Nat Commun 2021, 12. <https://doi.org/10.1038/s41467-021-24119-3>
• Hao Zi-kai, Lv Hai-feng, Wang Da-yong, Wu Xiao-jun: High-performance chemical information database towards accelerating discovery of metal-organic frameworks for gas adsorption with machine learning. Chinese Journal of Chemical Physics 2021, 34, 436. <https://doi.org/10.1063/1674-0068/cjcp2104079>
• Tribedi Soumi, Chakraborty Anish, Maitra Rahul: Formulation of a Dressed Coupled-Cluster Method with Implicit Triple Excitations and Benchmark Application to Hydrogen-Bonded Systems. J. Chem. Theory Comput. 2020, 16, 6317. <https://doi.org/10.1021/acs.jctc.0c00736>
• Kang Sungwoo, Woo Jeheon, Kim Jaewook, Kim Hyeonsu, Kim Yongjun, Lim Jaechang, Choi Sunghwan, Kim Woo Youn: ACE-Molecule: An open-source real-space quantum chemistry package. The Journal of Chemical Physics 2020, 152. <https://doi.org/10.1063/5.0002959>
• Meier de Andrade Ageo, Kullgren Jolla, Broqvist Peter: Quantitative and qualitative performance of density functional theory rationalized by reduced density gradient distributions. Phys. Rev. B 2020, 102. <https://doi.org/10.1103/PhysRevB.102.075115>
• Czernek Jiří, Brus Jiří: Parametrizing the Spatial Dependence of 1H NMR Chemical Shifts in π-Stacked Molecular Fragments. IJMS 2020, 21, 7908. <https://doi.org/10.3390/ijms21217908>
• Řezáč Jan: Description of halogen bonding in semiempirical quantum‐mechanical and self‐consistent charge density‐functional tight‐binding methods. J Comput Chem 2019, 40, 1633. <https://doi.org/10.1002/jcc.25816>
• Cai Wei, Liu Conghu, Lai Kee-hung, Li Li, Cunha Jorge, Hu Luoke: Energy performance certification in mechanical manufacturing industry: A review and analysis. Energy Conversion and Management 2019, 186, 415. <https://doi.org/10.1016/j.enconman.2019.02.041>
• Pham Buu Q., Gordon Mark S.: Compressing the Four-Index Two-Electron Repulsion Integral Matrix using the Resolution-of-the-Identity Approximation Combined with the Rank Factorization Approximation. J. Chem. Theory Comput. 2019, 15, 2254. <https://doi.org/10.1021/acs.jctc.8b01256>
• Proppe Jonny, Gugler Stefan, Reiher Markus: Gaussian Process-Based Refinement of Dispersion Corrections. J. Chem. Theory Comput. 2019, 15, 6046. <https://doi.org/10.1021/acs.jctc.9b00627>
• Leduc Théo, Aubert Emmanuel, Espinosa Enrique, Jelsch Christian, Iordache Cristian, Guillot Benoît: Polarization of Electron Density Databases of Transferable Multipolar Atoms. J. Phys. Chem. A 2019, 123, 7156. <https://doi.org/10.1021/acs.jpca.9b05051>
• Wappett Dominique A., Goerigk Lars: Toward a Quantum-Chemical Benchmark Set for Enzymatically Catalyzed Reactions: Important Steps and Insights. J. Phys. Chem. A 2019, 123, 7057. <https://doi.org/10.1021/acs.jpca.9b05088>
• Sattasathuchana Tosaporn, Xu Peng, Gordon Mark S.: An Accurate Quantum-Based Approach to Explicit Solvent Effects: Interfacing the General Effective Fragment Potential Method with Ab Initio Electronic Structure Theory. J. Phys. Chem. A 2019, 123, 8460. <https://doi.org/10.1021/acs.jpca.9b05801>
• Alkan Melisa, Xu Peng, Gordon Mark S.: Many-Body Dispersion in Molecular Clusters. J. Phys. Chem. A 2019, 123, 8406. <https://doi.org/10.1021/acs.jpca.9b05977>
• Parks Holden L., McGaughey Alan. J. H., Viswanathan Venkatasubramanian: Uncertainty Quantification in First-Principles Predictions of Harmonic Vibrational Frequencies of Molecules and Molecular Complexes. J. Phys. Chem. C 2019, 123, 4072. <https://doi.org/10.1021/acs.jpcc.8b11689>
• Rincon Luis, Javier Torres F., Becerra Marcos, Liu Shubin, Fritsch Alain, Almeida Rafael: On the separation of the information content of the Fermi and Coulomb holes and their influence on the electronic properties of molecular systems. Molecular Physics 2019, 117, 610. <https://doi.org/10.1080/00268976.2018.1530462>
• Cipcigan F. S., Crain J., Sokhan V. P., Martyna G. J.: Electronic coarse graining: Predictive atomistic modeling of condensed matter. Rev. Mod. Phys. 2019, 91. <https://doi.org/10.1103/RevModPhys.91.025003>
• Suárez Dimas, Díaz Natalia, Francisco Evelio, Martín Pendás Angel: Application of the Interacting Quantum Atoms Approach to the S66 and Ionic‐Hydrogen‐Bond Datasets for Noncovalent Interactions. ChemPhysChem 2018, 19, 973. <https://doi.org/10.1002/cphc.201701021>
• Cai Wei, Liu Fei, Dinolov Ognyan, Xie Jun, Liu Peiji, Tuo Junbo: Energy benchmarking rules in machining systems. Energy 2018, 142, 258. <https://doi.org/10.1016/j.energy.2017.10.030>
• Řezáč Jan, Bím Daniel, Gutten Ondrej, Rulíšek Lubomír: Toward Accurate Conformational Energies of Smaller Peptides and Medium-Sized Macrocycles: MPCONF196 Benchmark Energy Data Set. J. Chem. Theory Comput. 2018, 14, 1254. <https://doi.org/10.1021/acs.jctc.7b01074>
• Dutta Narendra Nath, Patkowski Konrad: Improving “Silver-Standard” Benchmark Interaction Energies with Bond Functions. J. Chem. Theory Comput. 2018, 14, 3053. <https://doi.org/10.1021/acs.jctc.8b00204>
• Clement Marjory C., Zhang Jinmei, Lewis Cannada A., Yang Chao, Valeev Edward F.: Optimized Pair Natural Orbitals for the Coupled Cluster Methods. J. Chem. Theory Comput. 2018, 14, 4581. <https://doi.org/10.1021/acs.jctc.8b00294>
• Kesharwani Manoj K., Manna Debashree, Sylvetsky Nitai, Martin Jan M. L.: The X40×10 Halogen Bonding Benchmark Revisited: Surprising Importance of (n–1)d Subvalence Correlation. J. Phys. Chem. A 2018, 122, 2184. <https://doi.org/10.1021/acs.jpca.7b10958>
• Kim Shinae, Kaliszewski Chelsea M., Guidez Emilie B., Gordon Mark S.: Benchmarking the Effective Fragment Potential Dispersion Correction on the S22 Test Set. J. Phys. Chem. A 2018, 122, 4076. <https://doi.org/10.1021/acs.jpca.7b11628>
• Schoeberle Luke, Guidez Emilie B., Gordon Mark S.: Benchmarking of the R–7 Anisotropic Dispersion Energy Term on the S22 Dimer Test Set. J. Phys. Chem. A 2018, 122, 6100. <https://doi.org/10.1021/acs.jpca.8b04451>
• Kesharwani Manoj K., Karton Amir, Sylvetsky Nitai, Martin Jan M. L.: The S66 Non-Covalent Interactions Benchmark Reconsidered Using Explicitly Correlated Methods Near the Basis Set Limit. Aust. J. Chem. 2018, 71, 238. <https://doi.org/10.1071/CH17588>
• Guttmann Robin, Sax Alexander F.: Dispersion Interactions and the Stability of Amine Dimers. ChemistryOpen 2017, 6, 571. <https://doi.org/10.1002/open.201700052>
• Sierański Tomasz: Discovering the stacking landscape of a pyridine-pyridine system. J Mol Model 2017, 23. <https://doi.org/10.1007/s00894-017-3496-4>
• Cai Wei, Liu Fei, Xie Jun, Liu Peiji, Tuo Junbo: A tool for assessing the energy demand and efficiency of machining systems: Energy benchmarking. Energy 2017, 138, 332. <https://doi.org/10.1016/j.energy.2017.07.039>
• Temelso Berhane, Mabey Joel M., Kubota Toshiro, Appiah-Padi Nana, Shields George C.: ArbAlign: A Tool for Optimal Alignment of Arbitrarily Ordered Isomers Using the Kuhn–Munkres Algorithm. J. Chem. Inf. Model. 2017, 57, 1045. <https://doi.org/10.1021/acs.jcim.6b00546>
• Manna Debashree, Kesharwani Manoj K., Sylvetsky Nitai, Martin Jan M. L.: Conventional and Explicitly Correlated ab Initio Benchmark Study on Water Clusters: Revision of the BEGDB and WATER27 Data Sets. J. Chem. Theory Comput. 2017, 13, 3136. <https://doi.org/10.1021/acs.jctc.6b01046>
• Wang Bing, Dobosh Paul A., Chalk Stuart, Sopek Mirek, Ostlund Neil S.: Computational Chemistry Data Management Platform Based on the Semantic Web. J. Phys. Chem. A 2017, 121, 298. <https://doi.org/10.1021/acs.jpca.6b10489>
• Goerigk Lars, Hansen Andreas, Bauer Christoph, Ehrlich Stephan, Najibi Asim, Grimme Stefan: A look at the density functional theory zoo with the advanced GMTKN55 database for general main group thermochemistry, kinetics and noncovalent interactions. Phys. Chem. Chem. Phys. 2017, 19, 32184. <https://doi.org/10.1039/C7CP04913G>
• Gonthier Jérôme F., Head-Gordon Martin: Compressed representation of dispersion interactions and long-range electronic correlations. The Journal of Chemical Physics 2017, 147. <https://doi.org/10.1063/1.4997186>
• Sylvetsky Nitai, Kesharwani Manoj K., Martin Jan M. L.: The aug-cc-pVnZ-F12 basis set family: Correlation consistent basis sets for explicitly correlated benchmark calculations on anions and noncovalent complexes. The Journal of Chemical Physics 2017, 147. <https://doi.org/10.1063/1.4998332>
• Burns Lori A., Faver John C., Zheng Zheng, Marshall Michael S., Smith Daniel G. A., Vanommeslaeghe Kenno, MacKerell Alexander D., Merz Kenneth M., Sherrill C. David: The BioFragment Database (BFDb): An open-data platform for computational chemistry analysis of noncovalent interactions. The Journal of Chemical Physics 2017, 147. <https://doi.org/10.1063/1.5001028>
• Řezáč Jan, Hobza Pavel: Benchmark Calculations of Interaction Energies in Noncovalent Complexes and Their Applications. Chem. Rev. 2016, 116, 5038. <https://doi.org/10.1021/acs.chemrev.5b00526>
• Christensen Anders S., Kubař Tomáš, Cui Qiang, Elstner Marcus: Semiempirical Quantum Mechanical Methods for Noncovalent Interactions for Chemical and Biochemical Applications. Chem. Rev. 2016, 116, 5301. <https://doi.org/10.1021/acs.chemrev.5b00584>
• Höfener Sebastian, Visscher Lucas: Wave Function Frozen-Density Embedding: Coupled Excitations. J. Chem. Theory Comput. 2016, 12, 549. <https://doi.org/10.1021/acs.jctc.5b00821>
• Brauer Brina, Kesharwani Manoj K., Kozuch Sebastian, Martin Jan M. L.: The S66x8 benchmark for noncovalent interactions revisited: explicitly correlated ab initio methods and density functional theory. Phys. Chem. Chem. Phys. 2016, 18, 20905. <https://doi.org/10.1039/C6CP00688D>
• Bernardo Carlos E. P., Silva Pedro J.: Computational exploration of the reaction mechanism of the Cu + -catalysed synthesis of indoles from N -aryl enaminones. R. Soc. open sci. 2016, 3, 150582. <https://doi.org/10.1098/rsos.150582>
• Huang Ming, Giese Timothy J., York Darrin M.: Nucleic acid reactivity: Challenges for next-generation semiempirical quantum models. J. Comput. Chem. 2015, 36, 1370. <https://doi.org/10.1002/jcc.23933>
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• Hughes Timothy J., Kandathil Shaun M., Popelier Paul L.A.: Accurate prediction of polarised high order electrostatic interactions for hydrogen bonded complexes using the machine learning method kriging. Spectrochimica Acta Part A: Molecular and Biomolecular Spectroscopy 2015, 136, 32. <https://doi.org/10.1016/j.saa.2013.10.059>
• Řezáč Jan, Huang Yuanhang, Hobza Pavel, Beran Gregory J. O.: Benchmark Calculations of Three-Body Intermolecular Interactions and the Performance of Low-Cost Electronic Structure Methods. J. Chem. Theory Comput. 2015, 11, 3065. <https://doi.org/10.1021/acs.jctc.5b00281>
• Sedlak Robert, Kolář Michal H., Hobza Pavel: Polar Flattening and the Strength of Halogen Bonding. J. Chem. Theory Comput. 2015, 11, 4727. <https://doi.org/10.1021/acs.jctc.5b00687>
• Kubillus Maximilian, Kubař Tomáš, Gaus Michael, Řezáč Jan, Elstner Marcus: Parameterization of the DFTB3 Method for Br, Ca, Cl, F, I, K, and Na in Organic and Biological Systems. J. Chem. Theory Comput. 2015, 11, 332. <https://doi.org/10.1021/ct5009137>
• Schlüns Danny, Klahr Kevin, Mück-Lichtenfeld Christian, Visscher Lucas, Neugebauer Johannes: Subsystem-DFT potential-energy curves for weakly interacting systems. Phys. Chem. Chem. Phys. 2015, 17, 14323. <https://doi.org/10.1039/C4CP04936E>
• Shao Yihan, Gan Zhengting, Epifanovsky Evgeny, Gilbert Andrew T.B., Wormit Michael, Kussmann Joerg, Lange Adrian W., Behn Andrew, Deng Jia, Feng Xintian, Ghosh Debashree, Goldey Matthew, Horn Paul R., Jacobson Leif D., Kaliman Ilya, Khaliullin Rustam Z., Kuś Tomasz, Landau Arie, Liu Jie, Proynov Emil I., Rhee Young Min, Richard Ryan M., Rohrdanz Mary A., Steele Ryan P., Sundstrom Eric J., Woodcock H. Lee, Zimmerman Paul M., Zuev Dmitry, Albrecht Ben, Alguire Ethan, Austin Brian, Beran Gregory J. O., Bernard Yves A., Berquist Eric, Brandhorst Kai, Bravaya Ksenia B., Brown Shawn T., Casanova David, Chang Chun-Min, Chen Yunqing, Chien Siu Hung, Closser Kristina D., Crittenden Deborah L., Diedenhofen Michael, DiStasio Robert A., Do Hainam, Dutoi Anthony D., Edgar Richard G., Fatehi Shervin, Fusti-Molnar Laszlo, Ghysels An, Golubeva-Zadorozhnaya Anna, Gomes Joseph, Hanson-Heine Magnus W.D., Harbach Philipp H.P., Hauser Andreas W., Hohenstein Edward G., Holden Zachary C., Jagau Thomas-C., Ji Hyunjun, Kaduk Benjamin, Khistyaev Kirill, Kim Jaehoon, Kim Jihan, King Rollin A., Klunzinger Phil, Kosenkov Dmytro, Kowalczyk Tim, Krauter Caroline M., Lao Ka Un, Laurent Adèle D., Lawler Keith V., Levchenko Sergey V., Lin Ching Yeh, Liu Fenglai, Livshits Ester, Lochan Rohini C., Luenser Arne, Manohar Prashant, Manzer Samuel F., Mao Shan-Ping, Mardirossian Narbe, Marenich Aleksandr V., Maurer Simon A., Mayhall Nicholas J., Neuscamman Eric, Oana C. Melania, Olivares-Amaya Roberto, O’Neill Darragh P., Parkhill John A., Perrine Trilisa M., Peverati Roberto, Prociuk Alexander, Rehn Dirk R., Rosta Edina, Russ Nicholas J., Sharada Shaama M., Sharma Sandeep, Small David W., Sodt Alexander, Stein Tamar, Stück David, Su Yu-Chuan, Thom Alex J.W., Tsuchimochi Takashi, Vanovschi Vitalii, Vogt Leslie, Vydrov Oleg, Wang Tao, Watson Mark A., Wenzel Jan, White Alec, Williams Christopher F., Yang Jun, Yeganeh Sina, Yost Shane R., You Zhi-Qiang, Zhang Igor Ying, Zhang Xing, Zhao Yan, Brooks Bernard R., Chan Garnet K.L., Chipman Daniel M., Cramer Christopher J., Goddard William A., Gordon Mark S., Hehre Warren J., Klamt Andreas, Schaefer Henry F., Schmidt Michael W., Sherrill C. David, Truhlar Donald G., Warshel Arieh, Xu Xin, Aspuru-Guzik Alán, Baer Roi, Bell Alexis T., Besley Nicholas A., Chai Jeng-Da, Dreuw Andreas, Dunietz Barry D., Furlani Thomas R., Gwaltney Steven R., Hsu Chao-Ping, Jung Yousung, Kong Jing, Lambrecht Daniel S., Liang WanZhen, Ochsenfeld Christian, Rassolov Vitaly A., Slipchenko Lyudmila V., Subotnik Joseph E., Van Voorhis Troy, Herbert John M., Krylov Anna I., Gill Peter M.W., Head-Gordon Martin: Advances in molecular quantum chemistry contained in the Q-Chem 4 program package. Molecular Physics 2015, 113, 184. <https://doi.org/10.1080/00268976.2014.952696>
• Peterson Kirk A., Kesharwani Manoj K., Martin Jan M.L.: The cc-pV5Z-F12 basis set: reaching the basis set limit in explicitly correlated calculations. Molecular Physics 2015, 113, 1551. <https://doi.org/10.1080/00268976.2014.985755>
• Bhattacharya Sohini, Mittal Shriyaa, Panigrahi Swati, Sharma Purshotam, S. P. Preethi, Paul Rahul, Halder Sukanya, Halder Antarip, Bhattacharyya Dhananjay, Mitra Abhijit: RNABP COGEST: a resource for investigating functional RNAs. Database 2015, 2015. <https://doi.org/10.1093/database/bav011>
• Sałdyka Magdalena: Interaction of N-hydroxyurea with strong proton donors: HCl and HF. Chemical Physics 2014, 444, 15. <https://doi.org/10.1016/j.chemphys.2014.09.009>
• Goldey Matthew B., Head-Gordon Martin: Convergence of attenuated second order Møller–Plesset perturbation theory towards the complete basis set limit. Chemical Physics Letters 2014, 608, 249. <https://doi.org/10.1016/j.cplett.2014.05.092>
• Li Amanda, Muddana Hari S., Gilson Michael K.: Quantum Mechanical Calculation of Noncovalent Interactions: A Large-Scale Evaluation of PMx, DFT, and SAPT Approaches. J. Chem. Theory Comput. 2014, 10, 1563. <https://doi.org/10.1021/ct401111c>
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• Goldey Matthew, Head-Gordon Martin: Separate Electronic Attenuation Allowing a Spin-Component-Scaled Second-Order Møller–Plesset Theory to Be Effective for Both Thermochemistry and Noncovalent Interactions. J. Phys. Chem. B 2014, 118, 6519. <https://doi.org/10.1021/jp4126478>
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• Vymětal Jiří, Bathula Sreenivas Reddy, Černý Jiří, Chaloupková Radka, Žídek Lukáš, Sklenář Vladimír, Vondrášek Jiří: Retro operation on the Trp-cage miniprotein sequence produces an unstructured molecule capable of folding similar to the original only upon 2,2,2-trifluoroethanol addition. Protein Engineering, Design and Selection 2014, 27, 463. <https://doi.org/10.1093/protein/gzu046>
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• Lepšík Martin, Řezáč Jan, Kolář Michal, Pecina Adam, Hobza Pavel, Fanfrlík Jindřich: The Semiempirical Quantum Mechanical Scoring Function for In Silico Drug Design. ChemPlusChem 2013, 78, 921. <https://doi.org/10.1002/cplu.201300199>
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