Thirty years of density functional theory in computational chemistry: an overview and extensive assessment of 200 density functionals

Generalized Gradient Approximation Made Simple

Perdew, J. P., Burke, K., & Ernzerhof, M. (1996) · Physical Review Letters · doi:10.1103/physrevlett.77.3865 · Cited by 215,824

Density-functional thermochemistry. III. The role of exact exchange

Becke, A. D. (1993) · The Journal of Chemical Physics · doi:10.1063/1.464913 · Cited by 103,767

Development of the Colle-Salvetti correlation-energy formula into a functional of the electron density

Lee, C., Yang, W., & Parr, R. G. (1988) · Physical Review B · doi:10.1103/physrevb.37.785 · Cited by 100,874

Self-Consistent Equations Including Exchange and Correlation Effects

Kohn, W., & Sham, L. J. (1965) · Physical Review · doi:10.1103/physrev.140.a1133 · Cited by 64,135

A consistent and accurate ab initio parametrization of density functional dispersion correction (DFT-D) for the 94 elements H-Pu

Grimme, S., Antony, J., Ehrlich, S., & Krieg, H. (2010) · The Journal of Chemical Physics · doi:10.1063/1.3382344 · Cited by 59,686

Density-functional exchange-energy approximation with correct asymptotic behavior

Becke, A. D. (1988) · Physical Review A · doi:10.1103/physreva.38.3098 · Cited by 54,100

Inhomogeneous Electron Gas

Hohenberg, P., & Kohn, W. (1964) · Physical Review · doi:10.1103/physrev.136.b864 · Cited by 53,541

Semiempirical GGA‐type density functional constructed with a long‐range dispersion correction

Grimme, S. (2006) · Journal of Computational Chemistry · doi:10.1002/jcc.20495 · Cited by 31,214

The M06 suite of density functionals for main group thermochemistry, thermochemical kinetics, noncovalent interactions, excited states, and transition elements: two new functionals and systematic testing of four M06-class functionals and 12 other functionals

Zhao, Y., & Truhlar, D. G. (2007) · Theoretical Chemistry Accounts · doi:10.1007/s00214-007-0310-x · Cited by 30,666

Effect of the damping function in dispersion corrected density functional theory

Grimme, S., Ehrlich, S., & Goerigk, L. (2011) · Journal of Computational Chemistry · doi:10.1002/jcc.21759 · Cited by 28,221

Cooperative Self‐Assembly in Linear Chains Based on Halogen Bonds

Vermeeren, P., Wolters, L. P., Paragi, G., & Guerra, C. F. (2021) · ChemPlusChem · doi:10.1002/cplu.202100093 · Cited by 17

On the inclusion of one double within CIS and TDDFT

Athavale, V., Teh, H.-H., & Subotnik, J. E. (2021) · The Journal of Chemical Physics · doi:10.1063/5.0064269 · Cited by 17

Theoretical Study of N-Heterocyclic-Carbene–ZnX2 (X = H, Me, Et) Complexes

Jabłoński, M. (2021) · Materials · doi:10.3390/ma14206147 · Cited by 17

Does the Presence of a Bond Path Really Mean Interatomic Stabilization? The Case of the Ng@Superphane (Ng = He, Ne, Ar, and Kr) Endohedral Complexes

Jabłoński, M. (2021) · Symmetry · doi:10.3390/sym13122241 · Cited by 17

Embedding Double Transition Metal Atoms in B-Modified Two-Dimensional Carbon-Rich Conjugated Frameworks for Efficient Ammonia Synthesis

Jiao, L., & Guo, L. (2022) · Inorganic Chemistry · doi:10.1021/acs.inorgchem.2c02958 · Cited by 17

Computational prediction on photophysical properties of two excited state intramolecular proton transfer (ESIPT) fluorophores bearing the benzothiazole group

Wen, K., Guo, X., & Zhang, J. (2018) · Molecular Physics · doi:10.1080/00268976.2018.1542169 · Cited by 17

$Ab~initio$ description of excited states of 1D uniform matter with the Hohenberg–Kohn-theorem-inspired functional-renormalization-group method

Yokota, T., Yoshida, K., & Kunihiro, T. (2018) · Progress of Theoretical and Experimental Physics · doi:10.1093/ptep/pty139 · Cited by 17

Density functional theory

Nomura, Y., & Akashi, R. (2023) · Elsevier eBooks · doi:10.1016/b978-0-323-90800-9.00148-7 · Cited by 20

Structural and spectroscopic properties, solvation effects, intermolecular interactions, and biological assays of a Mn(II)-complex with 1,10-phenanthroline and chloro ligands

de Souza, M. V., Neto, J. G. D. O., Viana, J. R., Dutra, R. P., Lage, M. R., dos Santos, A. O., & de Sousa, F. F. (2024) · Vibrational Spectroscopy · doi:10.1016/j.vibspec.2024.103710 · Cited by 18

DFT in catalysis: Complex equations for practical computing applications in chemistry

Brotons‐Rufes, A., Pérez, S. P., & Poater, A. (2025) · Digital Chemical Engineering · doi:10.1016/j.dche.2025.100285 · Cited by 17

Can We Predict the Pressure Induced Phase Transition of Urea? Application of Quantum Molecular Dynamics

Mazurek, A., Szeleszczuk, Ł., & Pisklak, D. M. (2020) · Molecules · doi:10.3390/molecules25071584 · Cited by 16

Bypassing the computational bottleneck of quantum-embedding theories for strong electron correlations with machine learning

Rogers, J., Lee, T.-H., Pakdel, S., Xu, W., Dobrosavljević, V., Yao, Y.-X., Ove Christiansen, A., & Lanatà, N. (2021) · Physical Review Research · doi:10.1103/physrevresearch.3.013101 · Cited by 16

Insights from the density functional performance of water and water–solid interactions: SCAN in relation to other meta-GGAs

Jana, S., Patra, A., Śmiga, S., Constantin, L. A., & Samal, P. (2020) · The Journal of Chemical Physics · doi:10.1063/5.0028821 · Cited by 16

Adsorption of CO, H2S and CH4 molecules on SnS2 monolayer: a first-principles study

Lin, L., Chen, R., Huang, J., Wang, P., Zhu, L., Yao, L., Hu, C., Tao, H., & Zhang, Z. (2020) · Molecular Physics · doi:10.1080/00268976.2020.1856429 · Cited by 16

Practical Computational Chemistry Course for a Comprehensive Understanding of Organic, Inorganic, and Physical Chemistry: From Molecular Interactions to Chemical Reactions

Kuroki, N., Mochizuki, Y., & Mori, H. (2023) · Journal of Chemical Education · doi:10.1021/acs.jchemed.2c00837 · Cited by 16

Entrainer selection for the extractive distillation of acrylic acid and propionic acid

Keestra, H., Brouwer, T., Schuur, B., & Lange, J. (2023) · Process Safety and Environmental Protection · doi:10.1016/j.cherd.2023.02.049 · Cited by 16

Cellulose based polyurethane with amino acid functionality: Design, synthesis, computational study and application in wastewater purification

Rub, H. A., Deghles, A., Hamed, O. A., Azzaoui, K., Hammouti, B., Taleb, M., Бериша, А., Dagdag, O., Mansour, W., Hacıosmanoğlu, G. G., et al. (2023) · International Journal of Biological Macromolecules · doi:10.1016/j.ijbiomac.2023.124328 · Cited by 16

Assessing the Accuracy of Density Functional Approximations for Predicting Hydrolysis Reaction Kinetics

Epstein, A. R., Spotte‐Smith, E. W. C., Venetos, M. C., Andriuc, O., & Persson, K. A. (2023) · Journal of Chemical Theory and Computation · doi:10.1021/acs.jctc.3c00176 · Cited by 16

Analytical harmonic vibrational frequencies with VV10-containing density functionals: Theory, efficient implementation, and benchmark assessments

Liang, J., Feng, X., Liu, X., & Head‐Gordon, M. (2023) · The Journal of Chemical Physics · doi:10.1063/5.0152838 · Cited by 17

Regularized and Opposite Spin-Scaled Functionals from Møller–Plesset Adiabatic Connection─Higher Accuracy at Lower Cost

Daas, K. J., Kooi, D. P., Peters, N. C., Fabiano, E. S., Sala, F. D., Gori‐Giorgi, P., & Vuckovic, S. (2023) · The Journal of Physical Chemistry Letters · doi:10.1021/acs.jpclett.3c01832 · Cited by 16

Carbon–Nitrogen Bond Formation Using Sodium Hexamethyldisilazide: Solvent-Dependent Reactivities and Mechanisms

You, Q., & Collum, D. B. (2023) · Journal of the American Chemical Society · doi:10.1021/jacs.3c07317 · Cited by 16

Benchmarking Quantum Mechanical Levels of Theory for Valence Parametrization in Force Fields

Behara, P. K., Jang, H., Horton, J. T., Gokey, T., Dotson, D., Boothroyd, S., Bayly, C. I., Cole, D. J., Wang, L., & Mobley, D. L. (2024) · The Journal of Physical Chemistry B · doi:10.1021/acs.jpcb.4c03167 · Cited by 16

Reaction barriers at metal surfaces computed using the random phase approximation: Can we beat DFT in the generalized gradient approximation?

Oudot, B., & Doblhoff-Dier, K. (2024) · The Journal of Chemical Physics · doi:10.1063/5.0220465 · Cited by 16

Thermochemical Conversion of Guaiacol in Aqueous Phase by Density Functional Theory

Agrawal, K., Verma, A. M., & Kishore, N. (2019) · ChemistrySelect · doi:10.1002/slct.201900437 · Cited by 16

Catalytic Mechanism of Calcium on the Formation of HCN during Pyrolysis of Pyrrole and Indole: A Theoretical Study

Liu, J., Fan, X.-R., Zhao, W., Hu, B., Liu, D.-J., Lü, Q., & Yang, Y. (2019) · Energy & Fuels · doi:10.1021/acs.energyfuels.9b02955 · Cited by 16

Comprehensive study of polymerization of pyrrole: A theoretical approach

Pang, S.-K. (2020) · Journal of Electroanalytical Chemistry · doi:10.1016/j.jelechem.2020.113886 · Cited by 16

Study of the influence of intermolecular interaction on classical and reverse substituent effects in para -substituted phenylboranes

Jabłoński, M., & Krygowski, T. M. (2020) · New Journal of Chemistry · doi:10.1039/d0nj01334j · Cited by 16

A computational study of hydrogen bonding motifs in halide, tetrafluoroborate, hexafluorophosphate, and tetraarylborate salts of chiral cationic ruthenium and cobalt guanidinobenzimidazole hydrogen bond donor catalysts; acceptor properties of the “BArf” anion

Wititsuwannakul, T., Hall, M. B., & Gladysz, J. A. (2020) · Polyhedron · doi:10.1016/j.poly.2020.114618 · Cited by 16

Efficient and Accurate Approach To Estimate Hybrid Functional and Large Basis-Set Contributions to Condensed-Phase Systems and Molecule–Surface Interactions

Ricard, T. C., & Iyengar, S. S. (2020) · Journal of Chemical Theory and Computation · doi:10.1021/acs.jctc.9b01089 · Cited by 16

The role of carboxylic acid impurity in the mechanism of the formation of aldimines in aprotic solvents

Rufino, V. C., & Pliego, J. R. (2020) · Computational and Theoretical Chemistry · doi:10.1016/j.comptc.2020.113053 · Cited by 16

SAMPL7: Host–guest binding prediction by molecular dynamics and quantum mechanics

Eken, Y., Almeida, N. M. S., Wang, C., & Wilson, A. K. (2020) · Journal of Computer-Aided Molecular Design · doi:10.1007/s10822-020-00357-3 · Cited by 16

Deep learning for predictions of hydrolysis rates and conditional molecular design of esters

Chiu, P.-H., Yang, Y.-L., Tsao, H., & Sheng, Y. (2021) · Journal of the Taiwan Institute of Chemical Engineers · doi:10.1016/j.jtice.2021.06.045 · Cited by 16

Surprisingly Good Performance of XYG3 Family Functionals Using a Scaled KS-MP3 Correlation

Santra, G., Semidalas, E. C., & Martin, J. M. L. (2021) · The Journal of Physical Chemistry Letters · doi:10.1021/acs.jpclett.1c02838 · Cited by 16

Integrating Computation and Experiment to Investigate Photoelectrodes for Solar Water Splitting at the Microscopic Scale

Wang, W., Radmilovic, A., Choi, K., & Galli, G. (2021) · Accounts of Chemical Research · doi:10.1021/acs.accounts.1c00418 · Cited by 16

The Good, the Bad, and the Ugly: “HiPen”, a New Dataset for Validating (S)QM/MM Free Energy Simulations

Kearns, F. L., Warrensford, L. C., Boresch, S., & Woodcock, H. L. (2019) · Molecules · doi:10.3390/molecules24040681 · Cited by 16

In Silico Screening and DFT Analysis of Nelumbo nucifera Phytochemicals as Potential BACE-1 Inhibitors for Alzheimer’s disease

Todkar, R. R., Shirote, P. J., & Mohite, S. K. (2025) · Prospects in Pharmaceutical Sciences · doi:10.56782/pps.379 · Cited by 15

The N···H hydrogen bond strength in the transition state at the limiting step determines the reactivity of cephalosporins in the active site of L1 metallo-β-lactamase

Khrenova, M. G., & Григорьевич, Ц. В. (2019) · Mendeleev Communications · doi:10.1016/j.mencom.2019.09.004 · Cited by 15

Electrochemistry of Ce(IV)/Ce(III) redox couples in mixed solutions for aqueous flow battery: Experimental and molecular modelling study

Schmickler, W., Nazmutdinov, R. R., Wang, Q., & Daoud, W. A. (2020) · Electrochimica Acta · doi:10.1016/j.electacta.2020.137601 · Cited by 15

The Charge-State and Structural Stability of Peptides Conferred by Microsolvating Environments in Differential Mobility Spectrometry

Ieritano, C., Rickert, D. A., Featherstone, J., Honek, J. F., Campbell, J. L., Blanc, J. C. Y. L., Schneider, B. B., & Hopkins, W. S. (2021) · Journal of the American Society for Mass Spectrometry · doi:10.1021/jasms.0c00469 · Cited by 15

Theoretical Calculation on the Reaction Mechanisms, Kinetics and Toxicity of Acetaminophen Degradation Initiated by Hydroxyl and Sulfate Radicals in the Aqueous Phase

Xu, M., Yao, J., Sun, S., Yan, S., & Sun, J. (2021) · Toxics · doi:10.3390/toxics9100234 · Cited by 15

Periodically reversing electrocoagulation technique for efficient removal of short-chain perfluoroalkyl substances from contaminated groundwater around a fluorochemical facility

Liu, Y., Lu, M., Bao, J., Shao, L.-X., Yu, W., Hu, X., & Zhao, X. (2023) · Chemosphere · doi:10.1016/j.chemosphere.2023.138953 · Cited by 17

Quantum Descriptors for Predicting and Understanding the Structure–Activity Relationships of Michael Acceptor Warheads

Liu, R., Vázquez-Montelongo, E. A., Ma, S., & Shen, J. (2023) · Journal of Chemical Information and Modeling · doi:10.1021/acs.jcim.3c00720 · Cited by 15

Opening the Density Functional Theory Black Box: A Collection of Pedagogic Jupyter Notebooks

Hirschi, J. S., Bashirova, D., & Zuehlsdorff, T. J. (2023) · Journal of Chemical Education · doi:10.1021/acs.jchemed.3c00535 · Cited by 15

Best-of-Both-Worlds Predictive Approach to Dissociative Chemisorption on Metals

Powell, A. D., Gerrits, N., Tchakoua, T., Somers, M. F., Busnengo, H. F., Meyer, J., Kroes, G., & Doblhoff-Dier, K. (2024) · The Journal of Physical Chemistry Letters · doi:10.1021/acs.jpclett.3c02972 · Cited by 15

Best-of-both-worlds computational approaches to difficult-to-model dissociation reactions on metal surfaces

Kroes, G., & Meyer, J. (2024) · Chemical Science · doi:10.1039/d4sc06004k · Cited by 15

Repartitioning the Hamiltonian in many-body second-order Brillouin–Wigner perturbation theory: Uncovering new size-consistent models

Dittmer, L. B., & Head‐Gordon, M. (2025) · The Journal of Chemical Physics · doi:10.1063/5.0242211 · Cited by 15

Accurate Water Properties from an Efficient ab Initio Method

Jana, S., Constantin, L. A., & Samal, P. (2020) · Journal of Chemical Theory and Computation · doi:10.1021/acs.jctc.9b01018 · Cited by 15

Computational Modeling Reveals the Mechanism of Fluorescent State Recovery in the Reversibly Photoswitchable Protein Dreiklang

Grigorenko, B. L., Polyakov, I. V., Krylov, A. I., & Nemukhin, A. V. (2019) · The Journal of Physical Chemistry B · doi:10.1021/acs.jpcb.9b06988 · Cited by 15

Energy Decomposition Analysis for Interactions of Radicals: Theory and Implementation at the MP2 Level with Application to Hydration of Halogenated Benzene Cations and Complexes between CO2–· and Pyridine and Imidazole

Loipersberger, M., Lee, J., Mao, Y., Das, A. K., Ikeda, K., Thirman, J., Head-Gordon, T. L., & Head‐Gordon, M. (2019) · The Journal of Physical Chemistry A · doi:10.1021/acs.jpca.9b08586 · Cited by 15

Electro-thermal transport in disordered nanostructures: a modeling perspective

Ducry, F., Aeschlimann, J., & Luisier, M. (2020) · Nanoscale Advances · doi:10.1039/d0na00168f · Cited by 15

Fitting elephants in the density functionals zoo: Statistical criteria for the evaluation of density functional theory methods as a suitable replacement for counting parameters

Peverati, R. (2020) · International Journal of Quantum Chemistry · doi:10.1002/qua.26379 · Cited by 15

Quantitative and qualitative performance of density functional theory rationalized by reduced density gradient distributions

de Andrade, A. M., Kullgren, J., & Broqvist, P. (2020) · Physical review. B./Physical review. B · doi:10.1103/physrevb.102.075115 · Cited by 15

Molecular growth upon ionization of van der Waals clusters containing HCCH and HCN is a pathway to prebiotic molecules

Stein, T., Bera, P. P., Lee, T. J., & Head‐Gordon, M. (2020) · Physical Chemistry Chemical Physics · doi:10.1039/d0cp03350b · Cited by 15

Robust All-Electron Optimization in Orbital-Free Density-Functional Theory Using the Trust-Region Image Method

Ryley, M. S., Withnall, M., Irons, T. J. P., Helgaker, T. U., & Teale, A. M. (2020) · The Journal of Physical Chemistry A · doi:10.1021/acs.jpca.0c09502 · Cited by 15

Molecular design principles of ionic liquids with a sulfonyl fluoride moiety

Siegel, D. J., Anderson, G. I., Cyr, N., Lambrecht, D. S., Zeller, M., Hillesheim, P. C., & Mirjafari, A. (2021) · New Journal of Chemistry · doi:10.1039/d0nj05603k · Cited by 15

The influence of the shape and configuration of sensitizer molecules on the efficiency of DSSCs: a theoretical insight

Krishnan, S., & Senthilkumar, K. (2021) · RSC Advances · doi:10.1039/d0ra10613e · Cited by 15

Evaluation of molecular photophysical and photochemical properties using linear response time-dependent density functional theory with classical embedding: Successes and challenges

Liang, W., Pei, Z., Mao, Y., & Shao, Y. (2022) · The Journal of Chemical Physics · doi:10.1063/5.0088271 · Cited by 15

Investigation of structural, optoelectronic and thermoelectric properties of GaCuX2 (X = S, Se and Te) chalcopyrites semiconductors using the accurate mBJ approach

Benaadad, M., Nafidi, A., Melkoud, S., Mahraj, I., & Salmi, M. (2022) · Physica B Condensed Matter · doi:10.1016/j.physb.2022.414118 · Cited by 15

Variational principle to regularize machine-learned density functionals: The non-interacting kinetic-energy functional

del Mazo‐Sevillano, P., & Hermann, J. (2023) · The Journal of Chemical Physics · doi:10.1063/5.0166432 · Cited by 15

Balance between Physical Interpretability and Energetic Predictability in Widely Used Dispersion-Corrected Density Functionals

Dasgupta, S., Palos, E., Pan, Y., & Paesani, F. (2023) · Journal of Chemical Theory and Computation · doi:10.1021/acs.jctc.3c00903 · Cited by 15

Theoretical and computational studies on nanofriction: A review

Sankar, K. M., Kakkar, D., Dubey, S., Garimella, S. V., Goyat, M. S., Joshi, S., & Pandey, J. K. (2019) · Proceedings of the Institution of Mechanical Engineers Part J Journal of Engineering Tribology · doi:10.1177/1350650119863993 · Cited by 15

Mean-field density matrix decompositions

Eriksen, J. J. (2020) · The Journal of Chemical Physics · doi:10.1063/5.0030764 · Cited by 17

Functional-Based Description of Electronic Dynamic and Strong Correlation: Old Issues and New Insights

Ai, W., Fang, W., & Su, N. Q. (2022) · The Journal of Physical Chemistry Letters · doi:10.1021/acs.jpclett.2c00084 · Cited by 15

Reactants, Products, and Transition States of Elementary Chemical Reactions Based on Quantum ChemistryPreprint

Grambow, C. A., Pattanaik, L., & Green, W. H. (2019) · ChemRxiv · doi:10.26434/chemrxiv.11400240 · Cited by 15

The Impact of DFT Functional, Cluster Model Size, and Implicit Solvation on the Structural Description of Single-Metal-Mediated DNA Phosphodiester Bond Cleavage: The Case Study of APE1

Kaur, R., Nikkel, D. J., Aboelnga, M. M., & Wetmore, S. D. (2022) · The Journal of Physical Chemistry B · doi:10.1021/acs.jpcb.2c06756 · Cited by 14

Interexcited State Photophysics I: Benchmarking Density Functionals for Computing Nonadiabatic Couplings and Internal Conversion Rate Constants

Manian, A., Hudson, R. J., Ramkissoon, P., Smith, T. A., & Russo, S. P. (2022) · Journal of Chemical Theory and Computation · doi:10.1021/acs.jctc.2c00888 · Cited by 14

Determination of pKa values and deprotonation order of methotrexate using a combined experimental-theoretical study and binding constants of the methotrexate-Laponite complex at different pH values

Alva-Ensastegui, J. C., Morales-Ávila, E., de la Luz, A. P., & Bernad‐Bernad, M. J. (2023) · Journal of Photochemistry and Photobiology A Chemistry · doi:10.1016/j.jphotochem.2023.115406 · Cited by 14

3D-QSAR-based pharmacophore modelling of quinazoline derivatives for the identification of acetylcholinesterase inhibitors through virtual screening, molecular docking, molecular dynamics and DFT studies

Kumar, V., Jangid, K., Kumar, N., Kumar, V., & Kumar, V. (2024) · Journal of Biomolecular Structure and Dynamics · doi:10.1080/07391102.2024.2313157 · Cited by 14

Assessing Exchange-Correlation Functionals for Heterogeneous Catalysis of Nitrogen Species

Kim, H., Yu, N.-K., Tian, N., & Medford, A. J. (2024) · The Journal of Physical Chemistry C · doi:10.1021/acs.jpcc.4c01497 · Cited by 14

Investigation of Ethane Dehydrogenation and Hydrogenolysis on Pt(111), Pt(211), and Pt(100): Bayesian Quantification and Correction of DFT-Based Enthalpic and Entropic Uncertainties

Bello, M., Bamidele, O. H., Terejanu, G., & Heyden, A. (2024) · ACS Catalysis · doi:10.1021/acscatal.4c03455 · Cited by 14

Smoother Semiclassical Dispersion for Density Functional Theory via D3S: Understanding and Addressing Unphysical Minima in the D3 Dispersion Correction Model

Tkachenko, N. V., & Head‐Gordon, M. (2024) · Journal of Chemical Theory and Computation · doi:10.1021/acs.jctc.4c01105 · Cited by 14

Effects of Hydrogen Bonding Solvation by Diverse Fluorinated Bulky Alcohols on the Reaction Rate and Selectivity in Crown Ether Mediated Nucleophilic Fluorination in an Aprotic Solvent

Ávila, E. P., de Almeida, M. V., Valle, M. S., & Pliego, J. R. (2024) · ACS Organic & Inorganic Au · doi:10.1021/acsorginorgau.4c00081 · Cited by 14

Quantum Chemical Evaluation and QSAR Modeling of N -Nitrosamine Carcinogenicity

Schieferdecker, S., & Vock, E. (2025) · Chemical Research in Toxicology · doi:10.1021/acs.chemrestox.4c00476 · Cited by 14

Barriometry – an enhanced database of accurate barrier heights for gas-phase reactions

Chan, B., & Simmie, J. M. (2018) · Physical Chemistry Chemical Physics · doi:10.1039/c7cp08045j · Cited by 14

Molecular Dynamics Simulation of Cyclooxygenase-2 Complexes with Indomethacin closo-Carborane Analogs

Sárosi, M. B., & Lybrand, T. P. (2018) · Journal of Chemical Information and Modeling · doi:10.1021/acs.jcim.8b00275 · Cited by 14

Synchrotron Radiation UV-VUV Photoabsorption of Gas Phase Molecules

Duflot, D., Hoffmann, S. V., Jones, N. C., & Limão-Vieira, P. (2019) · Bioanalysis · doi:10.1007/978-3-030-28247-9_2 · Cited by 14

Efficient yet accurate dispersion-corrected semilocal exchange–correlation functionals for non-covalent interactions

Patra, A., Jana, S., Constantin, L. A., & Samal, P. (2020) · The Journal of Chemical Physics · doi:10.1063/5.0011849 · Cited by 14

CLB18: A new structural database with unusual carbon–carbon long bonds

Morgante, P., & Peverati, R. (2020) · Chemical Physics Letters · doi:10.1016/j.cplett.2020.138281 · Cited by 14

Computational density-functional approaches on finite-size and guest-lattice effects in CO2@sII clathrate hydrate

Cabrera‐Ramírez, A., Yanes-Rodríguez, R., & Prosmiti, R. (2021) · The Journal of Chemical Physics · doi:10.1063/5.0039323 · Cited by 14

Ionic Liquid Vapors in Vacuum: Possibility to Derive Anodic Stabilities from DFT and UPS

Kuusik, I., Kook, M., Pärna, R., & Kisand, V. (2021) · ACS Omega · doi:10.1021/acsomega.0c05369 · Cited by 14

σ‐Electrons Responsible for Cooperativity and Ring Equalization in Hydrogen‐Bonded Supramolecular Polymers

Santos, L. D. A., Cesario, D., Vermeeren, P., van der Lubbe, S. C. C., Nunzi, F., & Guerra, C. F. (2021) · ChemPlusChem · doi:10.1002/cplu.202100436 · Cited by 14

Best-Practice Aspects of Quantum-Computer Calculations: A Case Study of the Hydrogen Molecule

Miháliková, I., Friák, M., Pivoluska, M., Plesch, M., Saip, M., & Šob, M. (2022) · Molecules · doi:10.3390/molecules27030597 · Cited by 16

An experimental and theoretical analysis of supercritical carbon dioxide extraction of Cu(II) and Pb(II) ions in the form of dithizone bidentate complexes

Halili, J., & Бериша, А. (2021) · TURKISH JOURNAL OF CHEMISTRY · doi:10.3906/kim-2110-44 · Cited by 14

Electronic and Vibrational Properties of Allene Carotenoids

Mačernis, M., Streckaitė, S., Litvín, R., Pascal, A. A., Llansola‐Portoles, M. J., Robert, B., & Valkūnas, L. (2022) · The Journal of Physical Chemistry A · doi:10.1021/acs.jpca.1c09393 · Cited by 14

Cobalt(III) Complexes as Bifunctional Hydrogen‐Bond Donor Catalysts Featuring Halide Anions for Cyclic Carbonate Synthesis at Ambient Temperature and Pressure: A Mechanistic Insight

Emelyanov, M. A., Lisov, A. A., Medvedev, M. G., Maleev, V. I., & Larionov, V. A. (2022) · Asian Journal of Organic Chemistry · doi:10.1002/ajoc.202100811 · Cited by 14

How Well Does Kohn–Sham Regularizer Work for Weakly Correlated Systems?

Kalita, B., Pederson, R. D., Chen, J., Li, L., & Burke, K. (2022) · The Journal of Physical Chemistry Letters · doi:10.1021/acs.jpclett.2c00371 · Cited by 14

A Computational and Experimental View of Hydrogen Bonding in Glycerol Water Clusters

Lu, W., Mackie, C. J., Xu, B., Head‐Gordon, M., & Ahmed, M. (2022) · The Journal of Physical Chemistry A · doi:10.1021/acs.jpca.2c00659 · Cited by 14

Fast and Accurate Quantum Mechanical Modeling of Large Molecular Systems Using Small Basis Set Hartree–Fock Methods Corrected with Atom-Centered Potentials

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