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

Kohn-Sham Density Functional Theory with Complex, Spin-Restricted Orbitals: Accessing a New Class of Densities without the Symmetry Dilemma

Lee, J., Bertels, L. W., Small, D. W., & Head‐Gordon, M. (2019) · Physical Review Letters · doi:10.1103/physrevlett.123.113001 · Cited by 32

Highly Accurate Prediction of NMR Chemical Shifts from Low-Level Quantum Mechanics Calculations Using Machine Learning

Li, J., Liang, J., Wang, Z., Ptaszek, A. L., Liu, X., Ganoe, B., Head‐Gordon, M., & Head-Gordon, T. L. (2024) · Journal of Chemical Theory and Computation · doi:10.1021/acs.jctc.3c01256 · Cited by 32

Lowering of the complexity of quantum chemistry methods by choice of representation

Mardirossian, N., McClain, J. D., & Chan, G. K. (2018) · The Journal of Chemical Physics · doi:10.1063/1.5007779 · Cited by 31

Assessment of Double-Hybrid Density Functional Theory for Magnetic Exchange Coupling in Manganese Complexes

Pantazis, D. A. (2019) · Inorganics · doi:10.3390/inorganics7050057 · Cited by 31

Mechanism of Organoscandium-Catalyzed Ethylene Copolymerization with Amino-Olefins: A Quantum Chemical Analysis

Chen, J., Motta, A., Zhang, J., Gao, Y., & Marks, T. J. (2019) · ACS Catalysis · doi:10.1021/acscatal.9b02317 · Cited by 31

How to Build Rigid Oxygen-Rich Tricyclic Heterocycles from Triketones and Hydrogen Peroxide: Control of Dynamic Covalent Chemistry with Inverse α-Effect

Yaremenko, I. A., Radulov, P. S., Medvedev, M. G., Krivoshchapov, N. V., Belyakova, Y. Y., Korlyukov, A. A., Ilovaisky, A. I., Terent'ev, A. O., & Alabugin, I. V. (2020) · Journal of the American Chemical Society · doi:10.1021/jacs.0c06294 · Cited by 31

Investigation of pristine and B/N/Pt/Au/Pd doped single-walled carbon nanotube as phosgene gas sensor: A first-principles analysis

Katta, S. S., Yadav, S., Singh, A. P., SanthiBhushan, B., & Srivastava, A. (2022) · Applied Surface Science · doi:10.1016/j.apsusc.2022.152989 · Cited by 31

A transferable recommender approach for selecting the best density functional approximations in chemical discovery

Duan, C., Nandy, A., Meyer, R., Arunachalam, N., & Kulik, H. J. (2022) · Nature Computational Science · doi:10.1038/s43588-022-00384-0 · Cited by 33

Barrier Height Prediction by Machine Learning Correction of Semiempirical Calculations

García-Andrade, X., Tahoces, P. G., Pérez‐Ríos, J., & Martı́nez-Núñez, E. (2023) · The Journal of Physical Chemistry A · doi:10.1021/acs.jpca.2c08340 · Cited by 32

Formulation of Small Test Sets Using Large Test Sets for Efficient Assessment of Quantum Chemistry Methods

Chan, B. (2018) · Journal of Chemical Theory and Computation · doi:10.1021/acs.jctc.8b00514 · Cited by 31

Structure and dynamics of liquid water from ab initio simulations: adding Minnesota density functionals to Jacob's ladder

Villard, J., Bircher, M. P., & Röthlisberger, U. (2024) · Chemical Science · doi:10.1039/d3sc05828j · Cited by 30

Method Calibration or Data Fitting?

Jensen, F. (2018) · Journal of Chemical Theory and Computation · doi:10.1021/acs.jctc.8b00477 · Cited by 30

Beyond the Coulson–Fischer point: characterizing single excitation CI and TDDFT for excited states in single bond dissociations

Hait, D., Rettig, A., & Head‐Gordon, M. (2019) · Physical Chemistry Chemical Physics · doi:10.1039/c9cp04452c · Cited by 30

Probing radical–molecule interactions with a second generation energy decomposition analysis of DFT calculations using absolutely localized molecular orbitals

Mao, Y., Levine, D. S., Loipersberger, M., Horn, P. R., & Head‐Gordon, M. (2020) · Physical Chemistry Chemical Physics · doi:10.1039/d0cp01933j · Cited by 30

HCN Production in Titan’s Atmosphere: Coupling Quantum Chemistry and Disequilibrium Atmospheric Modeling

Pearce, B. K. D., Molaverdikhani, K., Pudritz, R. E., Henning, T. K., & Hébrard, É. (2020) · The Astrophysical Journal · doi:10.3847/1538-4357/abae5c · Cited by 32

Computational Exploration of a Redox-Neutral Organocatalytic Mitsunobu Reaction

Zou, Y., Wong, J. J., & Houk, K. N. (2020) · Journal of the American Chemical Society · doi:10.1021/jacs.0c07487 · Cited by 30

Many-Body Dispersion

Xu, P., Alkan, M., & Gordon, M. S. (2020) · Chemical Reviews · doi:10.1021/acs.chemrev.0c00216 · Cited by 30

Polycyclic aromatic hydrocarbons: from small molecules through nano-sized species towards bulk graphene

Chan, B., & Karton, A. (2021) · Physical Chemistry Chemical Physics · doi:10.1039/d1cp01659h · Cited by 30

Approaching the basis set limit in Gaussian-orbital-based periodic calculations with transferability: Performance of pure density functionals for simple semiconductors

Lee, J., Feng, X., Cunha, L. A., Gonthier, J. F., Epifanovsky, E., & Head‐Gordon, M. (2021) · The Journal of Chemical Physics · doi:10.1063/5.0069177 · Cited by 30

Three decades of unveiling the complex chemistry of C -nitroso species with computational chemistry

Bianchi, P., & Monbaliu, J. M. (2021) · Organic Chemistry Frontiers · doi:10.1039/d1qo01415c · Cited by 30

The interplay of intra- and intermolecular errors in modeling conformational polymorphs

Beran, G. J. O., Wright, S. E., Greenwell, C., & Cabeza, A. J. C. (2022) · The Journal of Chemical Physics · doi:10.1063/5.0088027 · Cited by 31

Poisoning density functional theory with benchmark sets of difficult systems

Gould, T., & Dale, S. G. (2022) · Physical Chemistry Chemical Physics · doi:10.1039/d2cp00268j · Cited by 30

Inverse α-Effect as the Ariadne’s Thread on the Way to Tricyclic Aminoperoxides: Avoiding Thermodynamic Traps in the Labyrinth of Possibilities

Yaremenko, I. A., Belyakova, Y. Y., Radulov, P. S., Новиков, Р. А., Medvedev, M. G., Krivoshchapov, N. V., Korlyukov, A. A., Alabugin, I. V., & Terent'ev, A. O. (2022) · Journal of the American Chemical Society · doi:10.1021/jacs.2c00406 · Cited by 30

VIBFREQ1295: A New Database for Vibrational Frequency Calculations

Trujillo, J. C. Z., & McKemmish, L. K. (2022) · The Journal of Physical Chemistry A · doi:10.1021/acs.jpca.2c01438 · Cited by 33

Probing the Free Energy Landscape of Organophotoredox-Catalyzed Anti-Markovnikov Hydrofunctionalization of Alkenes

Mallojjala, S. C., Nyagilo, V. O., Corio, S. A., Adili, A., Dagar, A., Loyer, K. A., Seidel, D., & Hirschi, J. S. (2022) · Journal of the American Chemical Society · doi:10.1021/jacs.2c07807 · Cited by 30

Molecule‐Specific Uncertainty Quantification in Quantum Chemical Studies

Reiher, M. (2022) · Israel Journal of Chemistry · doi:10.1002/ijch.202100101 · Cited by 29

A Computational Protocol Combining DFT and Cheminformatics for Prediction of pH-Dependent Redox Potentials

Fornari, R. P., & de Silva, P. (2021) · Molecules · doi:10.3390/molecules26133978 · Cited by 29

Inq , a Modern GPU-Accelerated Computational Framework for (Time-Dependent) Density Functional Theory

Andrade, X., Pemmaraju, C. D., Kartsev, A., Xiao, J., Lindenberg, A. M., Rajpurohit, S., Tan, L. Z., Ogitsu, T., & Correa, A. A. (2021) · Journal of Chemical Theory and Computation · doi:10.1021/acs.jctc.1c00562 · Cited by 35

Multidimensional analysis for corrosion inhibition by new pyrazoles on mild steel in acidic environment: Experimental and computational approach

Arrouji, S. E., Karrouchi, K., Warad, I., Бериша, А., Alaoui, K. I., Rais, Z., Radi, S., Taleb, M., Ansar, M., & Zarrouk, A. M. (2022) · Chemical Data Collections · doi:10.1016/j.cdc.2022.100885 · Cited by 29

Challenges in modelling dynamic processes in realistic nanostructured materials at operating conditions

Speybroeck, V. V. (2023) · Philosophical Transactions of the Royal Society A Mathematical Physical and Engineering Sciences · doi:10.1098/rsta.2022.0239 · Cited by 30

Density functional theory study on the adsorption of alkali metal ions with pristine and defected graphene sheet

Sangavi, S., Santhanamoorthi, N., & Vijayakumar, S. (2018) · Molecular Physics · doi:10.1080/00268976.2018.1523480 · Cited by 29

Study of Beryllium, Magnesium, and Spodium Bonds to Carbenes and Carbodiphosphoranes

Jabłoński, M. (2021) · Molecules · doi:10.3390/molecules26082275 · Cited by 29

Toward a Quantum-Chemical Benchmark Set for Enzymatically Catalyzed Reactions: Important Steps and Insights

Wappett, D. A., & Goerigk, L. (2019) · The Journal of Physical Chemistry A · doi:10.1021/acs.jpca.9b05088 · Cited by 29

Toward Efficient and Unified Treatment of Static and Dynamic Correlations in Generalized Kohn–Sham Density Functional Theory

Wang, Y., Lin, Z., Ouyang, R., Jiang, B., Zhang, I. Y., & Xu, X. (2024) · JACS Au · doi:10.1021/jacsau.4c00488 · Cited by 28

“Hydridic Hydrogen-Bond Donors” Are Not Hydrogen-Bond Donors

Santos, L. D. A., Vermeeren, P., Bickelhaupt, F. M., & Guerra, C. F. (2024) · Journal of the American Chemical Society · doi:10.1021/jacs.4c07821 · Cited by 28

Role of Intermolecular Interactions in Deep Eutectic Solvents for CO 2 Capture: Vibrational Spectroscopy and Quantum Chemical Studies

Mishra, R., Bhawnani, R. R., Sartape, R., Chauhan, R., Thorat, A. S., Singh, M. R., & Shah, J. K. (2024) · The Journal of Physical Chemistry B · doi:10.1021/acs.jpcb.4c04509 · Cited by 28

London Dispersion as a Design Element in Molecular Catalysis

Domanski, M. H. J., Fuhrmann, M., & Schreiner, P. R. (2025) · Journal of the American Chemical Society · doi:10.1021/jacs.5c09212 · Cited by 28

Statistically representative databases for density functional theory via data science

Morgante, P., & Peverati, R. (2019) · Physical Chemistry Chemical Physics · doi:10.1039/c9cp03211h · Cited by 28

Global uncertainty analysis for the RRKM/master equation modeling of a typical multi-well and multi-channel reaction system

Huang, C., Li, S., Wang, J., Yang, B., & Zhang, F. (2020) · Combustion and Flame · doi:10.1016/j.combustflame.2020.01.039 · Cited by 28

Uptake of N2O5 by aqueous aerosol unveiled using chemically accurate many-body potentials

Cruzeiro, V. W. D., Galib, M., Limmer, D. T., & Götz, A. W. (2022) · Nature Communications · doi:10.1038/s41467-022-28697-8 · Cited by 28

Pursuing the basis set limit of CCSD(T) non-covalent interaction energies for medium-sized complexes: case study on the S66 compilation

Nagy, P. R., Gyevi‐Nagy, L., Lőrincz, B. D., & Kállay, M. (2022) · Molecular Physics · doi:10.1080/00268976.2022.2109526 · Cited by 28

Electronic and Vibrational Manifold of Tetracyanoethylene–Chloronaphthalene Charge Transfer Complex in Solution: Insights from TD-DFT and Ab Initio Molecular Dynamics

Coppola, F., Cimino, P., Perrella, F., Crisci, L., Petrone, A., & Rega, N. (2022) · The Journal of Physical Chemistry A · doi:10.1021/acs.jpca.2c05001 · Cited by 30

Faster Exact Exchange for Solids via occ-RI-K: Application to Combinatorially Optimized Range-Separated Hybrid Functionals for Simple Solids with Pseudopotentials Near the Basis Set Limit

Lee, J., Rettig, A., Feng, X., Epifanovsky, E., & Head‐Gordon, M. (2022) · Journal of Chemical Theory and Computation · doi:10.1021/acs.jctc.2c00742 · Cited by 28

Communication: xDH double hybrid functionals can be qualitatively incorrect for non-equilibrium geometries: Dipole moment inversion and barriers to radical-radical association using XYG3 and XYGJ-OS

Hait, D., & Head‐Gordon, M. (2018) · The Journal of Chemical Physics · doi:10.1063/1.5031027 · Cited by 28

Response Potential in the Strong-Interaction Limit of Density Functional Theory: Analysis and Comparison with the Coupling-Constant Average

Giarrusso, S., Vuckovic, S., & Gori‐Giorgi, P. (2018) · Journal of Chemical Theory and Computation · doi:10.1021/acs.jctc.8b00386 · Cited by 28

Performance of Electronic Structure Methods for the Description of Hückel–Möbius Interconversions in Extended π-Systems

Woller, T. M., Banerjee, A., Sylvetsky, N., Santra, G., Deraet, X., Proft, F. D., Martin, J. M. L., & Alonso, M. (2020) · The Journal of Physical Chemistry A · doi:10.1021/acs.jpca.9b10880 · Cited by 28

QUEST Database of Highly-Accurate Excitation Energies

Loos, P., Boggio‐Pasqua, M., Blondel, A., Lipparini, F., & Jacquemin, D. (2025) · Journal of Chemical Theory and Computation · doi:10.1021/acs.jctc.5c00975 · Cited by 27

Aqueous-Phase Conformations of Lactose, Maltose, and Sucrose and the Assessment of Low-Cost DFT Methods with the DSCONF Set of Conformers for the Three Disaccharides

Chan, B. (2020) · The Journal of Physical Chemistry A · doi:10.1021/acs.jpca.9b10932 · Cited by 27

Comparison of Spin-Flip TDDFT-Based Conical Intersection Approaches with XMS-CASPT2

Winslow, M., Cross, W. B., & Robinson, D. (2020) · Journal of Chemical Theory and Computation · doi:10.1021/acs.jctc.9b00917 · Cited by 29

Theoretical free energy profile and benchmarking of functionals for amino-thiourea organocatalyzed nitro-Michael addition reaction

Pliego, J. R. (2020) · Physical Chemistry Chemical Physics · doi:10.1039/d0cp00481b · Cited by 27

Computational Study of an Iron(II) Polypyridine Electrocatalyst for CO2 Reduction: Key Roles for Intramolecular Interactions in CO2 Binding and Proton Transfer

Loipersberger, M., Zee, D. Z., Panetier, J. A., Chang, C. J., Long, J. R., & Head‐Gordon, M. (2020) · Inorganic Chemistry · doi:10.1021/acs.inorgchem.0c00454 · Cited by 27

Assessment and development of DFT with the expanded CUAGAU ‐2 set of group‐11 cluster systems

Chan, B. (2020) · International Journal of Quantum Chemistry · doi:10.1002/qua.26453 · Cited by 27

Experimental and first-principles study of a new hydrazine derivative for DSSC applications

Badran, I., Tighadouini, S., Radi, S., Zarrouk, A. M., & Warad, I. (2020) · Journal of Molecular Structure · doi:10.1016/j.molstruc.2020.129799 · Cited by 27

Unity of Kohn-Sham density-functional theory and reduced-density-matrix-functional theory

Su, N. Q. (2021) · Physical Review A · doi:10.1103/physreva.104.052809 · Cited by 27

Superhalogens as Building Blocks of Ionic Liquids

Srivastava, A. K., Kumar, A., & Misra, N. (2021) · The Journal of Physical Chemistry A · doi:10.1021/acs.jpca.1c00599 · Cited by 27

Gator: A Python‐driven program for spectroscopy simulations using correlated wave functions

Rehn, D. R., Rinkevičius, Ž., Herbst, M. F., Li, X., Scheurer, M., Brand, M., Dempwolff, A. L., Brumboiu, I. E., Fransson, T., Dreuw, A., et al. (2021) · Wiley Interdisciplinary Reviews Computational Molecular Science · doi:10.1002/wcms.1528 · Cited by 27

Investigations of the intrinsic corrosion and hydrogen susceptibility of metals and alloys using density functional theory

Taylor, C. D., & Ke, H. (2021) · Corrosion Reviews · doi:10.1515/corrrev-2020-0094 · Cited by 27

Chasing unphysical TD-DFT excited states in transition metal complexes with a simple diagnostic tool

Maschietto, F., Campetella, M., Garcı́a, J. S., Adamo, C., & Ciofini, I. (2021) · The Journal of Chemical Physics · doi:10.1063/5.0050680 · Cited by 27

Experimental determination of the interaction potential between a helium atom and the interior surface of a C60 fullerene molecule

Bacanu, G. R., Jafari, T., Aouane, M., Rantaharju, J., Walkey, M. C., Hoffman, G., Shugai, A., Nagel, U., Jiménez-Ruiz, M., Horsewill, A. J., et al. (2021) · The Journal of Chemical Physics · doi:10.1063/5.0066817 · Cited by 27

Role of Defect Engineering and Surface Functionalization in the Design of Carbon Nanotube-Based Nitrogen Oxide Sensors

Valdés-Madrigal, M. A., Montejo‐Alvaro, F., Cernas-Ruiz, A. S., Rojas-Chávez, H., Román‐Doval, R., Cruz‐Martínez, H., & Medina, D. I. (2021) · International Journal of Molecular Sciences · doi:10.3390/ijms222312968 · Cited by 27

How Reliable Are Modern Density Functional Approximations to Simulate Vibrational Spectroscopies?

Sitkiewicz, S. P., Zaleśny, R., Ramos‐Cordoba, E., Luis, J. M., & Matito, E. (2022) · The Journal of Physical Chemistry Letters · doi:10.1021/acs.jpclett.2c01278 · Cited by 27

Impact of the current density on paramagnetic NMR properties

Franzke, Y. J., & Holzer, C. (2022) · The Journal of Chemical Physics · doi:10.1063/5.0103898 · Cited by 27

A Universal Framework for Featurization of Atomistic Systems

Lei, X., & Medford, A. J. (2022) · The Journal of Physical Chemistry Letters · doi:10.1021/acs.jpclett.2c02100 · Cited by 30

The computational road to reactivity scales

Vahl, M., & Proppe, J. (2023) · Physical Chemistry Chemical Physics · doi:10.1039/d2cp03937k · Cited by 27

Exploring the electronic, optical, and thermometric properties of novel AlCuX2 (X = S, Se, Te) semiconductors: a first-principles study

Benaadad, M., Gul, B., Khan, M. S., & Nafidi, A. (2023) · Journal of Materials Science · doi:10.1007/s10853-023-08506-3 · Cited by 27

Multiscale Simulations of the Covalent Inhibition of the SARS-CoV-2 Main Protease: Four Compounds and Three Reaction Mechanisms

Grigorenko, B. L., Polyakov, I. V., Khrenova, M. G., Giudetti, G., Faraji, S., Krylov, A. I., & Nemukhin, A. V. (2023) · Journal of the American Chemical Society · doi:10.1021/jacs.3c02229 · Cited by 27

Mechanism of Charge Transport in Lithium Thiophosphate

Gigli, L., Tisi, D., Grasselli, F., & Ceriotti, M. (2024) · Chemistry of Materials · doi:10.1021/acs.chemmater.3c02726 · Cited by 30

Dispersion-Corrected DFT Struggles with Predicting Three-Body Interaction Energies

Jankiewicz, W. K., Podeszwa, R., & Witek, H. A. (2018) · Journal of Chemical Theory and Computation · doi:10.1021/acs.jctc.8b00167 · Cited by 27

Soft experimental constraints for soft interactions: a spectroscopic benchmark data set for weak and strong hydrogen bonds

Oswald, S., & Suhm, M. A. (2019) · Physical Chemistry Chemical Physics · doi:10.1039/c9cp03651b · Cited by 27

The infrared spectra of protic ionic liquids: performances of different computational models to predict hydrogen bonds and conformer evolution

Palumbo, O., Cimini, A., Trequattrini, F., Brubach, J., Roy, P., & Paolone, A. (2020) · Physical Chemistry Chemical Physics · doi:10.1039/d0cp00907e · Cited by 27

Density Functionals for Hydrogen Storage: Defining the H2Bind275 Test Set with Ab Initio Benchmarks and Assessment of 55 Functionals

Veccham, S. P., & Head‐Gordon, M. (2020) · Journal of Chemical Theory and Computation · doi:10.1021/acs.jctc.0c00292 · Cited by 27

Synthesis, Characterization, In Silico DFT, Molecular Docking, and Dynamics Simulation Studies of Phenylhydrazono Phenoxyquinolones for Their Hypoglycemic Efficacy

Lohitha, N., Kumar, P. H., Sarveswari, S., Rathod, S., Chaudhari, S. Y., Tamboli, Y., Islam, I., & Vijayakumar, V. (2024) · ACS Omega · doi:10.1021/acsomega.4c00079 · Cited by 26

Computational Spectroscopy of Ionic Liquids for Bulk Structure Elucidation

Saielli, G. (2018) · Advanced Theory and Simulations · doi:10.1002/adts.201800084 · Cited by 26

SBS Thermoplastic Elastomer Based on Dynamic Metal‐Ligand Bond: Structure, Mechanical Properties, and Shape Memory Behavior

Wang, Q., He, Y., Li, Q., & Wu, C. (2021) · Macromolecular Materials and Engineering · doi:10.1002/mame.202000737 · Cited by 26

Exploring the Limits of Second- and Third-Order Møller–Plesset Perturbation Theories for Noncovalent Interactions: Revisiting MP2.5 and Assessing the Importance of Regularization and Reference Orbitals

Loipersberger, M., Bertels, L. W., Lee, J., & Head‐Gordon, M. (2021) · Journal of Chemical Theory and Computation · doi:10.1021/acs.jctc.1c00469 · Cited by 26

Reversible absorption of NF3 with high solubility in Lewis acidic ionic liquids

Ji, J., Xiong, W., Zhang, X., Peng, L., Shi, M., Wu, Y., & Hu, X. (2022) · Chemical Engineering Journal · doi:10.1016/j.cej.2022.135902 · Cited by 26

Detection of multi-reference character imbalances enables a transfer learning approach for virtual high throughput screening with coupled cluster accuracy at DFT cost

Duan, C., Chu, D. B. K., Nandy, A., & Kulik, H. J. (2022) · Chemical Science · doi:10.1039/d2sc00393g · Cited by 27

Benchmark of density functional theory methods for the study of organic polysulfides

Sharma, J., & Champagne, P. A. (2022) · Journal of Computational Chemistry · doi:10.1002/jcc.27007 · Cited by 26

Application of density functional theory (DFT) and response surface methodology (RSM) in drug discovery

Ahmad, I., Jagatap, V., & Patel, H. (2023) · Elsevier eBooks · doi:10.1016/b978-0-323-90593-0.00004-6 · Cited by 26

Gauge-Invariant Excited-State Linear and Quadratic Response Properties within the Meta-Generalized Gradient Approximation

Grotjahn, R., & Furche, F. (2023) · Journal of Chemical Theory and Computation · doi:10.1021/acs.jctc.3c00259 · Cited by 26

Deep Mind 21 functional does not extrapolate to transition metal chemistry

Zhao, H., Gould, T., & Vuckovic, S. (2024) · Physical Chemistry Chemical Physics · doi:10.1039/d4cp00878b · Cited by 26

Kohn–Sham energy decomposition for molecules in a magnetic field

Reimann, S., Borgoo, A., Austad, J., Tellgren, E. I., Teale, A. M., Helgaker, T. U., & Stopkowicz, S. (2018) · Molecular Physics · doi:10.1080/00268976.2018.1495849 · Cited by 26

Inner-shell X-ray absorption spectra of the cationic series NH y + ( y = 0–3)

Bari, S., Inhester, L., Schubert, K., Mertens, K., Schunck, J. O., Dörner, S., Deinert, S., Schwob, L., Schippers, S., Müller, A., et al. (2019) · Physical Chemistry Chemical Physics · doi:10.1039/c9cp02864a · Cited by 26

Making many-body interactions nearly pairwise additive: The polarized many-body expansion approach

Veccham, S. P., Lee, J., & Head‐Gordon, M. (2019) · The Journal of Chemical Physics · doi:10.1063/1.5125802 · Cited by 26

Noncollinear Relativistic Two-Component X2C Calculations of Hyperfine Couplings Using Local Hybrid Functionals. Importance of the High-Density Coordinate Scaling Limit

Wodyński, A., & Kaupp, M. (2019) · Journal of Chemical Theory and Computation · doi:10.1021/acs.jctc.9b00911 · Cited by 26

Asymptotic Behavior of the Exchange‐Correlation Energy Density and the Kohn‐Sham Potential in Density Functional Theory: Exact Results and Strategy for Approximations

Kraisler, E. (2020) · Israel Journal of Chemistry · doi:10.1002/ijch.201900103 · Cited by 26

Proof of concept for poor inhibitor binding and efficient formation of covalent adducts of KRAS G12C and ARS compounds

Khrenova, M. G., Kulakova, A. M., & Nemukhin, A. V. (2020) · Organic & Biomolecular Chemistry · doi:10.1039/d0ob00071j · Cited by 26

Challenges for density functional theory: calculation of CO adsorption on electrocatalytically relevant metals

Lininger, C. N., Gauthier, J. A., Li, W., Rossomme, E. C., Welborn, V. V., Lin, Z., Head-Gordon, T. L., Head‐Gordon, M., & Bell, A. T. (2021) · Physical Chemistry Chemical Physics · doi:10.1039/d0cp03821k · Cited by 26

A Comparison of Exact and Model Exchange–Correlation Potentials for Molecules

Kanungo, B., Zimmerman, P. M., & Gavini, V. (2021) · The Journal of Physical Chemistry Letters · doi:10.1021/acs.jpclett.1c03670 · Cited by 26

Strategies to Calculate Fukui Functions and Applications to Radicals with SOMO–HOMO Inversion

Morgante, P., & Autschbach, J. (2023) · Journal of Chemical Theory and Computation · doi:10.1021/acs.jctc.3c00256 · Cited by 25

Accurate Simulation for 2D Lubricating Materials in Realistic Environments: From Classical to Quantum Mechanical Methods

Hao, Y., Sun, T., Ye, J., Huang, L., & Wang, L. (2024) · Advanced Materials · doi:10.1002/adma.202312429 · Cited by 25

Navigating structure-based drug discovery with emerging innovations in physics- and knowledge-based approaches

Lam, J. H., & Katritch, V. (2025) · npj Drug Discovery. · doi:10.1038/s44386-025-00031-4 · Cited by 30

Gold-Standard Chemical Database 137 (GSCDB137): A Diverse Set of Accurate Energy Differences for Assessing and Developing Density Functionals

Liang, J., & Head‐Gordon, M. (2025) · Journal of Chemical Theory and Computation · doi:10.1021/acs.jctc.5c01380 · Cited by 30

Electron Spin Densities and Density Functional Approximations: Open-Shell Polycyclic Aromatic Hydrocarbons as Case Study

Savarese, M., Brémond, É. A. G., Ciofini, I., & Adamo, C. (2020) · Journal of Chemical Theory and Computation · doi:10.1021/acs.jctc.0c00059 · Cited by 25

Historical perspective and bibliometric analysis of molecular modeling applied in mineral flotation systems

Silva, L. A., Garrot, T. G., Pereira, A. M., & Correia, J. C. G. (2021) · Minerals Engineering · doi:10.1016/j.mineng.2021.107062 · Cited by 25

Local structure and NO adsorption/desorption property of Pd 2+ cations at different paired Al sites in CHA zeolite

Yasumura, S., Ueda, T., Ide, H., Otsubo, K., Liu, C., Tsunoji, N., Toyao, T., Maeno, Z., & Shimizu, K. (2021) · Physical Chemistry Chemical Physics · doi:10.1039/d1cp02668b · Cited by 25

B‐DNA Structure and Stability: The Role of Nucleotide Composition and Order

Nieuwland, C., Hamlin, T. A., Guerra, C. F., Barone, G., & Bickelhaupt, F. M. (2022) · ChemistryOpen · doi:10.1002/open.202100231 · Cited by 25

Do Double-Hybrid Functionals Benefit from Regularization in the PT2 Term? Observations from an Extensive Benchmark

Santra, G., & Martin, J. M. L. (2022) · The Journal of Physical Chemistry Letters · doi:10.1021/acs.jpclett.2c00718 · Cited by 25

Data-driven many-body potentials from density functional theory for aqueous phase chemistry

Palos, E., Dasgupta, S., Lambros, E., & Paesani, F. (2023) · Chemical Physics Reviews · doi:10.1063/5.0129613 · Cited by 25

Reproducibility of density functional approximations: How new functionals should be reported

Lehtola, S., & Marques, M. A. L. (2023) · The Journal of Chemical Physics · doi:10.1063/5.0167763 · Cited by 25

A thorough benchmark of density functional methods for general main group thermochemistry, kinetics, and noncovalent interactions

Goerigk, L., & Grimme, S. (2011) · Physical Chemistry Chemical Physics · doi:10.1039/c0cp02984j · Cited by 2,036

ω B97M-V: A combinatorially optimized, range-separated hybrid, meta-GGA density functional with VV10 nonlocal correlation

Mardirossian, N., & Head‐Gordon, M. (2016) · The Journal of Chemical Physics · doi:10.1063/1.4952647 · Cited by 1,348

Mapping the genome of meta-generalized gradient approximation density functionals: The search for B97M-V

Mardirossian, N., & Head‐Gordon, M. (2015) · The Journal of Chemical Physics · doi:10.1063/1.4907719 · Cited by 446

Quest for a universal density functional: the accuracy of density functionals across a broad spectrum of databases in chemistry and physics

Peverati, R., & Truhlar, D. G. (2014) · Philosophical Transactions of the Royal Society A Mathematical Physical and Engineering Sciences · doi:10.1098/rsta.2012.0476 · Cited by 756

Designing and assessing density functionals

Mardirossian, N. (2016) · eScholarship (California Digital Library)