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

Approaching coupled-cluster accuracy for molecular electronic structures with multi-task learning

Tang, H., Xiao, B., He, W., Subašić, P., Harutyunyan, A. R., Wang, Y., Liu, F., Xu, H., & Li, J. (2024) · Nature Computational Science · doi:10.1038/s43588-024-00747-9 · Cited by 28

Efficient Implementation of NOCI-MP2 Using the Resolution of the Identity Approximation with Application to Charged Dimers and Long C–C Bonds in Ethane Derivatives

Yost, S. R., & Head‐Gordon, M. (2018) · Journal of Chemical Theory and Computation · doi:10.1021/acs.jctc.8b00697 · Cited by 25

Gas phase formation of c-SiC 3 molecules in the circumstellar envelope of carbon stars

Yang, T., Bertels, L. W., Dangi, B. B., Li, X., Head‐Gordon, M., & Kaiser, R. I. (2019) · Proceedings of the National Academy of Sciences · doi:10.1073/pnas.1810370116 · Cited by 25

Intermolecular Interactions in Molecular Organic Crystals upon Relaxation of Lattice Parameters

Stein, M., & Heimsaat, M. (2019) · Crystals · doi:10.3390/cryst9120665 · Cited by 25

Assessing the validity of DLPNO‐CCSD (T) in the calculation of activation and reaction energies of ubiquitous enzymatic reactions

Paiva, P., Ramos, M. J., & Fernandes, P. A. (2020) · Journal of Computational Chemistry · doi:10.1002/jcc.26401 · Cited by 25

Approximately Self-Consistent Ensemble Density Functional Theory: Toward Inclusion of All Correlations

Gould, T. (2020) · The Journal of Physical Chemistry Letters · doi:10.1021/acs.jpclett.0c02894 · Cited by 25

Accurate Thermochemistry for Main-Group Elements up to Xenon with the Wn-P34 Series of Composite Methods

Chan, B. (2021) · Journal of Chemical Theory and Computation · doi:10.1021/acs.jctc.1c00598 · Cited by 25

Accurate Spectral Properties within Double-Hybrid Density Functional Theory: A Spin-Scaled Range-Separated Second-Order Algebraic-Diagrammatic Construction-Based Approach

Mester, D., & Kállay, M. (2022) · Journal of Chemical Theory and Computation · doi:10.1021/acs.jctc.1c01100 · Cited by 25

Roadmap on methods and software for electronic structure based simulations in chemistry and materials

Blum, V., Asahi, R., Autschbach, J., Bannwarth, C., Bihlmayer, G., Blügel, S., Burns, L. A., Crawford, T. D., Dawson, W., de Jong, W. A., et al. (2024) · Electronic Structure · doi:10.1088/2516-1075/ad48ec · Cited by 24

Quantum chemical modeling of hydrogen binding in metal–organic frameworks: validation, insight, predictions and challenges

Chakraborty, R., Talbot, J. J., Shen, H., Yabuuchi, Y., Carsch, K. M., Jiang, H. Z. H., Furukawa, H., Long, J. R., & Head‐Gordon, M. (2024) · Physical Chemistry Chemical Physics · doi:10.1039/d3cp05540j · Cited by 24

Computational Ab Initio Approaches for Area-Selective Atomic Layer Deposition: Methods, Status, and Perspectives

Pieck, F., & Tonner, R. (2025) · Chemistry of Materials · doi:10.1021/acs.chemmater.4c03477 · Cited by 24

Revisiting a large and diverse data set for barrier heights and reaction energies: best practices in density functional theory calculations for chemical kinetics

Liu, X., Spiekermann, K., Menon, A., Green, W. H., & Head‐Gordon, M. (2025) · Physical Chemistry Chemical Physics · doi:10.1039/d5cp01181g · Cited by 25

Assessment of a set of twelve density functionals to estimate the global reactivity of myricetin through the Koopmans’ theorem

Sandoval-Yáñez, C., & Martínez‐Araya, J. I. (2018) · Chemical Physics Letters · doi:10.1016/j.cplett.2018.11.056 · Cited by 24

The Selective N‐Functionalization of Indoles via aza‐Michael Addition in the Ligand Sphere of a Chiral Nickel(II) Complex: Asymmetric Synthesis of (S)‐1H‐Indole‐Alanine Derivatives

Larionov, V. A., Savel’yeva, T. F., Medvedev, M. G., Stoletova, N. V., Smol’yakov, A. F., Gugkaeva, Z. T., Cruchter, T., & Maleev, V. I. (2019) · European Journal of Organic Chemistry · doi:10.1002/ejoc.201900650 · Cited by 24

The reduced cohesion of homoconfigurational 1,2-diols

Hartwig, B., Lange, M., Poblotzki, A., Medel, R., Zehnacker, A., & Suhm, M. A. (2019) · Physical Chemistry Chemical Physics · doi:10.1039/c9cp04943f · Cited by 24

Reduction of 1,2,3-trichloropropane (TCP): pathways and mechanisms from computational chemistry calculations

Torralba–Sanchez, T. L., Bylaska, E. J., Salter‐Blanc, A. J., Meisenheimer, D. E., Lyon, M. A., & Tratnyek, P. G. (2020) · Environmental Science Processes & Impacts · doi:10.1039/c9em00557a · Cited by 24

Experimental and theoretical investigation of a copolymer combined with surfactant for preventing scale formation in oil wells

Fernandes, R. D. S., Beserra, N. L. R., de Souza, M. A. F., de Lima, D. F., de Castro, B. B., & Balaban, R. D. C. (2020) · Journal of Molecular Liquids · doi:10.1016/j.molliq.2020.114036 · Cited by 24

Molecular Modeling Reveals the Mechanism of Ran-RanGAP-Catalyzed Guanosine Triphosphate Hydrolysis without an Arginine Finger

Khrenova, M. G., Grigorenko, B. L., & Nemukhin, A. V. (2021) · ACS Catalysis · doi:10.1021/acscatal.1c00582 · Cited by 24

Understanding the Reactivity and Decomposition of a Highly Active Iron Pincer Catalyst for Hydrogenation and Dehydrogenation Reactions

Curley, J. B., Smith, N. E., Bernskoetter, W. H., Ertem, M. Z., Hazari, N., Mercado, B. Q., Townsend, T. M., & Wang, X. P. (2021) · ACS Catalysis · doi:10.1021/acscatal.1c03347 · Cited by 24

Pure and Hybrid SCAN, rSCAN, and r2SCAN: Which One Is Preferred in KS- and HF-DFT Calculations, and How Does D4 Dispersion Correction Affect This Ranking?

Santra, G., & Martin, J. M. L. (2021) · Molecules · doi:10.3390/molecules27010141 · Cited by 24

Self-Consistent Implementation of Kohn–Sham Adiabatic Connection Models with Improved Treatment of the Strong-Interaction Limit

Śmiga, S., Sala, F. D., Gori‐Giorgi, P., & Fabiano, E. S. (2022) · Journal of Chemical Theory and Computation · doi:10.1021/acs.jctc.2c00352 · Cited by 24

Generalization of ETS-NOCV and ALMO-COVP Energy Decomposition Analysis to Connect Any Two Electronic States and Comparative Assessment

Shen, H., Wang, Z., & Head‐Gordon, M. (2022) · Journal of Chemical Theory and Computation · doi:10.1021/acs.jctc.2c00901 · Cited by 24

Toward routine Kohn–Sham inversion using the “Lieb-response” approach

Gould, T. (2023) · The Journal of Chemical Physics · doi:10.1063/5.0134330 · Cited by 24

Synergism of mixed cationic collectors in the flotation of quartz unveiled by AFM, solution chemistry and quantum chemical calculations

Monte, M. B. D. M., Pimentel, D. A., de Albuquerque, M. D. D. F., Neumann, R., Silva, L. A., Correia, J. C. G., & Uliana, A. (2023) · Journal of Molecular Liquids · doi:10.1016/j.molliq.2023.121397 · Cited by 24

On the potentially transformative role of auxiliary-field quantum Monte Carlo in quantum chemistry: A highly accurate method for transition metals and beyond

Shee, J., Weber, J. L., Reichman, D. R., Friesner, R. A., & Zhang, S. (2023) · The Journal of Chemical Physics · doi:10.1063/5.0134009 · Cited by 27

Improved Description of Intra- and Intermolecular Interactions through Dispersion-Corrected Second-Order Møller–Plesset Perturbation Theory

Beran, G. J. O., Greenwell, C., Cook, C. J., & Řezáč, J. (2023) · Accounts of Chemical Research · doi:10.1021/acs.accounts.3c00578 · Cited by 24

Noncovalently bound excited-state dimers: a perspective on current time-dependent density functional theory approaches applied to aromatic excimer models

Hancock, A. C., & Goerigk, L. (2023) · RSC Advances · doi:10.1039/d3ra07381e · Cited by 24

Nonlocal machine-learned exchange functional for molecules and solids

Bystrom, K., & Kozinsky, B. (2024) · Physical review. B./Physical review. B · doi:10.1103/physrevb.110.075130 · Cited by 33

Small Basis Set Allowing the Recovery of Dispersion Interactions with Double-Hybrid Functionals

Garcı́a, J. S., Brémond, É. A. G., Campetella, M., Ciofini, I., & Adamo, C. (2019) · Journal of Chemical Theory and Computation · doi:10.1021/acs.jctc.8b01203 · Cited by 24

Expansion of bond dissociation prediction with machine learning to medicinally and environmentally relevant chemical space

V., S. S. S., Kim, Y., Kim, S., John, P. C. S., & Paton, R. S. (2023) · Digital Discovery · doi:10.1039/d3dd00169e · Cited by 23

Delocalization error poisons the density-functional many-body expansion

Broderick, D. R., & Herbert, J. M. (2024) · Chemical Science · doi:10.1039/d4sc05955g · Cited by 23

Interactions of nanoparticles with living and synthetic bio-membranes

Kariuki, R., Mirihana, K. A., Penman, R., Hung, A., Meftahi, N., Bryant, G., Ramsland, P. A., Voı̈tchovsky, K., Conn, C. E., Contini, C., et al. (2025) · Chemical Society Reviews · doi:10.1039/d5cs00841g · Cited by 23

Kinetics and Thermodynamics of Reactions Involving Criegee Intermediates: An Assessment of Density Functional Theory and Ab Initio Methods Through Comparison with CCSDT(Q)/CBS Data

Smith, C. D., & Karton, A. (2019) · Journal of Computational Chemistry · doi:10.1002/jcc.26106 · Cited by 23

Enabling Large-Scale Condensed-Phase Hybrid Density Functional Theory-Based Ab Initio Molecular Dynamics II: Extensions to the Isobaric–Isoenthalpic and Isobaric–Isothermal Ensembles

Ko, H.-Y., Santra, B., & DiStasio, R. A. (2021) · Journal of Chemical Theory and Computation · doi:10.1021/acs.jctc.0c01194 · Cited by 23

Performance of Made Simple Meta-GGA Functionals with rVV10 Nonlocal Correlation for H 2 + Cu(111), D 2 + Ag(111), H 2 + Au(111), and D 2 + Pt(111)

Smeets, E. W. F., & Kroes, G. (2021) · The Journal of Physical Chemistry C · doi:10.1021/acs.jpcc.0c11034 · Cited by 23

Kinetic Modeling of API Oxidation: (2) Imipramine Stress Testing

Wu, H., Dana, A. G., Ranasinghe, D. S., Pickard, F. C., Wood, G. P. F., Zelesky, T. C., Sluggett, G. W., Mustakis, J. G., & Green, W. H. (2022) · Molecular Pharmaceutics · doi:10.1021/acs.molpharmaceut.2c00043 · Cited by 24

On Aromaticity of the Aromatic α-Amino Acids and Tuning of the NICS Indices to Find the Aromaticity Order

Dudek, W. M., Ostrowski, S., & Dobrowolski, J. C. (2022) · The Journal of Physical Chemistry A · doi:10.1021/acs.jpca.2c00346 · Cited by 23

First Example of Fluorinated Phenanthroline Diamides: Synthesis, Structural Study, and Complexation with Lanthanoids

Avagyan, N. A., Lemport, P. S., Lysenko, K. A., Gudovannyy, A. O., Roznyatovsky, V. A., Petrov, V. S., Vokuev, M. F., Ustynyuk, Y. A., & Nenajdenko, V. G. (2022) · Molecules · doi:10.3390/molecules27154705 · Cited by 23

A double-hybrid density functional based on good local physics with outstanding performance on the GMTKN55 database

Becke, A. D., Santra, G., & Martin, J. M. L. (2023) · The Journal of Chemical Physics · doi:10.1063/5.0141238 · Cited by 23

Optimal Small Basis Set and Geometric Counterpoise Correction for DFT Computations

Chan, B. (2023) · Journal of Chemical Theory and Computation · doi:10.1021/acs.jctc.3c00298 · Cited by 23

Range-Separated Local Hybrid Functionals with Small Fractional-Charge and Fractional-Spin Errors: Escaping the Zero-Sum Game of DFT Functionals

Fürst, S., Kaupp, M., & Wodyński, A. (2023) · Journal of Chemical Theory and Computation · doi:10.1021/acs.jctc.3c00877 · Cited by 23

Harmonic and anharmonic vibrational computations for biomolecular building blocks: Benchmarking DFT and basis sets by theoretical and experimental IR spectrum of glycine conformers

Xu, R., Jiang, Z., Yang, Q., Bloino, J., & Biczysko, M. (2024) · Journal of Computational Chemistry · doi:10.1002/jcc.27377 · Cited by 23

Hierarchy of exchange-correlation functionals in computing lattice thermal conductivities of rocksalt and zinc-blende semiconductors

Wei, J., Xia, Z., Xia, Y., & He, J. (2024) · Physical review. B./Physical review. B · doi:10.1103/physrevb.110.035205 · Cited by 23

Faster Quantum Chemistry Simulations on a Quantum Computer with Improved Tensor Factorization and Active Volume Compilation

Caesura, A., Cortes, C. L., Pol, W., Sim, S., Steudtner, M., Anselmetti, G.-L., Degroote, M., Moll, N., Santagati, R., Streif, M., et al. (2025) · PRX Quantum · doi:10.1103/yngp-5fpm · Cited by 47

Rational Density Functional Selection Using Game Theory

McAnanama-Brereton, S. R., & Waller, M. P. (2017) · Journal of Chemical Information and Modeling · doi:10.1021/acs.jcim.7b00542 · Cited by 23

Operando computational catalysis: shape, structure, and coverage under reaction conditions

Vrieze, J. E. D., Gunasooriya, G. T. K. K., Thybaut, J. W., & Saeys, M. (2019) · Current Opinion in Chemical Engineering · doi:10.1016/j.coche.2019.03.003 · Cited by 23

Neural network interpolation of exchange-correlation functional

Ryabov, A. A., Akhatov, I., & Zhilyaev, P. A. (2020) · Scientific Reports · doi:10.1038/s41598-020-64619-8 · Cited by 23

Double hybrid DFT calculations with Slater type orbitals

Förster, A., & Visscher, L. (2020) · Journal of Computational Chemistry · doi:10.1002/jcc.26209 · Cited by 23

Theoretical investigation of benzo(a)pyrene formation

Reizer, E., Csizmadia, I. G., Nehéz, K., Viskolcz, B., & Fiser, B. (2021) · Chemical Physics Letters · doi:10.1016/j.cplett.2021.138564 · Cited by 23

A benchmark dataset for Hydrogen Combustion

Guan, X., Das, A. K., Stein, C. J., Heidar‐Zadeh, F., Bertels, L. W., Liu, M., Haghighatlari, M., Li, J., Zhang, O., Hao, H., et al. (2022) · Scientific Data · doi:10.1038/s41597-022-01330-5 · Cited by 23

Extending quantum-mechanical benchmark accuracy to biological ligand-pocket interactions

Puleva, M., Sandonas, L. R. M., Lőrincz, B. D., Charry, J. A., Rogers, D. O. W., Nagy, P. R., & Tkatchenko, A. (2025) · Nature Communications · doi:10.1038/s41467-025-63587-9 · Cited by 22

Machine learning interatomic potentials at the centennial crossroads of quantum mechanics

Kalita, B., Gökcan, H., & Isayev, O. (2025) · Nature Computational Science · doi:10.1038/s43588-025-00930-6 · Cited by 32

Self-trapped holes (small polarons) in ferroelectric KH 2 PO 4 crystals

Dodson, T. E. R., Halliburton, L. E., Kedziora, G. S., Lenyk, C. A., & Giles, N. C. (2019) · Journal of Physics Condensed Matter · doi:10.1088/1361-648x/ab3fe9 · Cited by 22

Too big, too small, or just right? A benchmark assessment of density functional theory for predicting the spatial extent of the electron density of small chemical systems

Hait, D., Liang, Y. H., & Head‐Gordon, M. (2021) · The Journal of Chemical Physics · doi:10.1063/5.0038694 · Cited by 22

Study of the structural and optoelectronic properties of dye solar cells based on phosphonic acid anchoring by DFT functionals

Fadili, D., Bouzzine, S. M., & Hamidi, M. (2020) · New Journal of Chemistry · doi:10.1039/d0nj03971c · Cited by 22

Assessing the Role of Site Isolation and Compartmentalization in Packed-Bed Flow Reactors for Processes Involving Wolf-and-Lamb Scenarios

Borah, P., Fianchini, M., & Pericàs, M. À. (2021) · ACS Catalysis · doi:10.1021/acscatal.1c00889 · Cited by 23

Benchmark calculations for bond dissociation energies and enthalpy of formation of chlorinated and brominated polycyclic aromatic hydrocarbons

Xu, S., Wang, Q., Sun, M.-M., Yin, G., & Liang, J. (2021) · RSC Advances · doi:10.1039/d1ra05391d · Cited by 22

The Cost of Improving the Precision of the Variational Quantum Eigensolver for Quantum Chemistry

Miháliková, I., Pivoluska, M., Plesch, M., Friák, M., Nagaj, D., & Šob, M. (2022) · Nanomaterials · doi:10.3390/nano12020243 · Cited by 25

A DFT investigation of the host–guest interactions between boron-based aromatic systems and β-cyclodextrin

Rahali, S., Belhocine, Y., Allal, H., Bouhadiba, A., Assaba, I. M., & Seydou, M. (2021) · Structural Chemistry · doi:10.1007/s11224-021-01835-6 · Cited by 22

Computational Investigation of the Monomer Ratio and Solvent Environment for the Complex Formed between Sulfamethoxazole and Functional Monomer Methacrylic Acid

Ektirici, S., Kurç, Ö., Jalilzadeh, M., Aşır, S., & Türkmen, D. (2022) · ACS Omega · doi:10.1021/acsomega.2c00862 · Cited by 22

Assessing the stability of Pd-exchanged sites in zeolites with the aid of a high throughput quantum chemistry workflow

Aljama, H. A., Head‐Gordon, M., & Bell, A. T. (2022) · Nature Communications · doi:10.1038/s41467-022-29505-z · Cited by 24

Efficient Integral-Direct Methods for Self-Consistent Reduced Density Matrix Functional Theory Calculations on Central and Graphics Processing Units

Lemke, Y., Kußmann, J., & Ochsenfeld, C. (2022) · Journal of Chemical Theory and Computation · doi:10.1021/acs.jctc.2c00231 · Cited by 22

Efficient periodic resolution-of-the-identity Hartree–Fock exchange method withk-point sampling and Gaussian basis sets

Bussy, A., & Hutter, J. (2024) · The Journal of Chemical Physics · doi:10.1063/5.0189659 · Cited by 22

In Situ Graft-on Fibrous Composites and Nanostructure Interlocking Facilitate Highly Stable Wearable Sensors for SIDS Prevention

Chen, K., Wang, W., Ye, Z., Dong, Y., Wan, L., Zhang, Z., Lin, C. T., Liu, L., Leng, J., Wang, X., et al. (2024) · Advanced Fiber Materials · doi:10.1007/s42765-024-00382-z · Cited by 22

Curcuma Longa-Based Green and Sustainable Antioxidants for Biopolymers

Sattar, M. A. (2024) · ACS Sustainable Chemistry & Engineering · doi:10.1021/acssuschemeng.3c07597 · Cited by 22

Density functional theory for van der Waals complexes: Size matters

Gray, M., & Herbert, J. M. (2024) · Annual reports in computational chemistry · doi:10.1016/bs.arcc.2024.03.001 · Cited by 22

vdW‐TSSCDS—An automated and global procedure for the computation of stationary points on intermolecular potential energy surfaces

Kopec, S., Martı́nez-Núñez, E., Soto, J., & Peláez, D. (2019) · International Journal of Quantum Chemistry · doi:10.1002/qua.26008 · Cited by 22

Effect of Basicity and Structure on the Hydration of Protonated Molecules, Proton-Bound Dimer and Cluster Formation: An Ion Mobility-Time of Flight Mass Spectrometry and Theoretical Study

Valadbeigi, Y., Ilbeigi, V., Michalczuk, B., Sabo, M., & Matejčík, Š. (2019) · Journal of the American Society for Mass Spectrometry · doi:10.1007/s13361-019-02180-z · Cited by 22

Kinetic Correlation Functionals from the Entropic Regularization of the Strictly Correlated Electrons Problem

Gerolin, A., Grossi, J., & Gori‐Giorgi, P. (2019) · Journal of Chemical Theory and Computation · doi:10.1021/acs.jctc.9b01133 · Cited by 22

The Production and Potential Detection of Hexamethylenetetramine-Methanol in Space

Materese, C. K., Nuevo, M., Sandford, S. A., Bera, P. P., & Lee, T. J. (2020) · Astrobiology · doi:10.1089/ast.2019.2147 · Cited by 22

Negative Charge Management to Make Fragile Bonds Less Fragile toward Electrons for Robust Organic Optoelectronic Materials

Wang, R., Meng, Q., Wang, Y., & Qiao, J. (2021) · CCS Chemistry · doi:10.31635/ccschem.021.202100778 · Cited by 22

Exploring Avenues beyond Revised DSD Functionals: II. Random-Phase Approximation and Scaled MP3 Corrections

Santra, G., Semidalas, E. C., & Martin, J. M. L. (2021) · The Journal of Physical Chemistry A · doi:10.1021/acs.jpca.1c01295 · Cited by 22

Fragmentation study of tryptophan-derived metabolites induced by electrospray ionization mass spectrometry for highly sensitive analysis

Asakawa, D., Mizuno, H., Sugiyama, E., & Todoroki, K. (2021) · The Analyst · doi:10.1039/d0an02069a · Cited by 22

Handling Ensemble N-Representability Constraint in Explicit-by-Implicit Manner

Yao, Y., Fang, W., & Su, N. Q. (2021) · The Journal of Physical Chemistry Letters · doi:10.1021/acs.jpclett.1c01835 · Cited by 22

Range‐separated multiconfigurational density functional theory methods

Pernal, K., & Hapka, M. (2021) · Wiley Interdisciplinary Reviews Computational Molecular Science · doi:10.1002/wcms.1566 · Cited by 22

In situ Bi/carboxyphenyl-modified glassy carbon electrode as a sensor platform for detection of Cd2+ and Pb2+ using square wave anodic stripping voltammetry.

Phal, S., Nguyen, H. T., Бериша, А., & Tesfalidet, S. (2021) · Sensing and Bio-Sensing Research · doi:10.1016/j.sbsr.2021.100455 · Cited by 22

Comparison of the Performance of Density Functional Methods for the Description of Spin States and Binding Energies of Porphyrins

Morgante, P., & Peverati, R. (2023) · Molecules · doi:10.3390/molecules28083487 · Cited by 22

The 125Te Chemical Shift of Diphenyl Ditelluride: Chasing Conformers over a Flat Energy Surface

Bortoli, M., Tiezza, M. D., Muraro, C., Saielli, G., & Orian, L. (2019) · Molecules · doi:10.3390/molecules24071250 · Cited by 21

BODIPY dimers: structure, interaction, and absorption spectrum

Rybczyński, P., & Kaczmarek‐Kędziera, A. (2021) · Structural Chemistry · doi:10.1007/s11224-021-01759-1 · Cited by 21

Open-Shell Variant of the London Dispersion-Corrected Hartree–Fock Method (HFLD) for the Quantification and Analysis of Noncovalent Interaction Energies

Altun, A., Neese, F., & Bistoni, G. (2022) · Journal of Chemical Theory and Computation · doi:10.1021/acs.jctc.1c01295 · Cited by 21

Small-Basis Set Density-Functional Theory Methods Corrected with Atom-Centered Potentials

Prasad, V. K., Otero‐de‐la‐Roza, A., & DiLabio, G. A. (2022) · Journal of Chemical Theory and Computation · doi:10.1021/acs.jctc.2c00036 · Cited by 21

Density functional theory modeling of critical properties of perovskite oxides for water splitting applications

Ghose, K. K., Brown, J. J., Frankcombe, T. J., Page, A. J., & Bayón, A. (2023) · Wiley Interdisciplinary Reviews Energy and Environment · doi:10.1002/wene.476 · Cited by 22

GradDFT. A software library for machine learning enhanced density functional theory

Casares, P. A. M., Baker, J. S., Medvidović, M., dos Reis, R., & Arrazola, J. M. (2024) · The Journal of Chemical Physics · doi:10.1063/5.0181037 · Cited by 25

Computational Design of Ligands for the Ir-Catalyzed C5-Borylation of Indoles through Tuning Dispersion Interactions

Zheng, T., Ma, J., Chen, H., Jiang, H., Lu, S., Shi, Z., Liu, F., Houk, K. N., & Liang, Y. F. (2024) · Journal of the American Chemical Society · doi:10.1021/jacs.4c08027 · Cited by 21

A General and Transferable Local Hybrid Functional for Electronic Structure Theory and Many-Fermion Approaches

Holzer, C., & Franzke, Y. J. (2024) · Journal of Chemical Theory and Computation · doi:10.1021/acs.jctc.4c01309 · Cited by 21

A Systematic Protocol for Benchmarking Guest–Host Interactions by First‐Principles Computations: Capturing CO2 in Clathrate Hydrates

Arismendi‐Arrieta, D. J., Valdés, Á., & Prosmiti, R. (2018) · Chemistry - A European Journal · doi:10.1002/chem.201800497 · Cited by 21

Efficiently Capturing Weak Interactions in ab Initio Molecular Dynamics with on-the-Fly Basis Set Extrapolation

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