Skip to main content
Disciplines
Automotive Business IT + Informatics Construction + Real Estate Electrical Engineering + Electronics Energy + Sustainability Insurance + Risk Finance + Banking Management + Leadership Marketing + Sales Mechanical Engineering + Materials
Events
DE
EN
Books
Journals
Topic Page
Marketing
Start single access now
Access for companies
EXTENDED SEARCH
Log in
Top
Topics in Catalysis
Published in: Topics in Catalysis 1-4/2022

24-07-2021 | Original Paper

The Effect of Hartree-Fock Exchange on Scaling Relations and Reaction Energetics for C–H Activation Catalysts

Authors: Vyshnavi Vennelakanti, Aditya Nandy, Heather J. Kulik

Published in: Topics in Catalysis | Issue 1-4/2022

Log in

Activate our intelligent search to find suitable subject content or patents.

search-config
loading …

Abstract

High-throughput computational catalyst studies are typically carried out using density functional theory (DFT) with a single, approximate exchange-correlation functional. In open shell transition metal complexes (TMCs) that are promising for challenging reactions (e.g., C–H activation), the predictive power of DFT has been challenged, and properties are known to be strongly dependent on the admixture of Hartree-Fock (HF) exchange. We carry out a large-scale study of the effect of HF exchange on the predicted catalytic properties of over 1200 mid-row (i.e., Cr, Mn, Fe, Co) 3d TMCs for direct methane-to-methanol conversion. Reaction energy sensitivities across this set depend both on the catalytic rearrangement and ligand chemistry of the catalyst. These differences in sensitivities change both the absolute energetics predicted for a catalyst and its relative performance. Previous observations of the poor performance of global linear free energy relationships (LFERs) hold with both semi-local DFT widely employed in heterogeneous catalysis and hybrid DFT. Narrower metal/oxidation/spin-state specific LFERs perform better and are less sensitive to HF exchange than absolute reaction energetics, except in the case of some intermediate/high-spin states. Importantly, the interplay between spin-state dependent reaction energetics and exchange effects on spin-state ordering means that the choice of DFT functional strongly influences whether the minimum energy pathway is spin-conserved. Despite these caveats, LFERs involving catalysts that can be expected to have closed shell intermediates and low-spin ground states retain significant predictive power.
previous article Uncovering the Activity of Alkaline Earth Metal Hydrogenation Catalysis Through Molecular Volcano Plots
next article Automated Construction and Optimization Combined with Machine Learning to Generate Pt(II) Methane C–H Activation Transition States

Dont have a licence yet? Then find out more about our products and how to get one now:

Springer Professional "Wirtschaft+Technik"

Online-Abonnement

Mit Springer Professional "Wirtschaft+Technik" erhalten Sie Zugriff auf:

  • über 102.000 Bücher
  • über 537 Zeitschriften

aus folgenden Fachgebieten:

  • Automobil + Motoren
  • Bauwesen + Immobilien
  • Business IT + Informatik
  • Elektrotechnik + Elektronik
  • Energie + Nachhaltigkeit
  • Finance + Banking
  • Management + Führung
  • Marketing + Vertrieb
  • Maschinenbau + Werkstoffe
  • Versicherung + Risiko

Jetzt Wissensvorsprung sichern!

inform now

Springer Professional "Technik"

Online-Abonnement

Mit Springer Professional "Technik" erhalten Sie Zugriff auf:

  • über 67.000 Bücher
  • über 390 Zeitschriften

aus folgenden Fachgebieten:

  • Automobil + Motoren
  • Bauwesen + Immobilien
  • Business IT + Informatik
  • Elektrotechnik + Elektronik
  • Energie + Nachhaltigkeit
  • Maschinenbau + Werkstoffe




 

Jetzt Wissensvorsprung sichern!

inform now
Appendix
Available only for authorised users
Literature
1.
Spivey JJ, Krishna KS, Kumar CSSR, Dooley KM, Flake JC, Haber LH, Xu Y, Janik MJ, Sinnott SB, Cheng YT, Liang T, Sholl DS, Manz TA, Diebold U, Parkinson GS, Bruce DA, de Jongh P (2014) Synthesis, characterization, and computation of catalysts at the center for atomic-level catalyst design. J Phys Chem C 118(35):20043–20069CrossRef
2.
Sperger T, Sanhueza IA, Kalvet I, Schoenebeck F (2015) Computational studies of synthetically relevant homogeneous organometallic catalysis involving Ni, Pd, Ir, and Rh: an overview of commonly employed DFT methods and mechanistic insights. Chem Rev 115(17):9532–9586PubMedCrossRef
3.
Sperger T, Sanhueza IA, Schoenebeck F (2016) Computation and experiment: a powerful combination to understand and predict reactivities. Acc Chem Res 49(6):1311–1319PubMedCrossRef
4.
Medford AJ, Vojvodic A, Hummelshoj JS, Voss J, Abild-Pedersen F, Studt F, Bligaard T, Nilsson A, Norskov JK (2015) From the Sabatier principle to a predictive theory of transition-metal heterogeneous catalysis. J Catal 328:36–42CrossRef
5.
Cheng GJ, Zhang XH, Chung LW, Xu LP, Wu YD (2015) Computational organic chemistry: bridging theory and experiment in establishing the mechanisms of chemical reactions. J Am Chem Soc 137(5):1706–1725PubMedCrossRef
6.
Vogiatzis KD, Polynski MV, Kirkland JK, Townsend J, Hashemi A, Liu C, Pidko EA (2018) Computational approach to molecular catalysis by 3d transition metals: challenges and opportunities. Chem Rev 119(4):2453–2523PubMedPubMedCentralCrossRef
7.
Raugei S, DuBois DL, Rousseau R, Chen S, Ho M-H, Bullock RM, Dupuis M (2015) Toward molecular catalysts by computer. Acc Chem Res 48(2):248–255PubMedCrossRef
8.
Greeley J (2016) Theoretical heterogeneous catalysis: scaling relationships and computational catalyst design. Annu Rev Chem Biomol Eng 7:605–635PubMedCrossRef
9.
Nørskov JK, Bligaard T, Rossmeisl J, Christensen CH (2009) Towards the computational design of solid catalysts. Nat Chem 1(1):37–46PubMedCrossRef
10.
Foscato M, Jensen VR (2020) Automated in silico design of homogeneous catalysts. ACS Catal 10(3):2354–2377CrossRef
11.
Nandy A, Zhu J, Janet JP, Duan C, Getman RB, Kulik HJ (2019) Machine learning accelerates the discovery of design rules and exceptions in stable metal-oxo intermediate formation. ACS Catal 9:8243–8255CrossRef
12.
13.
Kim JY, Kulik HJ (2018) When is ligand pKa a good descriptor for catalyst energetics? In search of optimal CO2 hydration catalysts. J Phys Chem A 122(18):4579–4590PubMedCrossRef
14.
Gani TZH, Kulik HJ (2018) Understanding and breaking scaling relations in single-site catalysis: methane to methanol conversion by FeIV=O. ACS Catal 8:975–986CrossRef
15.
Cramer CJ, Truhlar DG (2009) Density functional theory for transition metals and transition metal chemistry. Phys Chem Chem Phys 11(46):10757–10816PubMedCrossRef
16.
Janet JP, Zhao Q, Ioannidis EI, Kulik HJ (2017) Density functional theory for modelling large molecular adsorbate-surface interactions: a mini-review and worked example. Mol Simul 43(5–6):327–345CrossRef
17.
Gaggioli CA, Stoneburner SJ, Cramer CJ, Gagliardi L (2019) Beyond density functional theory: the multiconfigurational approach to model heterogeneous catalysis. ACS Catal 9(9):8481–8502CrossRef
18.
Jimenez-Hoyos CA, Janesko BG, Scuseria GE (2009) Evaluation of range-separated hybrid and other density functional approaches on test sets relevant for transition metal-based homogeneous catalysts. J Phys Chem A 113(43):11742–11749PubMedCrossRef
19.
Zhao Q, Kulik HJ (2019) Stable surfaces that bind too tightly: can range-separated hybrids or DFT + U improve paradoxical descriptions of surface chemistry? J Phys Chem Lett 10(17):5090–5098PubMedPubMedCentralCrossRef
20.
Schimka L, Harl J, Stroppa A, Grüneis A, Marsman M, Mittendorfer F, Kresse G (2010) Accurate surface and adsorption energies from many-body perturbation theory. Nat Mater 9(9):741–744PubMedCrossRef
21.
Kulik HJ (2015) Perspective: treating electron over-delocalization with the DFT plus U method. J Chem Phys 142(24):240901
22.
Yu HS, Li SL, Truhlar DG (2016) Perspective: Kohn-Sham density functional theory descending a staircase. J Chem Phys 145(13):130901PubMedCrossRef
23.
Cohen AJ, Mori-Sanchez P, Yang W (2008) Fractional charge perspective on the band gap in density-functional theory. Phys Rev B 77(11):115123
24.
Perdew JP, Parr RG, Levy M, Balduz JL Jr (1982) Density-functional theory for fractional particle number - derivative discontinuities of the energy. Phys Rev Lett 49(23):1691–1694CrossRef
25.
Yang WT, Zhang YK, Ayers PW (2000) Degenerate ground states and a fractional number of electrons in density and reduced density matrix functional theory. Phys Rev Lett 84(22):5172–5175PubMedCrossRef
26.
Cohen AJ, Mori-Sanchez P, Yang W (2008) Insights into current limitations of density functional theory. Science 321(5890):792–794PubMedCrossRef
27.
Janesko BG, Proynov E, Kong J, Scalmani G, Frisch MJ (2017) Practical density functionals beyond the overdelocalization–underbinding zero-sum game. J Phys Chem Lett 8(17):4314–4318PubMedCrossRef
28.
Johnson BG, Gonzales CA, Gill PMW, Pople JA (1994) A density-functional study of the simplest hydrogen abstraction reaction - effect of self-interaction correction. Chem Phys Lett 221(1–2):100–108CrossRef
29.
Ruzsinszky A, Perdew JP, Csonka GI, Vydrov OA, Scuseria GE (2006) Spurious fractional charge on dissociated atoms: pervasive and resilient self-interaction error of common density functionals. J Chem Phys 125(19):194112PubMedCrossRef
30.
Ruzsinszky A, Perdew JP, Csonka GI, Vydrov OA, Scuseria GE (2007) Density functionals that are one- and two- are not always many-electron self-interaction-free, as shown for H-2(+), He-2(+), LiH+, and Ne-2(+). J Chem Phys 126(10):104102PubMedCrossRef
31.
Dutoi AD, Head-Gordon M (2006) Self-interaction error of local density functionals for alkali-halide dissociation. Chem Phys Lett 422(1–3):230–233CrossRef
32.
Bally T, Sastry GN (1997) Incorrect dissociation behavior of radical ions in density functional calculations. J Phys Chem A 101(43):7923–7925CrossRef
33.
Zhang Y, Yang W (1998) A challenge for density functionals: self-interaction error increases for systems with a non integer number of electrons. J Chem Phys 109(7):2604–2608CrossRef
34.
Wilbraham L, Verma P, Truhlar DG, Gagliardi L, Ciofini I (2017) Multiconfiguration pair-density functional theory predicts spin state ordering in iron complexes with the same accuracy as complete active space second-order perturbation theory at a significantly reduced computational cost. J Phys Chem Lett 8(9):2026–2030PubMedCrossRef
35.
Ioannidis EI, Kulik HJ (2017) Ligand-field-dependent behavior of meta-GGA exchange in transition-metal complex spin-state ordering. J Phys Chem A 121(4):874–884PubMedCrossRef
36.
Ioannidis EI, Kulik HJ (2015) Towards quantifying the role of exact exchange in predictions of transition metal complex properties. J Chem Phys 143(3):034104
37.
Mortensen SR, Kepp KP (2015) Spin propensities of octahedral complexes from density functional theory. J Phys Chem A 119(17):4041–4050PubMedCrossRef
38.
Droghetti A, Alfe D, Sanvito S (2012) Assessment of density functional theory for iron(II) molecules across the spin-crossover transition. J Chem Phys 137(12):124303
39.
Ganzenmuller G, Berkaine N, Fouqueau A, Casida ME, Reiher M (2005) Comparison of density functionals for differences between the high-(T-5(2 g)) and low-((1)A(1 g)) spin states of iron(II) compounds. IV. Results for the ferrous complexes [Fe(L)(‘NHS4’)]. J Chem Phys 122:23CrossRef
40.
Kulik HJ, Cococcioni M, Scherlis DA, Marzari N (2006) Density functional theory in transition-metal chemistry: a self-consistent Hubbard U approach. Phys Rev Lett 97(10):103001PubMedCrossRef
41.
Tozer DJ, De Proft F (2005) Computation of the hardness and the problem of negative electron affinities in density functional theory. J Phys Chem A 109(39):8923–8929PubMedCrossRef
42.
Teale AM, De Proft F, Tozer DJ (2008) Orbital energies and negative electron affinities from density functional theory: insight from the integer discontinuity. J Chem Phys 129(4):044110PubMedCrossRef
43.
Peach MJG, Teale AM, Helgaker T, Tozer DJ (2015) Fractional electron loss in approximate DFT and Hartree-Fock theory. J Chem Theory Comput 11(11):5262–5268PubMedCrossRef
44.
Mori-Sanchez P, Cohen AJ, Yang WT (2008) Localization and delocalization errors in density functional theory and implications for band-gap prediction. Phys Rev Lett 100:14CrossRef
45.
Mahler A, Janesko BG, Moncho S, Brothers EN (2018) When Hartree-Fock exchange admixture lowers DFT-predicted barrier heights: natural bond orbital analyses and implications for catalysis. J Chem Phys 148(24)
46.
47.
Reiher M, Salomon O, Hess BA (2001) Reparameterization of hybrid functionals based on energy differences of states of different multiplicity. Theor Chem Acc 107(1):48–55CrossRef
48.
Coskun D, Jerome SV, Friesner RA (2016) Evaluation of the performance of the B3LYP, PBE0, and M06 DFT functionals, and DBLOC-corrected versions, in the calculation of redox potentials and spin splittings for transition metal containing systems. J Chem Theory Comput 12(3):1121–1128PubMedCrossRef
49.
Haunschild R, Henderson TM, Jimenez-Hoyos CA, Scuseria GE (2010) Many-electron self-interaction and spin polarization errors in local hybrid density functionals. J Chem Phys 133(13):134116PubMedCrossRef
50.
Mori-Sanchez P, Cohen AJ, Yang WT (2006) Many-electron self-interaction error in approximate density functionals. J Chem Phys 125(20)
51.
Schmidt T, Kummel S (2016) One- and many-electron self-interaction error in local and global hybrid functionals. Phys Rev B 93(16)
52.
Kim MC, Sim E, Burke K (2013) Understanding and reducing errors in density functional calculations. Phys Rev Lett 111:7CrossRef
53.
Zheng X, Liu M, Johnson ER, Contreras-Garcia J, Yang W (2012) Delocalization error of density-functional approximations: a distinct manifestation in hydrogen molecular chains. J Chem Phys 137(21):214106PubMedCrossRef
54.
Simm GN, Reiher M (2016) Systematic error estimation for chemical reaction energies. J Chem Theory Comput 12(6):2762–2773PubMedCrossRef
55.
Sutton JE, Guo W, Katsoulakis MA, Vlachos DG (2016) Effects of correlated parameters and uncertainty in electronic-structure-based chemical kinetic modelling. Nat Chem 8(4):331–337PubMedCrossRef
56.
Walker E, Ammal SC, Terejanu GA, Heyden A (2016) Uncertainty quantification framework applied to the water–gas shift reaction over Pt-based catalysts. J Phys Chem C 120(19):10328–10339CrossRef
57.
Wellendorff J, Lundgaard KT, Mogelhoj A, Petzold V, Landis DD, Norskov JK, Bligaard T, Jacobsen KW (2012) Density functionals for surface science: exchange-correlation model development with Bayesian error estimation. Phys Rev B 85(23):235149CrossRef
58.
Medford AJ, Wellendorff J, Vojvodic A, Studt F, Abild-Pedersen F, Jacobsen KW, Bligaard T, Nørskov JK (2014) Assessing the reliability of calculated catalytic ammonia synthesis rates. Science 345(6193):197–200PubMedCrossRef
59.
Sumaria V, Krishnamurthy D, Viswanathan V (2018) Quantifying confidence in DFT predicted surface Pourbaix diagrams and associated reaction pathways for chlorine evolution. ACS Catal 8(10):9034–9042CrossRef
60.
Christensen R, Hansen HA, Vegge T (2015) Identifying systematic DFT errors in catalytic reactions. Catal Sci Technol 5(11):4946–4949CrossRef
61.
Wellendorff J, Silbaugh TL, Garcia-Pintos D, Norskov JK, Bligaard T, Studt F, Campbell CT (2015) A benchmark database for adsorption bond energies to transition metal surfaces and comparison to selected DFT functionals. Surf Sci 640:36–44CrossRef
62.
Houchins G, Viswanathan V (2017) Quantifying confidence in density functional theory predictions of magnetic ground states. Phys Rev B 96(13):134426CrossRef
63.
Gani TZH, Kulik HJ (2017) Unifying exchange sensitivity in transition metal spin-state ordering and catalysis through bond valence metrics. J Chem Theory Comput 13:5443–5457PubMedCrossRef
64.
65.
Janesko BG, Scuseria GE (2008) Hartree-Fock orbitals significantly improve the reaction barrier heights predicted by semi local density functionals. J Chem Phys 128(24):244112PubMedPubMedCentralCrossRef
66.
Gani TZH, Kulik HJ (2016) Where does the density localize? Convergent behavior for global hybrids, range separation, and DFT + U. J Chem Theory Comput 12:5931–5945PubMedCrossRef
67.
68.
69.
70.
71.
72.
Hammond C, Forde MM, Rahim A, Hasbi M, Thetford A, He Q, Jenkins RL, Dimitratos N, Lopez-Sanchez JA, Dummer NF (2012) Direct catalytic conversion of methane to methanol in an aqueous medium by using copper‐promoted Fe‐ZSM‐5. Angew Chem Int Ed 51(21):5129–5133CrossRef
73.
Jones C, Taube D, Ziatdinov VR, Periana RA, Nielsen RJ, Oxgaard J, Goddard WA (2004) Selective oxidation of methane to methanol catalyzed, with C-H activation, by homogeneous, cationic gold. Angew Chem Int Ed 116(35):4726–4729CrossRef
74.
Palkovits R, Antonietti M, Kuhn P, Thomas A, Schüth F (2009) Solid catalysts for the selective low-temperature oxidation of methane to methanol. Angew Chem Int Ed 48(37):6909–6912CrossRef
75.
76.
Balcells D, Moles P, Blakemore JD, Raynaud C, Brudvig GW, Crabtree RH, Eisenstein O (2009) Molecular recognition in Mn-catalyzed C–H oxidation. Reaction mechanism and origin of selectivity from a DFT perspective. Dalton Trans 30:5989–6000CrossRef
77.
78.
79.
Fajin JLC, Vines F, Cordeiro MNDS, Illas F, Gomes JRB (2016) Effect of the exchange-correlation potential on the transferability of Bronsted-Evans-Polanyi relationships in heterogeneous catalysis. J Chem Theory Comput 12(5):2121–2126PubMedCrossRef
80.
Curnan MT, Kitchin JR (2015) Investigating the energetic ordering of stable and metastable TiO2 polymorphs using DFT + U and hybrid functionals. J Phys Chem C 119(36):21060–21071CrossRef
81.
82.
83.
84.
Wodrich MD, Sawatlon B, Busch M, Corminboeuf C (2021) The genesis of molecular volcano plots. Acc Chem Res 54(5):1107–1117PubMedCrossRef
85.
Anand M, Rohr B, Statt MJ, Nørskov JK (2020) Scaling relationships and volcano plots in homogeneous catalysis. J Phys Chem Lett 11(20):8518–8526PubMedCrossRef
86.
Busch M, Wodrich MD, Corminboeuf C (2015) Linear scaling relationships and volcano plots in homogeneous catalysis–revisiting the Suzuki reaction. Chem Sci 6(12):6754–6761PubMedPubMedCentralCrossRef
87.
Andrikopoulos PC, Michel C, Chouzier S, Sautet P (2015) In silico screening of iron-oxo catalysts for CH bond cleavage. ACS Catal 5(4):2490–2499CrossRef
88.
89.
90.
Pérez-Ramírez J, López N (2019) Strategies to break linear scaling relationships. Nat Catal 2(11):971–976CrossRef
91.
Marshall-Roth T, Libretto NJ, Wrobel AT, Anderton KJ, Pegis ML, Ricke ND, Van Voorhis T, Miller JT, Surendranath Y (2020) A pyridinic Fe-N 4 macrocycle models the active sites in Fe/N-doped carbon electrocatalysts. Nat Commun 11(1):1–14CrossRef
92.
Liu F, Yang T, Yang J, Xu E, Bajaj A, Kulik HJ (2019) Bridging the homogeneous-heterogeneous divide: modeling spin and reactivity in single atom catalysis. Front Chem 7:219PubMedPubMedCentralCrossRef
93.
Xu H, Cheng D, Cao D, Zeng XC (2018) A universal principle for a rational design of single-atom electrocatalysts. Nat Catal 1(5):339–348CrossRef
94.
Sours T, Patel A, Nørskov J, Siahrostami S, Kulkarni A (2020) Circumventing scaling relations in oxygen electrochemistry using metal–organic frameworks. J Phys Chem Lett 11(23):10029–10036PubMedCrossRef
95.
Abram S-L, Monte-Perez I, Pfaff FF, Farquhar ER, Ray K (2014) Evidence of two-state reactivity in alkane hydroxylation by Lewis-acid bound copper-nitrene complexes. Chem Commun 50(69):9852–9854CrossRef
96.
Zhu B, Guan W, Yan L-K, Su Z-M (2016) Two-state reactivity mechanism of benzene C–C activation by trinuclear titanium hydride. J Am Chem Soc 138(35):11069–11072PubMedCrossRef
97.
Schwarz H (2017) Menage-a-trois: single-atom catalysis, mass spectrometry, and computational chemistry. Catal Sci Technol 7(19):4302–4314CrossRef
98.
Liu WG, Zhang LL, Liu X, Liu XY, Yang XF, Miao S, Wang WT, Wang AQ, Zhang T (2017) Discriminating catalytically active FeNx species of atomically dispersed Fe-N-C catalyst for selective oxidation of the C–H bond. J Am Chem Soc 139(31):10790–10798PubMedCrossRef
99.
100.
101.
102.
103.
Shaik S, Danovich D, Fiedler A, Schroder D, Schwarz H (1995) 2-State reactivity in organometallic gas-phase ion chemistry. Helv Chim Acta 78(6):1393–1407CrossRef
104.
Schroder D, Shaik S, Schwarz H (2000) Two-state reactivity as a new concept in organometallic chemistry. Acc Chem Res 33(3):139–145PubMedCrossRef
105.
106.
Ufimtsev IS, Martinez TJ (2009) Quantum chemistry on graphical processing units. 3. Analytical energy gradients, geometry optimization, and first principles molecular dynamics. J Chem Theory Comput 5(10):2619–2628PubMedCrossRef
107.
108.
109.
110.
Nandy A, Duan C, Janet JP, Gugler S, Kulik HJ (2018) Strategies and software for machine learning accelerated discovery in transition metal chemistry. Ind Eng Chem Res 57(42):13973–13986CrossRef
111.
Lee C, Yang W, Parr RG (1988) Development of the Colle-Salvetti correlation-energy formula into a functional of the electron density. Phys Rev B 37:785–789CrossRef
112.
Becke AD (1993) Density-functional thermochemistry. III. The role of exact exchange. J Chem Phys 98(7):5648–5652CrossRef
113.
Stephens PJ, Devlin FJ, Chabalowski CF, Frisch MJ (1994) Ab initio calculation of vibrational absorption and circular dichroism spectra using density functional force fields. J Phys Chem 98(45):11623–11627CrossRef
114.
Grimme S, Antony J, Ehrlich S, Krieg H (2010) A consistent and accurate ab initio parametrization of density functional dispersion correction (DFT-D) for the 94 elements H-Pu. J Chem Phys 132(15):154104PubMedCrossRef
115.
Becke AD, Johnson ER (2005) A density-functional model of the dispersion interaction. J Chem Phys 123(15):154101PubMedCrossRef
116.
117.
Hay PJ, Wadt WR (1985) Ab initio effective core potentials for molecular calculations. Potentials for the transition metal atoms Sc to Hg. J Chem Phys 82(1):270–283CrossRef
118.
Ditchfield R, Hehre WJ, Pople JA (1971) Self-consistent molecular-orbital methods.9. Extended Gaussian-type basis for molecular-orbital studies of organic molecules. J Chem Phys 54(2):724–728CrossRef
119.
Wang L-P, Song C (2016) Geometry optimization made simple with translation and rotation coordinates. J Chem Phys 144(21):214108PubMedCrossRef
120.
121.
122.
123.
Bowman DN, Jakubikova E (2012) Low-spin versus high-spin ground state in pseudo-octahedral iron complexes. Inorg Chem 51(11):6011–6019PubMedCrossRef
124.
Kepp KP (2016) Theoretical study of spin crossover in 30 iron complexes. Inorg Chem 55(6):2717–2727PubMedCrossRef
Metadata
Title
The Effect of Hartree-Fock Exchange on Scaling Relations and Reaction Energetics for C–H Activation Catalysts
Authors
Vyshnavi Vennelakanti
Aditya Nandy
Heather J. Kulik
Publication date
24-07-2021
Publisher
Springer US
Published in
Topics in Catalysis / Issue 1-4/2022
Print ISSN: 1022-5528
Electronic ISSN: 1572-9028
DOI
https://doi.org/10.1007/s11244-021-01482-5

Other articles of this Issue 1-4/2022

Topics in Catalysis 1-4/2022 Go to the issue

Original Paper

Effect of Lewis Acids on the Catalyst Activity for Alkene Metathesis, Z-/E- Selectivity and Stability of Tungsten Oxo Alkylidenes

Original Paper

The Role of Zeolite Framework in Zeolite Stability and Catalysis from Recent Atomic Simulation

Original Paper

Toward E-selective Olefin Metathesis: Computational Design and Experimental Realization of Ruthenium Thio-Indolate Catalysts

Original Paper

What Role Does the Electric Double Layer Play in Redox Reactions at Planar Electrostatically Charged Insulating Surfaces?

Original Paper

Optimizing Nitrogen Reduction Reaction on Nitrides: A Computational Study on Crystallographic Orientation

Original Paper

Achievements and Expectations in the Field of Computational Heterogeneous Catalysis in an Innovation Context

Premium Partners

    Image Credits