Computational study of adsorption of cobalt on benzene and coronene

Stella, Martina; Bennie, Simon J.; Manby, Frederick R.

doi:10.1080/00268976.2015.1018359

Cited by 15 publications

(23 citation statements)

References 72 publications

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“…236,237 However, the correct description of magnetocrystalline anisotropy requires usage of hybrid functionals 238,239 and the inclusion of spin--orbit coupling. 233 The nature of the metal--graphene interaction may be anywhere between non--covalent and partially covalent, [240][241][242] indicating that any computational method used to study these interactions must reliably describe both London dispersive forces and chemical bonding. 243,244 For catalytic applications involving bond--breaking and bond formation, it is also necessary to use methods that do not suffer from the electron self--interaction error, which leads to underestimation of reaction barriers.…”

Section: Graphene and Metalsmentioning

confidence: 99%

Modelling of graphene functionalization

Pykal

Jurečka

Karlický

et al. 2016

Phys. Chem. Chem. Phys.

205

121

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Graphene has attracted great interest because of its remarkable properties and numerous potential applications. A comprehensive understanding of its structural and dynamic properties and those of its derivatives will be required to enable the design and optimization of sophisticated new nanodevices. While it is challenging to perform experimental studies on nanoscale systems at the atomistic level, this is the 'native' scale of computational chemistry. Consequently, computational methods are increasingly being used to complement experimental research in many areas of chemistry and nanotechnology. However, it is difficult for non-experts to get to grips with the plethora of computational tools that are available and their areas of application. This perspective briefly describes the available theoretical methods and models for simulating graphene functionalization based on quantum and classical mechanics. The benefits and drawbacks of the individual methods are discussed, and we provide numerous examples showing how computational methods have provided new insights into the physical and chemical features of complex systems including graphene and graphene derivatives. We believe that this overview will help non-expert readers to understand this field and its great potential.

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Section: Graphene and Metalsmentioning

confidence: 99%

Modelling of graphene functionalization

Pykal

Jurečka

Karlický

et al. 2016

Phys. Chem. Chem. Phys.

205

121

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“…The embedding of CC in DFT can overcome the limitations of commonly used density functionals, potentially removing the uncertainty the choice of functional and allowing for the calculation of chemical properties with high accuracy. 32,[34][35][36][37] Scheme 1. The Claisen rearrangement of chorismate to form prephenate, the reaction catalyzed by the enzyme chorismate mutase.…”

Section: Introductionmentioning

confidence: 99%

Projector-Based Embedding Eliminates Density Functional Dependence for QM/MM Calculations of Reactions in Enzymes and Solution

Ranaghan

Shchepanovska

Bennie

et al. 2019

J. Chem. Inf. Model.

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Combined quantum mechanics/molecular mechanics (QM/MM) methods are increasingly widely utilized in studies of reactions in enzymes and other large systems. Here, we apply a range of QM/MM methods to investigate the Claisen rearrangement of chorismate to prephenate, in solution, and in the enzyme chorismate mutase. Using projector-based embedding in a QM/MM framework, we apply treatments up to the CCSD(T) level. We test a range of density functional QM/MM methods and QM region sizes. The results show that the calculated reaction energetics are significantly more sensitive to the choice of density functional than they are to the size of the QM region in these systems. Projector-based embedding of a wavefunction method in DFT reduced the 13 kcal/mol spread in barrier heights calculated at the DFT/MM level to a spread of just 0.3 kcal/mol, essentially eliminating dependence on the functional. Projector-based embedding of correlated ab initio methods provides a practical method for achieving high accuracy for energy profiles derived from DFT and DFT/MM calculations for reactions in condensed phases.well with the CI-NEB path and indicates that the reaction coordinate used here performs well for this reaction.Structures were taken from the corresponding solution or enzyme SCCDFTB/CHARMM22 MD stochastic boundary simulations (120 ps) of the model systems for use in adiabatic mapping calculations. For this, Jaguar 68 and Tinker 69 , linked by the interface program QoMMMa 70 , were used for QM and MM calculations, with electronic coupling between the two regions treated by including MM charges in the QM Hamiltonian.CHARMM27 Lennard-Jones parameters (for standard CHARMM27 atom types, see Table S1) were used to describe QM/MM van der Waals interactions. The QM region was treated at the hybrid density functional B3LYP/6-31G(d) level of theory, which gives a reasonably good description of the reaction. 12 The enzyme model consisted of 7077 atoms and the solution model contained 7218 atoms. The MM region comprised an approximate 25 Å radius sphere of protein and/or solvent, treated with the CHARMM27 forcefield. 71 The outer 5 Å in each case was fixed (3324 atoms fixed in the enzyme model and 3535 fixed in the solution model),with all other atoms free to move. As there is no evidence for large-scale conformational changes during the reaction, this approach should give a representative sample of reactive conformations in the enzyme. 49,51, 53,54 Each initial structure was fully optimized at the B3LYP/6-31G(d)/CHARMM27 QM/MM level, while restraining the reaction coordinate (r) to -0.5 Å with a harmonic force constant of 500 kcal/mol/Å 2 , to generate starting structures.Reaction pathways were generated by restrained optimizations in both directions along the reaction coordinate, towards the reactant and the product, in steps of 0.2 Å (0.1 Å around the TS), with both the MM and QM systems fully and consistently optimized at each step. Energy profiles were calculated from r = −2.2 Å to 2.2 Å, to identify the reactant and product mini...

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“…For these reasons, several other applications of projection-based WF-in-DFT em- bedding have also focused on transition-metal complexes. 57,58,70,74 Enzyme Catalysis…”

Section: Transition-metal Catalysismentioning

confidence: 99%

“…59 The approach is implemented in the widely used Molpro software package, 60 allowing straightforward application of projection-based WF-in-DFT embedding for quantum chemical studies. 58,65,[67][68][69][70][71][72][73][74][75][76][77][78][79][80] Looking forward, we anticipate continued refinement of the projection-based embedding methodology, as well as increasingly widespread application in diverse areas of chemistry, biology, and materials science.…”

Section: Outlook and Conclusionmentioning

confidence: 99%

Projection-Based Wavefunction-in-DFT Embedding

Lee¹,

Welborn

Manby³

et al. 2019

Acc. Chem. Res.

Self Cite

130

153

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Complex chemical systems present challenges to electronic structure theory, stemming from large system sizes, subtle interactions, coupled dynamical timescales, or electronically nonadiabatic effects. New methods are needed to perform reliable, rigorous, and affordable electronic structure calculations for simulating the properties and dynamics of such systems. This Account reviews projection-based quantum embedding for electronic structure. The method provides a simple, robust, and accurate approach for describing a small part of a chemical system at the level of a correlated wavefunction (WF) method while the remainder of the system is described at the level of density functional theory (DFT). We present the theoretical underpinnings of projection-based embedding, describe use of the method for combining wavefunction and density-functional theories, and discuss technical refinements that have improved the applicability and robustness of the method. Applications of projection-based WFin-DFT embedding are also reviewed, with particular focus on recent work on transition-metal catalysis, enzyme reactivity, and battery electrolyte decomposition. Looking forward, we anticipate continued refinement of the projectionbased embedding methodology, as well as increasingly widespread application in diverse areas of chemistry, biology, and materials science.

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Computational study of adsorption of cobalt on benzene and coronene

Cited by 15 publications

References 72 publications

Modelling of graphene functionalization

Modelling of graphene functionalization

Projector-Based Embedding Eliminates Density Functional Dependence for QM/MM Calculations of Reactions in Enzymes and Solution

Projection-Based Wavefunction-in-DFT Embedding

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