Electronic coupling for charge transfer in donor–bridge–acceptor systems. Performance of the two-state FCD model

Voityuk, Alexander A.

doi:10.1039/c2cp40579b

Cited by 51 publications

(56 citation statements)

References 33 publications

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“…For example, this choice is invoked by several works in the literature. 86,[90][91][92] Others, 44 have favored the choice E = E D , which is non-symmetric (i.e. forward CT become not equivalent to backward CT), however, it is still a valid choice.…”

Section: Theory Of Effective Donor-bridge-acceptor Couplingsmentioning

confidence: 99%

Quantifying Environmental Effects on the Decay of Hole Transfer Couplings in Biosystems

Ramos

Pavanello

2014

J. Chem. Theory Comput.

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In the past two decades, many research groups worldwide have tried to understand and categorize simple regimes in the charge transfer of such biological systems as DNA. Theoretically speaking, the lack of exact theories for electron-nuclear dynamics on one side, and poor quality of the parameters needed by model Hamiltonians and nonadiabatic dynamics alike (such as couplings and site energies) on the other, are the two main difficulties for an appropriate description of the charge transfer phenomena. In this work, we present an application of a previously benchmarked and linear-scaling subsystem DFT method for the calculation of couplings, site energies and superexchange decay factors (β ) of several biological donor-acceptor dyads, as well as double stranded DNA oligomers comprised of up to 5 base pairs. The calculations are all-electron, and provide a clear view of the role of the environment on superexchange couplings in DNA -they follow experimental trends and confirm previous semiempirical calculations. The subsystem DFT method is proven to be an excellent tool for long-range, bridge-mediated coupling and site energy calculations of embedded molecular systems.

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Section: Theory Of Effective Donor-bridge-acceptor Couplingsmentioning

confidence: 99%

Quantifying Environmental Effects on the Decay of Hole Transfer Couplings in Biosystems

Ramos

Pavanello

2014

J. Chem. Theory Comput.

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“…Although the two-state model is not exact anymore, in many cases it provides reasonable values of electronic couplings. 13,21,22 Several relationships, μ A 2 + μ B 2 = M i 2 + M j 2 , f A + f B = F i + F j , or eq 11, may be used to check whether the contributions of other diabatic states to the adiabatic states of interest is small enough and whether the twostate approximation is still applicable. The model should work well if the ratio R, e.g.,…”

Section: ■ Methodsmentioning

confidence: 99%

Estimation of Electronic Coupling for Singlet Excitation Energy Transfer

Voityuk

2014

J. Phys. Chem. C

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Electronic coupling is a key parameter that controls the efficiency of excitation energy transfer (EET) and exciton delocalization. A new approach to estimate electronic coupling is introduced. Within a two-state model, the EET coupling V of two chromophores is expressed via the vertical excitation energies (E i and E j ), transition dipole moments (M i and M j ) of the system and transition moments (μ A and μ B ) of the individual chromophores:}. These quantities are directly available from quantum mechanical calculations. As the estimated coupling accounts for both short-range and long-range interactions, this approach allows for the treatment of systems with short intermolecular distances, in particular, π-stacked chromophores. For a system of two identical chromophores, the coupling is given bywhere F i and F j are the corresponding oscillator strengths and cos θ is determined by the relative position of the chromophores in the dimer. Thus, the coupling can be derived from purely experimental data. The developed approach is used to calculate the EET coupling and exciton delocalization in two π-stacks of pyrimidine nucleobases 5′-TT-3′ and 5′-CT-3′ showing quite different EET properties. ■ INTRODUCTIONTheoretical and computational methods have been successfully applied to study excitation energy transfer (EET) in various molecular systems. Recent developments in this field were considered in detail in several reviews. 1−4 The efficiency of EET between two chromophores A and B, A*−B → A−B*, is controlled by electronic coupling of two diabatic states φ A and φ B . In the reference states, the exciton is localized on the corresponding molecules. Commonly, φ A and φ B are defined as excited states of the separated chromophores. The electronic coupling of the reference excited states is a key parameter that controls delocalization of excited states and the probability of energy transfer between the chromophores. 1−4The coupling of singlet excited states V includes both a shortrange term, which depends on the orbital overlap between the excited states, and a long-range Coulomb contribution. The Coulomb coupling of two molecules A and B can be estimated as the interaction of their transition dipole moments μ A and μ Bwhere R AB is the intermolecular distance. This widely used dipole−dipole scheme suggested by Forster 60 year ago 5 provides good estimates when the spatial extension of the transition densities in the molecules is much smaller than the distance R AB . More accurate values can be computed using transition atomic charges 6In eq 2, i runs over all atoms of the molecule A, and j runs over all atoms of B; q i and q j are transition charges derived from quantum mechanical (QM) calculations of excited states φ A and φ B of the individual molecules. At large distances between the chromophores, V dd ≈ V tc . Both eq 1 and eq 2 account only for the long-range interaction of the excited states, whereas the orbital and exchange terms are neglected. The performance of the transition charge (TC) model was discussed...

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“…Fernández-Fueyo et al using PELE [56] and electronic couplings calculations by the fragment charge difference (FCD) approach [80], provided computational information for the ABTS oxidation at the heme-propionate channel and the relation between the C-tail length and the MnPs catalytic properties. Since only small differences exist between long and extralong MnPs, there was no representative for the long MnP subfamily.…”

Section: Manganese Peroxidasementioning

confidence: 99%

Computational Modeling Methods for Understanding the Interaction of Lignin and Its Derivatives with Oxidoreductases as Biocatalysts

Alzate‐Morales¹,

Recabarren²,

Fuenzalida-Valdivia³

et al. 2018

Lignin - Trends and Applications

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This chapter will be presented as follow. First, a brief introduction to structure and characterization of lignin and its derivatives is presented, as well as their importance as chemical scaffolds for obtaining value-added products in chemical, food, pharmaceutical and agriculture industry. Second, an extensive review of different reports using computational modeling methods-like molecular dynamics simulations, quantum mechanics and hybrid calculation methods, among others-in the understanding of enzyme-substrate interaction and biocatalysis will be presented. Third, and as last part of chapter, some hand picked examples from literature will be chosen as successful cases where the interplay between experiment and computation has given as a result protein engineered oxidoreductases with improved catalytic capabilities.

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Electronic coupling for charge transfer in donor–bridge–acceptor systems. Performance of the two-state FCD model

Cited by 51 publications

References 33 publications

Quantifying Environmental Effects on the Decay of Hole Transfer Couplings in Biosystems

Quantifying Environmental Effects on the Decay of Hole Transfer Couplings in Biosystems

Estimation of Electronic Coupling for Singlet Excitation Energy Transfer

Computational Modeling Methods for Understanding the Interaction of Lignin and Its Derivatives with Oxidoreductases as Biocatalysts

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