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    Accurate SPICE compatible CNT interconnect and CNTFET models for circuit design and simulation
    (Pergamon-Elsevier Science Ltd, 2013) Yamaçlı, Serhan; Avci, Mutlu
    SPICE compatible CNT interconnect and CNTFET models in Verilog-A hardware description language are presented in this paper. Metallic CNTs are shown to have current saturation characteristics above a threshold voltage and then modelled with piecewise linear functions. On the other hand, the CNTFET model developed utilizes the calculation of the self-consistent potential of the CNT channel depending on gate and drain voltages. Unlike the previous SPICE-enabled CNTFET models using approximations and curve fittings, the proposed model employs a self-consistent method for the calculation of the channel potential in SPICE, providing more accuracy. The versatility of the CNT interconnect model and that of the CNTFET model are shown in CNT circuit simulations. (C) 2012 Elsevier Ltd. All rights reserved.
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    Computation of the Binding Energies between Human ACE2 and Spike RBDs of the Original Strain, Delta and Omicron Variants of the SARS-CoV-2: A DFT Simulation Approach
    (Wiley-V C H Verlag Gmbh, 2022) Yamaçlı, Serhan; Avci, Mutlu
    The receptor binding domain (RBD) of SARS-CoV-2 binds to human ACE2 leading to infection. In this study, the complexes that are formed by the attachment of the SARS-CoV-2 spike RBDs of the original strain, delta and omicron variants to the human ACE2 are investigated via density functional theory (DFT) simulations to obtain binding energies. The DFT computations are performed without fragmenting the interfaces to involve longer-range interactions for improved accuracy, which is one of the primary features of the approach used in this study. Basis set superposition error corrections and van der Waals dispersions are also included in the DFT simulations. The binding energies of the SARS-CoV-2 spike RBDs of the original strain, delta and omicron variants to the human ACE2 are computed as -4.76, -6.68, and -11.77 eV, respectively. These binding energy values indicate that the binding of the omicron variant to the ACE2 is much more favorable than the binding of the original strain and the delta variant, which constitute a molecular reason for the takeover of the omicron variant. The binding energies and the decomposition of these energies found in this study are expected to aid in the development of neutralizing agents.
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    Öğe
    Density functional theory computation of the binding free energies between various mutations of SARS-CoV-2 RBD and human ACE2: molecular level roots of the contagiousness
    (Cell Press, 2022) Yamaçlı, Serhan; Avci, Mutlu
    The receptor-binding domain (RBD) of SARS-CoV-2 attaches to the human ACE2 to initiate binding of SARS-CoV-2 to human cell and leads to the infection process afterwards. In this study, various mutations of SARS-CoV-2 spike RBD and human ACE2 complexes are investigated via density functional theory (DFT) computations to obtain binding free energies. The DFT computations are performed without fragmenting the interfaces to involve longer-range quantum mechanical interactions for improving accuracy. The vibrational free energies, van der Waals dispersion forces and basis set superposition error corrections are also included in the calculations. The results show that the absolute value of the binding energy of B.1.1.7 mutated spike RBD-ACE2 complex is more than five times higher than that of the original strain. The results of this study are expected to be useful for a deeper understanding of the relation of the binding free energies and the level of contagiousness.
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    Öğe
    Investigation and comparison of graphene nanoribbon and carbon nanotube based SARS-CoV-2 detection sensors: An ab initio study
    (Elsevier, 2023) Yamaçlı, Serhan; Avci, Mutlu
    The rapid detection of SARS-CoV-2, the pathogen of the Covid-19 pandemic, is obviously of great importance for stopping the spread of the virus by detecting infected individuals. Here, we report the ab initio analysis results of graphene nanoribbon (GNR) and carbon nanotube (CNT) based SARS-CoV-2 detection sensors which are experimentally demonstrated in the literature. The investigated structures are the realistic molecular models of the sensors that are employing 1-pyrenebutyric acid N-hydroxysuccinimide ester as the antibody linker. Density functional theory in conjunction with non-equilibrium Green's function formalism (DFT-NEGF) is used to obtain the transmission spectra, current-voltage and resistance-voltage characteristics of the sensors before and after the attachment of the SARS-CoV-2 spike protein. The operation mechanism of the GNR and CNT based SARS-CoV-2 sensors are exposed using the transmission spectrum analysis. Moreover, it is observed that GNR based sensor has more definitive detection characteristics compared to its CNT based counterpart.