• Proceedings of the Korean Vacuum Society Conference
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• 2013.02a
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• pp.654-654
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• 2013

One of the most important yet unresolved problems in molecular electronics is the controversy over the number and nature of multiple conductance peaks in single-molecule junctions. Currently, there are three competing explanations of this observation: (1) manifestation of different molecule-electrode contact geometries, (2) formation of gauche defects within the molecular core, (3) involvement of different electrode surface orientations [1]. However, the exact origin of multiple conductance peaks is not yet fully understood, which indicates our incomplete understanding of the scientifically as well as techno-logically important organic-metal contacts. To theoretically resolve this problem, we previously applied a multiscale computational approach that combines force fields molecular dynamics (FF MD), density functional theory (DFT), and matrix Green's function (MGF) calculations [2] to a thermally fluctuating haxanedithiol (C6DT) molecule stretched between flat Au(111) electrodes, but could observe only a single conductance peak [3]. In this presentation, using DFT geometry optimizations and MGF calculations, we consider molecular junctions with more realistic molecule-metal contact conformations and Au(111) electrode surface directions. We also conduct DFT-based molecular dynamics for the highly stretched junction models to confirm our conclusion. We conclude that the S-Au coordination number should be the more dominant factor than the electrode surface orientation.

• Journal of Power Electronics
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• v.19 no.5
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• pp.1248-1258
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• 2019

This paper presents a moth-flame optimization (MFO)-based maximum power point tracking (MPPT) method for photovoltaic (PV) systems. The MFO algorithm is a new optimization method that exhibits satisfactory performance in terms of exploration, exploitation, local optima avoidance, and convergence. Therefore, the MFO algorithm is quite suitable for solving multiple peaks of PV systems under partial shading conditions (PSCs). The proposed MFO-MPPT is compared with four MPPT algorithms, namely the perturb and observe (P&O)-MPPT, incremental conductance (INC)-MPPT, particle swarm optimization (PSO)-MPPT and whale optimization algorithm (WOA)-MPPT. Simulation and experiment results demonstrate that the proposed algorithm can extract the global maximum power point (MPP) with greater tracking speed and accuracy under various conditions.