Fluorescence energy transfer enhancement in aluminum nanoapertures

Zero-mode waveguides (ZMWs) are confining light into attoliter volumes, enabling single molecule fluorescence experiments at physiological micromolar concentrations. Among the fluorescence spectroscopy techniques that can be enhanced by ZMWs, F\"{o}rster resonance energy transfer (FRET) is one of the most widely used in life sciences. Combining zero-mode waveguides with FRET provides new opportunities to investigate biochemical structures or follow interaction dynamics at micromolar concentration with single molecule resolution. However, prior to any quantitative FRET analysis on biological samples, it is crucial to establish first the influence of the ZMW on the FRET process. Here, we quantify the FRET rates and efficiencies between individual donor-acceptor fluorophore pairs diffusing in aluminum zero-mode waveguides. Aluminum ZMWs are important structures thanks to their commercial availability and the large literature describing their use for single molecule fluorescence spectroscopy. We also compare the results between ZMWs milled in gold and aluminum, and find that while gold has a stronger influence on the decay rates, the lower losses of aluminum in the green spectral region provide larger fluorescence brightness enhancement factors. For both aluminum and gold ZMWs, we observe that the FRET rate scales linearly with the isolated donor decay rate and the local density of optical states (LDOS). Detailed information about FRET in ZMWs unlocks their application as new devices for enhanced single molecule FRET at physiological concentrations

Nanophotonic enhancement of the F\"orster resonance energy transfer rate on single DNA molecules

Nanophotonics achieves accurate control over the luminescence properties of a single quantum emitter by tailoring the light-matter interaction at the nanoscale and modifying the local density of optical states (LDOS). This paradigm could also benefit to F\"orster resonance energy transfer (FRET) by enhancing the near-field electromagnetic interaction between two fluorescent emitters. Despite the wide applications of FRET in nanosciences, using nanophotonics to enhance FRET remains a debated and complex challenge. Here, we demonstrate enhanced energy transfer within single donor-acceptor fluorophore pairs confined in gold nanoapertures. Experiments monitoring both the donor and the acceptor emission photodynamics at the single molecule level clearly establish a linear dependence of the FRET rate on the LDOS in nanoapertures. These findings are applied to enhance the FRET rate in nanoapertures up to six times, demonstrating that nanophotonics can be used to intensify the near-field energy transfer and improve the biophotonic applications of FRET

Plasmonic antennas and zero mode waveguides to enhance single molecule fluorescence detection and fluorescence correlation spectroscopy towards physiological concentrations

Single-molecule approaches to biology offer a powerful new vision to elucidate the mechanisms that underpin the functioning of living cells. However, conventional optical single molecule spectroscopy techniques such as F\"orster fluorescence resonance energy transfer (FRET) or fluorescence correlation spectroscopy (FCS) are limited by diffraction to the nanomolar concentration range, far below the physiological micromolar concentration range where most biological reaction occur. To breach the diffraction limit, zero mode waveguides and plasmonic antennas exploit the surface plasmon resonances to confine and enhance light down to the nanometre scale. The ability of plasmonics to achieve extreme light concentration unlocks an enormous potential to enhance fluorescence detection, FRET and FCS. Single molecule spectroscopy techniques greatly benefit from zero mode waveguides and plasmonic antennas to enter a new dimension of molecular concentration reaching physiological conditions. The application of nano-optics to biological problems with FRET and FCS is an emerging and exciting field, and is promising to reveal new insights on biological functions and dynamics.Comment: WIREs Nanomed Nanobiotechnol 201

Planning of Fast Charging Infrastructure for Electric Vehicles in a Distribution System and Prediction of Dynamic Price

The increasing number of electric vehicles (EVs) has led to the need for installing public electric vehicle charging stations (EVCS) to facilitate ease of use and to support users who do not have the option of residential charging. The public electric vehicle charging infrastructures (EVCIs) must be equipped with a good number of EVCSs, with fast charging capability, to accommodate the EV traffic demand, which would otherwise lead to congestion at the charging stations. The location of these fast-charging infrastructures significantly impacts the distribution system (DS). We propose the optimal placement of fast-charging EVCIs at different locations in the distribution system, using multi-objective particle swarm optimization (MOPSO), so that the power loss and voltage deviations are kept at a minimum. Time-series analysis of the DS and EV load variations are performed using MATLAB and OpenDSS. We further analyze the cost benefits of the EVCIs under real-time pricing conditions and employ an autoregressive integrated moving average (ARIMA) model to predict the dynamic price. The simulated test system without any EVCI has a power loss of 164.36 kW and squared voltage deviations of 0.0235 p.u. Using the proposed method, the results obtained validate the optimal location of 5 EVCIs (each having 20 EVCSs with a 50kWh charger rating) resulting in a minimum power loss of 201.40 kW and squared voltage deviations of 0.0182 p.u. in the system. Significant cost benefits for the EVCIs are also achieved, and an R-squared value of dynamic price predictions of 0.9999 is obtained. This would allow the charging station operator to make promotional offers for maximizing utilization and increasing profits

Identification of Forced Oscillation Sources in Wind Farms using E-SINDy

The rapid growth of wind power generation has led to increased interest in understanding and mitigating the adverse effects of wind turbine wakes and forced oscillations in wind farms. In this paper, we model a wind farm consisting of three wind turbines connected to a distribution system. Forced oscillations due to wind shear and tower shadow are injected into the system. If these oscillations are unchecked, they could pose a severe threat to the operation of the system and damage to the equipment. Identifying the source and frequency of forced oscillations in wind farms from measurement data is challenging. Thus, we propose a data-driven approach that discovers the underlying equations governing a nonlinear dynamical system from measured data using the Ensemble-Sparse Identification of Nonlinear Dynamics (E-SINDy) method. The results suggest that E-SINDy is a valuable tool for identifying sources of forced oscillations in wind farms and could facilitate the development of suitable control strategies to mitigate their negative impacts

Peer-to-Peer Sharing of Energy Storage Systems under Net Metering and Time-of-Use Pricing

Sharing economy has become a socio-economic trend in transportation and housing sectors. It develops business models leveraging underutilized resources. Like those sectors, power grid is also becoming smarter with many flexible resources, and researchers are investigating the impact of sharing resources here as well that can help to reduce cost and extract value. In this work, we investigate sharing of energy storage devices among individual households in a cooperative fashion. Coalitional game theory is used to model the scenario where utility company imposes time-of-use (ToU) price and net metering billing mechanism. The resulting game has a non-empty core and we can develop a cost allocation mechanism with easy to compute analytical formula. Allocation is fair and cost effective for every household. We design the price for peer to peer network (P2P) and an algorithm for sharing that keeps the grand coalition always stable. Thus sharing electricity of storage devices among consumers can be effective in this set-up. Our mechanism is implemented in a community of 80 households in Texas using real data of demand and solar irradiance and the results show significant cost savings for our method

Modelling of the Electric Vehicle Charging Infrastructure as Cyber Physical Power Systems: A Review on Components, Standards, Vulnerabilities and Attacks

The increasing number of electric vehicles (EVs) has led to the growing need to establish EV charging infrastructures (EVCIs) with fast charging capabilities to reduce congestion at the EV charging stations (EVCS) and also provide alternative solutions for EV owners without residential charging facilities. The EV charging stations are broadly classified based on i) where the charging equipment is located - on-board and off-board charging stations, and ii) the type of current and power levels - AC and DC charging stations. The DC charging stations are further classified into fast and extreme fast charging stations. This article focuses mainly on several components that model the EVCI as a cyberphysical system (CPS)