Optical Bistability in Nonlinear Optical Coupler with Negative Index Channel

We discuss a novel kind of nonlinear coupler with one channel filled with a negative index material (NIM). The opposite directionality of the phase velocity and the energy flow in the NIM channel facilitates an effective feedback mechanism that leads to optical bistability and gap soliton formation

Calorimetric and acoustic study of binary mixtures containing an isomeric chlorobutane and butyl ethyl ether or methyl tert-butyl ether

Densities and speeds of sound in the temperature range 283.15-313.15 K have been measured for the binary mixtures formed by an isomeric chlorobutane (1-chlorobutane, 2-chlorobutane, 1-chloro-2-methylpropane, or 2-chloro-2-methylpropane) and butyl ethyl ether or methyl tert-butyl ether. Excess isentropic compressibilities were calculated from the experimental data. Excess enthalpies at T = 298.15 K are also included for the same binary mixtures. All these properties provide an insight into the nature of interactions operating on the present systems. Finally, the Prigogine-Flory-Patterson theory has been used to analyze the H E results and to estimate the isentropic compressibility values of the mixtures at T = 298.15 K

Vessel Recognition in Induction Heating Appliances - A Deep-Learning Approach

The selection of a vessel by an induction-hob user has a significant impact on the performance of the appliance. Due to the induction heating physical phenomena, there exist many factors that modify the equivalent impedance of induction hobs and, consequently, the operational conditions of the inverter. In particular, the type of vessel, which is a sole decision of the user, strongly affects these parameters. Besides, the ferromagnetic properties of the different materials the vessels are made with, vary differently with the excitation level, and given that most of the domestic induction hobs are based on an ac-bus voltage arrangement, the excitation level continuously varies. The algorithm proposed in this work takes advantage of this fact to identify the equivalent impedance of the load and recognize the pot. This is accomplished through a phase-sensitive detector that was already proposed in the literature and the application of deep learning. Different convolutional neural networks are tested on an augmented experimental-based dataset and the proposed algorithm is implemented in an experimental prototype with a system-on-chip. The proposed implementation is presented as an effective and accurate method to characterize and discriminate between different pots that could enable further functionalities in new generations of induction hobs

Output voltage estimation of a half-bridge inverter for domestic induction heating applications

The power supplied to a vessel by a domestic induction-heating appliance is strongly dependent on several parameters the designer of the system has no control over: the type and the size of the vessel, misalignments between the pot and the inductor, temperatures, etc. A reliable estimation of the power is essential to ensure that the home appliance works under the expected conditions and the user experience is suitable. Furthermore, any reduction of hardware is totally welcome by consumer-electronics manufacturers. In this work, two methods to estimate the output voltage of a half-bridge inverter without digitizing it with an analog-to-digital converter are proposed and the effects that this estimation has on the power calculation are evaluated. Both methods are implemented and experimentally verified in a real prototype with an FPGA (Field-Programmable Gate Array)

Soc-based in-cycle load identification of induction heating appliances

The equivalent load of an induction hob is strongly dependent on many parameters such as the switching frequency, the excitation level and the size, type, and material of the vessel. However, real-time methods with the ability to capture the variation of the load with the excitation level have not been proposed in the literature. This is an essential issue as most of the commercial induction hobs are based on an ac-bus voltage arrangement. This article proposes a method based on a phase-sensitive detector that offers an online tracking of the equivalent impedance for this type of arrangements. This algorithm enables advanced control functionalities such as clustering of vessels, material recognition, and premature detection of ferromagnetic saturation, among others. After simulation and experimental validation, the method is implemented into a prototype with a system-on-chip to verify its real-time behavior. The proposed approach is applied to different real-life situations that prove its great performance and applicability

Reduced-order models of series resonant inverters in induction heating applications

From the controller design framework, a simple analytical model that captures the dominant behavior in the range of interest is the optimal. When modeling resonant circuits, complex mathematical models are obtained. These high-order models are not the most suitable for controller design. Although some assumptions can be made for simplifying these models, variable frequency operation or load uncertainty can make these premises no longer valid. In this work, a systematic modeling order reduction technique, Slowly Varying Amplitude and Phase (SVAP), is considered for obtaining simpler analytical models of resonant inverters. SVAP gives identical results as the classical model-order residualization technique from automatic control theory. A slight modification of SVAP, Slowly Varying Amplitude Derivative and Phase (SVADP) is applied in this paper to obtain a better validity range. SVADP is validated for a half-bridge series resonant inverter (HBSRI) and for a high- order plant, a dual-half bridge series resonant inverter (DHBSRI) giving analytical second-order transfer functions for both topologies. Simulation and experimental results are provided to show the validity range of the reduced-order models

Long-lived quantum coherence in photosynthetic complexes at physiological temperature

Photosynthetic antenna complexes capture and concentrate solar radiation by transferring the excitation to the reaction center which stores energy from the photon in chemical bonds. This process occurs with near-perfect quantum efficiency. Recent experiments at cryogenic temperatures have revealed that coherent energy transfer - a wavelike transfer mechanism - occurs in many photosynthetic pigment-protein complexes (1-4). Using the Fenna-Matthews-Olson antenna complex (FMO) as a model system, theoretical studies incorporating both incoherent and coherent transfer as well as thermal dephasing predict that environmentally assisted quantum transfer efficiency peaks near physiological temperature; these studies further show that this process is equivalent to a quantum random walk algorithm (5-8). This theory requires long-lived quantum coherence at room temperature, which never has been observed in FMO. Here we present the first evidence that quantum coherence survives in FMO at physiological temperature for at least 300 fs, long enough to perform a rudimentary quantum computational operation. This data proves that the wave-like energy transfer process discovered at 77 K is directly relevant to biological function. Microscopically, we attribute this long coherence lifetime to correlated motions within the protein matrix encapsulating the chromophores, and we find that the degree of protection afforded by the protein appears constant between 77 K and 277 K. The protein shapes the energy landscape and mediates an efficient energy transfer despite thermal fluctuations. The persistence of quantum coherence in a dynamic, disordered system under these conditions suggests a new biomimetic strategy for designing dedicated quantum computational devices that can operate at high temperature.Comment: PDF files, 15 pages, 3 figures (included in the PDF file

Integrated study of Mediterranean deep canyons: Novel results and future challenges

This volume compiles a number of scientific papers resulting from a sustained multidisciplinary research effort of the deep-sea ecosystem in the Mediterranean Sea. This started 20 years ago and peaked over the last few years thanks to a number of Spanish and European projects such as PROMETEO, DOS MARES, REDECO, GRACCIE, HERMES, HERMIONE and PERSEUS, amongst others. The geographic focus of most papers is on the NW Mediterranean Sea including the Western Gulf of Lion and the North Catalan margin, with a special attention to submarine canyons, in particular the Blanes and Cap de Creus canyons. This introductory article to the Progress in Oceanography special issue on "Mediterranean deep canyons" provides background information needed to better understand the individual papers forming the volume, comments previous reference papers related to the main topics here addressed, and finally highlights the existing relationships between atmospheric forcing, oceanographic processes, seafloor physiography, ecosystem response, and litter and chemical pollution. This article also aims at constituting a sort of glue, in terms of existing knowledge and concepts and novel findings, linking together the other twenty papers in the volume, also including some illustrative figures. The main driving ideas behind this special issue, particularly fitting to the study area of the NW Mediterranean Sea, could be summarized as follows: (i) the atmosphere and the deep-sea ecosystem are connected through oceanographic processes originating in the coastal area and the ocean surface, which get activated at the occasion of high-energy events leading to fast transfers of matter and energy to the deep; (ii) shelf indented submarine canyons play a pivotal role in such transfers, which involve dense water, sedimentary particles, organic matter, litter and chemical pollutants; (iii) lateral inputs (advection) from the upper continental margin contributes significantly to the formation of intermediate and deep-water masses, and the associated fluxes of matter and energy are a main driver of deep-sea ecosystems; (iv) deep-sea organisms are highly sensitive to the arrival of external inputs, starting from the lowest food web levels and propagating upwards as time passes, which also relies upon the biology, nutritional needs and life expectancy of each individual species; and (v) innovative knowledge gained through such multidisciplinary research is of the utmost significance for an improved management of deep-sea living resources, such as the highly priced red shrimp Aristeus antennatus, for which a pilot management plan largely based in the findings described here and in related articles has been recently published (BOE, 2013). The researchers involved in such challenging endeavour have learnt tremendously from the results obtained so far and from each other, but are fully aware that there are still many unsolved questions. That is why this introductory article also includes "Future challenges" both in the title and as an individual section at the end, to express that there is still a long way to go