Collimated directional emission from a peanut-shaped microresonator

Collimated directional emission is essentially required an asymmetric resonant cavity. In this paper, we theoretically investigate a type of peanut-shaped microcavity which can support highly directional emission with the emission divergence as small as 2.5o. The mechanism of the collimated emission is explained with the short-term ray trajectory and the intuitive lens model in detail. Wave simulation also confirms these results. This extremely narrow divergence of the emission holds a great potential in highly collimated lasing from on-chip microcavities

Broadband enhancement of light harvesting in luminescent solar concentrator

Luminescent solar concentrator (LSC) can absorb large-area incident sunlight, then emit luminescence with high quantum efficiency, which finally be collected by a small photovoltaic (PV) system. The light-harvesting area of the PV system is much smaller than that of the LSC system, potentially improving the efficiency and reducing the cost of solar cells. Here, based on Fermi-golden rule, we present a theoretical description of the luminescent process in nanoscale LSCs where the conventional ray-optics model is no longer applicable. As an example calculated with this new model, we demonstrate that a slot waveguide consisting of a nanometer-sized low-index slot region sandwiched by two high-index regions provides a broadband enhancement of light harvesting by the luminescent centers in the slot region. This is because the slot waveguide can (1) greatly enhance the spontaneous emission due to the Purcell effect, (2) dramatically increase the effective absorption cross-section of luminescent centers, and (3) strongly improve the quantum efficiency of luminescent centers. It is found that about 80% solar photons can be ultimately converted to waveguide-coupled luminescent photons even for a low luminescent quantum efficiency of 0.5. This LSC is potential to construct a tandem structure which can absorb nearly full-spectrum solar photons, and also may be of special interest for building integrated nano-PV applications

Generating optical cat states via quantum interference of multi-path free-electron-photons interactions

The novel quantum effects induced by the free-electron-photons interaction have attracted increasing interest due to their potential applications in ultrafast quantum information processing. Here, we propose a scheme to generate optical cat states based on the quantum interference of multi-path free-electron-photons interactions that take place simultaneously with strong coupling strength. By performing a projection measurement on the electron, the state of light changes significantly from a coherent state into a non-Gaussian state with either Wigner negativity or squeezing property, both possess metrological power to achieve quantum advantage. More importantly, we show that the Wigner negativity oscillates with the coupling strength, and the optical cat states are successfully generated with high fidelity at all the oscillation peaks. This oscillation reveals the quantum interference effect of the multiple quantum pathways in the interaction of the electron with photons, by that various nonclassical states of light are promising to be fast prepared and manipulated. These findings inspire further exploration of emergent quantum phenomena and advanced quantum technologies with free electrons

Fine-Grained Emotion Analysis Based on Mixed Model for Product Review

Nowadays, with the rapid development of B2C e-commerce and the popularity of online shopping, the Web storages huge number of product reviews comment by customers. A large number of reviews made it difficult for manufacturers or potential customers to track the comments and suggestions that customers made. This paper presents a method for extracting emotional elements containing emotional objects and emotional words and their tendencies from product reviews based on mixed model. First we constructed conditional random fields to extract emotional elements, lead-in semantic and word meaning as features to improve the robustness of feature template and used rules for hierarchical filtering errors. Then we constructed support vector machine to classify the emotional tendency of the fine-grained elements to achieve key information from product reviews. Deep semantic information imported based on neural network to improve the traditional bag of word model. Experimental results show that the proposed model with deep features efficiently improved the F-Measure

Pretreatment of microcrystalline cellulose in organic electrolyte solutions for enzymatic hydrolysis

<p>Abstract</p> <p>Background</p> <p>Previous studies have shown that the crystalline structure of cellulose is negatively correlated with enzymatic digestibility, therefore, pretreatment is required to break down the highly ordered crystalline structure in cellulose, and to increase the porosity of its surface. In the present study, an organic electrolyte solution (OES) composed of an ionic liquid (1-allyl-3-methylimidazolium chloride ([AMIM]Cl)) and an organic solvent (dimethyl sulfoxide; DMSO) was prepared, and used to pretreat microcrystalline cellulose for subsequent enzymatic hydrolysis; to our knowledge, this is the first time that this method has been used.</p> <p>Results</p> <p>Microcrystalline cellulose (5 wt%) rapidly dispersed and then completely dissolved in an OES with a molar fraction of [AMIM]Cl per OES (χ _[AMIM]Cl) of greater than or equal to 0.2 at 110°C within 10 minutes. The cellulose was regenerated from the OES by precipitation with hot water, and enzymatically hydrolyzed. As the χ _[AMIM]Clof the OES increased from 0.1 to 0.9, both the hydrolysis yield and initial hydrolysis rate of the regenerated cellulose also increased gradually. After treatment using OES with χ _[AMIM]Clof 0.7, the glucose yield (54.1%) was 7.2 times that of untreated cellulose. This promotion of hydrolysis yield was mainly due to the decrease in the degree of crystallinity (that is, the crystallinity index of cellulose I).</p> <p>Conclusions</p> <p>An OES of [AMIM]Cl and DMSO with χ _[AMIM]Clof 0.7 was chosen for cellulose pretreatment because it dissolved cellulose rapidly to achieve a high glucose yield (54.1%), which was only slightly lower than the value (59.6%) obtained using pure [AMIM]Cl. OES pretreatment is a cost-effective and environmentally friendly technique for hydrolysis, because it 1) uses the less expensive OES instead of pure ionic liquids, 2) shortens dissolution time, 3) requires lower energy for stirring and transporting, and 4) is recyclable.</p