Dark matter absorption via electronic excitations

We revisit the calculation of bosonic dark matter absorption via electronic excitations. Working in an effective field theory framework and consistently taking into account in-medium effects, we clarify the relation between dark matter and photon absorption. As is well-known, for vector (dark photon) and pseudoscalar (axion-like particle) dark matter, the absorption rates can be simply related to the target material’s optical properties. However, this is not the case for scalar dark matter, where the dominant contribution comes from a different operator than the one contributing to photon absorption, which is formally next-to-leading-order and does not suffer from in-medium screening. It is therefore imperative to have reliable first-principles numerical calculations and/or semi-analytic modeling in order to predict the detection rate. We present updated sensitivity projections for semiconductor crystal and superconductor targets for ongoing and proposed direct detection experiments.

Crystallization Control of N,N′-Dioctyl Perylene Diimide by Amphiphilic Block Copolymers Containing poly(3-Hexylthiophene) and Polyethylene Glycol

The preparation of micron- to nanometer-sized functional materials with well-defined shapes and packing is a key process to their applications. There are many ways to control the crystal growth of organic semiconductors. Adding polymer additives has been proven a robust strategy to optimize semiconductor crystal structure and the corresponding optoelectronic properties. We have found that poly(3-hexylthiophene) (P3HT) can effectively regulate the crystallization behavior of N,N′-dioctyl perylene diimide (C8PDI). In this study, we combined P3HT and polyethylene glycol (PEG) to amphiphilic block copolymers and studied the crystallization modification effect of these block copolymers. It is found that the crystallization modification effect of the block copolymers is retained and gradually enhanced with P3HT content. The length of C8PDI crystals were well controlled from 2 to 0.4 μm, and the width from 210 to 35 nm. On the other hand, due to the water solubility of PEG block, crystalline PEG-b-P3HT/C8PDI micelles in water were successfully prepared, and this water phase colloid could be stable for more than 2 weeks, which provides a new way to prepare pollution-free aqueous organic semiconductor inks for printing electronic devices.

Prediction Of Material Properties By Neural Network Fusing The Atomic Local Environment And Global Description: Applied To Organic Molecules And Crystals

Machine learning has brought great convenience to material property prediction. However, most existing models can only predict properties of molecules or crystals with specific size, and usually only local atomic environment or molecular global descriptor representation be used as the characteristics of the model, resulting in poor model versatility and cannot be applied to multiple systems. We propose a method that combines the description of the local atomic environment and the overall structure of the molecule, a fusion model consisting of a graph convolutional neural network and a fully connected neural network is used to predict the properties of molecules or crystals, and successfully applied to QM9 organic molecules and semiconductor crystal materials. Our method is not limited to a specific size of a molecule or a crystal structure. According to the calculation principle of the properties of the material molecules, the influences of the local atomic environment and the overall structure of the molecules on the properties are respectively considered, an appropriate weighting ratio is selected to predict the properties. As a result, the prediction performance has been greatly improved. In fact, the proposed method is not limited to organic molecules and crystals and is also applicable to other structures, such as clusters.

A lean production system design for semiconductor crystal-ingot pulling manufacturing using hybrid Taguchi method and simulation optimization

Purpose The purpose of this study is to propose an innovative methodology in solving the lean production design from semiconductor crystal-ingot pulling manufacturing which is an important industry. Due to the complexity of the system, it is computationally prohibited by an analytical approach; thus, simulation optimization is adopted for this study. Design/methodology/approach Four control factors that affect the system’s performance, including the pulling strategy, machine limitations, dispatching rules and batch-size control, are identified to generate the future-state value stream mapping. Taguchi two-step procedure and simulation optimization are used to determine the optimal parameter values for a robust system. Findings The proposed methodology improved the system performances by 6.42 and 12.02 per cent for service level and throughput, respectively. Research limitations/implications This study does not investigate operations management issues such as setup reduction, demand forecasting and layout design. Practical implications A real-world crystal-ingot pulling manufacturing factory was used for the case study. The results are promising and are readily applied to other industrial applications. Social implications The improved performances, service level and throughout rate, can result in an improved customer satisfaction level and a reduced resources consumption, respectively. Originality/value The proposed methodology innovatively solved a practical application and the results are promising.

Quantum Dots: Method of Preparation and Biological Application

Quantum dots are inorganic semiconductor crystal of nanometer size which having distinctive conductive property depend on its size & shape. After administration of quantum dots parentally they identify target and bound them. Also quantum dots having light emitting property depend on size & shape. Quantum dots are prepared by chemical synthesis method include both organic & water phase synthesis & also by top- bottom approach. Tumor cell targeting & detection of pathogen & toxin are the main application of quantum dots & also in targeting drug delivery system. This review provides the overview of method of preparation of quantum dots & its biological application. Keywords: Quantum dot, targeting drug delivery, biological application