No Arabic abstract
We will describe the thermal performance of power semiconductor module, which consists of hetero-junction bipolar transistors (HBTs), for mobile communication systems. We calculate the thermal resistance between the HBT fingers and the bottom surface of a multi-layer printed circuit board (PCB) using a finite element method (FEM). We applied a steady state analysis to evaluate the influence of design parameters on thermal resistance of the module. We found that the thickness of GaAs substrate, the thickness of multi-layer circuit board, the thermal conductivity of bonding material under GaAs substrate, and misalignment of thermal vias between each layer of PCB are the dominant parameter in thermal resistance of the module.
This paper presents a study of accuracy issues in thermal modeling of high power LED modules on system level. Both physical as well as numerical accuracy issues are addressed. Incorrect physical assumptions may result in seemingly correct, but erroneous results. It is therefore important to motivate the underlying key physical assumptions of a thermal model. In this paper thermal measurements are used to calibrate a computational fluid dynamics (CFD) model of a high power LED module model at a reference application condition, and to validate it at other application conditions.
Light Emitting Diodes emits no IR and no UV and their spectrum is fully in the visible part. But LEDs are not cold and all energy losses are thermal losses. The aim of this paper is to prove the feasibility to reuse the thermal losses to produce light through a thermoelectric module. Papers where Peltier modules are included in LEDs systems are all the time used for cooling [1-6]. At the knowledge of the authors, this the first time that thermal losses are used to increase the global efficiency of a high power LED lighting system by using Peltier modules to produce light.
Free space optical communication has been applied in many scenarios because of its security, low cost and high rates. In such scenarios, a tracking system is necessary to ensure an acceptable signal power. Free space optical links were considered unable to support optical mobile communication when nodes are randomly moving at a high speed because existing tracking schemes fail to track the nodes accurately and rapidly. In this paper, we propose a novel tracking system exploiting multiple beacon laser sources. At the receiver, each beacon lasers power is measured to estimate the orientation of the target. Unlike existing schemes which drive servo motors multiple times based on consecutive measurements and feedback, our scheme can directly estimate the next optimal targeting shift for the servo motors based on a single measurement, allowing the tracking system to converge much faster. Closed-form outage probability expression is derived for the optical mobile communication system with ideal tracking, where pointing error and moving statistics are considered. To maintain sufficient average power and reduce the outage probability, the recommended size of a source spot is expressed in closed form as a function of the targets statistics of random moving, providing insights to the system design.
We developed an inverse design framework enabling automated generation of stable multi-component crystal structures by optimizing the formation energies in the latent space based on reversible crystal graphs with continuous representation. It is demonstrated that 9,160 crystal structures can be generated out of 50,000 crystal graphs, leading to 8,310 distinct cases using a training set of 52,615 crystal structures from Materials Project. Detailed analysis on 15 selected systems reveals that unreported crystal structures below the convex hull can be discovered in 6 material systems. Moreover, the generation efficiency can be further improved by considering extra hypothetical structures in the training. This paves the way to perform inverse design of multicomponent materials with possible multi-objective optimization.
In this paper the methodology and the results of creating temperature dependent battery models for ambient intelligence applications is presented. First the measurement technology and the model generation process is presented in details, and then the characteristic features of the models are discussed.