اشترك بالحزمة الذهبية واحصل على وصول غير محدود شمرا أكاديميا
تسجيل مستخدم جديدCreating temperature dependent Ni-MH battery models for low power mobile devices
160
0
0.0
(
0
)
اسأل ChatGPT حول البحث
ﻻ يوجد ملخص باللغة العربية
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.
قيم البحث
اقرأ أيضاً
Surface acoustic wave (SAW) devices based on thin films of ZnO are a well established technology. However, SAW devices on bulk ZnO crystals are not practical at room temperature due to the significant damping caused by finite electrical conductivity
of the crystal. Here, by operating at low temperatures, we demonstrate effective SAW devices on the (0001) surface of bulk ZnO crystals, including a delay line operating at SAW wavelengths of {lambda} = 4 and 6 {mu}m and a one-port resonator at a wavelength of {lambda} = 1.6 {mu}m. We find that the SAW velocity is temperature dependent, reaching $v simeq 2.68$ km/s at 10mK. Our resonator reaches a maximum quality factor of $Q_i simeq 1.5times 10^5$, demonstrating that bulk ZnO is highly viable for low temperature SAW applications. The performance of the devices is strongly correlated with the bulk conductivity, which quenches SAW transmission above about 200 K.
Lithium titanium oxide Li$_4$Ti$_5$O$_{12}$ (LTO) is an intriguing anode material promising particularly long lived batteries, due to its remarkable phase stability during (dis)charging of the cell. However, its usage is limited by its low intrinsic
electronic conductivity. Introducing oxygen vacancies can be one method to overcome this drawback, possibly by altering the charge carrier transport mechanism. We use Hubbard corrected density-functional theory (DFT+U) to show that polaronic states in combination with a possible hopping mechanism can play a crucial role in the experimentally observed increase of electronic conductivity. To gauge polaronic charge mobility, we compute relative stabilities of different localization patterns and estimate polaron hopping barrier heights. With this we finally show how defect engineering can indeed raise the electronic conductivity of LTO up to the level of its ionic conductivity, thereby explaining first experimental results for reduced LTO.
Layered two-dimensional (2D) materials display great potential for a range of applications, particularly in electronics. We report the large-scale synthesis of thin films of platinum diselenide (PtSe2), a thus far scarcely investigated transition met
al dichalcogenide. Importantly, the synthesis by thermal assisted conversion is performed at 400 {deg}C, representing a breakthrough for the direct integration of this novel material with silicon (Si) technology. Besides the thorough characterization of this new 2D material, we demonstrate its promise for applications in high-performance gas sensing with extremely short response and recovery times observed due to the 2D nature of the films. Furthermore, we realized vertically-stacked heterostructures of PtSe2 on Si which act as both photodiodes and photovoltaic cells. Thus this study establishes PtSe2 as a potential candidate for next-generation sensors and (opto-)electronic devices, using fabrication protocols compatible with established Si technologies.
Owing to its superior visible light absorption and high chemical stability, chalcogenide perovskite barium zirconium sulfide has attracted significant attention in the past few years as a potential alternative to hybrid halide perovskites for optoele
ctronics. However, the high processing temperatures of BaZrS3 thin films at above 1000 C severely limits their potential for device applications. Herein, we report the synthesis of BaZrS3 thin films at temperatures as low as 500 C, by changing the chemical reaction pathway. The single phase BaZrS3 thin film was confirmed by X-ray diffraction and Raman spectroscopies. Atomic force microscopy and scanning electron microscopy show that crystalline size and surface roughness were consistently reduced with decreasing annealing temperature. The lower temperatures further eliminate sulfur vacancies and carbon contaminations associated with high temperature processing. The ability to synthesize chalcogenide perovskite thin films at lower temperatures removes a major hurdle for their device fabrication. The photodetectors demonstrate fast response and an on/off ratio of 80. The fabricated field effect transistors show an ambipolar behavior with electron and hole mobilities of 16.8 cm2/Vs and 2.6 cm2/Vs, respectively.
A pruning-based AutoML framework for run-time reconfigurability, namely RT3, is proposed in this work. This enables Transformer-based large Natural Language Processing (NLP) models to be efficiently executed on resource-constrained mobile devices and
reconfigured (i.e., switching models for dynamic hardware conditions) at run-time. Such reconfigurability is the key to save energy for battery-powered mobile devices, which widely use dynamic voltage and frequency scaling (DVFS) technique for hardware reconfiguration to prolong battery life. In this work, we creatively explore a hybrid block-structured pruning (BP) and pattern pruning (PP) for Transformer-based models and first attempt to combine hardware and software reconfiguration to maximally save energy for battery-powered mobile devices. Specifically, RT3 integrates two-level optimizations: First, it utilizes an efficient BP as the first-step compression for resource-constrained mobile devices; then, RT3 heuristically generates a shrunken search space based on the first level optimization and searches multiple pattern sets with diverse sparsity for PP via reinforcement learning to support lightweight software reconfiguration, which corresponds to available frequency levels of DVFS (i.e., hardware reconfiguration). At run-time, RT3 can switch the lightweight pattern sets within 45ms to guarantee the required real-time constraint at different frequency levels. Results further show that RT3 can prolong battery life over 4x improvement with less than 1% accuracy loss for Transformer and 1.5% score decrease for DistilBERT.
سجل دخول لتتمكن من نشر تعليقات
التعليقات
جاري جلب التعليقات
سجل دخول لتتمكن من متابعة معايير البحث التي قمت باختيارها
