Research and Simulation of DC Microgrid Three-Phase AC-DC Converter Control Strategy Based on Double Loop

The new voltage and current double loop control strategy is proposed to solve the DC microgrid bus voltage fluctuation caused by loads fluctuation, parameters perturbation and unbalanced three-phase power supply. Firstly, the dq axis mathematical model of three-phase AC-DC bidirectional converter in DC microgrid is analyzed and established, and then the controllers are designed according to the dq axis mathematical model. The outer loop is a voltage loop based on variable gain linear extended state observer (VGLESO) and sliding mode theory. VGLESO can not only effectively overcome the problem of peak output of traditional high-gain LESO in the initial stage of operation, and ensure that the system has good startup characteristics, but also quickly track and compensate the total disturbance of the system without additional current sensors. The inner loop is a current loop based on adaptive PI, which can eliminate the influence of system parameters perturbation on bus voltage and improve the system\u27s adaptability. Under the action of the inner and outer loops, the system has good dynamic and static characteristics. Finally, the feasibility and correctness of the control strategy are verified by Matlab/Simulink

Test structure, circuits and extraction methods to determine the radius of infuence of STI and polysilicon pattern density

Advanced CMOS processes need new methodologies to extract, characterize and model process variations and their sources. Most prior studies have focused on understanding the effect of local layout features on transistor performance; limited work has been done to characterize medium-range (≈ 10μm to 2mm) pattern density effects. We propose a new methodology to extract the radius of influence, or the range of neighboring layout that should be taken into account in determining transistor characteristics, for shallow trench isolation (STI) and polysilicon pattern density. A test chip, with 130k devices under test (DUTs) and step-like pattern density layout changes, is designed in 65nm bulk CMOS technology as a case study. The extraction result of the measured data suggests that the local layout geometry, within the DUT cell size of 6μm × 8μm, is the dominant contributor to systematic device variation. Across-die medium-range layout pattern densities are found to have a statistically significant and detectable effect, but this effect is small and contributes only 2-5% of the total variation in this technology

Methodology for analysis of TSV stress induced transistor variation and circuit performance

As continued scaling becomes increasingly difficult, 3D integration with through silicon vias (TSVs) has emerged as a viable solution to achieve higher bandwidth and power efficiency. Mechanical stress induced by thermal mismatch between TSVs and the silicon bulk arising during wafer fabrication and 3D integration, is a key constraint. In this work, we propose a complete flow to characterize the influence of TSV stress on transistor and circuit performance. First, we analyze the thermal stress contour near the silicon surface with single and multiple TSVs through both finite element analysis (FEA) and linear superposition methods. Then, the biaxial stress is converted to mobility and threshold voltage variations depending on transistor type and geometric relation between TSVs and transistors. Next, we propose an efficient algorithm to calculate circuit variation corresponding to TSV stress based on a grid partition approach. Finally, we discuss a TSV pattern optimization strategy, and employ a series of 17-stage ring oscillators using 40 nm CMOS technology as a test case for the proposed approach

Fast wide-field quantum sensor based on solid-state spins integrated with a SPAD array

Achieving fast, sensitive, and parallel measurement of a large number of quantum particles is an essential task in building large-scale quantum platforms for different quantum information processing applications such as sensing, computation, simulation, and communication. Current quantum platforms in experimental atomic and optical physics based on CMOS sensors and CCD cameras are limited by either low sensitivity or slow operational speed. Here we integrate an array of single-photon avalanche diodes with solid-state spin defects in diamond to build a fast wide-field quantum sensor, achieving a frame rate up to 100~kHz. We present the design of the experimental setup to perform spatially resolved imaging of quantum systems. A few exemplary applications, including sensing DC and AC magnetic fields, temperature, strain, local spin density, and charge dynamics, are experimentally demonstrated using an NV ensemble diamond sample. The developed photon detection array is broadly applicable to other platforms such as atom arrays trapped in optical tweezers, optical lattices, donors in silicon, and rare earth ions in solids

Study on effect of extrusion of the former tube based on DEFORM-3D

In order to obtain the optimum forming process of the Former tube, two forming schemes were made based on the actual production and processing experience and theory. The two forming schemes were simulated by DEFORM-3D. The optimal forming scheme was determined and the influence of different friction factors and different mould hardness on mould wear and forming load were analyzed; The research results of this paper can provide theoretical guidance for the production and processing of the former tube parts, which can improve the machining quality and precision of the parts, reduce the cost of the test module, and obtain a better shaping effect

Reinforcement learning-guided long-timescale simulation of hydrogen transport in metals

Atomic diffusion in solids is an important process in various phenomena. However, atomistic simulations of diffusion processes are confronted with the timescale problem: the accessible simulation time is usually far shorter than that of experimental interests. In this work, we developed a long-timescale method using reinforcement learning that simulates diffusion processes. As a testbed, we simulate hydrogen diffusion in pure metals and a medium entropy alloy, CrCoNi, getting hydrogen diffusivity reasonably consistent with previous experiments. We also demonstrate that our method can accelerate the sampling of low-energy configurations compared to the Metropolis-Hastings algorithm using hydrogen migration to copper (111) surface sites as an example

Chronic and Cumulative Adverse Life Events in Women with Primary Ovarian Insufficiency:An Exploratory Qualitative Study

BACKGROUND AND PURPOSE: Primary ovarian insufficiency (POI) has serious physical and psychological consequences due to estradiol deprivation, leading to increased morbidity and mortality. However, the causes of most POI cases remain unknown. Psychological stress, usually caused by stressful life events, is known to be negatively associated with ovarian function. It is important to explore high-frequency adverse life events among women with POI for future interventions. METHODS: Forty-three women (mean age=33·8 years) were recruited who were newly- diagnosed with idiopathic POI (FSH levels >40 IU/L) to participate in semi-structured interviews through convenience sampling. The main questions covered by the topic guide were designed to explore adverse life events prior to POI diagnosis. Interviews were audio recorded, transcribed and analyzed thematically. Data were analyzed from June 2019 to August 2020. RESULTS: Among the women with POI, mean age at diagnosis of POI was 33·8 years (range from 19 to 39 years), and the average time between the onset of irregular menstruation and POI diagnosis was 2.3 years. These women with POI had a relatively normal menstrual cycle before the diagnosis. A number of stressful life events prior to POI diagnosis were discussed by them as important factors influencing their health. Four core themes emerged: 1) persistent exposure to workplace stress, 2) persistent exposure to family-related adverse life events, 3) sleep problem/disturbance existed in women with POI before diagnosis, and 4) participants’ general cognition and concerns about POI. CONCLUSIONS: Persistent exposures to adverse life events related to work stress, family stress and sleep problem existed in women with POI. Our findings are consistent with the hypothesis that adverse life events play a role in the development of POI. Future research should investigate how social environmental factors influence POI disease risks, and whether provision of tailored interventions (i.e. preventing or mitigating impact of adverse life events) aimed at high-risk populations may help prevent new POI cases and improve conditions of women with POI. We gained an in-depth understanding of the experiences of these women via 1:1 qualitative method, and find adverse life events are frequent in women with POI prior to the diagnosis

Eight-Port Modified E-Slot MIMO Antenna Array with Enhanced Isolation for 5G Mobile Phone

An eight-element antenna system operating at sub 6 GHz is presented in this work for a future multiple-input multiple-output (MIMO) system based on a modified E-slot on the ground. The modified E-slot significantly lowers the coupling among the antenna components by suppressing the ground current effect. The design concept is validated by accurately measuring and carefully fabricating an eight-element MIMO antenna. The experimentation yields higher element isolation greater than −21 dB in the 3.5 GHz band and the desired band is achieved at −6 dB impedance bandwidth. The E-shape slot occupies an area of 17.8 mm × 5.6 mm designed on an FR-4 substrate with dimensions of 150 mm × 75 mm × 0.8 mm. We fed the I-antenna element with an L-shape micro-strip feedline, the size of the I-antenna is 20.4 × 5.2 mm2, which operates in the (3.4–3.65 GHz) band. Moreover, our method obtained an envelope correlation coefficient (ECC) of <0.01 and an ergodic channel capacity of 43.50 bps/Hz. The ECC and ergodic channel capacity are important metrics for evaluating MIMO system performance. Results indicate that the proposed antenna system is a good option to be used in 5G mobile phone applications

Blind quantum machine learning with quantum bipartite correlator

Distributed quantum computing is a promising computational paradigm for performing computations that are beyond the reach of individual quantum devices. Privacy in distributed quantum computing is critical for maintaining confidentiality and protecting the data in the presence of untrusted computing nodes. In this work, we introduce novel blind quantum machine learning protocols based on the quantum bipartite correlator algorithm. Our protocols have reduced communication overhead while preserving the privacy of data from untrusted parties. We introduce robust algorithm-specific privacy-preserving mechanisms with low computational overhead that do not require complex cryptographic techniques. We then validate the effectiveness of the proposed protocols through complexity and privacy analysis. Our findings pave the way for advancements in distributed quantum computing, opening up new possibilities for privacy-aware machine learning applications in the era of quantum technologies.Comment: 11 pages, 3 figure