Analysis of stepwise charging limits and its implementation for efficiency improvement in switched capacitor DC–DC converters

In this work we analysed the stepwise charging technique to find the limits from which it is beneficial in terms of load capacitance and charge–discharge frequency. We included in the analysis practical limitations such as the consumption of auxiliary logic needed to implement the technique and the minimum size of auxiliary switches imposed by the technology. We proposed an ultra-low-power logic block to push these limits and to obtain benefits from this technique in small capacitances. Finally, we proposed to use a stepwise driver in the driving of the gate capacitance of power switches in switched-capacitor (SC) DC–DC converters. We designed and manufactured, in a 130 nm process, a SC DC–DC converter and measured a 29% energy reduction in the gate-drive losses of the converter. This accounts for an improvement of 4% (from 69 to 73%) in the overall converter efficiency.

     

Superradiant Emission from Coherent Excitons in van Der Waals Heterostructures

Recent advancements in isolation and stacking of layered van der Waals materials have created an unprecedented paradigm for demonstrating varieties of 2D quantum materials. Rationally designed van der Waals heterostructures composed of monolayer transition-metal dichalcogenides (TMDs) and few-layer hBN show several unique optoelectronic features driven by correlations. However, entangled superradiant excitonic species in such systems have not been observed before. In this report, it is demonstrated that strong suppression of phonon population at low temperature results in a formation of a coherent excitonic-dipoles ensemble in the heterostructure, and the collective oscillation of those dipoles stimulates a robust phase synchronized ultra-narrow band superradiant emission even at extremely low pumping intensity. Such emitters are in high demand for a multitude of applications, including fundamental research on many-body correlations and other state-of-the-art technologies. This timely demonstration paves the way for further exploration of ultralow-threshold quantum-emitting devices with unmatched design freedom and spectral tunability.     

Pareto Equilibrium of Objections and Counterobjections in a Differential Three-Person Game

Automation and Remote Control - A linear-quadratic positional differential game of three persons is considered. Coefficient criteria are established under which there is no Nash equilibrium...     

Feature selection methods for root-cause analysis among top-level product attributes

Manufacturing companies not only strive to deliver flawless products but also monitor product failures in the field to identify potential quality issues. When product failures occur, quality engineers must identify the root cause to improve any affected product and process. This root-cause analysis can be supported by feature selection methods that identify relevant product attributes, such as manufacturing dates with an increased number of product failures. In this paper, we present different methods for feature selection and evaluate their ability to identify relevant product attributes in a root-cause analysis. First, we compile a list of feature selection methods. Then, we summarize the properties of product attributes in warranty case data and discuss these properties regarding the challenges they pose for machine learning algorithms. Next, we simulate datasets of warranty cases, which emulate these product properties. Finally, we compare the feature selection methods based on these simulated datasets. In the end, the univariate filter information gain is determined to be a suitable method for a wide range of applications. The comparison based on simulated data provides a more general result than other publications, which only focus on a single use case. Due to the generic nature of the simulated datasets, the results can be applied to various root-cause analysis processes in different quality management applications and provide a guideline for readers who wish to explore machine learning methods for their analysis of quality data.     

Optimization methods in inverse problems and applications to science and engineering

Optimization and Engineering -     

A novel strategy based on salp swarm algorithm for extracting the maximum power of proton exchange membrane fuel cell

Cell temperature and water content of the membrane have a significant effect on the performance of fuel cells. The current-power curve of the fuel cell has a maximum power point (MPP) that is needed to be tracked. This study presents a novel strategy based on a salp swarm algorithm (SSA) for extracting the maximum power of proton-exchange membrane fuel cell (PEMFC). At first, a new formula is derived to estimate the optimal voltage of PEMFC corresponding to MPP. Then the error between the estimated voltage at MPP and the actual terminal voltage of the fuel cell is fed to a proportional-integral-derivative controller (PID). The output of the PID controller tunes the duty cycle of a boost converter to maximize the harvested power from the PEMFC. SSA determines the optimal gains of PID. Sensitivity analysis is performed with the operating fuel cell at different cell temperature and water content of the membrane. The obtained results through the proposed strategy are compared with other programmed approaches of incremental resistance method, Fuzzy-Logic, grey antlion optimizer, wolf optimizer, and mine-blast algorithm. The obtained results demonstrated high reliability and efficiency of the proposed strategy in extracting the maximum power of the PEMFC.     

Synthesis and characterization of transition metal mixed oxide doped graphene embedded durable electrocatalyst for hydrogen evolution reaction

A promising electrocatalyst containing variable percentage of V₂O₅–TiO₂ mixed oxide in graphene oxide support was prepared by embedding the catalyst on Cu substrate through facile electroless Ni–Co–P plating for hydrogen evolution reaction. The solvothermal decomposition method was opted for tuning the crystalline characteristics of prepared material. The optimized mixed oxide was well characterized, active sites centres were identified and explained by X-ray diffraction, high resolution tunnelling electron microscopy, scanning electron microscopy coupled with energy dispersive X-ray and X-ray photon spectroscopy analysis. The structural and electronic characteristics of material was done by fourier transform infrared spectroscopy and the electrochemical behaviour of the prepared material was evaluated by using Tafel plot, electrochemical impedance analysis, linear sweep voltammetry, open circuit analysis and chronoamperometry measurements. The results show the enhanced catalytic activity of Ni–Co–P than pure Ni–P plate, due to synergic effect. Moreover, the prepared mixed oxide incorporated Ni–Co–P plate has a high activity towards HER with low over potential of 101 mV, low Tafel slope of 36 mVdec^?1, high exchange current density of 9.90 × 10^?2 Acm^?2.     

Research and development of liquid hydrogen (LH2) temperature monitoring system for marine applications

Monitoring the temperature in liquid hydrogen (LH₂) storage tanks on ships is important for the safety of maritime navigation. In addition, accurate temperature measurement is also required for commercial transactions. Temperature and pressure define the density of liquid hydrogen, which is directly linked to trading interests. In this study, we developed and tested a liquid hydrogen temperature monitoring system that uses platinum resistance sensors with a nominal electrical resistance of approximately 1000 Ω at room temperature, PT-1000, for marine applications. The temperature measurements were carried out using a newly developed temperature monitoring system under different pressure conditions. The measured values are compared with a calibrated reference PT-1000 resistance thermometer. We confirm a measurement accuracy of ±50 mK in a pressure range of 0.1 MPa–0.5 MPa.     

Full AC analysis of value of DER to the grid and optimal DER scheduling

This paper presents part of the work ComEd and Quanta Technology have performed to quantify the locational and temporal value of DER to avoid distribution grid upgrade investments. It focuses on the formulation of a robust and efficient algorithm for DER optimal dispatch on a distribution feeder to mitigate the violation of current and voltage limits using the allocated cost of capacity and locational marginal value of real and reactive DER injection/withdrawal.     

A Conversion Method for the Preparation of Calcium Formate

Theoretical Foundations of Chemical Engineering - Calcium formate is widely used in construction, tanning, and textile manufacture and as an E238 biological additive in cosmetology and the food...