An investigation of PDMS structures for optimized ferroelectret performance

This paper reports the ANSYS simulation and fabrication processes for optimising PDMS ferroelectret performance. The proposed model extends the previously published analytical models and compares this with simulation of individual void geometry. The ferroelectret material is fabricated from PDMS using 3D-printed plastic moulds. The analytical model and Ansys simulation results predict the variation in performance of the PDMS ferroelectret with the different void geometry and surface charge density. The theoretical maximum piezoelectric coefficient d33 achieved was about 220 pC/N. The experimental maximum d33 obtained was 172 pC/N

Analyses and optimizations of timing-constrained embedded systems considering resource synchronization and machine learning approaches

Nowadays, embedded systems have become ubiquitous, powering a vast array of applications from consumer electronics to industrial automation. Concurrently, statistical and machine learning algorithms are being increasingly adopted across various application domains, such as medical diagnosis, autonomous driving, and environmental analysis, offering sophisticated data analysis and decision-making capabilities. As the demand for intelligent and time-sensitive applications continues to surge, accompanied by growing concerns regarding data privacy, the deployment of machine learning models on embedded devices has emerged as an indispensable requirement. However, this integration introduces both significant opportunities for performance enhancement and complex challenges in deployment optimization. On the one hand, deploying machine learning models on embedded systems with limited computational capacity, power budgets, and stringent timing requirements necessitates additional adjustments to ensure optimal performance and meet the imposed timing constraints. On the other hand, the inherent capabilities of machine learning, such as self-adaptation during runtime, prove invaluable in addressing challenges encountered in embedded systems, aiding in optimization and decision-making processes. This dissertation introduces two primary modifications for the analyses and optimizations of timing-constrained embedded systems. For one thing, it addresses the relatively long access times required for shared resources of machine learning tasks. For another, it considers the limited communication resources and data privacy concerns in distributed embedded systems when deploying machine learning models. Additionally, this work provides a use case that employs a machine learning method to tackle challenges specific to embedded systems. By addressing these key aspects, this dissertation contributes to the analysis and optimization of timing-constrained embedded systems, considering resource synchronization and machine learning models to enable improved performance and efficiency in real-time applications with stringent constraints

Metal oxide functionalized nanoporous gold catalysts for hydrogen production

Nanoporous gold (npAu) has shown potential for applications in many fields, in particular for heterogeneous catalysis. Much progress has been made in utilizing the high reactivity of npAu catalysts for selective oxidation reactions at low temperatures. However, its tendency to coarsen at high temperatures severely limits the practical applications of npAu, as it results in the loss of catalytically active surface. To solve this problem, we explored a wetness impregenation method and a sol-gel method in order to deposit dispersed oxide nanoparticles on npAu. In addition to drastically improving the thermal stability and mechanical properties of npAu, the functionalization opens up a range of new and beforehand unseen applications, for example, for hydrogen production reactions, such as the water gas shift reaction (WGSR) and steam reforming of methanol (SRM). The focus of the present work was to investigate the effect of adding oxide deposits on npAu and to understand the origins of the catalytic activity of these systems. An inverse ceria/npAu catalysts was first prepared by wet impregnation and thermal decomposition of a cerium nitrate precursor on a npAu substrate. The ceria loadings were about 3 to 10 atom %. The presence of ceria oxide on the nanosized gold ligaments play a key role in helping to increase the thermal stability of the material. Subsequently, a series of TiO2-CeO2 mixed oxides was synthesized inside the npAu network using a sol-gel method in order to further improve the catalytic activity of the npAu-based inverse catalyst. The structural characterization of the samples with TEM indicated that the gold ligaments were abundantly covered by small oxide agglomerates with sizes of about 1-2 nm. These materials exhibited similar properties as compared to ceria functionalized npAu, i.e. showed excellent stability and reproducibility up to temperatures of over 500AdegreeC. Raman spectroscopy has been used to study interactions of different gases (O2, H2O, CO) with the oxide functionalized npAu samples. The characterization of the crystallinity and the behavior of oxygen vacancies in the npAu supported metal oxides under different gases conditions (O2, H2O, CO) indicated that there is a dynamic correlation between the crystallization (oxygen storage) of the metal-oxides and the oxidizing and reducing conditions, which also implies that the addition of oxide deposits can effectively improve the chemical reactivity of the system. Water-gas shift (WGS) reaction tests on CeOx/npAu showed formation of CO2 at temperatures as low as 135AdegreeC. The loss of activity after about 15 h of catalytic conversion at temperatures up to 535AdegreeC was only about 10%. Photoelectron spectroscopy studies of the material revealed that defect rich ceria (Ce3 ) plays a key role in the dissociation of H2O. By comparing the catalytic activities of different catalysts, it was found that the Ce1Ti2Ox/npAu sample yields the highest activity which was nearly twice as high as the activity of all other samples at 300AdegreeC. This was related to its high dissociation ability for water. In addition to WGSR, another important hydrogen production process, namely the steam reforming of methanol (SRM), was studied. The reaction of methanol with water yielded hydrogen as a reaction product quantitatively. The flow reactor study showed that both, CeOx/npAu and Ce1Ti2Ox/npAu, had a high activity and selectivity for the reforming reaction. To understand the origins of the catalytic activity of the oxide functionalized npAu, photoelectron spectroscopy and diffuse reflectance infrared spectroscopy (DRIFT) have been used. The investigations revealed that the activation of water and the formation of OHads are key factors for the different activity/selectivity of the catalysts

Bifurcation and spatiotemporal patterns in a homogeneous diffusive predator-prey system

A diffusive predator-prey system with Holling type-II predator functional response subject to Neumann boundary conditions is considered. Hopf and steady state bifurcation analysis are carried out in details. In particular we show the existence of multiple spatially non-homogeneous periodic orbits while the system parameters are all spatially homogeneous. Our results and global bifurcation theory also suggest the existence of loops of spatially non-homogeneous periodic orbits and steady state solutions. These results provide theoretical evidences to the complex spatiotemporal dynamics found by numerical simulation. (c) 2008 Elsevier Inc. All rights reserved

Global asymptotical behavior of the Lengyel-Epstein reaction-diffusion system

The Lengyel-Epstein reaction-diffusion system of the CIMA reaction is revisited. We construct a Lyapunov function to show that the constant equilibrium solution is globally asymptotically stable when the feeding rate of iodide is small. We also show that for small spatial domains, all solutions eventually converge to a spatially homogeneous and time-periodic solution. (C) 2008 Elsevier Ltd. All rights reserved

Hopf bifurcations in a reaction-diffusion population model with delay effect

A reaction-diffusion population model with a general time-delayed growth rate per capita is considered. The growth rate per capita can be logistic or weak Allee effect type. From a careful analysis of the characteristic equation, the stability of the positive steady state solution and the existence of forward Hopf bifurcation from the positive steady state solution are obtained via the implicit function theorem, where the time delay is used as the bifurcation parameter. The general results are applied to a food-limited population model with diffusion and delay effects as well as a weak Allee effect population model. (C) 2009 Elsevier Inc. All rights reserved