Stress Effects on Stabilizing Antiferroelectric Phase in Multilayer Ceramics

Controllable phase transformation between antiferroelectric (AFE) and ferroelectric (FE) states suggests multifunctional properties valuable for many device applications. Compared to AFE bulk ceramics with large voltage required for driving electric field‐induced phase transition, implementation of structures comprising multiple thin AFE ceramic layers can realize applications by reducing the switching operation voltage in the feasible range. Here, it is found that a compressive residual stress is developed in multilayer (Pb_0.97,La_0.02)(Zr_0.66,Sn_x,Ti_0.34?x)O₃ (PLZST) ceramic co‐fired with multiple Pd/Ag electrode layers, and the compressive residual stress can stabilize AFE phase. AFE phase forms in the PLZST multilayer ceramic with composition corresponding to FE in the bulk materials. Thermodynamic analysis based on free energy of FE and AFE phases well explains the FE to AFE phase transformation observed in the multilayer ceramic under the compressive stress. The findings exhibit a new strategy to tune structure and functional properties of multilayer ceramics through stress engineering for achieving device applications.     

Safety analysis of discrete event systems using a simplified Petri net controller

This paper deals with the problem of forbidden states in discrete event systems based on Petri net models. So, a method is presented to prevent the system from entering these states by constructing a small number of generalized mutual exclusion constraints. This goal is achieved by solving three types of Integer Linear Programming problems. The problems are designed to verify the constraints that some of them are related to verifying authorized states and the others are related to avoiding forbidden states. The obtained constraints can be enforced on the system using a small number of control places. Moreover, the number of arcs related to these places is small, and the controller after connecting them is maximally permissive.     

Localization of emergency acoustic sources by micro aerial vehicles

For micro aerial vehicles (MAVs) involved in search and rescue missions, the ability to locate the source of a distress sound signal is significantly important and allows fast localization of victims and rescuers during nighttime, through foliage and in dust, fog, and smoke. Most emergency sound sources, such as safety whistles and personal alarms, generate a narrowband signal that is difficult to localize by human listeners or with the common localization methods suitable for broadband sounds. In this paper, we present three methods for MAV‐based emergency sound localization system. The first method involves designing a new emergency source for immediate localization by the MAV using a common localization method. The other two novel methods allow localizing the currently available emergency sources, or other narrowband sounds in general, that are difficult to localize due to the periodicity in the sequence of sound samples. The second method exploits the Doppler shift in the sound frequency, caused due to the motion of the MAV and the dynamics of the MAV to assist with the localization. The third method involves active control of the robot's attitude and fusing acoustic and attitude measurements for achieving accurate and robust estimates. We evaluate our methods in real‐world experiments with real flying robots.     

Effects and Mechanism of Combinational Chemical Agents on Solution‐Derived K0.5Na0.5NbO3 Piezoelectric Thin Films

Sodium potassium niobate (KNN) piezoelectric ceramic thin films were prepared by a chemical solution deposition method, in which the introduction of appropriately combinational organic stabilizing agents, including monoethanolamine (MEA), diethanolamine (DEA), and ethylenediaminetetraacetic acid (EDTA), dramatically suppressed the volatile loss of the alkali ions, improved the crystallinity, and promoted crystal orientation of the perovskite phase in the resulting KNN thin films. Theoretical analyses including ab initio calculation based on molecular model indicated that stronger binding structure could form comprising the alkali ions and the combinational EDTA‐(DEA‐MEA) chemical agents than the cases of using individual binding agents separately. Outstandingly large effective piezoelectric strain coefficient d₃₃ under the substrate clamping condition was achieved. The theoretical and experimental results provide the insight on the underlying interaction mechanism between the multiple stabilizing chemical agents and metal ions, and the guidance for establishing the methodology for producing high quality oxide thin films from chemical solutions with dedicatedly designed combinational stabilizing agents.     

Structural evolution of thermal sprayed bismuth sodium titanate piezoelectric ceramic coatings

The structural evolution of lead-free piezoelectric bismuth sodium titanate (BNT) coatings with excess Bi derived from thermal spray process was investigated with transmission electron microscopy (TEM). Bi-rich composition was identified as the nucleation agent of the BNT perovskite phase, and fine-grained microstructure was obtained with more excess Bi. The Bi-rich composition of the perovskite phase crystallized from melt was Bi_xNa_yTiO₃ (0.5 ≤ X ≤ 0.55, 0.46 ≤ y ≤ 0.5). The crystallization of the Bi-rich BNT perovskite phase first from liquid precursor phase would result in continuous depletion of Bi composition in the residual amorphous phase, and thus Ti-rich amorphous phase in the as-deposited coating and sodium titanate secondary phase in the heat-treated coating formed in the composition without enough access Bi. The results and analyses suggest only appropriate compensation with adequate amount of excess Bi can realize single perovskite phase in thermal sprayed BNT-based coatings and hence the superior piezoelectric performance property.     

How To Quantify the Efficiency Potential of Neat Perovskite Films: Perovskite Semiconductors with an Implied Efficiency Exceeding 28%

Perovskite photovoltaic (PV) cells have demonstrated power conversion efficiencies (PCE) that are close to those of monocrystalline silicon cells; however, in contrast to silicon PV, perovskites are not limited by Auger recombination under 1-sun illumination. Nevertheless, compared to GaAs and monocrystalline silicon PV, perovskite cells have significantly lower fill factors due to a combination of resistive and non-radiative recombination losses. This necessitates a deeper understanding of the underlying loss mechanisms and in particular the ideality factor of the cell. By measuring the intensity dependence of the external open-circuit voltage and the internal quasi-Fermi level splitting (QFLS), the transport resistance-free efficiency of the complete cell as well as the efficiency potential of any neat perovskite film with or without attached transport layers are quantified. Moreover, intensity-dependent QFLS measurements on different perovskite compositions allows for disentangling of the impact of the interfaces and the perovskite surface on the non-radiative fill factor and open-circuit voltage loss. It is found that potassium-passivated triple cation perovskite films stand out by their exceptionally high implied PCEs > 28%, which could be achieved with ideal transport layers. Finally, strategies are presented to reduce both the ideality factor and transport losses to push the efficiency to the thermodynamic limit.     

Risk identification and assessment for build–operate–transfer projects: A fuzzy multi attribute decision making model

In recent years, BOT approach has provided an increasingly popular project financing to move toward infrastructure development in Asian countries such as Iran. There are many complexities in projects because of the variety of factors in project’s trend and also the dependence of project on mainly national factors. Due to these complexities and their long-term operating, the projects meet with uncertainty and numerous risks. In this paper, an attempt is made at identifying common risks in BOT projects. A novel hierarchical structure of risks is presented on the basis of the project-oriented point of view; next, some effective criteria for risk ranking in BOT projects are introduced.Then, the problem is defined in Fuzzy Multi Attribute Decision Making (FMADM) field. Therefore, Fuzzy Technique for Order Preference by Similarity to Ideal Solution (FTOPSIS) and Fuzzy Linear Programming Technique for Multidimensional Analysis of Preference (FLINMAP) methods are presented in order to rank high risks in BOT projects. In this study, these two methods are compared in four respects: separation among alternatives, fuzzy error in criteria’s weights, risk response planning, and numerousness of alternatives in proportion to criteria. The proposed model is used for identifying and assessing risks in Iran BOT power plant project. Finally, the rankings of high risks are determined according to their results at the end of this paper.     

Concrete corrosion in wastewater systems: Prediction and sensitivity analysis using advanced extreme learning machine

The implementation of novel machine learning models can contribute remarkably to simulating the degradation of concrete due to environmental factors. This study considers the sulfuric acid corrosive factor in wastewater systems to simulate concrete mass loss using five machine learning models. The models include three different types of extreme learning machines, including the standard, online sequential, and kernel extreme learning machines, in addition to the artificial neural network, classification and regression tree model, and statistical multiple linear regression model. The reported values of concrete mass loss for six different types of concrete are the target values of the machine learning models. The input variability was assessed based on two scenarios prior to the application of the predictive models. For the first assessment, the machine learning models were developed using all the available cement and concrete mixture input variables; the second assessment was conducted based on the gamma test approach, which is a sensitivity analysis technique. Subsequently, the sensitivity analysis of the most effective parameters for concrete corrosion was tested using three different approaches. The adopted methodology attained optimistic and reliable modeling results. The online sequential extreme learning machine model demonstrated superior performance over the other investigated models in predicting the concrete mass loss of different types of concrete.     

Design and analysis of DC gain and transconductance boosted recycling folded cascode OTA

A new technique for improving the transconductance and low frequency output impedance of recycling folded cascode (RFC) amplifiers is presented. This enhancement was achieved by using a positive feedback and upgrading the recycling structure. The new structure profits from better transconductance, slew rate, and DC gain in comparison with conventional folded cascode (FC) amplifier. Moreover, the input referred noise is reduced and the phase-margin improved. The enhanced amplifier, simulated in 0.18 μm CMOS technology, exhibits a DC gain enhancement of 16.3 dB as well as 115.5 MHz increase in gain bandwidth compared to conventional FC configuration. The amplifier consumes 360 μW @ 1.2 V which makes it suitable for low-voltage applications.     

Plant‐mediated green synthesis of silver nanoparticles using Trifolium resupinatum seed exudate and their antifungal efficacy on Neofusicoccum parvum and Rhizoctonia solani

In recent years, biosynthesis and the utilisation of silver nanoparticles (AgNPs) has become an interesting subject. In this study, the authors investigated the biosynthesis of AgNPs using Trifolium resupinatum (Persian clover) seed exudates. The characterisation of AgNPs were analysed using ultraviolet–visible spectroscopy, X‐ray diffraction (XRD), transmission electron microscopy (TEM) and Fourier transform infra‐red spectroscopy. Also, antifungal efficacy of biogenic AgNPs against two important plant‐pathogenic fungi (Rhizoctonia solani and Neofusicoccum Parvum) in vitro condition was evaluated. The XRD analysis showed that the AgNPs are crystalline in nature and have face‐centred cubic geometry. TEM images revealed the spherical shape of the AgNPs with an average size of 17 nm. The synthesised AgNPs were formed at room temperature and kept stable for 4 months. The maximum distributions of the synthesised AgNPs were seen to range in size from 5 to 10 nm. The highest inhibition effect was observed against R. solani at 40 ppm concentration of AgNPs (94.1%) followed by N. parvum (84%). The results showed that the antifungal activity of AgNPs was dependent on the amounts of AgNPs. In conclusion, the AgNPs obtained from T. resupinatum seed exudate exhibit good antifungal activity against the pathogenic fungi R. solani and N. Parvum.Inspec keywords: silver, nanoparticles, botany, ultraviolet spectra, visible spectra, X‐ray diffraction, transmission electron microscopy, Fourier transform infrared spectra, nanobiotechnology, biological techniquesOther keywords: plant‐mediated green synthesis, silver nanoparticles, Trifolium resupinatum seed exudate, antifungal efficacy, Neofusicoccum parvum, Rhizoctonia solani, biosynthesis, ultraviolet–visible spectroscopy, X‐ray diffraction, transmission electron microscopy, Fourier transform infrared spectroscopy, plant‐pathogenic fungi, XRD analysis, TEM images, antifungal activity, temperature 293 K to 298 K, Ag