Progressive NO2 Sensors with Rapid Alarm and Persistent Memory-Type Responses for Wide-Range Sensing Using Antimony Triselenide Nanoflakes

Antimony triselenide (Sb₂Se₃) nanoflake-based nitrogen dioxide (NO₂) sensors exhibit a progressive bifunctional gas-sensing performance, with a rapid alarm for hazardous highly concentrated gases, and an advanced memory-type function for low-concentration (<1 ppm) monitoring repeated under potentially fatal exposure. Rectangular and cuboid shaped Sb₂Se₃ nanoflakes, comprising van der Waals planes with large surface areas and covalent bond planes with small areas, can rapidly detect a wide range of NO₂ gas concentrations from 0.1 to 100 ppm. These Sb₂Se₃ nanoflakes are found to be suitable for physisorption-based gas sensing owing to their anisotropic quasi-2D crystal structure with extremely enlarged van der Waals planes, where they are humidity-insensitive and consequently exhibit an extremely stable baseline current. The Sb₂Se₃ nanoflake sensor exhibits a room-temperature/low-voltage operation, which is noticeable owing to its low energy consumption and rapid response even under a NO₂ gas flow of only 1 ppm. As a result, the Sb₂Se₃ nanoflake sensor is suitable for the development of a rapid alarm system. Furthermore, the persistent gas-sensing conductivity of the sensor with a slow decaying current can enable the development of a progressive memory-type sensor that retains the previous signal under irregular gas injection at low concentrations.     

Dielectric behavior of gelatine–glycosaminoglycans blends: An impedance analysis

The dielectric behavior of the gelatine–GAGs based blend systems has been studied to understand the dynamic behavior of the water at the protein–GAGs interfaces which are relevant for tissue engineering application. Impedance (Z) and phase have been measured as a function of frequencies from 0.01 Hz to 100 kHz. GAGs tunes the ionic charge drift which initiates polarization mechanisms through charge accumulation at structural interfaces and creates conduction currents. The admittance results showed that at high frequency, the conductivity increases with increasing GAGs concentration indicating changes in hydration shell of the gelatine by the GAGs.     

Size dependent ferromagnetism in dodecyl amine capped ZnO nanoparticles

We investigated the size dependent ferromagnetism in dodecyl amine capped zinc oxide nanoparticle. X-ray diffraction and X-ray photoelectron spectroscopy analysis demonstrated that density of oxygen vacancies was enhanced due to an increase in compressive strain concomitant with the decrease in particle size. Magnetic measurements showed increased ferromagnetic ordering in ZnO nanoparticles with reduced particle size. It was also found that the increase in coercive field, saturation magnetization and magnetic hysteresis loop area were invariably associated with increased oxygen defect population. The observed ferromagnetism in organic capped zinc oxide nanocrystals has therefore been assigned to defect induced phenomena. Results of sample characterization using optical absorption spectroscopy, photo luminescence spectroscopy and high resolution transmission electron microscope have also been presented.     

Synthesis and compressive behavior of Cr2GeC up to 48 GPa

M_n+1AX_n compounds have gathered huge momentum because of its exciting properties. In this paper we report the synthesis of ternary layered ceramic Cr₂GeC, a 211 M_n+1AX_n compound by hot-pressing. Scanning electron microscopy and X-ray diffraction have been employed to characterize the new synthesized phase. High-pressure compressibility of Cr₂GeC were measured using diamond anvil cell and synchrotron radiation at room temperature up to 48 GPa. No phase transformation was observed in the experimental pressure range. The bulk modulus of Cr₂GeC calculated using the Birch–Murnaghan equation of state is 169 ± 3 GPa, with K′ = 3.05 ± 0.15.     

Solid waste removes toxic liquid waste: adsorption of chromium(VI) by iron complexed protein waste

The leather processing industry generates huge amounts of wastes, both in solid and liquid form. Fleshing from animal hides/skins is one such waste that is high in protein content. In this study, raw fleshing has been complexed with iron and is used for removal of chromium(VI). The effect of pH and the initial concentration of chromium(VI) on the removal of Cr(IV) by iron treated fleshing is presented. Iron treatment is shown to greatly improve adsorption of the fleshing for hexavalent chromium. The ultimate adsorption capacity of iron treated fleshing is 51 mg of chromium(VI) per gram of fleshing. That of untreated fleshing is 9 mg/g such that iron treatment increases the adsorption capacity of fleshing by 10-fold. The measured adsorption kinetics is well described by a pseudo-second-order kinetic model. The uptake of chromium(VI) by fleshing is best described by the Langmuir adsorption isotherm model. X-ray photoelectron spectroscopic (XPS) studies show that the iron is incorporated into the protein matrix. Shifts in XPS spectra suggest that dichromate binding occurs with iron at active adsorption sites and that iron treated fleshing removes chromium(VI) without reducing it to chromium(III).     

Modeling and simulation of temperature drift for ISFET-based pH sensor and its compensation through machine learning techniques

The paper presents modeling and simulation of ion-sensitive field-effect transistor (ISFET)-based pH sensor with temperature-dependent behavioral macromodel and proposes to compensate the temperature drift in the sensor using intelligent machine learning (ML) models. The macromodel is built using SPICE by introducing electrochemical parameters in a metal-oxide-semiconductor field-effect transistor (MOSFET) model to simulate ISFET characteristics. We account for the temperature dependence of electrochemical and semiconductor parameters in our macromodel to increase its robustness. The macromodel is then exported as a subcircuit element, which is used to design the readout interface circuit. A simple constant-voltage, constant-current (CVCC) topology is utilized to generate the data for temperature drift in ISFET pH sensor, which is used to train and test state-of-the-art ML-based regression models in order to compensate the drift behavior. The experimental results demonstrate that the random forest (RF) technique achieves the best performance with very high correlation and low error rate. Corresponding curves for output signal using the trained models show highly temperature-independent characteristics when tested for pH 2, 4, 7, 10, and 12, and we obtained a root mean squared error (RMS) variation of ΔpH ≤ 0.024 over a temperature range of 15°C to 55°C in comparison with ΔpH ≤ 1.346 for uncompensated output signal. This work establishes the framework for integration of ML techniques for drift compensation of ISFET chemical sensor to improve its performance.     

Place Making for Knowledge Generation and Innovation: Planning and Branding Brisbane's Knowledge Community Precincts

Knowledge generation and innovation have been a priority for global city administrators particularly during the last couple of decades. This is mainly due to the growing consensus in identifying knowledge-based urban development as a panacea for burgeoning economic problems. Place making has become a critical element for success in knowledge-based urban development as planning and branding places is claimed to be an effective marketing tool for attracting investment and talent. This paper aims to investigate the role of planning and branding in place making by assessing the effectiveness of planning and branding strategies in the development of knowledge and innovation milieus. The methodology of the study comprises reviewing the literature thoroughly, developing an analysis framework, and using this framework to analyze Brisbane's knowledge community precincts—namely Boggo Road Knowledge Precinct, Kelvin Grove Urban Knowledge Village, and Sippy Downs Knowledge Town. The analysis findings generate invaluable insights into Brisbane's journey in place making for knowledge and innovation milieus and communities. The results suggest as much as good planning, branding strategies, and good practice, the requirements of external and internal conditions also need to be met for successful place making in knowledge community precincts.     

Utilization of the Antiferromagnetic IrMn Electrode in Spin Thermoelectric Devices and Their Beneficial Hybrid for Thermopiles

The thermoelectric effect in various magnetic systems, in which electric voltage is generated by a spin current, has attracted much interest owing to its potential applications in energy harvesting, but its power generation capability has to be improved further for actual applications. In this study, the first instance of the formation of a spin thermopile via a simplified and straightforward method which utilizes two distinct characteristics of antiferromagnetic IrMn is reported: the inverse spin Hall effect and the exchange bias. The former allows the IrMn efficiently to convert the thermally induced spin current into a measurable voltage, and the latter can be used to control the spin direction of adjacent ferromagnetic materials. It is observed that a thermoelectric signal is successfully amplified in spin thermopiles with exchange‐biased IrMn/CoFeB structures, where an alternating magnetic alignment is formed using the IrMn thickness dependence of the exchange bias. The scalable signal on a number of thermopiles allowing a large‐area application paves the way toward the development of practical spin thermoelectric devices. A detailed model analysis is also provided for a quantitative understanding of the thermoelectric voltages, which consist of the spin Seebeck and anomalous Nernst contributions.     

Blast resistance and energy absorption of foam-core cylindrical sandwich shells under external blast

The early time, through-thickness stress wave response of a foam-core, composite sandwich cylindrical shell under external blast is examined in this paper. Solutions for the transient response of the facesheets were derived as stress waves propagated through an elastic–plastic, crushable foam core. These solutions were found to be in good agreement with results from finite element analysis. The blast response of the composite sandwich cylindrical shell was shown to be affected by the magnitude and duration of the pressure pulse. High amplitude, low duration (impulsive) pressure pulses induced the greatest energy absorption. Low amplitude, long duration pressure pulses caused minimal energy absorption. The amount of energy absorbed increased and the failure load decreased with increasing core thickness. Sandwich shells with foams of varying density, compressive modulus and crushing resistance were also examined. The sandwich shells with the foam of the highest density, compressive modulus and crushing resistance (Divinycell HCP100) were found to be the most blast resistant to failure even though no energy was absorbed by them. Per unit weight, however, the shells with a lighter, less stiff and strong, Divinycell H200 foam core were more blast resistant to failure than shells with a Divinycell HCP100 foam core.