Modeling unaccounted-for gas among residential natural gas consumers using a comprehensive fuzzy cognitive map

Residential natural gas consumption depends on several factors. Available tools and methods to identify, categorize, and validate effective factors have some limitations, making consumption modeling more complex. Once a comprehensive model of effective consumption factors is developed for residential gas consumers, it can predict consumption. In addition, such a model could be used to verify the accuracy of measuring devices in order to reduce unaccounted for gas (UFG). The key factors affecting residential gas consumption were identified based on previous studies and their mutual effects were analyzed using a fuzzy cognitive mapping (FCM) method. The most significant factors and their effects on natural gas consumption in the residential sector were determined. In this study, for the first time, the expected consumption for each consumer was estimated using a consumption index. Generally, if the estimated consumption is significantly different from the amount recorded by the meter, it could suggest a potential source of UFG. The proposed method was applied to the data collected from the residential gas consumers of a small region in Iran (Dasht-e Arjan region, Fars province), and the results demonstrate the effectiveness of the proposed method.     

Estimating long-term time-resolved indoor PM2.5 of outdoor and indoor origin using easily obtainable inputs

To evaluate the separate impacts on human health and establish effective control strategies, it is crucial to estimate the contribution of outdoor infiltration and indoor emission to indoor PM_2.5 in buildings. This study used an algorithm to automatically estimate the long-term time-resolved indoor PM_2.5 of outdoor and indoor origin in real apartments with natural ventilation. The inputs for the algorithm were only the time-resolved indoor/outdoor PM_2.5 concentrations and occupants’ window actions, which were easily obtained from the low-cost sensors. This study first applied the algorithm in an apartment in Tianjin, China. The indoor/outdoor contribution to the gross indoor exposure and time-resolved infiltration factor were automatically estimated using the algorithm. The influence of outdoor PM_2.5 data source and algorithm parameters on the estimated results was analyzed. The algorithm was then applied in four other apartments located in Chongqing, Shenyang, Xi'an, and Urumqi to further demonstrate its feasibility. The results provided indirect evidence, such as the plausible explanations for seasonal and spatial variation, to partially support the success of the algorithm used in real apartments. Through the analysis, this study also identified several further development directions to facilitate the practical applications of the algorithm, such as robust long-term outdoor PM_2.5 monitoring using low-cost light-scattering sensors.     

NiFe layered double hydroxide as an efficient bifunctional catalyst for electrosynthesis of hydrogen peroxide and oxygen

Two electron oxygen reduction reaction to produce hydrogen peroxide (H₂O₂) is a promising alternative technique to the multistep and high energy consumption anthraquinone process. Herein, Ni–Fe layered double hydroxide (NiFe-LDH) has been firstly demonstrated as an efficient bifunctional catalyst to prepare H₂O₂ by electrochemical oxygen reduction (2e^? ORR) and oxygen evolution reaction (OER). Significantly, the NiFe-LDH catalyst possesses a high faraday efficiency of 88.75% for H₂O₂ preparation in alkaline media. Moreover, the NiFe-LDH catalyst exhibits excellent OER electrocatalytic property with small overpotential of 210 mV at 10 mA cm^?2 and high stability in 1 M KOH solution. On this basis, a new reactor has been designed to electrolyze oxygen and generate hydrogen peroxide. Under the ultra-low cell voltage of 1 V, the H₂O₂ yield reaches to 47.62 mmol g_cat^?1 h^?1. In order to evaluate the application potential of the bifunctional NiFe-LDH catalyst for H₂O₂ preparation, a 1.5 V dry battery has been used as the power supply, and the output of H₂O₂ reaches to 83.90 mmol g_cat^?1 h^?1. The excellent electrocatalytic properties of 2e^? ORR and OER make NiFe-LDH a promising bifunctional electrocatalyst for future commercialization. Moreover, the well-designed 2e^? ORR-OER reactor provides a new strategy for portable production of H₂O₂.     

An integrated dimensionality reduction and surrogate optimization approach for plant-wide chemical process operation

With liquefied natural gas becoming increasingly prevalent as a flexible source of energy, the design and optimization of industrial refrigeration cycles becomes even more important. In this article, we propose an integrated surrogate modeling and optimization framework to model and optimize the complex CryoMan Cascade refrigeration cycle. Dimensionality reduction techniques are used to reduce the large number of process decision variables which are subsequently supplied to an array of Gaussian processes, modeling both the process objective as well as feasibility constraints. Through iterative resampling of the rigorous model, this data-driven surrogate is continually refined and subsequently optimized. This approach was not only able to improve on the results of directly optimizing the process flow sheet but also located the set of optimal operating conditions in only 2 h as opposed to the original 3 weeks, facilitating its use in the operational optimization and enhanced process design of large-scale industrial chemical systems.     

Characterization of barium titanate reinforced acrylonitrile butadiene rubber composites for flexible electronic applications: influences of barium titanate content

The aim of this study was to develop high dielectric constant flexible polymers with a highly efficient and cost‐effective approach using acrylonitrile butadiene rubber (NBR) as the polymer matrix and barium titanate (BT) as the high dielectric constant filler. The BT powder was synthesized with a solid‐state reaction and was characterized using a particle size analyzer, XRD, SEM and Fourier transform infrared spectroscopy. NBR/BT composites were fabricated using an internal mixer with various BT loadings up to 160 phr. The influence of BT loading on the cure characteristics and mechanical, dynamic mechanical, thermal, dielectric and morphological properties was determined. The incorporation of BT in the NBR matrix shortened scorch time and increased delta torque. The mechanical properties, thermal stability and dielectric constant were greatly improved and increased with BT loading. The results suggest that the reinforcement effect was achieved due to strong hydrogen bonding or polar–polar interactions between NBR matrix and BT filler. This is further corroborated by the good dispersion of BT filler in the NBR matrix observed with SEM imaging. These findings can be applied to produce high‐performance dielectric elastomers. © 2020 Society of Industrial Chemistry     

Plant Copper Amine Oxidases: Key Players in Hormone Signaling Leading to Stress-Induced Phenotypic Plasticity

Polyamines are ubiquitous, low-molecular-weight aliphatic compounds, present in living organisms and essential for cell growth and differentiation. Copper amine oxidases (CuAOs) oxidize polyamines to aminoaldehydes releasing ammonium and hydrogen peroxide, which participates in the complex network of reactive oxygen species acting as signaling molecules involved in responses to biotic and abiotic stresses. CuAOs have been identified and characterized in different plant species, but the most extensive study on a CuAO gene family has been carried out in Arabidopsis thaliana. Growing attention has been devoted in the last years to the investigation of the CuAO expression pattern during development and in response to an array of stress and stress-related hormones, events in which recent studies have highlighted CuAOs to play a key role by modulation of a multilevel phenotypic plasticity expression. In this review, the attention will be focused on the involvement of different AtCuAOs in the IAA/JA/ABA signal transduction pathways which mediate stress-induced phenotypic plasticity events.     

Effect of H2O2 concentration on electrochemical growth and properties of vertically oriented ZnO nanorods electrodeposited from chloride solutions

In this work, ZnO nanostructures are electrodeposited on a transparent conducting glass from chloride baths. The influence of H₂O₂ concentration on the electrochemical characteristics has been studied using cyclic voltammetry (CV) and chronoamperometry (CA) techniques. From the analysis of the current transients on the basis of the Scharifker–Hills model, it is found that nucleation mechanism is progressive with a typical three-dimensional (3D) nucleation and growth process; independently with the concentration of H₂O₂. However, the nucleation rate of the ZnO changes with the increase of H₂O₂ concentration. The Mott–Schottky measurements demonstrate an n-type semiconductor character for all samples with a carrier density varying between 5.14×10¹⁸ cm⁻³ and 1.47×10¹⁸ cm⁻³. Scanning electron microscopy (SEM) observations show arrays of vertically aligned ZnO nanorods (NRs) with good homogeneity. The X-ray diffraction (XRD) patterns show that the ZnO deposited crystallises according to a hexagonal Würtzite-type structure and with the c-axis perpendicular to the electrode surface. The directional growth along (002) crystallographic plane is very important for deposits obtained at 5 and 7 mM of H₂O₂. The high optical properties of the ZnO NRs with a low density of deep defects was checked by UV–vis transmittance analyses, the band gap energy of films varies between 3.23 and 3.31 eV with transparency around 80–90%.     

The formation of fibrous structure of polyamide 6 induced by the three-step forming process and its prominent reinforcement in nitrile rubber

Nitrile rubber (NBR) blends with excellent performance have always been a hot research topic in petroleum field. Due to the excellent performance and compatibility of polyamide 6 (PA6), it provides an opportunity for the preparation of high-performance NBR/PA6 blends. In this article, NBR/PA6 blends were prepared by the three-step molding process. Experimentally, it was found that PA6 has a prominent reinforcement effect in NBR matrix. The variation of this mechanical property was investigated from different aspects of the crystal structure, crystallinities, phase morphology, and so on. It can be cleared that the formation of fibrous structure of PA6 phase is the main factor for reinforcement of the polymer blends. Meanwhile, the formation mechanism of the special phase structure induced by the three-step process is deeply expounded and its structural evolution schematic is established. © 2019 Wiley Periodicals, Inc. J. Appl. Polym. Sci. 2019 , 136, 47472.