Stability enhancement of polypyrrole thin film ammonia sensor by camphor sulfonic acid dopant

Journal of Materials Science: Materials in Electronics - The main weakness of polymer gas sensors is its stability. Here, we report stability enhancement of a 100 nm polypyrrole (PPy) thin...     

Identification and U-control of a state-space system with time-delay

This article presents a state-space model with time-delay to map the relationship between known input-output data for discrete systems. For the given input-output data, a model identification algorithm combining parameter estimation and state estimation is proposed in line with the causality constraints. Consequently, this article proposes a least squares parameter estimation algorithm, and analyzes its convergence for the studied systems to prove that the parameter estimation errors converge to zero under the persistent excitation conditions. In control system design, the U-model based control is introduced to provide a unilateral platform to improve the design efficiency and generality. A simulation portfolio from modeling to control is provided with computational experiments to validate the derived results.     

Fe3O4-carbon spheres core–shell supported palladium nanoparticles: A robust and recyclable catalyst for suzuki coupling reaction

Suzuki-Miyaura (S-M) is regarded the most powerful way for synthesis biaryls, triaryls, or incorporating of substituted aryl moieties in organic preparation by the cross-coupling of aryl boronic acid with aryl halides using the Pd catalyst. This work reports the combining of the hydrothermal and microwave-assisted protocol to convert the glucose to magnetic carbon spheres (Fe₃O₄-CSPs) decorated with Pd nanoparticles (NPs) as the catalyst for Suzuki-Miyaura cross-coupling reactions. The physicochemical properties in the produced composite were examined using FESEM, HRTEM, nitrogen isotherms, Raman spectroscopy, FTIR, XPS, and XRD. The as-fabricated composite Pd/Fe₃O₄-CSPs is mostly spherical with a core–shell structure and possesses a great surface area of 253.2 m²·g^-1. Its catalytic performance demonstrates that the composite has excellent stability and high tolerance Suzuki-Miyaura cross-coupling reactions in 30 min at 80 ℃. Both activated and deactivated aryl halides provided excellent yield. The as-fabricated catalyst was recycled for up to four catalytic cycles without a substantial decline in performance. Moreover, this research offers a facile roadmap for synthesizing Pd/Fe₃O₄-CSPs composites and promoting the practical implementation of Pd/Fe₃O₄-CSPs catalysts for organic transformation processes.     

Efficient conversion of light paraffinic naphtha to aromatics over metal-modified Mo/MFI catalysts

Journal of Porous Materials - The transformation of light naphtha to value-added aromatic compounds is gaining momentum in the petrochemical industry. In this work, a series of metal modified...     

A machine learning‐based operational control framework for reducing energy consumption of an amine‐based gas sweetening process

This study proposes a data‐driven operational control framework using machine learning‐based predictive modeling with the aim of decreasing the energy consumption of a natural gas sweetening process. This multi‐stage framework is composed of the following steps: (a) a clustering algorithm based on Density‐Based Spatial Clustering of Applications with Noise methodology is implemented to characterize the sampling space of all possible states of the operation and to determine the operational modes of the gas sweetening unit, (b) the lowest steam consumption of each operational mode is selected as a reference for operational control of the gas sweetening process, and (c) a number of high‐accuracy regression models are developed using the Gradient Boosting Machines algorithm for predicting the controlled parameters and output variables. This framework presents an operational control strategy that provides actionable insights about the energy performance of the current operations of the unit and also suggests the potential of energy saving for gas treating plant operators. The ultimate goal is to leverage this data‐driven strategy in order to identify the achievable energy conservation opportunity in such plants. The dataset for this research study consists of 29 817 records that were sampled over the course of 3 years from a gas train in the South Pars Gas Complex. Furthermore, our offline analysis demonstrates that there is a potential of 8% energy saving, equivalent to 5 760 000 Nm³ of natural gas consumption reduction, which can be achieved by mapping the steam consumption states of the unit to the best energy performances predicted by the proposed framework.     

4-aperture differential image motion monitor as a new approach for estimating atmospheric turbulence parameters

The present study aims to evaluate the possibility of simultaneous measurements of Fried parameter and atmospheric Zernike defocus by measuring defocus aberration with 4-aperture differential image motion monitor (DIMM) for a portable telescope. Based on the results, a relation was observed between the variances of the defocus aberration (4-aperture defocus) and Fried parameter for G-tilt and Z-tilt methods. In addition, the variance of the 4-aperture defocus was compared with those of the Zernike defocus and the conventional DIMM and the results indicated a linear relationship. Based on the telescope and 4-aperture specifications, the variance of the 4-aperture defocus was converted into the Zernike defocus or the DIMM variances. Finally, the ability of estimating atmospheric coherence time by measuring the variance of the Zernike defocus velocity or the sum of the variances of two astigmatisms velocities with 4-aperture DIMM was investigated.     

An integrated approach for aircraft turbofan engine fault detection based on data mining techniques

The present study proposes an algorithm for fault detection in terms of condition‐based maintenance with data mining techniques. The proposed algorithm is applied on an aircraft turbofan engine using flight data and consists of two main sections. In the first section, the relationship between engine exhaust gas temperature (EGT) as the main engine health monitoring criterion and other operational and environmental parameters of the engine was modelled using the data‐driven models. In the second section, a data set including EGT residuals, that is, the difference between the actual EGT of the system and the EGT estimated by the developed model in the health conditions of the engine, was created. Finally, faults occurring in each flight were detected based on the identification of abnormal events by a one‐class support vector machine trained by the health condition EGT residual data set. The results indicated that the proposed algorithm was an effective approach for inspecting aircraft engine conditions and detecting faults, with no need for technical knowledge on the interior characteristics of the aircraft engine.     

A lightweight and cost effective edge intelligence architecture based on containerization technology

World Wide Web - The integration of Cloud computing and Internet of Things led to rapid growth in the edge computing field. This would not be achievable without combining the data centers’...     

Uptake of Nickel(II) Ion by Silica-o-Phenylenediamine Derived from Rice Husk Ash

Silicon - The silica-ortho-phenylenediamine(RHAOPDA) derived from Rice Husk Ash and o- phenylenediamine (OPDA) were synthesized. The prepared material was characterized by different techniques; N2-...     

Synthesis of Poly (Vinylidene Fluoride)/Modified SBA-15 Nanoparticles Composite Membrane for Water Purification

One of the methods of pollution separating from urban and industrial wastewater is the use of composite membranes based on polymer. The modified composite