Thermal stability of HCl‐doped‐polyaniline and TiO2 nanoparticles‐based nanocomposites

Electrically conductive HCl doped polyaniline (Pani) : titanium dioxide (TiO₂) nanocomposites thin films were prepared by in‐situ oxidative polymerization of aniline in the presence of different amounts of TiO₂ nanoparticles. Later film casting was done using N‐Methyl‐2‐pyrrolidone (NMP) as a solvent. The formation of Pani : TiO₂ nanocomposites were characterized by Fourier Transform Infra‐Red spectroscopy (FTIR), x‐ray diffraction (XRD) and thermogravimetric analysis (TGA). The stability of the nanocomposites in terms of direct‐current electrical conductivity retention was studied in air by isothermal and cyclic techniques. The films of Pani : TiO₂ nanocomposites were observed thermally more stable under ambient environmental conditions than pure polyaniline film. The stability was seen to be highly dependent on the content of TiO₂ nanoparticles in the nanocomposite films. Due to their high stability, such type of nanocomposites can find place as a replacement material for pure polyaniline in electrical and electronic devices. © 2011 Wiley Periodicals, Inc. J Appl Polym Sci, 2011     

Boron in Tribology: From Borates to Ionic Liquids

Boron compounds are widely used in a range of tribological applications such as friction modifiers, antioxidants, antiwear additives, and in many cases as environmentally friendly lubricants. The chemical nature and structure of boron compounds provide multifunctionality. They are used as (1) solid lubricants such as boric acid and hexagonal boron nitride, (2) liquid lubricants such as ionic liquids, (3) lubricant additives such as borate derivatives of various organic and inorganic compounds, and (4) coatings such as cubic boron nitride and different metal borides. Boron is also one of the most favorable elements for coatings and thin films in biotribological and biomedical applications. This review outlines the growing role of boron in lubrication over the past several decades, summarizes the main findings, and identifies future challenges related to boron chemistry.     

Electroanalytical studies on electrically conducting polyaniline:polyethyleneterephthalate composite films

Polyaniline (PANI):polyethyleneterephthalate (PET) composite was prepared by chemical polymerization of aniline diffused in the PET matrix. Thus prepared composite films were characterized by fourier‐transform infrared spectroscopy and scanning electron microscopy and their electrical properties and the thermo‐oxidative stability was studied by thermogravimetry and differential thermal analysis. The stability in terms of DC electrical conductivity retention was studied in an oxidative environment by two slightly different techniques viz. isothermal and cyclic techniques. DC electrical conductivity of composite films was found to be stable up to 90°C for most of the composites under ambient conditions. The composite films were employed as cathode material in secondary cells containing 1M ZnCl₂ solution. The studies were carried out on the charge/discharge cycles under a constant current load 140 mA. The composite films showed similar behavior in electrolyte solution and cell response is reversible. To determine the diffusion coefficient for the chloride ions diffusion into the composite films electrochemically, galvanostatic pulse method was used. The diffusion coefficient was estimated to be ～ 3.28 × 10^?12 cm² s^?1. © 2010 Wiley Periodicals, Inc. J Appl Polym Sci, 2010     

Reconstruction of Grenfell Tower fire. Part 3—Numerical simulation of the Grenfell Tower disaster: Contribution to the understanding of the fire propagation and behaviour during the vertical fire spread

The dramatic event of the Grenfell Tower (June 2017), involving a combustible façade system, has raised concerns regarding the fire risk that these systems address. Indeed, as façades are complex systems, it is not straightforward to assess which part of the system is involved in the global fire behaviour. Understanding such façade fires is thus very complex as it depends on a combination of various products and system characteristics, including window frames or air gap or cavity barriers. Fire development inside the initial apartment was investigated using an appropriate CFD model with different scenarios for the fire source and ventilation conditions in a previous study. Fire propagation through the window to the external façade and to higher apartments was modelled and validated against visual observations. This paper describes CFD modelling of the complete Grenfell tower facade, and investigates vertical fire spread behaviour over the full height façade from the initial apartment. Contributions from the combustion of all the apartments' furniture, depending on window failure, and architectural details of the refurbished façade are considered in the numerical model. The modelling results are validated by comparison with photographic and video observations of the real fire.     

Recent progress in silicon-based solid-state solar cells

Silicon (Si)-based solar cells constitute about 90% of the photovoltaic (PV) market, and a drastic reduction in module cost and significant improvement in PV performance have been observed since its first inception in 1941. This article aims to present the comprehensive review of prominent advancements enacted in Si solar cells after the year 2000. Monocrystalline Si solar cell has been the matured technology with the record efficiency (η) of 26.6% achieved so far. As the drive to push η around 30% Schokley–Quiesser limit is foreseeable in the near future, PV community is actively striving to fabricate efficient yet cost-effective devices. Polycrystalline Si solar cells contain small-sized grains, and efforts are underway to enhance the η beyond 21.9% by controlling the recombination at grain boundaries, optimising the passivated interfaces and deposition process. Thin-film amorphous Si technology proffers low-cost fabrication process and η of 13.6% has been recorded for a multijunction solar cell. Employment of sophisticated nanowire-based light trapping schemes and dopant-free carrier-selective layers along with the development of hybrid solar cells of organic and Si materials are among the emerging research trends for Si solar cells.     

Projection Pursuit Evaluation Model of Regional Surface Water Environment Based on Improved Chicken Swarm Optimization Algorithm

A Projection Pursuit Evaluation model of surface water environment based on an Improved Chicken Swarm Optimization Algorithm (ICSOA-PPE) is constructed using the ICSOA to optimize the optimal projection direction. Using the Jiansanjiang Administration in Heilongjiang Province, China as an example, 15 subordinate farms were used as an evaluation unit by selecting water quality indexes including COD_Mn, NH₃-N, TP, TN, F^? to evaluate the environmental quality of surface water using the ICSOA-PPE model. The results show that the environmental quality of surface water from all farms in this region was generally poor, except for that at the Qinglongshan, Qindeli and Daxing farms. These three farms met the standard for drinking water sources, while the remaining farms failed to reach the standard. By analyzing the relationship between the total amount of chemical fertilizer application per ha, the amount of nitrogen fertilizer application per ha, the amount of phosphate fertilizer application per ha and the environmental quality of the surface water, a conclusion could be reached that the total amount of chemical fertilizer has a substantial effect on water environment. Additionally, the contribution rate of the amount of nitrogen fertilizer application per ha to the organic pollution and the concentration of NH₃-N is substantial, and the amount of phosphate fertilizer influences the water environmental quality to some extent. An analysis and comparison of the traversal capacity, the offset capacity and the convergence capacity of the Genetic Algorithm (GA), the Chicken Swarm Optimization Algorithm (CSOA) and ICSOA reveal that ICSOA is the better optimization algorithm, indicating that the ICSOA-PPE model is logical and reliable.     

Simulation of an efficient silicon heterostructure solar cell concept featuring molybdenum oxide carrier‐selective contact

Transition metal oxides/silicon heterocontact solar cells are the subject of intense research efforts owing to their simpler processing steps and reduced parasitic absorption as compared with the traditional silicon heterostructure counterparts. Recently, molybdenum oxide (MoO_x, x < 3) has emerged as an integral transition metal oxide for crystalline silicon (cSi)‐based solar cell based on carrier‐selective contacts (CSCs). In this paper, we physically modelled the CSC‐based cSi solar cell featuring MoO_x/intrinsic a‐Si:H/n‐type cSi/intrinsic a‐Si:H/n⁺‐type a‐Si:H for the first time using Silvaco technology computer‐aided design simulator. To analyse the optical and electrical properties of the proposed solar cell, several technological parameters such as work function and thickness of MoO_x contact layer, intrinsic a‐Si:H band gap, interface recombination, series resistance, and temperature coefficient have been evaluated. It has been shown that higher work function of MoO _x induces the formation of a favourable Schottky barrier height as well as an inversion at the front interface, stimulating least resistive path for holes. Utilising thinner MoO_x layer implies reduced tunnelling of minority charge carriers, thus enabling the device to numerically attain 25.33% efficiency. With an optimised interface recombination velocity and reduced parasitic absorption, the proposed device exhibited higher V_oc of 752 mV, J_sc of 38.8 mA/cm², fill‐factor of 79.0%, and an efficiency of 25.6%, which can be termed as the harbinger for industrial production of next‐generation efficient solar cell technology.     

A meta-heuristic framework for forecasting household electricity consumption

It may be difficult to model household electricity consumption with conventional methods such as regression due to seasonal and monthly changes. This paper illustrates a flexible integrated meta-heuristic framework based on Artificial Neural Network (ANN) Multi Layer Perceptron (MLP), conventional regression and design of experiment (DOE) for forecasting household electricity consumption. Previous studies base their verification by the difference in error estimation, whereas this study uses various error estimation methods and design of experiment (DOE). Moreover, DOE is based on analysis of variance (ANOVA) and Duncan Multiple Range Test (DMRT). Furthermore, actual data is compared with ANN MLP and conventional regression model through ANOVA. If the null hypothesis is accepted, DMRT is used to select either ANN MLP or conventional regression. However, if the null hypothesis is accepted then the proposed framework selects either the MLP or regression model based on the average of Minimum Absolute Percentage Error (MAPE), Mean Square Error (MSE) and Mean Absolute Error (MAE). The significance of this study is the integration of ANN MLP, conventional regression and DOE for flexible modeling and improved processing, development and testing of household electricity consumption. Some of the previous studies assume that ANN MLP provide better estimation and others estimate electricity consumptions based on the conventional regression approach. However, this study presents a flexible integrated framework to locate the best model based on the actual data. Moreover, it would provide more reliable and precise forecasting for policy makers. To show the applicability and superiority of the integrated approach, annual household electricity consumption in Iran from 1974 to 2003 was collected for processing, training and testing purpose.