Index for vehicle acoustical comfort inside a passenger car

Sound quality is among the main factors that influence customers’ preference for choosing good automobile products. It all started more than 10 years ago and grows up so fast due to high competition in the automotive industries. A-weighted noise levels and sound power are usually utilised to measure the noise but they are not adequate to characterise the impact sound inside a car. The most popular approach to determine sound quality of a product is to define an annoyance or specific index, which involves both subjective and objective evaluations. Subjective and objective tests should be studied concurrently in order to determine the sound quality inside a passenger car. This approach is used in this paper to evaluate vehicle comfort index according to most frequently used sound quality metrics, namely; Zwicker loudness, sharpness, roughness and fluctuation strength. As a result researchers of different fields of automotive acoustics investigations can use this index according to the type of road (international road roughness) without any need to perform time-consuming jury tests. The metrics are correlated with jury test results that show which of them and how much has affected the acoustical comfort of the vehicle. The relation between road roughness and vehicle acoustical comfort index is another point of interest in this research.     

Selective hydroaminomethylation of olefins using simple and efficient Rh–phosphinite complex catalyst

Hydroaminomethylation of various olefins with primary and secondary amines was carried out using a simple and efficient rhodium–phosphinite complex catalyst. The influence of various reaction parameters including the effects of temperature, pressure, catalyst loading, time and solvents has been investigated. The present protocol is general with wider substrate applicability for the synthesis of an important class of aliphatic amines and arylethylamines. High activity and selectivity for amines was achieved with a very good substrate/catalyst molar ratio (turnover number 2500) under mild reaction conditions. Copyright © 2013 John Wiley & Sons, Ltd.     

Artificial neural network‐based modeling of snow properties using field data and hyperspectral imagery

This study attempts to model snow wetness and snow density of Himalayan snow cover using a combination of Hyperspectral image processing and Artificial Neural Network (ANN). Initially, a total of 300 spectral signature measurements, synchronized with snow wetness and snow density, were collected in the field. The spectral reflectance of snow was then modeled as a function of snow properties using ANN. Four snow wetness and three snow density models were developed. A strong correlation was observed in near‐infrared and shortwave‐infrared region. The correlation analysis of ANN modeled snow density and snow wetness showed a strong linear relationship with field‐based data values ranging from 0.87–0.90 and 0.88–0.91, respectively. Our results indicate that an Artificial Intelligence (AI) approach, using a combination of Hyperspectral image processing and ANN, can be efficiently used to predict snow properties (wetness and density) in the Himalayan region. Recommendations for resource managers

• Snow properties, such as snow wetness and snow density are mainly investigated through field‐based survey but rugged terrains, difficult weather conditions, and logistics management issues establish remote sensing as an efficient alternative to monitor snow properties, especially in the mountain environment.
• Although Hyperspectral remote sensing is a powerful tool to conduct the quantitative analysis of the physical properties of snow, only a few studies have used hyperspectral data for the estimation of snow density and wetness in the Himalayan region. This could be because of the lack of synchronized snow properties data with field‐based spectral acquisitions.
• In combination with Hyperspectral image processing, Artificial Neural Network (ANN) can be a useful tool for effective snow modeling because of its ability to capture and represent complex input‐output relationships.
• Further research into understanding the applicability of neural networks to determine snow properties is required to obtain results from large snow cover areas of the Himalayan region.

     

Amperometric determination of nanomolar mercury(II) by layered double nanocomposite of zinc/aluminium hydroxide-3(4-methoxyphenyl)propionate modified single-walled carbon nanotube paste electrode

Ionics - A mercury(II) sensor was developed by using single-walled carbon nanotube (SWCNT) paste electrode modified with layered double Zn/Al hydroxide-3(4-methoxyphenyl)propionate nanocomposite...     

Surface Functionalization of Magnetite Nanoparticles with Multipotent Antioxidant as Potential Magnetic Nanoantioxidants and Antimicrobial Agents

Functionalized magnetite nanoparticles (Fe₃O₄) were prepared using the coprecipitation method followed by functionalization with a multipotent antioxidant (MPAO). The MPAO was synthesized and analyzed using FTIR and NMR techniques. In this study, the functionalized nanoparticles (IONP@AO) were produced and evaluated using the FTIR, XRD, Raman, HRTEM, FESEM, VSM, and EDX techniques. The average determined particle size of IONP@AO was 10 nanometers. In addition, it demonstrated superparamagnetic properties. The magnitude of saturation magnetization value attained was 45 emu g⁻¹. Virtual screenings of the MPAO’s potential bioactivities and safety profile were performed using PASS analysis and ADMET studies before the synthesis step. For the DPPH test, IONP@AO was found to have a four-fold greater ability to scavenge free radicals than unfunctional IONP. The antimicrobial properties of IONP@AO were also demonstrated against a variety of bacteria and fungi. The interaction of developed nanoantioxiants with biomolecules makes it a broad-spectrum candidate in biomedicine and nanomedicine.     

Biotic Cathode of Graphite Fibre Brush for Improved Application in Microbial Fuel Cells

The biocathode in a microbial fuel cell (MFC) system is a promising and a cheap alternative method to improve cathode reaction performance. This study aims to identify the effect of the electrode combination between non-chemical modified stainless steel (SS) and graphite fibre brush (GFB) for constructing bio-electrodes in an MFC. In this study, the MFC had two chambers, separated by a cation exchange membrane, and underwent a total of four different treatments with different electrode arrangements (anodeǁcathode)—SSǁSS (control), GFBǁSS, GFBǁGFB and SSǁGFB. Both electrodes were heat-treated to improve surface oxidation. On the 20th day of the operation, the GFBǁGFB arrangement generated the highest power density, up to 3.03 W/m³ (177 A/m³), followed by the SSǁGFB (0.0106 W/m³, 0.412 A/m³), the GFBǁSS (0.0283 W/m³, 17.1 A/m³), and the SSǁSS arrangements (0.0069 W/m⁻³, 1.64 A/m³). The GFBǁGFB had the lowest internal resistance (0.2 kΩ), corresponding to the highest power output. The other electrode arrangements, SSǁGFB, GFBǁSS, and SSǁSS, showed very high internal resistance (82 kΩ, 2.1 kΩ and 18 kΩ, respectively) due to the low proton and electron movement activity in the MFC systems. The results show that GFB materials can be used as anode and cathode in a fully biotic MFC system.     

Gas by-products of CF3I under AC partial discharge

This paper presents the decomposition by-products of trifluro-iodo-methane and their relative proportions in the gas phase under the occurrence of partial discharge. The experiment was performed in the presence of water vapor from 250 to 400 ppm under a non-uniform electric field configuration. The experimental results reveal that the by-products of C₂F₆, C₂F₄, C₂F₅I with the amount of 1300, 200, and 55 (CH₃I) ppm, respectively, were produced for a cumulative charge of 161 mC. Other by-products, such as C₃F₈, CHF₃, C₃F₆ CH₃I were obtained at less than 30 ppm C₂F₆ was the dominant gas by-product of trifluro-iodo-methane suffering partial discharge.     

Indentation studies on 〈1 0 0〉, 〈0 0 1〉 and 〈1 0 1〉 face of ammonium dihydrogen phosphate (ADP) single crystals: A novel nonlinear optical material

In the present work, Vickers microhardness measurements were carried out on different faces i.e. (1 0 0), (0 0 1) and (1 0 1) of ammonium dihydrogen phosphate (ADP) single crystals grown by slow evaporation solution technique at room temperature in the load ranging from 0.2 to 2 N. The obtained results show that the load independent hardness values are 0.8, 0.7 and 0.66 GPa, respectively at different faces of ADP crystal. From the crack length measurements, the fracture toughness values (K_c) was estimated using Evans and Anstis model and the present studies suggest that Evans model is more relevant when compared to Anstis model. The load variation of some mechanical properties viz. brittle index number (B_i) and yield strength (σ_y) for ADP have also been calculated for the first time.