Surface Morphology and Thermo-Electrical Energy Analysis of Polyaniline (PANI) Incorporated Cotton Fabric

With the exponential development in wearable electronics,a significant paradigm shift is observed from rigid electronics to flexible wearable devices.Polyaniline(PANI)is considered as a dominant material in this sector,as it is endowed with the optical properties of both metal and semiconductors.However,its widespread application got delineated because of its irregular rigid form,level of conductivity,and precise choice of solvents.Incorporating PANI in textile materials can generate promising functionality for wearable applications.This research work employed a straightforward in-situ chemical oxidative polymerization to synthesize PANI on Cotton fabric surfaces with varying dopant(HCl)concentrations.Pre-treatment using NaOH is implemented to improve the conductivity of the fabric surface by increasing the monomer absorption.This research explores the morphological and structural analysis employing SEM,FTIR and EDX.The surface resistivity was measured using a digital multimeter,and thermal stability is measured using TGA.Upon successful polymerization,a homogenous coating layer is observed.It is revealed that the simple pre-treatment technique significantly reduces the surface resistivity of Cotton fabric to 1.27 kΩ/cm with increasing acid concentration and thermal stability.The electro-thermal energy can also reach up to 38.2°C within 50 s with a deployed voltage of 15 V.The modified fabric is anticipated to be used in thermal regulation,supercapacitor,sensor,UV shielding,antimicrobial and other prospective functional applications.

Artificial Intelligence-Driven Vehicle Fault Diagnosis to Revolutionize Automotive Maintenance:A Review

Conventional fault diagnosis systems have constrained the automotive industry to damage vehicle maintenance and component longevity critically.Hence,there is a growing demand for advanced fault diagnosis technologies to mitigate the impact of these limitations on unplanned vehicular downtime caused by unanticipated vehicle breakdowns.Due to vehicles’increasingly complex and autonomous nature,there is a growing urgency to investigate novel diagnosis methodologies for improving safety,reliability,and maintainability.While Artificial Intelligence(AI)has provided a great opportunity in this area,a systematic review of the feasibility and application of AI for Vehicle Fault Diagnosis(VFD)systems is unavailable.Therefore,this review brings new insights into the potential of AI in VFD methodologies and offers a broad analysis using multiple techniques.We focus on reviewing relevant literature in the field of machine learning as well as deep learning algorithms for fault diagnosis in engines,lifting systems(suspensions and tires),gearboxes,and brakes,among other vehicular subsystems.We then delve into some examples of the use of AI in fault diagnosis and maintenance for electric vehicles and autonomous cars.The review elucidates the transformation of VFD systems that consequently increase accuracy,economization,and prediction in most vehicular sub-systems due to AI applications.Indeed,the limited performance of systems based on only one of these AI techniques is likely to be addressed by combinations:The integration shows that a single technique or method fails its expectations,which can lead to more reliable and versatile diagnostic support.By synthesizing current information and distinguishing forthcoming patterns,this work aims to accelerate advancement in smart automotive innovations,conforming with the requests of Industry 4.0 and adding to the progression of more secure,more dependable vehicles.The findings underscored the necessity for cross-disciplinary cooperation and examined the total potential of AI in vehicle default analysis.

Forestvoltaics,Floatovoltaics and Building Applied Photovoltaics(BAPV)Potential for a University Campus

The United Nations’Sustainable Development Goals(SDGs)highlight the importance of affordable and clean energy sources.Solar energy is a perfect example,being both renewable and abundant.Its popularity shows no signs of slowing down,with solar photovoltaic(PV)panels being the primary technology for converting sunlight into electricity.Advancements are continuously being made to ensure cost-effectiveness,high-performing cells,extended lifespans,and minimal maintenance requirements.This study focuses on identifying suitable locations for implementing solar PVsystems at theUniversityMalaysia PahangAl SultanAbdullah(UMPSA),Pekan campus including buildings,water bodies,and forest areas.A combined technical and economic analysis is conducted using Helioscope for simulations and the Photovoltaic Geographic Information System(PVGIS)for economic considerations.Helioscope simulation examine case studies for PV installations in forested areas,lakes,and buildings.This approach provides comprehensive estimations of solar photovoltaic potential,annual cost savings,electricity costs,and greenhouse gas emission reductions.Based on land coverage percentages,Floatovoltaics have a large solar PV capacity of 32.3 Megawatts(MW);forest-based photovoltaics(Forestvoltaics)achieve maximum yearly savings of RM 37,268,550;and Building Applied Photovoltaics(BAPV)have the lowest CO2 emissions and net carbon dioxide reduction compared to other plant sizes.It also clarifies the purpose of using both software tools to achieve a comprehensive understanding of both technical and economic aspects.

Overview of Jute Fibre as Thermoplastic Matrix Polymer Reinforcement

Recent decades have seen a substantial increase in interest in research on natural fibres that is aligned with sustainable development goals(SDGs).Due to their renewable resources and biodegradability,natural fiberreinforced composites have been investigated as a sustainable alternative to synthetic materials to reduce the usage of hazardous waste and environmental pollution.Among the natural fibre,jute fibre obtained from a bast plant has an increasing trend in the application,especially as a reinforcement material.Numerous research works have been performed on jute fibre with regard to reinforced thermoset and thermoplastic composites.Nevertheless,current demands on sustainable materials have required new developments in thermoplastic composites.In this paper,the author reviews jute plants as reinforcement materials for thermoplastic matrix polymers.This review provides an overview of the sustainability of jute plants as reinforcement material for thermoplastic matrix polymers.The overview on jute based thermoplastic composites focused on the thermal behavior and mechanical properties.Apart from physical,chemical,and mechanical properties,the study also covers the current and perspectives for future research challenges faced by the researchers on jute fibre reinforced thermoplastic composites.

Impact damage behavior of sandwich composite with aluminum foam core

Impact property of the sandwich composite with aluminum foam core was investigated by experiment and simulation analysis. Impact energies of 50, 70 and 100 J were applied to the specimens in impact tests. The results show that the striker penetrates the upper face sheet, causing the core to be damaged at 50 J test but the lower face sheet remains intact with no damage. At 70 J test, the striker penetrates the upper face sheet and the core,and causes the lower face sheet to be damaged. Finally at 100 J test, the striker penetrates both the upper face sheet and the core, and even the lower face sheet. The experimental and simulation results agree with each other. By the confirmation with the experimental results, all these simulation results can be applied on structure study of real sandwich composite with aluminum foam core effectively.

A review of conventional and renewable biodiesel production

The need for sustainable fuels has resulted in the production of renewables from a wide range of sources,in particular organic fats and oils.The use of biofuel is becoming more widespread as a result of environmental and economic considerations.Several efforts have been made to substitute fossil fuels with green fuels.Ester molecules extracted from processed animal fats and organic plant materials are considered alternatives for the use in modern engine technologies.Two different methods have been adopted for converting esters in vegetable oils/animal fats into compounds consistent with petroleum products,namely the transesterification and the hydro-processing of ester bonds for the production of biodiesel.This review paper primarily focuses on conventional and renewable biodiesel feedstocks,the catalyst used and reaction kinetics of the production process.

Biochemical and Thermal Analysis of Spirulina Biomass through FTIR, TGA, CHN

Spirulina is a sort of algae that grows in both fresh and seawater.It is considered the Earth’s most nutritionally dense food.Certain claims about Spirulina’s beneficial health properties are attributed to the relatively high protein content of the cells.Spirulina’s lipid,fatty acid profile,and biochemical composition have received little attention.The purpose of this study is to investigate the nature and decomposition of spirulina biomass at various temperatures.In the present investigation,Fourier transforms infrared spectroscopy,thermogravimetric analysis,and elemental analysis were used to study spirulina biomass biochemical characteristics.The optimal content of spirulina protein,lipid,and the amino acid was identified and reported.In this study,the various frequency ranges corresponding to functional groups are evaluated and reported.Spirulina FT-IR spectra were recorded and reported at different frequency ranges from 3870–3448 cm−1 to 695–545 cm−1.FTIR studies for spirulina biomass affirmed the occurrence of–OH,–COOH,NH,C–H,and C=O groups.Protein(3453 and 1645 cm−1)and carbohydrate(1032 and 1033 cm−1)were the main components with distinct IR spectra fingerprint characteristics.Results indicate that Spirulina sp.biomass is viable green energy and the biggest protein source.The mechanism underlying the high rate of protein accumulation of spirulina may aid in not only elucidating the biochemistry but also in modifying the chemical composition and strain selection for the production of specific chemicals and products.

Effect of Dust and Shadow on Performance of Solar Photovoltaic Modules: Experimental Analysis

This study presents an experimental performance of a solar photovoltaic module under clean,dust,and shadow conditions.It is found that there is a significant decrease in electrical power produced(40%in the case of dust panels and 80%in the case of shadow panels)and a decrease in efficiency of around 6%in the case with dust and 9%in the case with the shadow,as compared to the clean panel.From the results,it is clear that there is a substantial effect of a partial shadow than dust on the performance of the solar panel.This is due to the more obstruction of the sunlight by the shadowed area compared to the dust.The dust being finer particles for the given local experimental condition did not influence the panel than the shadow.The main outcome of this study is that the shadowing effect may cause more harm to the PV module than dust for the given experimental conditions.However,Further long-term studies on the effect of dust and shadow are needed to understand the effect on performance degradation and module life.

Review of MXenes as a component in smart textiles and an adsorbent for textile wastewater remediation

Two-dimensional(2D)MXenes have emerged as an archetypical layered material combining the properties of an organic-inorganic hybrid offering materials sustainability for a range of applications.Their surface functional groups and the associated chemical properties'tailorability through functionalizing MXenes with other materials as well as hydrophilicity and high conductivity enable them to be the best successor for various applications in textile industries,especially in the advancement of smart textiles and remediation of textile wastewater.MXene-based textile composite performs superb smartness in high-performance wearables as well as in the reduction of textile dyes from wastewater.This article critically reviews the significance of MXenes in two sectors of the textile industry.Firstly,we review the improvement of textile raw materials such as fiber,yarn,and fabric by using MXene as electrodes in supercapacitors,pressure sensors.Secondly,we review advancements in the removal of dyes from textile wastewater utilizing MXene as an absorbent by the adsorption process.MXene-based textiles demonstrated superior strength through the strong bonding between MXene and textile structures as well as the treatment of adsorbate by adsorbent(MXene in the adsorption process).We identify critical gaps for further research to enable their real-life applications.

Effects of Spark Energy on Spark Plug Fault Recognition in a Spark Ignition Engine

The increasing demands for fuel economy and emission reduction have led to the development of lean/diluted combustion strategies for modern Spark Ignition(SI)engines.The new generation of SI engines requires higher spark energy and a longer discharge duration to improve efficiency and reduce the backpressure.However,the increased spark energy gives negative impacts on the ignition system which results in deterioration of the spark plug.Therefore,a numerical model was used to estimate the spark energy of the ignition system based on the breakdown voltage.The trend of spark energy is then recognized by implementing the classification method.Significant features were identified from the Information Gain(IG)scoring of the statistical analysis.k-Nearest Neighbor(KNN),Artificial Neural Network(ANN),and SupportVector Machine(SVM)models were studied to identify the best classifier for the classification stage.For all classifiers,the entire featured dataset was randomly divided into standardized parameter values of training and testing data sets with the ratio of 70-30 for each class.It was shown in the study that the KNN classifier acquired the highest Classification Accuracy(CA)of 94.1%compared to ANN and SVM that score 77.3%and 87.9%on the test data,respectively.

Industrial and Small-Scale Biomass Dryers:An Overview

The quality of the drying process depends mainly on the efficient use of thermal energy.Sustainable systems based on solar energy takes a leading role in the drying of agro-products because of low operating cost.However,they are limited in use during off–sun periods.Biomass dryer is one of the simplest ways of drying because of its potential to dry products regardless of time and climate conditions.The other benefit is that crop residues could be used as fuel in these systems.However,the major limitation of the dryer is unequal drying because of poor airflow distribution in the drying medium,which can be improved by integrating some design changes in the dryer.This review analyses the two types of biomass dryers:industrial biomass dryers and small biomass dryers for food product,along with their efficiency.Further,studies on technical,sustainability and economic aspects are expected to provide a greater understanding of biomass drying.

Effect of Flow Field Geometry on Hydrodynamics of Flow in Redox Flow Battery

This study computationally investigates the hydrodynamics of different serpentine flow field designs for redox flow batteries,which considers the Poiseuille flow in the flow channel and the Darcy flow porous substrate.Computational Fluid Dynamics(CFD)results of the in-house developed code based on Finite Volume Method(FVM)for conventional serpentine flow field(CSFF)agreed well with those obtained via experiment.The deviation for pressure drop(ΔP)was less than 5.1%for all the flow rates,thus proving the present CFD analysis’s validity on the modified variation of serpentine flow fields.Modified serpentine flow field-2(MSFF2)design provided least pressure drop across the channel and maximum velocity penetration across the porous substrate when compared to the other designs.This increases its wetting ability,which is very important in terms of mass transfer over potential for electrochemical reaction happening in the porous substrate to achieve effective electrochemical cell performance.

Latent Heat Prediction of Nano Enhanced Phase Change Material by ANN Method

Thermal characteristics of phase change material(PCM)are important in design and utilization of thermal energy storage or other applications.PCMs have great latent heat but suffer from low thermal conductivity.Then,in recent years,nano particles have been added to PCM to improve their thermophysical properties such as thermal conductivity.Effect of this nano particles on thermophysical properties of PCM has been a question and many experimental and numerical studies have been done to investigate them.Artificial intelligence-based approach can be a good candidate to predict thermophysical properties of nano enhance PCM(NEPCM).Then,in this study an artificial neural network(ANN)has been developed to predict the latent heat of the NEPCM.A comprehensive literature search was conducted to acquire thermal characteristics data from various NEPCM to train and test this artificial neural network model.Twenty different types of Nano particle and paraffin based PCMs were used in ANN development.The most important properties which are used as the input for the developed ANN model are NP size,density of NP,latent heat of PCM,density of PCM,concentration and latent heat of NEPCM in the range of 1-60 nm,100-8960 kg/m^(3),89.69-311 kJ/kg,760 to 1520 kg/m^(3),0.02-20 wt%and 60.72-338.6 kJ/kg,respectively.The output variable was latent heat of NEPCM.The result indicates that the ANN model can be applied to predict the latent heat of nano enhanced PCM satisfactory.The correlation coefficient of the created model was 0.97.This result shows ability of ANN to predict the latent heat of NEPCM.

含Mxene新型纳米流体太阳能托盘的数值研究

本研究通过计算研究了Mxene-大豆油纳米流体在单个太阳能托盘中的热学和流体行为。太阳能托盘具有输入口和输出口。在稳定的热通量下,将Mxene纳米流体以不同的体积浓度泵送通过太阳能板。采用计算流体动力学(CFD)流体流动辐射模型,利用太阳能板模拟Mxene纳米流体的热物理实验数据。研究了温度、内能、努塞尔数、传热速率、表面传热系数和表面摩擦因数等热力学和流体力学参数的影响。对于Mxene纳米流体,出口温度、内能和表面摩擦因数的最大增幅分别为3.46%、1.2%和11%。太阳能板的效率提高了30%~32%。此外,新开发的Mxene纳米流体具有很好的热应用前景,热物性能也经过方差分析得到证实。

Energy, economic and environmental performance assessment of a grid-tied rooftop system in different cities of India based on 3E analysis

India is very rich in solar energy,with a total of 3000 sunshine hours annually in most places.The installation of on-grid rooftop electricity-generation photovoltaic(PV)systems is currently undergoing substantial growth and extension as an alternate source of energy that contributes to Indian buildings.This paper analyses the viability of mounting solar PV plants in distinct cities of India in various locations with different climate conditions such as Delhi,Bhopal,Udaipur,Ahmadabad,Thiruvananthapuram,Pune and Madurai.The technical feasibility of installing a 100-kWp system is evaluated using PVsyst software under local climatic conditions.The performance ratio is between 70%and 80%,with a capacity utilization factor of 19-21%and estimated energy output of 170 MWh annually at all sites.The system produces 400-500 kWh of energy daily at a per-unit cost of INR 6-7(Indian rupees)in all locations.The lifespan of the system is~25-30 years,reducing about 150-170 tons of carbon-dioxide emission to the atmosphere every year.The payback period of the system is~5-6 years,which defines its feasibility.This information would encourage organizations and individuals to install such PV plants on the rooftops of buildings to use solar electricity for meeting the energy demands of the country.

Efficiency enhancement of building multi-layer solar collector with SiO2–TiO2 hybrid nanofluids

Due to the depletion of conventional energy sources and its limitless resources,solar energy is currently being considered as a viable alternative,especially for water heating systems.The thermal performance of multilayer solar collectors for water heating systems can be improved further by introducing hybrid nanofluids as advanced fluids.This study demonstrates the utilisation of hybrid nanofluids in heating systems by employing a multilayer absorber solar collector.The SiO2–TiO2 hybrid nanofluids at volume concentrations up to 2.0%were tested at various flow rates(1.7 to 3.7 LPM)and solar radiation intensities(250 to 1000 W/m2).The thermal performance of the solar collector was assessed by measuring the temperature variation,heat loss,and overall efficiency of the collector.At the optimal volume concentration,the temperature difference for solar collectors employing SiO2–TiO2 hybrid nanofluids increased significantly.The optimal volume concentration of 1.5%yields a maximum temperature difference of 9.5°C.In addition,the efficiency and fluid temperature of the solar collector containing hybrid nanofluids have been enhanced by 22%and 37%,respectively.The SiO2–TiO2 hybrid nanofluids with the optimal volume concentration of 1.5%were therefore recommended for maximum efficiency in the solar collector.