A data mining approach to analyze the role of biomacromolecules-based nanocomposites in sustainable packaging.

Recent decades have witnessed a surge in research interest in bio-nanocomposite-based packaging materials, but still, a lack of systematic analysis exists in this domain. Bio-based packaging materials pose a sustainable alternative to petroleum-based packaging materials. The current work employs bibliometric analysis to deliver a comprehensive outline on the role of bio nanocomposites in packaging. India, Iran, and China were revealed to be the top three nations actively engaged in this domain in total publications. Islamic Azad University in Iran and Universiti Putra Malaysia in Malaysia are among the world's best institutions in active research and publications in this field. The extensive collaboration between nations and institutions highlights the significance of a holistic approach towards bio-nanocomposite. The National Natural Science Foundation of China is the leading funding body in this field of research. Among authors, Jong whan Rhim secured the topmost citations (2234) in this domain (13 publications). Among journals, Carbohydrate Polymers secured the maximum citation count (4629) from 36 articles; the initial one was published in 2011. Bio nanocomposite is the most frequently used keyword. Researchers and policymakers focussing on sustainable packaging solutions will gain crucial insights on the current research status on packaging solutions using bio-nanocomposites from the conclusions.

Heat Transfer Enhancement by Hybrid Nano Additives-Graphene Nanoplatelets/Cellulose Nanocrystal for the Automobile Cooling System (Radiator).

A radiator is used to remove a portion of the heat generated by a vehicle engine. It is challenging to efficiently maintain the heat transfer in an automotive cooling system even though both internal and external systems need enough time to keep pace with catching up with evolving engine technology advancements. The effectiveness of a unique hybrid's heat transfer nanofluid was investigated in this study. The hybrid nanofluid was mainly composed of graphene nanoplatelets (GnP), and cellulose nanocrystals (CNC) nanoparticles suspended in a 40:60 ratio of distilled water and ethylene glycol. A counterflow radiator equipped with a test rig setup was used to evaluate the hybrid nano fluid's thermal performance. According to the findings, the proposed GNP/CNC hybrid nanofluid performs better in relation to improving the efficiency of heat transfer of a vehicle radiator. The suggested hybrid nanofluid enhanced convective heat transfer coefficient by 51.91%, overall heat transfer coefficient by 46.72%, and pressure drop by 34.06% with respect to distilled water base fluid. Additionally, the radiator could reach a better CHTC with 0.01% hybrid nanofluid in the optimized radiator tube by the size reduction assessment using computational fluid analysis. In addition to downsizing the radiator tube and increasing cooling capacity over typical coolants, the radiator takes up less space and helps to lower the weight of a vehicle engine. As a result, the suggested unique hybrid graphene nanoplatelets/cellulose nanocrystal-based nanofluids perform better in heat transfer enhancement in automobiles.

Advancing renewable fuel integration: A comprehensive response surface methodology approach for internal combustion engine performance and emissions optimization.

In the realm of internal combustion engines, there is a growing utilization of alternative renewable fuels as substitutes for traditional diesel and gasoline. This surge in demand is driven by the imperative to diminish fuel consumption and adhere to stringent regulations concerning engine emissions. Sole reliance on experimental analysis is inadequate to effectively address combustion, performance, and emission issues in engines. Consequently, the integration of engine modelling, grounded in machine learning methodologies and statistical data through the response surface method (RSM), has become increasingly significant for enhanced analytical outcomes. This study aims to explore the contemporary applications of RSM in assessing the feasibility of a wide range of renewable alternative fuels for internal combustion engines. Initially, the study outlines the fundamental principles and procedural steps of RSM, offering readers an introduction to this multifaceted statistical technique. Subsequently, the study delves into a comprehensive examination of the recent applications of alternative renewable fuels, focusing on their impact on combustion, performance, and emissions in the domain of internal combustion engines. Furthermore, the study sheds light on the advantages and limitations of employing RSM, and discusses the potential of combining RSM with other modelling techniques to optimise results. The overarching objective is to provide a thorough insight into the role and efficacy of RSM in the evaluation of renewable alternative fuels, thereby contributing to the ongoing discourse in the field of internal combustion engines.

Fused Deposition Modelling of Polymer Composite: A Progress.

Additive manufacturing (AM) highlights developing complex and efficient parts for various uses. Fused deposition modelling (FDM) is the most frequent fabrication procedure used to make polymer products. Although it is widely used, due to its low characteristics, such as weak mechanical properties and poor surface, the types of polymer material that may be produced are limited, affecting the structural applications of FDM. Therefore, the FDM process utilises the polymer composition to produce a better physical product. The review's objective is to systematically document all critical information on FDMed-polymer composite processing, specifically for part fabrication. The review covers the published works on the FDMed-polymer composite from 2011 to 2021 based on our systematic literature review of more than 150 high-impact related research articles. The base and filler material used, and the process parameters including layer height, nozzle temperature, bed temperature, and screw type are also discussed in this review. FDM is utilised in various biomedical, automotive, and other manufacturing industries. This study is expected to be one of the essential pit-stops for future related works in the FDMed-polymeric composite study.

A comprehensive review on fused deposition modelling of polylactic acid.

Fused Deposition Modelling (FDM) is one of the additive manufacturing (AM) techniques that have emerged as the most feasible and prevalent approach for generating functional parts due to its ability to produce neat and intricate parts. FDM mainly utilises one of the widely used polymers, polylactic acid, also known as polylactide (PLA). It is an aliphatic polyester material and biocompatible thermoplastic, with the best design prospects due to its eco-friendly properties; when PLA degrades, it breaks down into water and carbon dioxide, neither of which are hazardous to the environment. However, PLA has its limitations of poor mechanical properties. Therefore, a filler reinforcement may enhance the characteristics of PLA and produce higher-quality FDM-printed parts. The processing parameters also play a significant role in the final result of the printed parts. This review aims to study and discover the properties of PLA and the optimum processing parameters. This review covers PLA in FDM, encompassing its mechanical properties, processing parameters, characterisation, and applications. A comprehensive description of FDM processing parameters is outlined as it plays a vital role in determining the quality of a printed product. In addition, PLA polymer is highly desirable for various field industrial applications such as in a medical, automobile, and electronic, given its excellent thermoplastic and biodegradability properties.

Ultrasonication an intensifying tool for preparation of stable nanofluids and study the time influence on distinct properties of graphene nanofluids - A systematic overview.

Optimum ultrasonication time will lead to the better performance for heat transfer in addition to preparation methods and thermal properties of the nanofluids. Nano particles are dispersed in base fluids like water (water-based fluids), glycols (glycol base fluids) &oils at different mass or volume fraction by using different preparation techniques. Significant preparation technique can enhance the stability, effects various parameters & thermo-physical properties of fluids. Agglomeration of the dispersed nano particles will lead to declined thermal performance, thermal conductivity, and viscosity. For better dispersion and breaking down the clusters, Ultrasonication method is the highly influential approach. Sonication hour is unique for different nano fluids depending on their response to several considerations. In this review, systematic investigations showing effect on various physical and thermal properties based on ultrasonication/ sonication time are illustrated. In this analysis it is found that increased power or time of ideal sonication increases the dispersion, leading to higher stable fluids, decreased particle size, higher thermal conductivity, and lower viscosity values. Employing the ultrasonic probe is substantially more effective than ultrasonic bath devices. Low ultrasonication power and time provides best outcome. Various sonication time periods by various research are summarized with respect to the different thermophysical properties. This is first review explaining sonication period influence on thermophysical properties of graphene nanofluids.

Response Ant Colony Optimization of end milling surface roughness.

Metal cutting processes are important due to increased consumer demands for quality metal cutting related products (more precise tolerances and better product surface roughness) that has driven the metal cutting industry to continuously improve quality control of metal cutting processes. This paper presents optimum surface roughness by using milling mould aluminium alloys (AA6061-T6) with Response Ant Colony Optimization (RACO). The approach is based on Response Surface Method (RSM) and Ant Colony Optimization (ACO). The main objectives to find the optimized parameters and the most dominant variables (cutting speed, feedrate, axial depth and radial depth). The first order model indicates that the feedrate is the most significant factor affecting surface roughness.

Thermal Performance of Hybrid-Inspired Coolant for Radiator Application.

Due to the increasing demand in industrial application, nanofluids have attracted the considerable attention of researchers in recent decades. The addition of nanocellulose (CNC) with water (W) and ethylene glycol (EG) to a coolant for a radiator application exhibits beneficial properties to improve the efficiency of the radiator. The focus of the present work was to investigate the performance of mono or hybrid metal oxide such as Al2O3 and TiO2 with or without plant base-extracted CNC with varying concentrations as a better heat transfer nanofluid in comparison to distilled water as a radiator coolant. The CNC is dispersed in the base fluid of EG and W with a 60:40 ratio. The highest absorption peak was noticed at 0.9% volume concentration of TiO2, Al2O3, CNC, Al2O3/TiO2, and Al2O3/CNC nanofluids which indicates a better stability of the nanofluids' suspension. Better thermal conductivity improvement was observed for the Al2O3 nanofluids in all mono nanofluids followed by the CNC and TiO2 nanofluids, respectively. The thermal conductivity of the Al2O3/CNC hybrid nanofluids with 0.9% volume concentration was found to be superior than that of the Al2O3/TiO2 hybrid nanofluids. Al2O3/CNC hybrid nanofluid dominates over other mono and hybrid nanofluids in terms of viscosity at all volume concentrations. CNC nanofluids (all volume concentrations) exhibited the highest specific heat capacity than other mono nanofluids. Additionally, in both hybrid nanofluids, Al2O3/CNC showed the lowest specific heat capacity. The optimized volume concentration from the statistical analytical tool was found to be 0.5%. The experimental results show that the heat transfer coefficient, convective heat transfer, Reynolds number and the Nusselt number have a proportional relationship with the volumetric flow rate. Hybrid nanofluids exhibit better thermal conductivity than mono nanofluids. For instance, a better thermal conductivity improvement was shown by the mono Al2O3 nanofluids than the CNC and TiO2 nanofluids. On the other hand, superior thermal conductivity was observed for the Al2O3/CNC hybrid nanofluids compared to the other mono and hybrid ones (Al2O3/TiO2).