Experimental assessment of a novel eutectic binary molten salt-based hexagonal boron nitride nanocomposite as a promising PCM with enhanced specific heat capacity

In this study, novel nanocomposites containing the pre-defined mass ratio of binary molten salt (NaNO3-KNO3: 60-40 wt. %) dispersed with hexagonal boron nitride (hBN) nanoparticles with nominal size of 70 nm, were prepared through one-phase preparation method. Four different types of samples including pure binary molten salt and binary molten salt-based hBN nanocomposites with loading concentrations of 0.5, 1 and 1.5 wt. % were prepared. The proposed amount of sodium nitrate and potassium nitrate was added to certain amount of DI water, comprising with 0.5, 1 and 1.5 wt. % concentration of hBN nanoparticles. Scanning electronic microscopy (SEM) was conducted to evaluate the uniformity of the synthesized binary molten salt-based hBN nanocomposites. The SEM images revealed uniform dispersion of hexagonal boron nitride nanoparticles and fractal-like structures were observed clearly. Specific heat capacity (cp) and melting temperature measurements were performed using a differential scanning calorimetry (DSC). The experimental achieved data for melting temperature proved that hexagonal boron nitride nanoparticles do not affect the melting temperature of the synthesized nanocomposites. The experimentally achieved data for the average cp values of the binary molten salt in solid and liquid phases were 1.14 and 1.13 J/g K, respectively. While, the average cp values for the binary molten salt-based hBN nanocomposite with the highest loading concentration of nanoparticles (1.5 wt. %) in solid and liquid phases were 2 and 3.17 J/g K, respectively. The measured average cp value in the liquid phase for binary molten salt-based hBN nanocomposite with the highest loading concentration (1.5 wt. %) of nanoparticles revealed enhancement of ~180% in comparison with pure binary molten salt. Thermal stability measurements expressed enhancement of thermal stability in binary molten salt induced with hBN nanoparticles. Binary molten salt-based hBN nanocomposite with loading concentration of 1.5 wt. % represented ~16% enhancement in thermal stability over the binary molten salt

An overview of hydrogen as a vehicle fuel

As hydrogen fuel cell vehicles move from manifestation to commercialization, the users expec t safe, convenient and customer-friendly fuelling. Hydrogen quality affects fuel cell stack performance and life time, as well as other factors such as valve operation. In this paper, previous researcher’s development on hydrogen as a possible major fuel of the future has been studied thoroughly .Hydrogen is one of the energy carriers which can replace fossil fuel and can be used as fuel in an internal combustion engines and as a fuel cell in vehicles. To use hydrogen as a fuel of internal combustion engine, engine design should be considered for avoiding abnormal combustion. As a result it can improve engine efficiency, power output and reduce NOx emissions. The emission of fuel cell is low as compared to conventional vehicles but as penalty, fuel cell vehicles need additional space and weight to install the battery and storage tank, thus increases it production cost. The production of hydrogen can be ‘carbon-free’ only if it is generated by employing genuinely carbon-free renewable energy sources. The acceptability of hydrogen technology depends on the knowledge and awareness of the hydrogen benefits towards environment and human life. Recent study shows that people still do not have the sufficient information of hydrogen

ChatGPT and Academic Research: A Review and Recommendations Based on Practical Examples

In the academic world, academicians, researchers, and students have already employed Large Language Models (LLMs) such as ChatGPT to complete their various academic and non-academic tasks, including essay writing, different formal and informal speech writing, summarising literature, and generating ideas. However,  yet, it is a controversial issue to use ChatGPT in academic research. Recently, its impact on academic research and publication has been scrutinized. The fundamental objective of this study is to highlight the application of ChatGPT in academic research by demonstrating a practical example with some recommendations. Data for this study was gathered using published articles, websites, blogs, and visual and numerical artefacts. We have analyzed, synthesized, and described our gathered data using an "introductory literature review." The findings revealed that for the initial idea generation for academic scientific research, ChatGPT could be an effective tool. However, in the case of literature synthesis, citations, problem statements, research gaps, and data analysis, the researchers might encounter some challenges. Therefore, in these cases, researchers must be cautious about using ChatGPT in academic research. Considering the potential applications and consequences of ChatGPT, it is a must for the academic and scientific community to establish the necessary guidelines for the appropriate use of LLMs, especially ChatGPT,  in research and publishing

The Effect of Calcination Rate on the Structure of Mesoporous Bioactive Glasses

Mesoporous bioactive glasses (MBGs) are designed to have high specific surface area. They are formulated by a sol–gel process to formulate the glass followed by calcination. This study evaluates how calcination heating rate influences the porous architecture, and thereby the specific surface area, of MBGs. MBGs of molar ratio 80:15:5 for SiO2 :CaO:P2 O 5 were calcined using both low (1 °C/min) and high (20 °C/min) heating rates, termed as L-MBG and H-MBG, respectively. The results obtained from small-angle X-ray diffraction (SAXRD) confirm that the MBGs possess 2D hexagonal (P6mm) spacing groups and wide-angle XRD confirms the amorphicity of both MBGs. Energy-dispersive X-ray spectroscopy and X-ray photoelectron spectroscopy confirm that both batches of MBGs have similar chemical composition. Fourier transform infrared spectroscopy identifies the same functional groups present in both batches. However, transmission electron microscopy indicates that H-MBG samples exhibited discontinuities in their ordered channel structure, confirmed by the lower SAXRD peak intensity of H-MBG compared to L-MBG. These discontinuities led to a reduced surface area. L-MBG exhibits more than quadruple the surface area and double the pore volume (373.87 m2 /g and 0.27 cm3 /g) of H-MBG (85.91 m2 /g and 0.13 cm3 /g), measured through Brunauer, Emmett, and Teller nitrogen adsorption analysis. This higher surface area resulted in a significant (p \u3c 0.05) increase in the quantity of ion release from the L-MBGs compared to the H-MBGs. It is concluded that the application of a low heating rate during calcination, of the order of 1 °C/min, is more likely to result in ordered mesoporous bioactive glasses with high surface area and pore volume than MBG samples processed at a higher heating rate. [Figure not available: see fulltext.]

Heat transfer and pressure drop characteristics of a plate heat exchanger using water based Al2O3 nanofluid for 30° and 60° chevron angles

Nanofluid is a new class of engineering fluid that has good heat transfer characteristics which is essential to increase the heat transfer performance in various engineering applications such as heat exchangers and cooling of electronics. In this study, experiments were conducted to compare the heat transfer performance and pressure drop characteristics in a plate heat exchanger (PHE) for 30° and 60° chevron angles using water based Al2O3 nanofluid at the concentrations from 0 to 0.5 vol.% for different Reynolds numbers. The thermo-physical properties has been determined and presented in this paper. At 0.5 vol% concentration, the maximum heat transfer coefficient, the overall heat transfer coefficient and the heat transfer rate for 60° chevron angle have attained a higher percentage of 15.14%, 7.8% and 15.4%, respectively in comparison with the base fluid. Consequently, when the volume concentration or Reynolds number increases, the heat transfer coefficient and the overall heat transfer coefficient as well as the heat transfer rate of the PHE (Plate Heat Exchangers) increases respectively. Similarly, the pressure drop increases with the volume concentration. 60° chevron angle showed better performance in comparison with 30° chevron angle

Experimental Investigation of Al2O3 - Water Ethylene Glycol Mixture Nanofluid Thermal Behaviour in a Single Cooling Plate for PEM Fuel Cell Application

AbstractThermal enhancement through application of nanofluid coolant in a single cooling plate of Proton Exchange Membrane (PEM) fuel cell was experimentally investigated in this paper. The study focuses on low concentration of Al2O3 dispersed in Water - Ethylene Glycol mixtures as coolant in a carbon graphite PEM fuel cell cooling plate. The study was conducted in a cooling plate size of 220mm x 300mm with 22 parallel mini channels and large fluid distributors. The mini channel dimensions are 100mm x 1mm x 5mm. A constant heat load of 100W was applied by a heater pad that represents the artificial heat load of a single cell. Al2O3 nanoparticle used was 0.1 and 0.5 vol % concentration which was then dispersed in 50:50 (water: Ethylene Glycol) mixture. The effect of different flow rates to heat transfer enhancement and fluid flow represented in Re number range of 20 to 120 was observed. Heat transfer was improved up to 13.87% for 0.5 vol % Al2O3 as compared to the base fluid. However the pressure drop also increase which result in pumping power increment up to 0.02W. The positive thermal results implied that Al2O3 nanofluid is a potential candidate for future applications in PEM fuel cell thermal management

Optimization of mixed convection in a Lid-driven enclosure with a heat generating circular body.

The physical model considered here is a lid-driven enclosure with bottom heating and top cooling conditions, and a heat generating circular body is placed at the center. The vertical walls of the cavity are kept thermally insulated, and the top lid moves at a constant speed. The steady two-dimensional governing equations for the physical problem are transformed in a dimensionless form with dimensionless governing parameters that decide the fluid flow and heat transfer characteristics in the system. The solution of these transport equations is obtained numerically with the finite element approach using the Galerkin method of weighted residuals. The parametric study has been carried out for variation of the heat generation parameters, the Reynolds numbers, solid-fluid thermal conductivity ratios as well as the Richardson numbers. The working fluid is assigned as air with a Prandtl number of 0.71 throughout the simulation. Results are presented in the form of streamlines, isotherms, average Nusselt number, bulk temperature, and drag force for the afore mentioned parameters. The numerical results indicate the strong influence of the mentioned parameters on the flow structure and heat transfer as well as average Nusselt number, average bulk temperature, and drag force. An optimum combination of the governing parameters would result in higher heat transfer and lower drag force

From ChatGPT-3 to GPT-4: A Significant Advancement in AI-Driven NLP Tools

Recent improvements in Natural Language Processing (NLP) have led to the creation of powerful language models like Chat Generative Pre-training Transformer (ChatGPT), Google’s BARD, Ernie which has shown to be very good at many different language tasks. But as language tasks get more complicated, having even more advanced NLP tool is essential nowadays. In this study, researchers look at how the latest versions of the GPT language model(GPT-4 & 5) can help with these advancements. The research method for this paper is based on a narrative analysis of the literature, which makes use of secondary data gathered from previously published studies including articles, websites, blogs, and visual and numerical facts etc. Findings of this study revealed that GPT-4 improves the model's training data, the speed with which it can be computed, the flawless answers that it provides with, and its overall performance. This study also shows that GPT-4 does much better than GPT-3.5 at translating languages, answering questions, and figuring out how people feel about things. The study provides a solid basis for building even more advanced NLP tools and programmes like GPT-5. The study will help the AI & LLM researchers, NLP developers and academicians in exploring more into this particular field of study. As this is the first kind of research comparing two NLP tools, therefore researchers suggested going for a quantitative research in the near future to validate the findings of this research

Molecular dynamic simulation on the thermal conductivity of nanofluids in aggregated and non-aggregated states

Nanofluids are engineered by suspending nanoparticles in convectional heat transfer fluids to enhance thermal conductivity. This study is aimed at identifying the role of nanoparticle aggregation in enhancing the thermal conductivity of nanofluids. Molecular dynamic simulation with the Green Kubo method was employed to compute thermal conductivity of nanofluids in aggregated and non-aggregated states. Results show that the thermal conductivity enhancement of nanofluids in an aggregated state is higher than in a non-aggregated state, by up to 35. The greater enhancement in aggregated nanofluids is attributed to both higher collision among nanoparticles and increases in the potential energy of nanoparticles