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Gaseous-liquid fuel combinations of biogas as primary fuel and diesel as pilot fuel were employed to power a compression ignition (CI) engine in this study. The effects of variable input factors such as engine load, compression ratio, and pilot fuel injection advance on the dual-fuel engine's combustion, thermal, and emission performance were investigated. The data acquired during this lab-based testing was used to develop a prognostic model using a Bayesian optimization strategy for hyperparameter optimization and a contemporary ensemble Gaussian process regression (GPR) technique. During model testing, the error analysis revealed that the developed model could predict the experimental data rather correctly, with R2 values ranging from 0.9995 to 0.9999 and MSE values ranging from 0.00018 to 0.1334. The mean absolute error was discovered to be between 0.0091 and 0.3065. Consequently, the developed GPR model can effectively simulate the on-board performance, emission, and combustion characteristics of a diesel-biogas dual-fuel setting. As a consequence, the current work established the GPR model in the existing CI engine meta-modeling framework as a consistent, trustworthy, and robust system analytical approach for diesel-biogas dual fuel mode of operation. • Waste-derived biogas was used to power the diesel engine in dual-fuel mode. • Gaussian process regression was employed to develop a prognostic model. • Bayesian approach was used for hyper parameter optimization for best results. • Used model could predict emission and performance of the engine with 99.9% accuracy. • A precise metamodel framework to simulate the input–output paradigm was developed. [ABSTRACT FROM AUTHOR]

Summary: Hybrid nanofluids are gaining popularity owing to the synergistic effects of nanoparticles, which provide them with better heat transfer capabilities than base fluids and normal nanofluids. The thermophysical characteristics of hybrid nanofluids are critical in shaping heat transmission properties. As a result, before using thermophysical qualities in industrial applications, an in‐depth investigation of thermophysical properties is required. In this paper, a metamodel framework is constructed to forecast the effect of nanofluid temperature and concentration on numerous thermophysical parameters of Fe3O4‐coated MWCNT hybrid nanofluids. Evolutionary gene expression programming (GEP) and an adaptive neural fuzzy inference system (ANFIS) were employed to develop the prediction models. The model was trained using 70% of the datasets, with the remaining 15% used for testing and validation. A variety of statistical measurements and Taylor's diagrams were used to assess the proposed models. The Pearson's correlation coefficient (R), coefficient of determination (R2) was used for the regression index, the error in the model was evaluated with root mean squared error (RMSE). The model's comprehensive assessment additionally includes modern model efficiency indices such as Kling‐Gupta efficiency (KGE) and Nash‐Sutcliffe efficiency (NSCE). The proposed models demonstrated impressive prediction capabilities. However, the GEP model (R > 0.9825, R2 > 0.9654, RMSE = 0.7929, KGE > 0.9188, and NSCE > 0.9566) outperformed the ANFIS model (R > 0.9601, R2 > 0.9218, RMSE = 1.495, KGE > 0.8015, and NSCE > 0.8745) for the majority of the findings. The generated metamodel was robust enough to replace the repetitive expensive lab procedures required to measure thermophysical properties. Highlights: Predictions of thermophysical properties of Fe3O4‐coated MWCNT hybrid nanofluidAI‐based ANFIS and GEP models performed well on statistical indicesANFIS and GEP‐based prognostic models validated and compared with Taylor diagrams [ABSTRACT FROM AUTHOR]

Parabolic system is regarded as a highly advanced solar technology. In this regard, the numerical simulation for thermal analysis of PTC with a wavy absorber pipe employing finite volume method was presented. The new wavy absorber tube within a solar system involving parabolic reflector has been investigated in the current article. Two phase model for a mixture of oil and CuO nanoparticles were applied. To find the amount of received heat to absorber, SolTrace were implemented. Turbulent flow has been simulated via k-ϵ approach. Pitch number (P), Re, and fraction of nano-powder (φ) have been examined. CuO/Oil was utilized as a working fluid. Contours of temperature, velocity, volume concentration, and exergy loss were presented. Increment in Re number from 5000 to 20,000 resulted in the reduction of friction factor by 28.96%, the heat transfer coefficient is improved by 180.13%, when φ = 0.01 , P=(0.4). As volume concentration elevates, friction factor, h , and outlet temperature were increased by 2.79%, 9.06%, and 0.56%, respectively. With the increment of P from 0 to 0.4, the f is increased by 57.33%, h is enhanced by 17.01% when φ = 0.01 , Re = 2e4. [ABSTRACT FROM AUTHOR]

In the past decade, nanotechnology's rapid developments have created quite a lot of prospects for researchers and engineers to check up on. And nanofluids are important consequences of this progression. Nanofluids are created by suspending nanoparticles with average diameters below 100 nm in conventional heat transfer carriers such as water, oil, ethylene glycol, etc. Nanofluids are considered to offer substantial advantages over usual heat transfer fluids. When dispersed in a uniform way and suspended stably in the base fluids, a minimal amount of nanoparticles can significantly improve the thermal properties of host fluids. Present work attempts to address this challenge considering state-of-the-art advances in understanding, discussing, and mitigating problems about nanofluids' stability. Stable and highly conductive nanofluids are produced by generally, one-step and two-step production methods. Both approaches suffer from problems with the nanoparticles' agglomeration to be an important one. Thus, numerous numerical models and the principal physical phenomena affecting the stability (fundamental physical principles that govern the interparticle interactions, clustering and deposition kinetics, and colloidal stability theories) have been analyzed. Concerning the particles' dynamic motion, the significance of different forces in nanofluid in particulate flows such as drag, lift (Magnus and Saffman), Brownian, thermophoretic, Van der Waals, electrostatic double-layer forces are investigated. Furthermore, an overview of nanofluids' thermophysical properties, physical models, and heat transfer models is​ included in this work. In order to realize the unexpected discoveries and overcome classical models' limitations, several researchers have suggested new physical concepts and mechanisms, and they have created new models to enhance the transport properties. This review study includes numerous aspects of the nanofluids' science by investigating applications, thermal properties and giving critical chronological milestones about the nanofluids' evolution. Also, the present review discusses in detail various modeling and slip mechanisms for the heat transfer of nanofluids. Potential novel 2D materials as nanofluids have also been discussed and reported. A brief overview of the potential applications utilizing nanofluids has been reviewed, and future research gaps have been reported. Furthermore, recommendations were extracted regarding current scientific gaps and future research directions to cover the physical phenomenon, stability, thermophysical properties, overview of some applications, and the limitations hindering these nanofluids' deployment. The review is presumed to be valuable for scholars and researchers working in the area of numerical simulations of nanofluids and experimental aspects and help them understand the fundamental physical phenomena taking place during these numerical simulations and experiments and explore the potential of nanofluids both in academia and industry. [Display omitted] [ABSTRACT FROM AUTHOR]

• Application of lattice Boltzmann method for convective mixing flow in CO 2 -VAPEX process. • Viscosity and diffusion coefficient of oil are dependent to dissolved CO 2 concentration. • Study of CO 2 sequestration opportunity in CO 2 -VAPEX process. • Improvement of reservoir permeability leads to a higher dissolution of CO 2 in oil. • Increasing of mobile oil orientation enhances the performance of CO 2 -VAPEX process. Carbon dioxide (CO 2) use in Vapor Extraction (VAPEX) has attracted attention for its potential to enhance oil recovery by altering oil density and viscosity, leading to convective-mixing flow in the VAPEX boundary layer. This study explores CO 2 sequestration via dissolution into this layer, with a focus on the impact of oil viscosity, permeability, and mobile oil orientation. An isothermal lattice Boltzmann model, which accounts for the variable oil properties like viscosity and diffusion coefficient dependent on dissolved CO 2 concentration, was developed for the analysis. Results show that reduced oil viscosity leads to accelerated growth of density fingers and an expanded area swept by CO 2 dissolution. Similarly, heightened permeability and mobile oil angle contribute to these effects. This research provides novel insights into optimizing CO 2 sequestration within the VAPEX process. [ABSTRACT FROM AUTHOR]

Since the last decades, solar energy has been used worldwide to overcome foreign dependency on crude oil and to control the pollution due to a limited source of non-renewable energy. Evacuated tube solar collectors are the most suitable solar technology for producing useful heat in both low and medium temperature levels. Evacuated tube solar collector is capable of working in hot, mild, cloudy or cold climates where flat plate collector is not an option. The objective of this review paper is the detailed investigation of evacuated tube solar collectors having heat pipe and direct flow are reviewed. All the design parameters which influence the collector performance are investigated and discussed in this work. More specifically, the tracking system, the collector design, the mass flow rate, the optical design and the kind of the working fluid are the main studied parameters. Moreover, this work focuses on the latest developments and advances, providing a review of experimental and numerical studies reported. Lastly, this work presents the future ideas that can be carried out to improve the performance of evacuated tube solar collectors. [ABSTRACT FROM AUTHOR]

This work aims to enhance the heat transfer of a small prototype linear Fresnel reflector by using rGO-Co 3 O 4 /water hybrid nanofluids at a location in Blida region, in Algeria. Hybrid nanofluids, with varying concentrations (0.05, 0.10, and 0.20 wt%) and temperatures (20–60 °C), are prepared. For 0.2 wt % of rGO-Co 3 O 4 nanofluids, the viscosity and density increased by 70.83%, and 0.47%, respectively, while the specific heat decreased by 0.17% at a temperature of 60 °C over the base fluid data. The receiver pipe energy balance equations are solved using MATLAB software. With the use of 0.2 wt% of hybrid nanofluid, the mean thermal efficiency enhanced by 2.75%–31.95%, the mean exergy efficiency improved by 23.67%–2.27%, and the mean temperature increased by 9.42 °C, while, the receiver pipe temperature decreased by 2.69 °C. In addition, the mean heat transfer coefficient, mean thermal conductivity, Nusselt number, and the performance evaluation criteria were improved by using rGO-Co 3 O 4 /water nanofluid at 0.2 wt % by 309.67%, 19.31%, 254.75%, and 240.92%, respectively, while the mean entropy generation and electrical energy consumption decreased by 59.48% and 20.30%, respectively, as the CO 2 emission mitigation was 253.94 kg. Image 1 • Stable rGo-Co 3 O 4 /Water hybrid nanofluids with excellent thermal properties was experimentally obtained. • Thermal conductivity increased by 19.14% at 0.2 wt% for 60 °C using hybrid nanofluids. • Thermal behavior of hybrid nanofluids was investigated in a small LFR. • LFR thermal efficiency enhanced by 2.75%–31.95% using rGo-Co 3 O 4 /Water with 0.20 wt %. • Mean performance evaluation criteria using rGo-Co 3 O 4 /Water with 0.20 wt % enhanced by 240.92%. [ABSTRACT FROM AUTHOR]

The thermal and thermodynamic performance of parabolic trough solar collector (PTC) could be enhanced by using nanofluids due to their enhanced thermophysical properties. In this work, numerical and experimental investigations were carried out to study the effect of suspended industrial-grade multi-walled carbon nanotubes (MWCNTs) in distilled water (DW) for low to medium temperature PTCs. Stable nanofluids were prepared at various volume concentration of 0.05%, 0.1%, and 0.3%. Moreover, a one-dimensional numerical model is developed to investigate the optical and thermo-hydraulic performance of the commercial IST-PTC at different locations in the United Arab Emirates (UAE). The results of simulations show that Abu Dhabi is the best location with the highest annual thermal efficiency of 49.52%. Also, the suspension of MWCNTs nanoparticles in water results in an improvement of Nusselt number by 12%, 16%, and 21% for nanoparticle concentrations of 0.05%, 0.1%, and 0.3%, respectively. The impact of inlet temperature and flow rate are also investigated, and a thermodynamic analysis is carried out to study the entropy generation. The use of nanofluid at low concentrations could enhance the thermo-hydraulic performance for flow rates lower than 0.2 L/s, while nanoparticles concentration should be increased at higher flow rates for better heat transfer. • Stable industrial grade MWCNT/DW nanofluid are prepared and characterized. • Abu Dhabi is the most suitable location in UAE for PTC technology. • Nusselt number is enhanced by up to 21% for 0.3% nanoparticle loading. • Thermo-hydraulic performance enhanced for flow rates below 0.2L/s. • Adding nanoparticle concentrations is needed for higher flow rates. [ABSTRACT FROM AUTHOR]

In the present study, ternary rGO-Fe 3 O 4 -TiO 2 nanocomposites was produced using a straightforward sol-gel technique. The nanofluids are synthesized using rGO-Fe 3 O 4 -TiO 2 hybrid nanoparticles suspended in ethylene glycol (EG). Ternary rGO-Fe 3 O 4 -TiO 2 nanocomposite (0.01–0.25 mass. %) were dispersed in EG acquiring stable nanofluids. The ternary rGO-Fe 3 O 4 -TiO 2 nanocomposite present in the colloidal phase has been categorized by FTIR, SEM, EDX, XRD, and Zeta potential. At varying temperatures between 25 and 60 °C, the thermal conductivity was explored. Experimental results show that the stability of all the studied rGO-Fe 3 O 4 -TiO 2 /EG nanofluid samples was above 52.04 mV. Enhancement in thermal conductivity for rGO-Fe 3 O 4 -TiO 2 /EG nanofluids significantly increases with mass concentration and temperature, with an enhancement of 13.3% at 60 °C for 0.25 wt%. The best R2 coefficient of determination estimated at 25 °C, 30 °C, 40 °C, 50 °C, and 60 °C was 95.6%, 98.2%, 95.4%, 97.6%, and 99.0%. Therefore, the investigated ternary hybrid nanofluid can be utilized for both heating and cooling applications with long term stability. Unlabelled Image • Novel ternary rGO-Fe 3 O 4 -TiO 2 nanocomposites was produced. • Stable nanofluids were prepared using Ternary rGO-Fe 3 O 4 -TiO 2 nanocomposite. • An enhancement of 11.5% at 40 °C for 0.25 wt%. was achieved. • Regression models for all the studied temperatures and mass concentration are provided. • A well-fitting is obtained between the experimental results and the regression model. [ABSTRACT FROM AUTHOR]

In this study industrial grade Multi-walled carbon nanotubes (MWCNTs) nanoparticles dispersed in distilled water (DW) are investigated to evaluate its impact on the thermal behavior of linear Fresnel solar reflector technology. The stability and thermophysical properties of the MWCNTs/DW nanofluids are obtained experimentally. Stable nanofluids that showed higher thermal conductivity compared to DW were obtained. Thermal conductivity (TC) of the nanofluids increased by 3%, 6% and 7% for the volume fractions of 0.05%, 0.1% and 0.3% at 25 °C, respectively. TC also increased with the increase in temperature (i.e. 11% for 0.3% volume fraction at 70 °C). A one-dimensional model is developed to evaluate the transient behavior of the nanofluid within the linear solar reflector. Matlab code based on the finite difference method is developed to solve the energy balance equations at the different components of the studied solar collector. The numerical model is then validated with experimental results, where a maximum experimental thermal efficiency of 29.205% at 14:00 is achieved. MWCNTs/DW nanofluid with 0.3% volume fraction has the highest thermal efficiency of 33.81% and the highest PEC value as well as the lowest entropy generation. • Small linear Fresnel reflector has been manufactured and experimentally tested. • The maximum experimental thermal efficiency of DW is equal to 29.205%. • Stability and thermophysical properties of the MWCNTs/DW nanofluids are obtained. • Thermal conductivity of the nanofluids increased with the increasing volume fractions. • Highest thermal efficiency of 33.81% was obtained for MWCNTs/DW nanofluid. [ABSTRACT FROM AUTHOR]

In this study, Carbon nanofiber (CNF), Functionalized Carbon nanofiber (F-CNF), Reduced graphene oxide (rGO), and rGo coated over F-CNF (F-CNF/rGO) were produced using Hummers modified method and chemical reduction methods as well as a hydrothermal technique. All of which were characterized by SEM, TEM, X-ray Photoelectron Spectrometer, and X-ray diffraction. Stability, density, viscosity, thermal and electrical conductivities of the prepared nanofluids (0.04 vol%) were experimentally obtained. Significant enhancements in thermal and electrical conductivity were obtained. F-CNF/rGO (hybrid) nanofluid showed enhanced thermal conductivity and lower electrical conductivity compared to the other prepared nanofluids. Results showed that the hydrothermal F-CNF/rGO (hybrid) nanofluid could result in better heat transfer compared to conventional heat transfer fluids. Moreover, based on the experimental dataset, an accurate model that simulates the thermophysical properties of nanofluids is created by fuzzy logic. A well-fitting is obtained between the experimental results and the fuzzy model. The suggested numbers for fuzzy models rules were 11, 16, 16 and 16 for density, viscosity, thermal conductivity, electrical conductivity models, respectively. Every fuzzy model has been trained for 50 epochs. The MSE of the fuzzy models' outputs are 1.4379e-07, 0.00011349, 1.0709e-05 and 1.9827e-06 density, viscosity, thermal conductivity and electrical conductivity. Unlabelled Image • Mono and hybrid nanofluids were produced. • Stable nanofluids were obtained for a period of 6 months. • Maximum increase in thermal conductivity was observed in F-CNF/rGO nanofluid. • Hydrothermal F-CNF/rGO (hybrid) nanofluid could result in better heat transfer. • A well-fitting is obtained between the experimental results and the fuzzy model. [ABSTRACT FROM AUTHOR]

The cutting fluid is significant in any metal cutting operation, for cooling the cutting tool and the surface of the workpiece, by lubricating the tool-workpiece interface and removing chips from the cutting zone. Recently, many researchers have been focusing on minimum quantity lubrication (MQL) among the numerous methods existing on the application of the coolant as it reduces the usage of coolant by spurting a mixture of compressed air and cutting fluid in an improved way instead of flood cooling. The MQL method has been demonstrated to be appropriate as it fulfills the necessities of 'green' machining. In the current study, firstly, various lubrication methods were introduced which are used in machining processes, and then, basic machining processes used in manufacturing industries such as grinding, milling, turning, and drilling have been discussed. The comprehensive review of various nanofluids (NFs) used as lubricants by different researchers for machining process is presented. Furthermore, some cases of utilizing NFs in machining operations have been reported briefly in a table. Based on the studies, it can be concluded that utilizing NFs as coolant and lubricant lead to lower tool temperature, tool wear, higher surface quality, and less environmental dangers. However, the high cost of nanoparticles, need for devices, clustering, and sediment are still challenges for the NF applications in metalworking operations. At last, the article identifies the opportunities for using NFs as lubricants in the future. It should be stated that this work offers a clear guideline for utilizing MQL and MQL-nanofluid approaches in machining processes. This guideline shows the physical, tribological, and heat transfer mechanisms associated with employing such cooling/lubrication approaches and their effects on different machining quality characteristics such as tool wear, surface integrity, and cutting forces. [ABSTRACT FROM AUTHOR]

Advanced heat removal technologies are critical for high-performance automotive engines. The conventional fluids being used today are based on a mixture of distilled water (DW) and ethylene glycol (EG), which widens the operational temperature range but at the same time limits the heat removal. Therefore, the use of nanofluids for improving heat transfer performance has soared over the past few years. The problem is that most of the reports highlight the short-term heat transfer results which may not be true over time. In this paper, a suggested best practice for analyzing the usage of nanofluids in heat transfer applications is presented, specifically for an actual car radiator. This work investigates the use of aluminum oxide (Al 2 O 3) and titanium dioxide (TiO 2) nanoparticles dispersed in DW and EG at 50:50 volumetric proportions. The choice of these oxide-based nanofluids is motivated by their anti-corrosive properties that are usually not analyzed or discussed in most of the articles. Furthermore, the emphasis is given on the presentation of a comprehensive characterization of the nanofluids including thermophysical properties (size, density, viscosity, thermal conductivity, corrosive behavior) and long-term stability (zeta potential) which are essential for an end-user to have. The results showed a maximum enhancement of the thermal performance by 24.21% using Al 2 O 3 at a volume fraction of 0.3%. Friction factor and performance evaluation criterion (PEC) for the radiator experiments are calculated in order to determine the penalty in the pressure drop and to evaluate it properly. Finally, it is found that the values of PEC lie in the range of 1.03–1.31 which indicates significant flow enhancement. • A critical review on stability and application of nanofluids (NFs) in a radiator is presented. • The effect of surfactant concentration on stability is investigated. • Thermophysical properties of Al 2 O 3 –DW/EG and TiO 2 -DW/EG NFs are experimentally investigated. • Effect of NFs with respect to corrosion for the pipping system of the radiator is investigated. [ABSTRACT FROM AUTHOR]

Integrating nanotechnology into phase change materials (PCMs) has emerged as a novel approach to improving PCM thermal properties and performance in various thermal energy storage applications. Nanofluids, nanoparticle suspensions in a base fluid, have been identified as a promising method of increasing the thermal conductivity of PCMs and thus reducing thermal energy charging and discharging duration. This review paper investigates recent advances in incorporating nanotechnology into PCMs, focusing on their applications in the solar energy sector. Thermal conductivity, specific heat, viscosity, density, and convective heat transfer coefficient of nanofluids are discussed, as are the thermal properties of nano-enhanced PCMs (NEPCMs), including thermal conductivity, latent heat, specific heat, viscosity, supercooling, and phase-change temperature. The paper also gives an in-depth look at the uses of nanofluids and NEPCMs in solar collectors, photovoltaic/thermal (PV/T) systems, coolants, and desalination, emphasizing their potential to improve system efficiency. The review also considers the potential environmental and human health concerns connected with using nanofluids and NEPCMs, emphasizing the importance of rigorous evaluation and risk assessment in developing and applying these materials. Overall, the review provides valuable insights into the potential benefits and challenges of incorporating nanotechnology into PCMs and emphasizes the importance of ongoing research and development in this field to further advance the use of thermal energy storage technologies in various applications, including solar energy systems. [Display omitted] • Nanofluids and nanomaterials are considered as innovative heat transfer medium. • Phase change materials (PCMs) for harvesting thermal energy are scrutinized. • Recent developments and properties of nanofluids and nano-enhanced PCM. • Potential applications of nanofluids and nano-enhanced PCM are fully presented. • Environmental impacts and human health risks are comprehensively discussed. [ABSTRACT FROM AUTHOR]

• Detailed and comprehensive overview of nanofluid production are discussed. • Stability analysis and thermophysical properties of nanofluids are presented. • Performance of different solar collector types using hybrid nanofluids are analyzed. • Environmental impacts and challenges to nanofluid applications are emphasized. • Critical recommendations are made regarding future research directions. Renewables are believed to be the future energy sources, given conventional energy sources' rapid depletion and environmental degradation. Among these, the ones used to harness solar energy have emerged as the most mature and promising. In these solar energy systems, nanofluids could be used as the conventional heat transfer fluid to overcome the low thermal conductivity of conventional fluids. This work gives an overview of the advancements made in the field of solar thermal collectors with a focus on nanofluids as heat transfer fluids for their performance enhancement. It also covers the description of the different solar collectors, including concentrated and non-concentrated solar collectors, and their potential applications in terms of space heating, hot water heating, space cooling, and industrial process heat. Environmental concerns about using nanofluids in these solar collectors are also considered. The impact of nanoparticles on friction factor, the outlet temperature of flowing fluid, optical properties, and pumping power is also briefly described. Different challenges such as production cost, volume and mass concentration factor, pressure drop, viscosity variation, and instability are investigated in detail. At the end of this study, future work is also proposed aiming to find suitable orientations for the next studies. [Display omitted] [ABSTRACT FROM AUTHOR]

Over the years, the development of nanofluids has created new possibilities for research in the field of renewable energy. There has been rapid progress in the study of the optical characteristics of nanofluids for their potential use in Direct Absorption Solar Collectors (DASCs). Nanofluids may significantly improve photothermal conversion because of their enhanced optical properties. This study introduces a numerical model aimed at assessing the performance of DASC using mono and hybrid nanofluids. The model achieves this goal by solving the coupled radiation transfer equations in a participating medium together with the thermal energy equations. The realistic incident solar spectrum and effective optical properties of copper and alumina nanoparticles are also considered. The mathematical model is validated with experimental results from the literature. A parametric study is then carried out to study the sensitivity of the DASC performance on some design and operation parameters, such as the aspect ratio, heat transfer coefficient, and incident angle. The influence of copper and alumina nanoparticles on the DASC efficiency is also studied and compared. Due to their optical characteristics, it is established that the useful gain in copper-based nanofluid is much higher than in alumina-based nanofluid. Moreover, the use of Cu–Al 2 O 3 hybrid nanofluid is studied at different combinations of volume fractions to understand the techno-economic impact on the DASC technology. The use of response surface methodology allows studying how modifications in the concentration of individual nanoparticles used in DASC can influence both its cost and performance. A multi-objective optimization is then performed at various loadings of the nanoparticles to maximize the DASC efficiency and minimize the total cost of the working fluid. Finally, Pareto front solutions are obtained as a guide for selecting the optimum combinations of nanoparticles that optimize the cost and performance of the DASC. • Improve photo-thermal conversion using nanofluids due to enhanced optical properties. • A numerical model is proposed and validated with experimental results to investigate nanofluid filled DASC. • Sensitivity of DASC performance to various design and operation parameters with different volume fractions is examined. • Nanoparticle combination for maximum DASC efficiency and minimum cost is optimized. [ABSTRACT FROM AUTHOR]

The current study aims to enhance the performance of nanofluid mixture by determining the optimal operating parameters using particle swarm optimization. More specifically, the use of aluminum oxide (Al 2 O 3) and titanium dioxide (TiO 2) nanoparticles dispersed in distilled water and ethylene glycol with 50:50 volumetric proportions are investigated to enhance the thermophysical properties. The nanofluid properties were measured using different volume fractions (0.05 & 0.3 vol%) and a temperature ranging from (25–70 °C). The effect of surfactant on the stability and thermophysical properties of the metal oxide based nanofluids were also investigated. With the help of the experimental data sets, the nanofluid model was constructed using fuzzy logic, and then the optimal operating parameters are identified using particle swarm optimization. In the optimization procedure, three parameters; temperature, and the volume fractions of both Al 2 O 3 and different operating parameters are used as decision variables. TiO 2. The effect of these three operating parameters on the mixtures density, viscosity, and thermal conductivity is studied. Applying the proposed methodology resulted in obtaining the best condition that produces the optimal output that can minimize both the density and viscosity and at the same time maximizes the thermal conductivity. Unlabelled Image • Stable nanofluids prepared which showed no sedimentations. • Higher volume fraction results in larger sized average particle diameter. • Density and viscosity decreased with the increasing temperature. • Thermal conductivity increased with higher volume fraction and increasing temperature. • Fuzzy logic approach is used to simulate nanofluid model from experimental data. [ABSTRACT FROM AUTHOR]

Abstract The quest for high performance supercapacitors from the energy-power point of view is commonly addressed from the constituting electrode materials and/or the electrolyte. Carbon-based double-layer capacitors are known for their high power density, whereas pseudocapacitors which use transition metal oxides/nitrides/sulfides or conductive polymers are known for their high energy density. In this work we show that one can modulate the energy storage capability of supercapacitors by mixing at preset ratios two types of carbon materials having two different energy storage capabilities. The time-domain and frequency-domain electrochemical characterization of five symmetric devices, in which electrodes made of carbon nanofibers (CNF) are mixed with cobalt-modified CNF (Co-CNF) at different mass proportions, show that as the Co-CNF content is increased, the effective capacitance, and hence the restored energy, is increased without affecting the power performance of the device. This opens up new opportunities for the modular design of supercapacitor electrodes using a small set of electric double-layer capacitive materials. Highlights • Mixing EDLC materials → series/parallel network of many small su-percapacitors. • Intermediate electrical properties can be obtained by mixing two EDLC materials. • Modulating the energy density of EDLC device while maintaining a constant power. [ABSTRACT FROM AUTHOR]

From the last few decades, due to the escalating requirement of heat and electricity, the relative utilization of Photovoltaic/thermal (PV/T) system has enlarged as compared to the photovoltaic or solar thermal system alone due to better performance of combined PV/T systems when compared to the conventional ones. PV/T hybrid systems generate both electrical and thermal energy concurrently, giving it a broad variety of applications. Recently, different nanoparticles mixed with base fluid (Nanofluid) have been used in these hybrid systems resulting in attracting the attention of numerous researchers. Due to its improved thermal conductivity nanofluid can be used as an optical filter and proficient coolant in PV/T systems. In the last years, much research has been focused on this domain because it is crucial for the design of sustainable and environmentally friendly energy systems. The primary focus of this review is to accomplish the briefing of diverse PV/T technologies at the outset together with aspects of their efficiencies, structure, thermal governing expressions and their applications as well as the latest technologies and parameters which profoundly affect the PV/T collector performance. We have also reviewed the various positive and adverse effects on the environment safety level by applying these solar techniques for the energy production as compared to the conventional energy sources techniques. As the solar techniques are tremendously helpful for the environment in several ways but at the same deployment of these resources on the wide-scale may lead to adverse implications for the environment. Moreover, the variations in the performance efficiency of the PV/T system using nanofluids, and finally, the suggestions for future research directions are presented. The outcome of this review paper would give an overview of further enhancements in solar PV/T systems with high practicability for extensive relevance in energy supply at all levels in the vicinity of future. [ABSTRACT FROM AUTHOR]

Solar energy exploitation is one of the most important weapons for facing the recent environmental and energy management dangers. Concentrating solar collectors can produce useful heat in medium and high-temperature levels. So, they can be used in a great variety of applications as space-cooling, industrial heat, chemical processes and electricity production. The use of nanofluids is one of the most effective ways for enhancing the performance of the concentrating collectors. In this paper, the use of nanofluids as working fluids in concentrating solar collectors is investigated in detail. The examined collector types are the following: Evacuated tube collectors with booster reflector, concentrating thermal photovoltaics, compound parabolic concentrator, parabolic trough collector, linear Fresnel reflector and solar dishes. Moreover, the use of nanofluid-based solar concentrating collectors in applications (heating, cooling, electricity, and trigeneration) is investigated in this work. The emphasis is given to the determination of the thermal efficiency enhancement of the collector with the use of the nanofluids in every case. The recent trends in nanofluid utilization are given in this work. Furthermore, the challenges and the future work about the nanofluid-based solar systems are discussed in details. [ABSTRACT FROM AUTHOR]

[Display omitted] • Food waste (FW) contains potential nutrients and compounds for circular bioeconomy. • Efficient management and valorization of FW is the most sustainable method. • Artificial Intelligence (AI) application could help in optimizing FW supply chain. • Machine learning (ML) can predict quite exactly the quantity and composition of FW. • Combination of AI and ML could monitor and manage well FW-based bioprocess. Food waste (FW) is a severe environmental and social concern that today's civilization is facing. Therefore, it is necessary to have an efficient and sustainable solution for managing FW bioprocessing. Emerging technologies like the Internet of Things (IoT), Artificial Intelligence (AI), and Machine Learning (ML) are critical to achieving this, in which IoT sensors' data is analyzed using AI and ML techniques, enabling real-time decision-making and process optimization. This work describes recent developments in valorizing FW using novel tactics such as the IoT, AI, and ML. It could be concluded that combining IoT, AI, and ML approaches could enhance bioprocess monitoring and management for generating value-added products and chemicals from FW, contributing to improving environmental sustainability and food security. Generally, a comprehensive strategy of applying intelligent techniques in conjunction with government backing can minimize FW and maximize the role of FW in the circular economy toward a more sustainable future. [ABSTRACT FROM AUTHOR]

The increasing temperature significantly influences the performance of a photovoltaic system. It reduces the efficiency as well as the operational life span of the PV panel. Thus pursuing an efficient cooling system that reduces the thermal stress in PV panels could improve PV system overall performance. A combination of passive cooling and active mist cooling is introduced and evaluated in detail. Paraffin wax as phase change material (PCM) and coconut husk as a passive cooling material are selected based on their availability, eco-friendly and stable nature. Initially, paraffin wax and husk are integrated on the rear side of PV panels. The results have indicated that under the average irradiance of 752 W/m2 and ambient temperature of 41.59 °C, the avg. front surface temperatures can reach up to 62.57 °C with a peak value of 67.37 °C and the avg. temperature on rear side ramps up to 69.02 °C with a peak value of 74.25 °C. PCM cooling reduces both front and rear surface temperatures by 0.92% and 12.83% as compared to the reference PV panel. A power enhancement of 2.05% has been observed. The integration of husk on the rear surface of the PV panel elevates both front and rear surface temperatures by 2.07% and 0.33%, respectively, resulting in a 0.82% reduction in PV power. The cooling process is enhanced by introducing hybrid cooling i.e. active mist cooling combined with passive cooling. Under an avg. irradiance of 725.53W/m2 and ambient temperature of 42.05 °C, the front and rear surfaces temperature of PV-Mist are 49.51 °C and 48.63 °C, respectively. In case of PV-PCM with mist cooling, the front surface temperature increases by 16.14% while the rear surface temperature decreases by 6.03%. This results in an overall improvement of the PV panel's power by 0.32%. On the other hand, with the application of husk, an increase of 0.70% in the front surface and a 17.87% increase in the rear surface temperature are observed, leading to the deterioration of PV power by 2.72%. The results conclude that the PV-PCM with mist cooling performs best among the analyzed techniques. [Display omitted] • Average front surface temperatures of PV can reach up to 62.57 °C with a peak value of 67.37 °C. • PV's average rear surface temperatures can reach up to 69.02 °C with a peak value of 74.25 °C. • PCM cooling decreases the front and rear surface temperatures by 0.92% and 12.83%. • Mist cooling with PCM further reduces the rear surface temperature by 6.03%. • Net power gain of 0.32% was achieved in the case of PV-PCM-Mist as compared to PV-Mist. [ABSTRACT FROM AUTHOR]

The increase in diesel fuel prices has compelled engine users to switch to cost-effective alternative energy sources, particularly in developing countries. This study aims to produce jatropha oil biodiesel extracted from the jatropha curcas plant using a catalyst as methanol and ethanol. Since the methyl ester of jatropha oil (JOME) has been extensively researched as an alternative fuel, however, there has been little research into the ethyl ester of jatropha oil (PJOEE) as a fuel in both unheated and preheated conditions. The yielding of JOME and JOEE were found as 93.52% and 98.23%, respectively. An increase in fuel inlet temperature from 30 °C to 90 °C causes a reduction in density, viscosity, and surface tension by 6.75%, 67.31%, 15.75% for methyl ester, and 6.61%, 66.39%, 15.38% for ethyl ester. Its impact on atomization, performance, and emission was investigated in the current study. A laser-diffraction-based setup named Malvern spraytec was used to measure Sauter mean diameter (SMD) at various ambient conditions. It was discovered that preheated ethyl ester and methyl ester had lower SMD than unheated methyl ester and ethyl ester, as well as diesel fuel. Moreover, the brake thermal efficiency of PJOEE was 4.1% higher than diesel at 6 bar of brake mean effective pressure (BMEP) and a decrease of 7.1% in brake-specific fuel consumption (BSFC) than neat diesel. Furthermore, engine emissions revealed that preheated ethyl esters of jatropha oil could reduce carbon monoxide (CO), unburned hydrocarbon (HC), and smoke opacity emissions at all BMEPs, followed by PJOME, which was nearly as effective as neat diesel except for NOx. Subsequently, a brief cost analysis was carried out, that indicated the cost of generating 1 kWh of energy preheating jatropha oil methyl and ethyl ester was 44.16% and 42.92% less than diesel fuel, with better performance and lower emissions. Thus, preheated methyl ester and ethyl ester of jatropha oil can be excellent substitute fuels for unmodified diesel engines. [Display omitted] • Biodiesel from jatropha oil was produced using methanol and ethanol. • Methyl and ethyl esters in heated state showed lowest SMD than other test fuels. • Ethyl esters exhibited better engine performance and emissions than methyl esters. • Ethyl and methyl ester of heated jatropha oil showed lowest cost of energy per kWh. [ABSTRACT FROM AUTHOR]

Carbon-based nanofluids are viewed as promising thermal fluids for heat transfer applications. However, other properties, such as electrical conductivity and electrochemical behavior, are usually overlooked and rarely investigated despite their importance for the overall performance characterization of a given application. In this study, we synthesized PAN-based carbon nanofibers (CNF) by electrospinning, and characterized them using electron microscopy, X-ray diffraction, X-ray photoelectron spectroscopy, Raman spectroscopy, and thermogravimetric analysis. Thermoelectrical and electrochemical measurements were carried out on nanofluids. We found that, although CNF nanofluids exhibit good thermal and electrical properties with a negligible corrosive effect, the suspensions tend to sediment within a few days. However, acid treatment of CNF (F-CNF), which resulted in the shortening of the fibers and the appearance of surface-oxygenated species, made F-CNF-based nanofluids exhibit superior stability in water that extended for more than 90 days, with consistent and superior thermal and electrical properties. [ABSTRACT FROM AUTHOR]

The main objective of this paper is to analyze and propose the United Arab Emirates (UAE) plan of Renewable Energy mix in 2030 to achieve the government target of reducing the greenhouse gas emissions of CO 2 while maintaining the electricity price to a minimum. The study includes many proposals of the energy mix for electricity to achieve the target, and a comparison study to IRENA's proposal to select the most suitable energy mix plan in terms of CO 2 reduction while maintaining the electricity price. The analysis has been conducted in two different cases: the first case analyzed where the government of UAE does not implement CO 2 taxation of hydrocarbon fuels used to generate electricity; however, the second case analyzed if the government apply CO 2 taxations what would the results be. Further on, calculations of the surplus energy were implemented for future studies on utilization of the excess energy or reducing the power capacity. This paper provides a background analysis of UAE's electricity consumptions and future government plans. [ABSTRACT FROM AUTHOR]

The numerical simulation of a shell-and-tube heat exchanger (STHE) depends on a large number of computational cells. The number of computational cells increases dramatically with increasing heat transfer surfaces in heat exchangers, such as increasing the number of tubes or using dimples as modified surfaces. Computational cost is one of the critical parameters in many industrial applications for heat exchanger analysis. The present study uses the P-NTU thermal analysis method, proposes correlations to predict heat transfer inside and outside the tubes, and then analyzes the STHE with elliptical dimples. The analytical approach shows 0.8% and 9% errors for two STHEs with specified heat performance, which is entirely acceptable. Also, for the STHE with elliptical dimples, the results indicate a 40.6% increase in the heat capacity of STHE. Increasing the heat capacity of STHE by using modified surfaces such as dimples significantly reduces the dimensions and weight of STHE in industrial applications. Furthermore, the analytical method can be used for different types of dimples with different geometries and arrangements. [ABSTRACT FROM AUTHOR]

• Diesel engine was powered with ternary blends of biodiesel-diesel-oxyhydrogen. • Third-generation biodiesel was synthesized from biomass of Azolla Pinnata. • A low-cost device-31 plates generator generated oxyhydrogen gas. • Oxyhydrogen addition improved engine performance and lowered emissions. • Box-Behnken design coupled with desirability approach used for optimization. The current study explores and improves the effects of engine load, injection time, and oxyhydrogen fuel flow rate on the combustion and emissions characteristics of a diesel engine. Experiment with the combustion and exhaust characteristics of a medium-sized diesel engine working in tri-fuel mode using microalgae oil methyl ester-diesel blends as injected fuel and an oxyhydrogen gas combination as inducted fuel. The Box-Behnken design (BBD) was used to reduce the number of testing. The parameters and proposed attributes were calculated utilizing response surface techniques and BBD-generated quadratic models. The response surface analysis displayed the patterns of input interactions on the output using surface diagrams. The desirability-based optimization revealed the optimal engine operating parameters as 22.92° crank angles advance, 76% engine load, and 0.92 L per minute oxyhydrogen flow rate. At these optimized operating ranges, the performance and combustion output of the study was 30.8 % brake thermal efficiency (BTE), 0.3 kg/kWh brake specific fuel consumption (BSFC), and 65.6 bar peak cylinder pressure (PCP). On the emission front, the CO emission was 0.0107%, UHC was 26 ppm, and NO x was 853 ppm. The optimized values were validated through experimental testing, and all the results were within 7% of the model-predicted output. The addition of oxyhydrogen significantly improved the combustion of an algal biodiesel-diesel-oxyhydrogen-powered diesel engine in terms of fuel efficiency and fuel consumption and lower carbon-based emission levels except for nitrogen oxide emissions. [ABSTRACT FROM AUTHOR]

[Display omitted] • Aviation fuel prepared from microalgal species Chlorella Pyrenoidosa. • Box-Behnken design used for economical use of resources during experiments. • Neuro-fuzzy approach used for robust prognostic modeling achieving R > 0.9995. • Desirability based optimization helped in gaining a 91% yield of esters. • Properties of aviation fuel prepared were comparable to Jet A-1 kerosene. The aviation sector has been one of the most significant contributors to greenhouse gas (GHG) emissions; there is an urgent need to transition from traditional fossil-based jet fuel to sustainable aviation fuel to meet net-zero targets by 2030. The use of renewable aviation fuel may be regarded as the most effective option for reducing GHG emissions in the aviation sector while allowing for long-term growth. In this study, the microalgae oil was transformed to develop hydrocarbons with the boiling point range of jet fuel. Following the transesterification of algal oil fatty acids to algal oil methyl ester, fractional distillation was carried out. The Box-Behnken technique was used to design experiments for efficient resource utilization by minimizing the number of tests during transesterification. The quantitative relationship function between input (molar ratio of methanol to oil, catalyst concentration, and temperature) and % yield of methyl ester as an output of the process was developed using analysis of variance (ANOVA). The ANFIS (adaptive neuro-fuzzy inference system) was utilized to develop a prognostic model with good prediction effectiveness. MORSM (multi-objective response surface methodology) was also used to build a prediction model using correlations. A set of statistical indicators and Theil's U2 were used to examine the prediction efficacy and model uncertainty of ANFIS and MORSM. On both statistical indices and Theil's U2, the ANFIS-based model outperformed. To get the best results, the desirability approach was used to improve operating parameters. According to the desirability approach, the best operating parameters were catalyst concentration at 2.09%, methanol to oil ratio at 9.17%, and temperature at 60.49 °C, which resulted in the greatest yield of 91%. [ABSTRACT FROM AUTHOR]

[Display omitted] • 5-hydroxymethylfurfural (HMF) and 2,5-dimethylfuran (DMF) are valuable chemicals. • HMF and DMF are synthesized from carbohydrate sources through catalytic pathway. • Reaction conditions and mechanism of forming HMF and DMF are thoroughly analyzed. • Yield of HMF and DMF using various catalysts and reaction conditions are evaluated. In recent years, green energy sources have been proposed as alternatives for fossil fuels to meet energy demand while minimizing environmental pollution and global climate change. In this context, agricultural residues can be catalytically converted into furan derivatives. Among furan-based compounds, 5-hydroxymethylfurfural (HMF) and 2,5-dimethylfuran (DMF) are the valuable chemicals that can be converted into desired materials, including fuels. This review article discusses various catalytic HMF and DMF production pathways and the influence of feedstocks, catalysts, solvents, and hydrogen donors on the process yield. Additionally, reaction temperature and H 2 pressure effects on the feedstock conversion and HMF and DMF production yields are also presented. The primary attention has been devoted to the literature published in the last five years. However, additional relevant examples have also been discussed to clarify the topic further where necessary. This review aims at providing state-to-the-art information on the current developmental state of DMF and HMF production for researchers in this field. [ABSTRACT FROM AUTHOR]

This work examined the thermal performance of a small-scale solar organic Rankine cycle system, in which a flat plate solar collector was employed to supply heat to the organic Rankine cycle system. In the ORC system, WO 3 +MWCNT/water nanofluid was employed for the solar collector, while MWCNT/R141b nano-refrigerant was used in the ORC system. In the first stage, the thermal and exergy efficiency of the ORC system was experimentally examined at different flow rates and concentrations of nanofluid. As a result, the peak thermal efficiency of 73.21% was attained at 3 L per minute (lpm) of nanofluid flow rate and 1.5 vol% of nanofluid concentration. Moreover, a significant increase in energy and exergy efficiency by 8.52% and 6.30%, respectively, was observed for 0.5 vol% of nanofluid concentration and 3 lpm of nanofluid flow rate in the collector. In the second stage, the experimental data was utilized to develop contemporary ensemble machine learning algorithms such as boosted regression trees (BRT) and Gaussian process regression (GPR) aiming to predict the solar collector's energy efficiency and the ORC system's energy-exergy efficiency. The GPR-based models performed exceptionally well as Pearson's coefficient (R), coefficient of determination (R2), mean squared error (MSE), and root mean squared error (RMSE) were 0.9999, 0.9998–0.9999, 0.0015–0.0524, and 0.0124–0.0723, respectively. For BRT-based model the R, R2, MSE and RMSE were 0.9604–0.9949, 0.97–0.99, 0.0969–0.8783, and 0.3113–0.9372. Theil's U2 was employed to calculate the uncertainty in the prediction framework, which was determined to be in the range of 0.002–0.00369 for GPR and 0.00228–0.1414 for the BRT-based model. Overall, both machine learning algorithms performed well, although GPR did better than BRT across the board. • Thermal performance of a solar-aided ORC system was modeled with GPR and BRT. • Peak thermal efficiency of ORC system reached 73.21% at 3 lpm of nanofluid flow rate. • Energy and exergy efficiency were increased by 8.52% and 6.30% as using nanofluid. • GPR-based models worked with exceptionally good indicators of R, R2, MSE, and RMSE. • Nanofluid flow rates were the most influential factor on ORC system performance. [ABSTRACT FROM AUTHOR]

[Display omitted] • Sonication impact on stability and thermophysical properties of nanofluids is studied. • Highest stability of –39.84 mv was achieved for 0.10% nanofluid concentration. • Sonication duration of 80 and 160 min shows maximum thermal conductivity. • Thermal conductivity improved to 5.90% for 0.1 vol%. • Highest surface tension value of 78.67 mN/m is observed at 0.10 vol%. Several reports have shown the potential of nanofluids in enhancing the performance of heat transfer applications. Multi-walled carbon nanotubes are getting substantial attention among researchers due to their excellent characteristics such as increased thermal conductivity. Functionalizing MWCNTs using COOH functional groups creates the carbon nanotubes hydrophilic; improves nanofluids' stability. The current experimental study used XRD and BET to characterize nanoparticles and investigates the effect of sonication duration and effect of three volume concentrations (0.05, 0.10, and 0.30 vol.%) of functionalized-multi walled carbon nanotubes (f-MWCNTs/water) nanofluid on stability and thermal conductivity, specific heat, contact angle, and surface tension. Referring to experimental findings, the volume concentration of 0.10 vol% shows the maximum and long-term stability (−39.84 mV) for 80 minutes of sonication duration. With increasing sonication time, the particle size becomes smaller, and 0.30 vol% concentration showed considerable variation. At sonication time of 20 minutes, the maximum thermal conductivity improvement was reported at 5.90% at 0.10 vol% and a temperature of 50 °C, while the maximum enhancement in specific heat (4.12%) has been reported for 0.30 vol.% concentration. The surface tension and contact angle reduced with rising volume concentration. In conclusion, the optimum volume concentration of 0.10 vol.% has been reported for better stability and enhanced thermal conductivity. This paper shall provide greater insight for the researcher to incorporate the optimum sonication duration and its effect on nanofluids' stability and thermophysical properties. [ABSTRACT FROM AUTHOR]

The present study is a 4E (Energy, Exergy, Economic, and Environmental) analysis of a nanofluid-based parabolic trough collector (PTC) which is conducted with a developed model in MATLAB. MXene (Ti 3 C 2) nanoparticles were added to the silicon oil at weight concentrations of 0.05, 0.08, and 0.1%. The result was the important enhancement of the thermal conductivity of the nanofluid on the rand of 70%–89% for the highest concentration. According to the results, the PTC's optical efficiency was estimated at 79%, while thermal and exergy efficiencies of 74.71% and 22.44% with 0.10 wt% concentration were recorded on July 17, 2019. It is found that the MXene based silicone oil can reduce the system's cost by 0.021 M$ and enhance the energy gained by 1.51% at 0.10 wt% concentration compared to pure oil. Also, the annual CO 2 mitigation from the energy side varies from 2.25 to 2.30-ton CO 2 /year, while the annual environmental gain ranged between 32.73 and 33.28 $/year and 9.065 to 9.102 $/year for the energy and exergy studies respectively. [Display omitted] • A nanofluid-based parabolic trough collector is studied with MXene. • The collector thermal efficiency enhancement is found up to 1.1%. • For the day July 17, 2019, the exergy efficiency was improved from 0.07% to 15.16%. • For energy analysis, the annual CO 2 mitigation varies from 2.26 to 2.30 ton CO 2. • The environmental gain from the energy analysis varies from 32.73 to 33.28 $/year. [ABSTRACT FROM AUTHOR]

To enhance the assimilation of light in the solar thermal area, we need to focus beyond the thermo-physical properties of the nanoparticles, i.e., optical properties of the nanoparticles (NPs) augment the optical characteristics of the solar spectrum; therefore, the concept of plasmonic nanofluids has been introduced. The plasmonic nanoparticles (mainly work on scattering and absorption mechanisms) suspended in a base fluid are known to enhance the thermal and photon efficiency of the volumetric solar thermal collectors compared to the conventional ones. Further, this study aims to review the most recently published works on plasmonic nanofluids that exclusively present its preparation methods, thermophysical properties, and applications in solar collectors. Following, an overview of the potential features of plasmonic nanofluids and their preparation methods are presented. Afterward, the stability and thermophysical properties of such nanofluids are discussed. Then, the application in solar energy collectors, automotive cooling, as well as biomedical applications are overviewed. Finally, some future directions for further research in this field of study are suggested. In this work, we reviewed the work done in the plasmonic field in the last decade, and we have tried to summarize the results based on published data and future outlooks. This work can benefit researchers in this field as there is no comprehensive review of plasmonic nanofluids available. This work is believed to help the researchers to modernize the latest trends and understand the potential research gap in the optical properties of nanofluids to enhance the performance of solar collectors further and reduce thermal losses. [ABSTRACT FROM AUTHOR]

A direct sol-gel technique was utilized to produce rGO-Fe 3 O 4 -TiO 2 ternary hybrid nanocomposites to produce ethylene glycol (EG) based stable nanofluids, characterized by energy-dispersive X-ray, X-ray dispersion, Fourier transform infrared spectroscopy, scanning electron microscopy, and zeta potential. Viscosity and density analysis were investigated by varying temperatures (25 to 50 °C), and wt% (0.01 to 0.25). For 0.25 wt% at 50 °C, density increased by 2.45%, and viscosity by 133.5%. The development of a prediction model by processing the variational parameters with machine learning and studying properties such as characterization, stability, and density of rGO-Fe3O4-TiO2 hybrid nanofluids has provided an unprecedented study in the literature. The nonlinear nature and volume of data generated by the subsequent experimental study were difficult to model using traditional analytical methods. As a result, for the creation of prognostic models, advanced machine learning techniques such as Boosted Regression Tree (BRT), Support Vector Machine (SVM), and Artificial Neural Networks (ANN) was applied. These prediction models' prognostic skills and uncertainty were assessed using statistical indices, Theil's statistics, and Taylor's diagram. The R-value for the BRT-based density (0.9989) and viscosity (0.9979) prediction models was higher than that of the ANN-based and SVM-based prediction models. In developed density models, Theil's U2 uncertainty was as low as 0.0689, 0.0775, and 0.0981 for BRT, ANN, and SVM, respectively. As a conclusion, it is stated that BRT, ANN, and SVM can accurately imitate the laboratory-based assessment of density and viscosity values of ternary hybrid nanofluids over a wide temperature and nanoparticle concentration ratio range. On the other hand, the BRT was marginally better than ANN but much better than SVM. The current study's findings are appropriate for applications needing long-term stability and improved heat transfer performance. [Display omitted] • Novel ternary rGO-Fe 3 O 4 -TiO 2 nanocomposites synthesized. • Hybrid nanofluid at 0.01 wt% showed +63.45 mV value of zeta potential. • Viscosity increased by 64.5% at 25 °C for 0.25 wt% of rGO-Fe 3 O 4 -TiO 2 nanofluids. • Statistical indices and Tayor's diagrams were used to compare efficacy of ANN, BRT, and SVM. • Theil's U2 uncertainty in developed BRT models was as low as 0.121 for viscosity models. [ABSTRACT FROM AUTHOR]

[Display omitted] • Thermophysical properties of water, water + ethylene glycol mixture is presented. • Thermal conductivity of water based hybrid nanofluid is enhanced to 17.76% at ϕ = 0.2% for 60 °C. • Viscosity of water based hybrid nanofluid is enhanced to 72.90% at ϕ = 0.2 vol% for 60 °C. • Thermal conductivity of 60:40 % W/EG mixture nanofluid is enhanced to 12.79% at ϕ = 0.2% for 60 °C. • MLR and MLRI models based on volume concentration, temperature, and base fluid are presented. This paper aims to study the thermophysical properties of water, water and ethylene glycol mixture-based nanodiamond + Fe 3 O 4 hybrid nanofluids experimentally and numerically using two data-driven approaches, namely, Multivariate linear regression (MLR) and Multivariate linear regression with interaction (MLRI) models. Three types of base fluids, such as (i) water, (ii) 40:60% water and ethylene glycol mixture, and (iii) 60:40% water and ethylene glycol mixture, were used to prepare the hybrid nanofluids. For all the base fluid, ϕ is used as 0.05%, 0.1%, and 0.2%. Results indicate that, higher values of thermal conductivity and viscosity is 17.76% and 72.9% at ϕ = 0.2% and 60 °C in comparison to water data. Similarly, for 40:60% water and ethylene glycol mixturebased nanodiamond + Fe 3 O 4 hybrid nanofluid, the maximum thermal conductivity and viscosity enhancements are 14.65% and 79.01% at ϕ = 0.2% and at 60 °C compared to the base fluid. However, the maximum thermal conductivity and viscosity enhancements for ϕ = 0.2% and at 60 °C of 60:40% water and ethylene glycol mixture-based nanodiamond + Fe 3 O 4 hybrid nanofluid are 12.79% and 50.84% over the basefluid data. Empirical and data-driven correlations were proposed based on the experimental data. The developed data-driven models resulted in robust individual relationships to predict the thermophysical properties of all types of hybrid nanofluids by superior performance compared to corresponding empirical correlations. The reported results exhibited that for thermal conductivity, density, Specific heat, and viscosity estimation, the MLRI (R = 0.9996), MLR (R = 0.99989), MLR (R = 0.9999998), and MLRI (R = 0.9857) had the best predictive performance. [ABSTRACT FROM AUTHOR]

Waste-derived biogas and third-generation algal biodiesel are attractive alternative fuels to substitute fossil diesel in a diesel engine. However, using biodiesel as a pilot liquid fuel and biogas as the main fuel in a diesel engine is a complicated and highly non-linear process. The current study seeks to predict and optimize the combustion and exhaust emission characteristics of a variable compression dual-fuel combustion engine. Data from experiments were obtained at a variety of engine loads, compression ratios, pilot fuel injection pressures, and timings. A multi-layer perceptron network was employed to develop an Artificial Neural Network (ANN) based prognostic model using the experimental data. The developed prognostic model was used to estimate brake thermal efficiency, biogas flow rates, peak in-cylinder pressure, carbon dioxide, unburned hydrocarbons, oxides of nitrogen, and carbon monoxide. The predictive model's robustness is demonstrated by statistical metrics such as R (0.9723–0.988) and R2 (0.9453–0.9761), Nash-Sutcliffe model efficiency (94–97%), and mean absolute percentage error (0.013–0.128%), Kling-Gupta efficiency (0.9548–0.9836), and Theil's U2 model uncertainty (0.162–0.368). To optimize the parameters of dual-fuel combustion, the Multi-Output Response Surface Methodology (RSM) was employed. The trade-off assessment between emission and efficiency using the desirability approach revealed that 84% engine load, 244 bar of fuel injection pressure, 28 °BTDC of injection timing, and 17.5 compression ratio are the best-operating conditions for the test engine. An experimental investigation was used to corroborate the RSM research findings, and errors were less than 9%. It was revealed that ANN-linked RSM is a good hybrid technique for modeling, prediction, and optimization of the performance of a dual-fuel engine. • Waste-derived biogas and third-generation biodiesel are used to power the CI engine. • An ANN-based prognostic model was developed for predicting engine behaviors. • Advanced statistical indices were used to establish the model's efficacy. • Box-Behnken design was used for optimizing engine operation parameters. • Proposed equations could forecast engine behaviors with a high accuracy degree. [ABSTRACT FROM AUTHOR]

[Display omitted] • Stability and thermophysical properties of Fe 3 O 4 coated MWCNT hybrid fluids studied. • Highest stability of –48 mv was achieved for 0.05% nanofluid concentration. • Thermal conductivity and viscosity improved to 28.33% and 50% for 0.3 vol%. • A robust MLP-ANN model with 99.38% accuracy was developed using experimental data. • Model's uncertainty was measured with Theil's U2 with high accuracy. Stability and thermophysical properties of water-based magnetite (Fe 3 O 4) material coated on multiwalled carbon nanotubes hybrid nanofluids was investigated. The in-situ growth approach was coupled with the chemical reduction method to make Fe 3 O 4 coated multiwalled carbon nanotubes, and X-ray diffraction, vibrating sample magnetometer, and scanning electron microscopy were used to validate these findings. The experiments were conducted for different particle volume loadings (0.05% to 0.3%). Highest stability value of –48 mv was achieved for ϕ = 0.05%. At, ϕ = 0.3% of nanofluid, the thermal conductivity was improved to 13.78%, and 28.33% at temperatures of 20 °C and 60 °C against water. Similarly, at ϕ = 0.3% of hybrid nanofluid, the viscosity has enhanced to 27.83%, and 50% at temperatures of 20 °C and 60 °C against water. Using the experimental data, sensitivity analysis was used to build Multi-Layer Perceptron Artificial Neural Networks (MLP-ANN) with appropriate topologies and training techniques. MLP-ANN was employed to establish the relationship between the inputs (temperature and mixture concentration) and the outputs (density, thermal conductivity, viscosity and, specific heat) for water-based magnetite (Fe 3 O 4) material coated on multiwalled carbon nanotubes hybrid nanofluids. The model performances were evaluated using the coefficient of correlation (0.9938–0.9999), coefficient of determination (0.9854–0.9996), root mean squared error (0.0072–0.2626), mean absolute percentage error (0.001%-2.09%), and Nash-Sutcliffe efficiency (0.9856–0.9999). The model's uncertainty was measured with Theil's U2 (0.035–0.267). The results revealed that the MLP-ANN could consistently emulate the experimental testing conditions proficiently, even for diverse temperatures and concentrations, with significant accuracy. [ABSTRACT FROM AUTHOR]

The research work was achieved to optimize the experimentally determined thermophysical properties of water based nanodiamond nanofluids using the Adaptive network-based fuzzy inference system model. The thermophysical properties were determined at various temperatures (20 °C to 60 °C) and various particle volume concentrations (0.2% to 1.0%). The stability of nanodiamond nanofluids was measured based on the dynamic light scattering method. Results indicated that the zeta potential of all the prepared nanodiamond/water nanofluids is above −30 mV. The thermophysical properties like thermal conductivity and viscosity augments are 22.86% and 79.16% at ϕ = 1.0 vol% compared to the water data at a temperature of 60 °C. Fuzzy logic is one of the artificial intelligence tools that have been used to analyze the optimized property value. The optimization process was applied in a single objective and a multi-objective procedure using a new and efficient optimizer, namely, the marine predators' algorithm. In a single objective, the lowest density and highest thermal conductivity values were found at 0.23% with 54.81o C and 1% with 60 °C, respectively. However, the viscosity and specific heat showed improvements only in the absence of the nanodiamond material and temperatures of 35.99 and 60 °C, respectively. In the multi-objective process, the optimizer confirmed that the thermophysical properties' optimal values could be obtained when no nanomaterial was added, and the best values were found at a temperature of 59.48 °C. This optimal point is found as close to the experimental data. [Display omitted] • Stable nanodiamond/water based nanofluids are prepared. • Thermal conductivity increased by 22.86% with 1 vol% concentration at 60 ℃. • Viscosity augmented by 79.16 with 1 vol% particle loading at 60 ℃. • Maximum Pr of 7.763 is attained at 30 ℃ with 1 vol.% loading. • Both single and multi-objective optimization was implemented. [ABSTRACT FROM AUTHOR]

• Latest developments in solar thermal applications using nanofluids are reviewed • Low to medium temperature solar collectors are summarized • Improvements in solar collectors using nanofluids as working fluid is compiled • Application of solar collectors in buildings is reviewed The efficient exploitation of solar irradiation is one of the most encouraging ways of handling numerous environmental concerns. Solar collectors are suitable devices that capture solar irradiation and convert it into thermal energy and electricity. In the last years, the nanofluids used in solar thermal systems have been studied as a useful technique for enhancing the solar collectors' performance and establishing them as viable and highly efficient systems. The present review paper aims to summarize and discuss the most important numerical and experimental studies in nanofluid-based solar systems for application at low and medium temperature levels, while the emphasis on the fundamental physical phenomena that occur. In the first part, numerous numerical models and the principal physical phenomena affecting the heat transfer rate in the nanofluid have been analyzed. More specifically, the importance of different forces in nanofluid flows that exist in particulate flows such as drag, lift (Magnus and Saffman), Brownian, thermophoretic, Van der Waals, electrostatic double-layer forces are considered. Moreover, an overview of the thermophysical properties, physical models, heat transfer models, and evaluation criteria of nanofluids are included in this work. In the second part, which is the main part of this work, a comprehensive review is performed to gather and discuss the new advantages in the nanofluid-based solar collectors that operate at low and medium temperatures. More specifically, the examined solar systems are the flat plate collectors, the evacuated tube collectors, the direct absorption collectors, and the thermal photovoltaic systems, while the investigated applications are space-heating, space-cooling, household hot water production, desalination, industrial activities, and power generation. The aforementioned collectors and applications are the most usual in the real systems, indicating the importance of the present work. Moreover, the emphasis is given in the thermal, exergy, economic, and environmental evaluation of the studied systems, as well as in the discussion of the possible limitations of the use of nanofluids like the lack of long-term stability, the agglomeration of nanoparticles, and the increased pumping work due to the increased pressure drop. Finally, it is found that the nanofluid utilization usually enhances the collector efficiency up to 5%, while higher enhancements can be found in thermal photovoltaics. Moreover, it is concluded that there is a need to emphasize issues such as stability and the use of eco-friendly solar systems. Lastly, the field's future trends are highlighted, and a clear image of the present situation and the next steps in the field are given. [ABSTRACT FROM AUTHOR]

Hybrid photovoltaic-thermal (PV-thermal) is a promising technology that could harness the maximum output from solar energy. In this work, a new thermal management system based on an innovative design of PV-thermal is designed and investigated under outdoor weather conditions in Sharjah, UAE. A numerical model is also developed to evaluate the thermal and electrical performances. Moreover, the energy and exergy evaluations are carried out to identify the performance enhancement of the PV system. The innovative absorber design adopted in this PV thermal system led to a considerable reduction of the module temperature. The results show that the novel cooling system enhanced both electrical and thermal performances. The maximum output power improved by an average of 15% with cooling, whereas the averaged module temperature decreased by almost 16 °C compared to the no-cooling case. The addition of front cooling to the PV-thermal system has also resulted in a further reduction of the module temperature by 26 °C and an increase of 17.6% in maximum output power with regard to the uncooled case. The exergy assessment showed that up to 61% increase in the overall exergy was achieved using the novel PV-thermal. [ABSTRACT FROM AUTHOR]

• Parabolic trough collector with MXene based Syltherm 800 industrial oil was studied numerically. • MXene-based nanofluids exhibit enhanced thermophysical properties, largely due to MXene's favorable localized surface plasmonic resonance (LSPR) effect. • A higher Nusselt number indicates improved heat transfer and improved exploitation of solar energy. • The MXene/Syltherm 800 nanofluid has the lowest required solar radiation. • According to environmental and economic analyses, the emission rate for MXene/Syltherm 800 is approximately 0.031 $/day, while for the base fluid, the cost is 0.033 $/day. This study examines LS-2 parabolic trough collectors (PTCs) using MXene/Syltherm 800 nanofluids for enhanced solar power generation, focusing on energy, exergy, environmental, and economic (4E) aspects. Despite MXenes' remarkable thermophysical properties, their application in nanofluids is underexplored. This research aims to fill this gap by analyzing the performance of MXene nanofluids across varied inlet temperatures (277 °C to 377 °C) and Reynolds numbers (104 to 22,000), areas often neglected in prior studies. Employing a rigorously verified one-dimensional heat transfer model, the study compares MXene/Syltherm 800 nanofluid (0.1 wt%) with other nanofluids like Al 2 O 3 , TiO 2 , and SiO 2 in Syltherm 800, highlighting the exceptional thermophysical properties of MXene-based nanofluids. This superiority is attributed mainly to the localized surface plasmonic resonance (LSPR) effect, which significantly enhances solar heat interaction. For an inlet temperature of 377 °C and Reynolds number of 104, MXene/Syltherm 800 nanofluid achieves a notable thermal efficiency increase of 6.572 %. MXene/Syltherm 800 consistently outperforms in various conditions, showcasing significant environmental benefits in energy and exergy analyses: MXene/Syltherm 800 nanofluid leads to reduced CO 2 emissions and associated costs compared to the Syltherm 800. Specifically, at 377 °C and a Reynolds number of 104, MXene/Syltherm 800 nanofluid records a CO 2 emission of 2.343 kg/day, lower than Syltherm 800′s 2.453 kg/day, alongside a corresponding reduction in emission costs. Future studies should investigate MXene's stability, synthesis, embodied energy, and potential in carbon capture. [ABSTRACT FROM AUTHOR]

Aviation fuels are essential for flight transportation. The increasing demand for such fuels threatens the present efforts to mitigate global warming. Changing to renewable energy sources and hydrogen to drive airplanes is not ready and will take a few decades. Therefore, alternative fuels such as sustainable aviation fuels (SAFs, also so-called bio-jet fuels) could play an excellent role in mitigating greenhouse emissions. SAFs encompass blends of bio and synthetic fuels. Some SAF pathways have already been certified (such as oil-to-jet, alcohol-to-jet, gas-to-jet, and sugar-to-jet), and some are on the way to being certified. This review starts by providing a detailed overview of the current status of aviation fuels, including their growth, types, and emission trends. After that, it comprehensively delves into a thorough discussion of SAFs, covering various aspects such as their types, combustion properties, production technologies and pathways, cost evolution, and life cycle assessments. The paper discusses the SAFs' future prospects while providing practical recommendations based on the analysis. It was shown that the oil-to-fuel (HEFA) pathway is more mature with less carbon emissions. SAFs face challenges, including high costs, limited production scale, feedstock availability, energy-intensive production methods, land-use competition, potential indirect environmental impacts, certification standards, infrastructure, and public acceptance. Much research is needed to reduce SAF costs substantially less than conventional aviation fuels. [ABSTRACT FROM AUTHOR]

In this study, rGO/Co 3 O 4 nanocomposite was synthesized, characterized, and then the thermophysical properties were obtained experimentally, after which the experimental data at varying values of temperature and particle loadings was used for optimization purposes. The study was concerned with different values of the controlling parameters. The in-situ/chemical reduction technique was used to synthesize the rGO/Co 3 O 4 nanocomposite and then characterized with x-ray diffraction, transmission electron microscope, and magnetometry. The system was studied at temperature values ranging at 20, 30, 40, 50, and 60 °C and with particle loadings of 0.05%, 0.1%, and 0.2% wt%. The authors in this article have introduced a novel population-based algorithm that is known as Marine Predators Algorithm to obtain the optimal values of the controlling parameters (i.e., temperature and nanofluid mixture percentage) that minimize two controlled variables (i.e., density and viscosity) as well as maximize the other two controlled variables (thermal conductivity and specific heat). The rGO/Co 3 O 4 nanocomposite nanofluid thermal conductivity and viscosity were investigated experimentally, and a maximum increment of 19.14% and 70.83% with 0.2% particle loadings at 60 °C was obtained. At 0.05%, 0.1%, and 0.2% particle loading wt%, the density increased by 0.115%, 0.23%, and 0.451% at a temperature of 20 °C; simultaneously, density increased by 0.117%%, 0.235%, and 0.469% at 60 °C, respectively as compared to water. At 0.2 wt%, the maximum decreased specific heat was 0.192% and 0.194% at 20 °C and 60 °C. When compared with water, no effect was observed with an increase in temperature/: a similar trend as that of the water was followed. The optimal values were found to be at a temperature of 60 °C and for 0.05% particle loading of the prepared nanofluid. However, among the conducted experiments, the optimizer pointed out that the optimal experiment was the one conducted at a temperature of 60 °C and a nanofluid percentage at 0.05. In conclusion, the proposed methodology of modelling with an artificial intelligence tool such as an adaptive network-based fuzzy inference system technique and then determining the optimal parameters with the marine predators algorithm accomplished the goal of the study with major success. Unlabelled Image • Novel rGO/Co 3 O 4 nanocomposite is synthesized and characterized. • Increment of 19.14% with 0.2% particle loadings at 60 °C was obtained for thermal conductivity. • Increment of 70.83% with 0.2% particle loadings at 60 °C was obtained for viscosity. • A maximum reduction in specific heat is 0.194% at 60 °C. • Optimal values were found to be at 60 °C and 0.056% of particle loading. [ABSTRACT FROM AUTHOR]

In the present work, the thermal conductivity (TC) of stable water base fly ash and fly ash-Copper (80:20 vol.%) nanofluid was determined experimentally in the temperature range of 30–60 °C for the volume concentration range of 0–4.0%. The two-step method was applied to prepare the nanofluids. The outcomes revealed that the TC of both the nanofluids augmented with the temperature and concentration, and also hybrid nanofluid had greater TC compared to the fly ash nanofluid and water. A new correlation was proposed for the calculation of the TC of these nanofluids based on obtained data. The maximum TC ratio of 1.32 and 1.50 obtained for a concentration of 4 vol.% of fly ash and hybrid nanofluid at 60 °C. In addition, to effectively predict and optimize the TC of water-based fly ash and studied hybrid nanofluid, multi-gene genetic programming (MGGP), and artificial neural network (ANN) approaches were applied. The comparative analysis showed the excellent ability of the ANN and MGGP model to predict the TC of fly ash and hybrid nanofluid with the regression coefficient (R) values of 0.9969 and 0.9966, respectively. [ABSTRACT FROM AUTHOR]

The heat transfer and flow characteristics of water-based fly ash nanofluid for concentrations of 0.1–1.5 vol.% that flow through a copper tube at an inlet fluid temperature of 303 K with constant heat flux boundary conditions are estimated numerically. Stability, viscosity, and thermal conductivity of fly ash nanofluid have been determined experimentally and compared with correlations available in the literature. STAR CCM + software was used to solve the governing equations using the finite volume method (FVM). Water and stable fly ash nanofluid were used as working fluids for the Reynolds number range of 4500–16,000. The Nusselt number and friction factor at 1.5% volume concentration are greater than the base fluid by 36% and 9.4%, respectively. The fly ash nanofluid showed a performance index (η ) value of more than 1 at all concentrations undertaken, indicating that the use of fly ash nanofluid in heat transfer applications is beneficial. The highest η value is determined to be 1.5 approximately for a nanofluid concentration of 1.5 vol.%. The fly ash nanofluid exhibits enhanced heat transfer performance contrasted to SiO2 nanofluid. The utilization of fly ash particles for heat transfer enhancement can aid in the reduction of environmental pollution to a certain extent. Novel correlations are suggested for the estimation of fly ash nanofluid Nusselt number and friction factor. [ABSTRACT FROM AUTHOR]

The current study intends to assess the impact of incorporating an oxygenated fuel additive (hydrogen peroxide (H2O2)) into a biodiesel/diesel fuel mix on diesel engine combustion efficiency and instability. The combustion, performance, and emission properties were evaluated using advanced test equipment to offer a full study. The combustion instabilities in terms of cyclic fluctuations were investigated to discover any unusual behavior when H2O2 was added to biodiesel/diesel fuel mixtures. Statistical and continuous wavelet transformations were used to investigate the cyclic fluctuations in peak cylinder pressure and indicated mean effective pressure (IMEP). Diesel, B20 (20%/80% of biodiesel/diesel fuel), B20H5 (20%/5%/75% of biodiesel/H2O2/diesel fuel), and B20H10 (20%/10%/70% of biodiesel/H2O2/diesel fuel) were tested in the study. Experiment results indicated that B20H10 produced the best results. In comparison to B20, B20H10 improved BTE by 6.56% and HRR by 8.5%, while decreasing BSFC by 7.98%, CO and HC emissions by 26.5%, and 6.67%, respectively. Furthermore, the peak pressure and IMEP cyclic changes were also well within permissible ranges. However, it was shown that adding H2O2 to B20 increased NOx emissions. The cyclic variations in the cylinder peak pressure and indicated mean effective pressure were analyzed using statistical methods and continuous wavelet transformation. No abnormality was detected in cyclic variation, thus ruling out any unsafe behavior in introducing test fuel additive to biodiesel blends. In principle, introducing H2O2 into a biodiesel/diesel fuel mix helped improve the engine performance and emissions while having no negative effects on engine life. [ABSTRACT FROM AUTHOR]

This paper presents a numerical investigation of the natural convection in an inclined rectangular enclosure with a baffle filled with Cu/water and then with Al2O3/water nanofluids using the finite difference method for tracking the thermal behavior within it versus the baffle length. The horizontal enclosure walls are assumed to be adiabatic, while the vertical ones are supposed to be a differentially heated. A thin horizontal baffle was attached to its left sidewall and is assumed to be cold. The flow and thermal fields are computed, respectively, for various values of Rayleigh number (103 ≤ Ra ≤ 105), inclination angle (0° ≤ ∅ ≤ 60°), baffle length (0.25 ≤ Lb ≤ 0.5), solid volume fraction (0.02 ≤ ϕ ≤ 0.06), and aspect ratio (1 ≤ AR ≤ 2). It was found that as the Rayleigh number, solid volume fraction, baffle length, and aspect ratio increase, an enhancement in the intensity of fluid flow in the enclosure was observed. In comparison, it reduces when the inclination angle increases. Moreover, it was found that the local Nusselt number (Nuc) enhances with the rise in Rayleigh number and the solid volume fraction. In contrast, it reduces with the increase in the aspect ratio and the inclination angle. [ABSTRACT FROM AUTHOR]

The objective of this study was to report electrocatalytic activity of tin selenide (SnSe) for oxygen evolution process (OER) and hydrogen evolution reaction (HER). Simple and inexpensive SnSe thin films were deposited onto a steel substrate using an electrodeposition method. Orthorhombic SnSe required a low overpotential value of 325, 317, 314 mV for OER and a low overpotential value of 273, 219, 194 mV for HER for SnSe-1, SnSe-2, and SnSe-3 electrodes, respectively, to reach a current density of 10 mA/cm2. The thickness of thin film increased over time 50, 60, and 70 min for each successive SnSe-1 to SnSe-3 samples. SEM image indicated crystalline in nature with compact grain-like morphology on the entire surface of the substrate. The SnSe-3 sample displayed low Tafel slopes of 90 and 68 mV/dec for OER and HER, respectively. EDX showed that atomic percentage ratio of Sn: Se was 54:46 for SnSe-3 thin film. Overall results suggest that electrochemically synthesized SnSe is a promising candidate as an efficient electrocatalyst for overall water splitting. [Display omitted] • Electrodeposited SnSe thin films were successfully synthesized. • The influence of deposition time on catalytic performance was examined. • Electrocatalytic analysis of SnSe was performed to capabilities of OER and HER. • The catalytic activity exhibited stability over a period of 12 h. [ABSTRACT FROM AUTHOR]

The increasing interest in wearable smart healthcare systems has sparked considerable attention toward flexible sensors owing to their high sensitivity and flexibility. However, these sensors still face challenges in terms of performance imbalances and instability. To address these issues, graphene-based conductive materials with exceptional mechanical and electrical properties have been incorporated into flexible sensors. Despite the potential of graphene, a comprehensive understanding of the sensing mechanisms and influence of fabrication methods on the performance of graphene-based flexible sensors is lacking. This article aims to bridge this gap by providing an overview of the latest research progress in flexible graphene sensors. We begin by analyzing the main properties of graphene materials, including tensile strength, specific surface area, thermal conductivity, and electrical conductivity. These properties highlight the superior characteristics of graphene for flexible sensor applications. The sensing mechanisms of strain/pressure, gas, and temperature flexible sensors are reviewed, with a focus on innovations in graphene composites, regular microstructures, and emerging preparation methods that enable an effective balance of the individual properties of a single flexible sensor. Furthermore, the article discusses graphene-based multifunctional flexible sensors that allow for the simultaneous monitoring of multiple stimuli, self-powered performance studies, and wireless communication performance studies. Performance analysis of these sensors in the context of flexible systems is provided. Finally, this article presents a comprehensive summary of flexible graphene sensors and offers an outlook for the future. We aim to provide theoretical guidance and technical support for the realization of individual whole-life physical sign detection using flexible graphene-based sensors. [ABSTRACT FROM AUTHOR]