To address the pressing housing demand brought on by issues with population increase, earth construction materials with good mechanical and thermal qualities must be developed. To meet this objective, earth bricks were reinforced with a hybrid blend of Opuntia ficus-indica cactus plant (OFICP) fibers and biochar obtained through the pyrolysis of the same plant. The fibers, incorporated at 0.5% and 1% by weight, underwent alkaline treatment using sodium bicarbonate (NaHCO3) at concentrations of 5%, 7%, and 10%, with immersion durations of 24, 72, and 168 hours. The multiple nonlinear regression models RSM et ANN were generated utilizing variables such fiber content, immersion time, and NaHCO3 content in order to predict compressive and flexural strength as well as thermal conductivity. According to the findings, 0.5% fibers treated with 7% NaHCO3 for 72 hours constituted the ideal formulation. The mix's workability was much improved by the addition of biochar. However, these mechanical characteristics gradually decreased as the fiber content increased above this level. Thermal conductivity dropped from 0.64 W/m & centerdot;K in specimens without OFICP fibers to 0.37 W/m & centerdot;K in those with 1% OFICP and biochar, demonstrating a significant decrease in heat transmission as a result of fiber inclusion and an improvement in thermal insulation. (sic)(sic)(sic)(sic)(sic)(sic)(sic)(sic)(sic)(sic)(sic)(sic)(sic)(sic)(sic)(sic)(sic), (sic)(sic)(sic)(sic)(sic)(sic)(sic)(sic)(sic)(sic)(sic)(sic)(sic)(sic)(sic)(sic)(sic)(sic)(sic)(sic)(sic)(sic)(sic).(sic)(sic)(sic)(sic)(sic)(sic), (sic)(sic)(sic)(sic)(sic)(sic)(sic)(sic) (Opuntia ficus-indica, (sic)(sic)OFICP)(sic)(sic)(sic)(sic)(sic)(sic)(sic)(sic)(sic)(sic)(sic)(sic)(sic)(sic)(sic)(sic)(sic)(sic)(sic)(sic)(sic), (sic)(sic)(sic)(sic)(sic)(sic)(sic).(sic)(sic)(sic)(sic)(sic)0.5%(sic)1%(sic)(sic)(sic), (sic)(sic)(sic)5%,7%(sic)10%(sic)(sic)(sic)(sic)(sic)(sic)(sic) (NaHCO3)(sic)(sic)(sic)(sic)(sic), (sic)(sic)(sic)(sic)(sic)(sic)(sic)24,72(sic)168(sic)(sic).(sic)(sic)(sic)(sic)(sic)(sic)(sic)(sic),(sic)(sic)(sic)(sic)(sic)NaHCO3(sic)(sic)(sic)(sic)(sic), (sic)(sic)(sic)(sic)(sic)(sic)(sic)(sic)(sic)(sic)(sic) (RSM)(sic)(sic)(sic)(sic)(sic)(sic)(sic) (ANN), (sic)(sic)(sic)(sic)(sic)(sic)(sic)(sic),(sic)(sic)(sic)(sic)(sic)(sic)(sic)(sic).(sic)(sic)(sic)(sic)(sic)(sic), (sic)0.5%(sic)(sic)(sic)(sic)7% NaHCO3(sic)(sic)72(sic)(sic)(sic)(sic)(sic), (sic)(sic)(sic)(sic)(sic)(sic)(sic)(sic).(sic)(sic)(sic)(sic)(sic)(sic), (sic)(sic)(sic)(sic)(sic)(sic)(sic)(sic)(sic)(sic)(sic).(sic)(sic), (sic)(sic)(sic)(sic)(sic)(sic)(sic)(sic)(sic)(sic)(sic), (sic)(sic)(sic)(sic)(sic)(sic)(sic)(sic)(sic)(sic)(sic).(sic)(sic)(sic)(sic)(sic)(sic) OFICP (sic)(sic)(sic)(sic)(sic)(sic)(sic) 0.64 W/m center dot K, (sic)(sic)(sic) 1% OFICP (sic)(sic)(sic)(sic)(sic)(sic)(sic)(sic)(sic)(sic) 0.37 W/m center dot K, (sic)(sic)(sic)(sic)(sic)(sic)(sic)(sic)(sic)(sic)(sic)(sic)(sic)(sic)(sic)(sic)(sic)(sic)(sic), (sic)(sic)(sic)(sic)(sic)(sic)(sic)(sic)(sic).(sic)(sic)(sic)(sic)(sic)(sic)(sic)(sic), (sic)(sic) 0.4% ((sic)(sic)(sic))(sic) 83 (sic)(sic) 8% NaHCO3 (sic)(sic)(sic) OFICP (sic)(sic)(sic)(sic)(sic)(sic)(sic) (SEBs), (sic)(sic)(sic)(sic)(sic)(sic)(sic)(sic)(sic)(sic)(sic)(sic).(sic)(sic)(sic)(sic)(sic)(sic)(sic)(sic)(sic)(sic)(sic)(sic)(sic)(sic)(sic)(sic)(sic)(sic)(sic)(sic)(sic)(sic)(sic)(sic)(sic)(sic), (sic)(sic)(sic)(sic)(sic)(sic)(sic)(sic)(sic)(sic)(sic)(sic)(sic)(sic)(sic)(sic)(sic)(sic).

This study investigates how key drilling parameters—feed rate (f), spindle speed (N), and drill diameter (d)—affect the delamination factor (Fd) during the machining of the Flower stalk of Agave americana (FSAa) fiber-reinforced biocomposites, using High-Speed Steel (HSS) and High-Speed Steel Coated with Titanium (HSS-TiN) tools. The experimental results show that increasing f and d leads to a decrease in Fd, reaching a minimum of 1.074 with the HSS tool compared to 1.020 with the HSS-TiN (N = 800 rpm, f = 150 mm/min, d = 5 mm). Conversely, a higher rotational speed slightly reduces delamination, with a maximum Fd of 1.204 obtained with HSS-TiN (N = 1600 rpm, f = 50 mm/min, d = 10 mm), compared to 1.261 for HSS under the same conditions. A comparative analysis shows that the HSS-TiN tool consistently outperforms the uncoated HSS tool, offering lower delamination levels due to reduced friction and better wear resistance. Modeling with response surface methodology (RSM) and artificial neural networks (ANN) was developed to predict Fd, with both models showing excellent agreement with experimental data. For HSS-TiN, the ANN model achieved a coefficient of determination R² of 98.94%, surpassing that of the RSM model, which was 98.11%. Similarly, for HSS, ANN obtained an R2 of 98.82%, slightly higher than that of RSM (98.04%), thus confirming the superior predictive capacity of the neural approach in both cases. The optimized numerical model for the delamination factor of the biocomposite using HSS-TiN tool showed the lowest delamination factor of 1.019 for a drill diameter of 9.97 mm, a feed rate of 138.59 mm/min and a spindle speed of 817.04 rev/min. The findings highlight the potential of surface-coated tools and advanced modeling techniques in improving drilling quality for sustainable composite materials.

This work is the first to examine the pyrolysis of Chamaerops humilis fibers (ChFs) and demonstrate their potential for bioenergy. Assessing the ChFs for pyrolysis-based bioenergy conversion involved examining thermodynamic and kinetic properties. Three different heating rates (beta) were applied during thermogravimetric analysis (TGA) under an inert atmosphere. The deconvolution function, employing an asymmetric double sigmoidal, indicates that modeling the pyrolysis of ChFs for biomass breakdown can be accurate. TGA showed that multiple stages occur during ChF's pyrolysis. The characteristics of the second stage were identified. Components stable at lower temperatures were heated at beta of 5, 10, and 20 degrees C/min, covering temperature ranges of 210-358 degrees C, 210-374 degrees C, and 210-396 degrees C. Using the Coats-Redfern method, twenty-one kinetic models were developed based on four main solid-state response procedures. The best-fitting diffusion model, with the highest correlation coefficients (R-2 > 0.99) across all beta values, employs the Jander equation (3D diffusion). Activation energies of 72.32, 85.06, and 102.09 kJ/mol were determined at beta of 5, 10, and 20 degrees C/min, respectively. Thermodynamic parameters (Delta H, Delta G, and Delta S) were determined from kinetic data. Overall, thermodynamic considerations suggest that ChFs are especially promising as inputs for biofuel and bioenergy production.

This study aims to predict the pyrolysis behavior of Chamaerops humilis fibers (ChFs) and gain insights into their thermal degradation, using artificial neural networks (ANNs) as a data-driven modeling tool. Thermogravimetric analysis (TGA) was performed on ChFs between 30 degrees C and 800 degrees C at six heating rates (5, 10, 20, 30, 40, and 50 degrees C/min) under a nitrogen atmosphere. A feed-forward ANN with two input neurons (temperature and heating rate) and one output neuron (weight loss) was developed. Twenty-seven network architectures were tested to identify the optimal model, which was then used to calculate kinetic and thermodynamic parameters. Model-free methods (Flynn-Wall-Ozawa, Kissinger-Akahira-Sunose, and Starink) were employed for comparison. The best ANN model (ANN26, 5 & times; 17 & times; 1) achieved excellent prediction accuracy (R & sup2; > 0.99996) for all heating rates. The ANN successfully predicted weight loss trends, enthalpy (Delta H), and Gibbs free energy (Delta G), while slightly overestimating activation energy (Ea) in the KAS method. The results demonstrate strong agreement between ANN predictions and experimental data across all stages of pyrolysis. This work shows that even a simple ANN can accurately model the complex thermal degradation of ChFs, providing a reliable tool for process optimization. The approach enables prediction of pyrolysis behavior at different heating rates, highlighting the potential of ANNs for data-driven biomass conversion studies.

Due to their exceptional heat transmission capabilities and variety of uses, Hybrid Nano-fluids have attracted to research community and scientists of modern era. The current work revealed the numerical approach to application of Hybrid Nano-fluids to competency modules of cylindrical battery and latest cooling systems. Principally Hybrid Nano-fluids are made of basic coolant fluid supplemented by using nano-particles of several materials for enhancing thermal conductivity of battery as well as cooling systems including properties of heat transmission. Through merging of two distinct sorts of nanoparticles, aluminum oxide and copper, which are disseminated throughout a water-based liquid, this study produces a Hybrid Nano-fluid of Cu + Al 2 O 3 /H 2 O. The energy equations under consideration are outcomes of viscous dissipation, heat production and Joule heating, convection boundary conditions are used in momentum equation and magnetic field variables are also taken in account. By use of suitable similarity variables, a structure of Nonlinear PDEs transmuted into the resultant ODEs. By exploiting extraordinary Levenberg-Marquardt Backpropagation Algorithm (LMBP-Algorithm) along with Artificial Intelligence's Neural Networks equations are numerically resolved. The competence of the foreseen NNs of AI with LMBP-Algorithm under several conditions is assessed through several performance metrics, including Mean square error, Histograms for error and Regression analysis. A detailed inspection is also applied to decide impacts of key constraints on velocity as well as temperature profiles. Increasing behavior of velocity profile for Local Grashof number, Heat source/sink factor and Brinkman number and a decreasing behavior for Magnetic field parameter, whereas an increasing behavior of temperature profile for all these four parameters is observed. They are considered most likely remarkable adoptions for effectively cooling battery packs in a variety of uses, comprising renewable energy storage, latest electronics along with modern electric vehicles.

To overcome the critical challenge of machining-induced structural degradation that restricts the industrial adoption of eco-friendly materials, this study aims to improve biocomposite performance by enhancing machinability and overall functionality, thereby broadening their applicability across multiple industries. By using natural fibers and environmentally friendly treatments, the research advances the development of sustainable materials in the composite sector. Crucially, this work introduces a novel comparative evaluation of the drilling machinability of hybrid sisal-jute/epoxy biocomposites treated with alkaline (NaOH) and eco-friendly sodium bicarbonate (NaHCO3) solutions was systematically investigated. Composites were fabricated with various stacking sequences of unidirectional sisal and bidirectional jute fibers, yielding three composite types: sisal jute/jute sisal (SJJS)/epoxy, SJJS-NaOH/epoxy, and SJJS-NaHCO3/epoxy. The experimental protocol evaluated three primary factors at three levels: drill diameter (d, 4, 7, 10 mm), spindle speed (N, 750, 1500, 3000 rev/min), and feed rate (f, 50, 100, 200 mm/min). The core methodological novelty lies in the concurrent deployment and rigorous comparison of Response Surface Methodology (RSM) and Artificial Neural Networks (ANN) to predict the delamination factor (Fd) coupled with advanced genetic algorithm (GA) optimization tailored for chemically treated hybrid structures. Results indicate that NaHCO3 treatment reduced delamination by up to 17.67% compared with untreated fibers. Specifically, the absolute delamination factor decreased from Fd = 1.5542 for the raw composite to Fd = 1.2795 for the treated specimens, providing a baseline for high-quality drilling. Optimization using an ANN/genetic algorithm and an RSM/desirability function identified optimal drilling conditions as d = 10 mm, N = 3000 rev/min, and f = 50 mm/min. In comparison to the RSM model, the ANN architecture of Fd1, Fd2, and Fd3 demonstrated higher predictive accuracy in capturing complex non-linear structural behaviors, as evidenced by a lower mean squared error (MSE = 0.1123, 0.1102, and 0.0653) and a higher coefficient of determination (R2 = 0.9918, 0.9912, and 0.9932). These outcomes underscore the potential of treated SJJS/epoxy biocomposites as sustainable alternatives for high-performance applications in the automotive and eco-construction sectors.

In today's construction projects, considering the environment and economy is essential. Alternatives to cement or natural aggregates lead to natural resource conservation and reduced carbon dioxide emissions. In this context, dune sand (DS) and Washingtonia waste (WW), which are abundant in the Algerian desert, were investigated as potential eco-friendly substitutes for cement in mortar manufacture. The initiative aims to create innovative, ecological, and cleaner building materials and lightweight, eco-friendly cement mortars. To this end, the response surface methodology (RSM) was applied for predicting and optimizing the physical characteristics of mortars composed of DS and WW, varying from 1 % to 3 % and treated for 4-24 h with sodium hydroxide solution (NaOH) at a 1-5 % concentration. The purpose of this study was to evaluate the suitability of the material for civil engineering, focusing on properties such as slump (S), specific gravity (rho), water absorption (WA), bending displacement (Yb), dynamic elastic modulus (Edyn), and other properties. Furthermore, the mortar's chemical composition and high- temperature behavior were investigated. To maximize mechanical qualities and minimize physical properties, an analysis of variance using the Box-Behnken Design was performed to optimize and forecast the factors and outcomes. The results revealed that WW content, NaOH concentration, and immersion time significantly influenced the physico-mechanical properties of the mortar. The optimal formulation obtained was 1.3 % WW, 5 % NaOH concentration, and 14.8 h of immersion time, leading to values of 1972.77 kg/m3 for rho, 16.62 cm for S, 2.63 % for WA, 0.26 mm for Yb, and 20.46 GPa for Edyn. The strong correlation between the RSM model and experimental data confirms the model's reliability. These findings demonstrate the potential of this sustainable mortar for eco-construction applications, such as bending elements and repairing damaged structures in buildings, highways, and bridges.

Investigating the fascinating world of natural fibers, where Syagrus romanzoffiana fibers (SrFs) are promising substitutes for glass and synthetic fibers in composite materials, is more than interesting. The improvement of SrFs through an environmentally friendly treatment employing sodium bicarbonate (NaHCO₃) at different concentrations (5 %, 10 %, 20 %, and 30 % by weight) over various durations (24, 72, and 168 h) is the subject of this study. The objective is to provide a sustainable and economical approach to enhancing fiber characteristics. Comparisons were made between treated and untreated fibers and fibers from semi-arid and humid regions to evaluate geographical influences. Key findings include considerable enhancements in tensile properties: a 58 % rise in Young's modulus and a 69 % rise in traction stress for fibers treated with 20 % NaHCO₃ for 72 h. The stretching at fracture of these treated fibers was measured at 1.04 ± 4.49 %. The treated fibers also showed an increased crystallinity index of 71.61 % and a crystal size of 2.38 nm. Fourier-transform infrared spectroscopy revealed the chemical modifications from the treatment. Thermogravimetric analysis (TGA) indicated thermal stability up to 327 °C and a kinetic activation energy of 53.84 kJ/mol, compared to 62.72 kJ/mol for untreated fibers. The study highlights an environmentally friendly approach to material development by showcasing the potential of treated SrFs in lightweight biocomposite applications. This study provides valuable information on the TGA/pyrolysis of SrFs at 10 °C/min for potential bioenergy production, including assessing environmental impact, opportunities concerning sustainable resource management, and integration with other renewable energy systems.

Research on natural fibers as greener substitutes for synthetic ones has surged in response to the growing need for sustainable materials. An underutilized natural resource, Chamaerops humilis trunk (ChT), is the subject of this study's extraction and characterization process. The work examines these fibers' possible uses in biocomposites by examining their structural, physicochemical, and mechanical characteristics. Numerous characterization techniques were used to evaluate ChT fibers (ChTFs) thoroughly, including density measurement, diameter determination, analysis of the fibers' moisture content, X-ray diffraction, scanning electron microscopy, Fourier transform infrared spectroscopy, thermal analysis, water absorption tests, and tensile testing. Experimental results show that ChTFs possess an average density of 0.97 g/cm3, an average diameter of 562 ± 60 μm, a moisture regain ranging from 7.94 to 8.63 %, an average linear density of 9.338 Tex, heat resistance to 225 °C and a mean traction resistance of 45.08 ± 9.92 MPa. Such findings underscore the significance of comprehending the ChT's mechanical characteristics to enhance fiber-reinforced composites and explore their possible uses in the textile sector besides their promising reinforcements in biocomposites and as a source of biomass for renewable bioenergy.

In response to the pressing need for more efficient thermal energy storage solutions, this study investigates the strategic implementation of baffles in phase change material (PCM) tanks to enhance thermal performance. PCM offers a promising solution for efficient thermal energy storage (TES); however, ensuring uniform temperature distribution inside the tanks remains challenging. Horizontal baffles with holes of varying diameters were introduced in Tanks 02, 03, and 04, while an inclined baffle with holes was used in Tank 05. The Tank 06 benefitted from an inclined baffle with holes of different diameters. A comprehensive analysis of all Tanks was evaluated by assessing PCM and water heat flux, PCM and water static enthalpy, Richardson number, velocity vectors, temperature, and liquid fraction contours. The results demonstrated that significant improvements were achieved with the addition of baffles. Tank 01, without a baffle, exhibited a melting time of 2860 s. However, the introduction of baffles resulted in reduced melting times for Tanks 02 to 06: 2360 s (17.48 %), 2350 s (17.83 %), 2400 s (16.08 %), 2320 s (18.88 %), and 2240 s (21.67 %), respectively; which led to enhance TES efficiency, and a quicker energy storage process. The study also includes a comprehensive economic analysis, evaluating the total cost (Ctotal) and performance-economic ratio (Pc). Tank 06 shows superior economic performance, with a Pc value of 0.26 despite a slightly higher cost than Tank 01 by $2 USD. These findings highlight the baffle design's effectiveness in achieving better heat transfer and uniform temperature distribution within PCM tanks, making them more efficient for TES applications.

The pressing issue of growing carbon dioxide (CO2) levels and global warming has prompted efforts to create new building materials with the capacity to absorb and store CO2. Using cement substitutes helps to preserve the environment by slowing the spread of carbon dioxide. As a result of the abundance of Washingtonia robusta waste (WRW) produced during maintenance operations on Washingtonia robusta (WR) and sand from the dunes of Algeria's Sahara desert, as well as the production of biochar made from a pyrolysis at 500 degrees C of these residues (WRWB) on the flexural, compressive properties and porosity of cementitious mortars are explored. The approach is based on gradually replacing cement with WFRB biochar and WRW fibre waste at varying rates: from 0 % to 2 % with a step of 0.5 % and treated for different periods of time (24, 72, and 168 hours) at different NaHCO3 concentrations (4, 8 and 16 %). According to the response surface method (RSM) and artificial neural networks (ANN), the optimal cement substitution of rates were 1,8 % of WRWB and 1,3 % of WRW treated with 4 % of CaCO3 concentration for a 23,6 hour. Furthermore, it is appropriate to note that predictive accuracy using ANN models is higher than that of RSM models, as demonstrated by their good correlation with developed models' experimental data. These techniques have increased the use of green mortars and their acceptance as construction materials.

To research the mechanisms of diffusion and water uptake kinetics biocomposites, various HDPE materials reinforced by varying quantities of Washingtonia filifera (WF) fibres (10 to 30 wt%) were submerged at room temperature in distilled water. To optimise the immersion time and WF fibre content in HDPE/WF biocomposite water uptake, an artificial neural network, the response surface methodology and the genetic algorithm were employed. In this research, the CCD model of RSM was utilised to carry out test design, modelling, and optimisation. It was found that the way water absorbs liquids follows the Fickian diffusion mode. The outcomes demonstrate that the incorporation of WF fibres into the HDPE matrix decreased the diffusivity. The ANOVA determined the relative significance of each variable and demonstrated the model's validity by demonstrating a high correlation between the observed data. Moreover, the results showed that the ANN models have training, test and validation correlation coefficients for water absorption prediction of 0.9955, 0.9915 and 0.9999, respectively. RSM-GA revealed that a 10% fibre content and a one-hour immersion duration produced the lowest levels of absorption. Additionally, a model that is very suitable for predicting biocomposites water uptake and is applicable to a variety of industrial applications is developed.

Employing sustainable biomaterials obtained from waste biomass and biopolymers provides a very promising method for eliminating organic dyes from wastewater. This study presents a novel adsorbent of modified dragon fruit peels and chitosan, addressing wastewater treatment and environmental waste management. Precisely, a bio-sourced multifunctional (high level of functional groups) adsorbent (hereinafter, CHS/DFP-ADP) was developed from chitosan and adipic acid activated-dragon fruit (Hylocereus polyrhizus) peels. This biomaterial was applied to effectively adsorb organic pollutants (safranin O dye, SAF-O) from water. The adsorption variables, namely A: CHS/DFP-ADP dosage (0.02-0.08 g), B: pH (4-10), and C: duration (10-40 min), were modeled and optimized using the Box-Behnken Design (BBD). The results of the BBD model showed the optimum adsorption parameters for achieving the highest level of SAF-O removal (94.83 %) were as follows: CHS/DFPADP does = 0.049 g, the pH similar to 10, and the contact duration = 40 min. The experimental results on the dye adsorption by CHS/DFP-ADP demonstrated conformity with the pseudo-first-order and Freundlich models. The biomaterial demonstrated a significant capability to adsorb SAF-O dye, with an adsorption capacity of 607.2 mg/g. The adsorption process of the cationic dye on the CHS/DFP-ADP involves several interactions, such as Yoshida H-bonding, electrostatic forces, n-pi, and H-bonding. This work aligns with the principles of green chemistry and sustainable development, offering an innovative approach to tackle environmental concerns and promote the circular economy. The present effort meets several Sustainable Development Goals (SDGs), such as SDG 6 (Clean Water and Sanitation), SDG 12 (Responsible Consumption and Production), SDG 13 (Climate Action), and SDG 14 (Life Below Water).

This study addresses the critical issue of determining the environmental impact of wastewater discharged from a petroleum complex's wastewater treatment plant (WWTP). The emphasis is on assessing the quality of purified water and its potential environmental consequences. Using the water quality index (WQI) as a comprehensive metric for water quality assessment, the study investigates the effects of key parameters such as pH, temperature, phosphates, and hydrocarbons derived from an oil refining complex WWTP. The aim is to contribute to water resource management and environmental monitoring. Machine learning models were trained on Principal Component Analysis (PCA) data, representing 70 % of the total data. The results show that water quality indices vary significantly across seasons, with maximum values for WQI in autumn (40.66), winter (32.96), spring (37.92), and summer (49.34). The ANN and RSM-BBD models effectively forecast experimental values with high predictive accuracy indicated by determination coefficients (R2). For WQI in autumn, winter, spring, and summer, R2 values for ANN were 0.9897, 0.9834, 0.9909, and 0.9956, respectively, and 0.9279, 0.9378, 0.9802, and 0.98866 for RSM-BBD. While the ANN model outperformed the RSM-BBD model, both demonstrated efficacy in predicting water quality indices. The study adds to our understanding of the ecological implications of discharged water from petroleum complexes by providing valuable insights into seasonal variations in water quality factors.

This work uses thermogravimetric analysis to perform the thermokinetics and thermodynamic studies of Syagrus romanzoffiana fibers (SRFs). In a nitrogen environment, SRFs were heated non-isothermally between 25 and 800 degrees C at four heating rates of 5 degrees C/min, 10 degrees C/min, 15 degrees C/min, and 20 degrees C/min. According to thermogravimetric examination, the pyrolysis of SRFs occurred in three steps. The second stage has had its kinetic and thermodynamic characteristics determined. The low-temperature stable components were decomposed at temperatures ranging from 218 to 376 degrees C, 218-391 degrees C, 218-394 degrees C, and 218-398 degrees C at heating rates of 5 degrees C/min, 10 degrees C/min, 15 degrees C/min, and 20 degrees C/min, respectively. The Coats-Redfern method was applied to twenty-one distinct kinetic models representing four key solid-phase reaction processes. The diffusion model using the Zhuravlev equation is the best-fitted model, having the most outstanding correlation coefficient values (R-2 > 0.99) for all heating rates. Heating rates of 5, 10, 15, and 20 degrees C/min resulted in activation energy values of 114.02, 118.77, 119.44, and 113.89 kJ/mol, respectively. Thermodynamic characteristics (Delta H, Delta G, and Delta S) were computed using kinetic parameters. The data presented here helps evaluate SRFs as a possible biomass renewable energy source for building reactors and generating chemicals.

In the current study, new prediction models were suggested to predict the compressive strength, porosity, and thermal conductivity of bio-mortar samples by replacing cement by weight with pyrolysis of Washingtonia filifera waste biochar (WFWB). Bio-mortars containing different biochar contents were prepared with the addition of 1%, 2%, 3%, 4%, and 5% pyrolyzed biochar at different temperatures 300°C, 400°C, and 500°C. The mortar samples produced were evaluated for compressive strength at 7 and 28 days. Relation between compressive strength porosity and thermal conductivity values (dependent values), and biochar replacement ratios and pyrolysis temperatures (independent values) was predicted by artificial neural network (ANN) machine learning techniques based on the Levenberg Marquardt algorithm. The results revealed compressive strength increase at 28 days of nearly 12%, 3%, and 2% at 1% optimal biochar replacement content for WFWB500, WFWB400, and WFWB300 specimens, respectively. Moreover, these results provide confidence in the manufacturability of bio-mortars with a compressive strength of 63.81 MPa at 28 days using only 1% substitution of WFWB500 and a thermal conductivity coefficient of 0.52 W/m.K. The importance measure of the variables shows that the most influential variables are the percentage of biochar. The statistical and experimental results also revealed satisfactory agreement.

The current paper provides unique smooth control methods for constructing resilient nonlinear autopilot systems and cooperative control protocols for single and multi-missile systems. To develop the single autopilots, a high-order framework based on asymptotic output stability principles and local relative degree for nonlinear affine systems is first applied. Then, using asymptotic exponential functions and graph theory, free-chattering distributed protocols are constructed to allow multi-missile systems to track and intercept high-risk targets. The Lyapunov approach is used to derive the essential requirements for smooth asymptotic consensus. The proposed method minimizes computing load while enhancing accuracy. The simulation results indicate the efficacy of the recommended strategies.

The building industry's current trend to reduce and protect environmental impact implies the design and fabrication of more ecological and sustainable building materials. Biochar has the potential to be incorporated in construction materials for its specific characteristics and environmental advantaaffnciges that it offers. Plasters are susceptible to cracking and spalling due to environmental conditions. This study offers the development of a novel bio-mortar biochar-reinforced plaster products obtained by pyrolysis of Washingtonia plant biomass biochar (WPBB). Three biochar contents (1, 2 and 3%) according to three temperatures (300, 400 and 500 °C) were examined. Sample characterization, such as FTIR (Fourier Transform Infrared Spectroscopy) and SEM (Scanning Electron Microscopy), was conducted to investigate bio-mortars obtained from biomass waste biochar. The incorporation of WPBB led to increased bending strength and decreased ductility compared to reference data of plaster biocomposite i.e.: 229%, 200% respectively, for the reinforced plaster with an optimum content of 1 w% pyrolyzed biochar at 500 °C. However, it was found that the use of less than 2 wt% biochar could give plaster biocomposites superior performance to conventional materials and the 2% biochar content improved the ductility compared to the 1% and 3% contents.; Adding biochar to mortar improved thermal performance compared to the reference mixture, allowing its use as a material for moisture control. Furthermore, the models generated using RSM response surface methodology and ANN neural networks agreed well with those obtained experimentally for the bending properties the newly conceived plaster/biochar biocomposite. Gypsum bio-mortars containing WPBB can be utilized to create lightweight mortars with exceptional qualities including low density and thermal insulation.

The aim of this study was to develop a lightweight epoxy based biocomposite for morphing wing and unmanned aerial vehicle (UAV) applications. The proposed composite was developed using a 3D printed high stiffness lignin-Acrylonitrile Butadiene Styrene (ABS) core and industrial hemp with aluminized glass fiber epoxy skin. The ABS was reinforced using lignin macromolecule derived from cashew nut shells via twin screw extruder and the core was printed using an industrial grade 3D printer. Furthermore, the composites were prepared by compression moulding with an ABS-lignin core and hemp/aluminized GF surface and characterized according to respective American society of testing and materials (ASTM) standards. The findings indicate that the addition of 30 vol% Al-glass and hemp fiber with lignin strengthened ABS core improved the mechanical properties. The composite material designated as "E2" exhibits the maximum mechanical properties, providing tensile strength, flexural strength, Izod impact, interlaminar shear strength (ILSS), and compression values of, 136 MPa, 168 MPa, 4.82 kJ/m2, 21 MPa, and 155 MPa respectively. The maximal energy absorbed by composite designation "E2," during drop load impact test is 20.6 J. Similarly, the composite designation "E2"gives fatigue life cycles of 33,709, 25,781 and 19,633 for 50 %, 70 % and 90 % of ultimate tensile strength (UTS) and 32.5 (K1c) MPa⋅m and 0.76 (G1c) MJ/m2 in fracture toughness and energy release rate respectively.

The aim of this study is to develop a light weight hybrid biocomposite using pineapple and Kevlar fiber with peanut husk cellulose in vinyl ester resin for applications in unmanned aerial vehicles. This study focuses on how the silane treatment on fiber and cellulose particle influences the mechanical, fatigue and low velocity impact properties of this hybrid biocomposites. Using hand lay-up technique, the biocomposite was prepared with cellulose loading ranging from 1 to 5 vol%. The results revealed that the 5 vol% of cellulose added composite had an improved tensile, impact, flexural, hardness and ILSS of 161 MPa, 224 MPa, 6.8 J, 84 shore-D and 21.4 MPa. Moreover, the biocomposite with the inclusion of 3 vol% cellulose had an improved fatigue life count of 42 697, 29 821, 22 381 and 18 164 at 25%, 50%, 75% and 90% of UTS. Similarly, the 3 vol% cellulose reinforced composite showed an improved low velocity impact toughness of 12.36 J. The obtained results clearly indicated that these mechanically strengthened and highly toughened biocomposites could be used as working material for number of applications, especially in making of UAVs for the aerospace industry, automotive components for the transportation sector and structural material in domestic infrastructure.