In this study, the thermal, spectroscopic, and crystallographic characteristics of 3D-printable filaments based on a Polyethylene Terephthalate Glycol (PETG) matrix reinforced with Hydroxyapatite (HA) and Silver nanoparticles (AgNPs) were experimentally examined. Ten different compositions of PETG nanocomposite pellets with varying HA (10, 15, and 20 wt%) and AgNPs (2 and 3 wt%) concentrations were prepared through melt compounding followed by extrusion using a twin-screw extruder. The resulting pellets were analysed using Fourier-transform infrared spectroscopy (FTIR) and Raman spectroscopy to investigate molecular structure and bonding characteristics. The crystalline phases were identified by X-ray diffraction, while the thermal behaviour was evaluated by Thermogravimetric Analysis (TGA) and Differential Scanning Calorimetry (DSC).Spectroscopic analysis indicated that the incorporation of HA and AgNPs caused only minor shifts in characteristic bands, suggesting limited alteration of the PETG molecular structure. The nanocomposite containing PETG with 15 wt% HA and 2 wt% AgNPs exhibited the lowest transmittance in the FTIR spectrum, indicating stronger interaction within the composite system. Crystallographic evaluation further showed that this composition achieved the highest crystallinity index (CI) of 19.9%. Thermal analysis revealed that the presence of HA and AgNPs influenced the thermal response of the nanocomposites, with the PETG + 15 wt% HA + 2 wt% AgNPs formulation demonstrating the highest glass transition temperature (Tg) of 81.4 °C, along with a degradation temperature of 466.20 °C and a residual weight of 15.80%.Overall, the PETG nanocomposite reinforced with 15 wt% HA and 2 wt% AgNPs exhibited the most favourable combination of crystallinity and thermal stability among the investigated formulations. These findings are expected to establish a benchmark for future research on PETG + HA + AgNPs nanocomposites, which could serve as a promising material for prosthetics and orthotics.

Escalating environmental imperatives have intensified the demand for machinable, low-carbon composite materials, exposing critical knowledge gaps in the drilling behavior of surface-engineered natural fiber systems. This study addresses this gap by systematically investigating the drilling performance of alkali–silanized Corchorus olitorius filler–reinforced polymer composites. The effects of spindle speed, feed rate, and drill diameter on thrust force, material removal rate, surface roughness, and roundness error were experimentally evaluated. The results demonstrate that high spindle speed combined with low feed rate and smaller drill diameter significantly minimizes drilling-induced damage, yielding lower thrust force, improved surface integrity, and enhanced dimensional accuracy. Chip morphology analysis revealed that parameter-controlled chip segmentation plays a critical role in governing surface quality and material removal efficiency. Furthermore, data-driven prediction models were developed, among which the Support Vector Machine (SVM) exhibited superior accuracy in forecasting drilling responses, outperforming ANN and KNN frameworks. These findings establish optimized drilling guidelines and reliable predictive capability for eco-engineered composites, highlighting their suitability for lightweight, cost-effective structural and residential applications where moderate mechanical performance is sufficient.

Amputees who lost a limb must depended on prosthetic devices. A lower limb prosthesis is an artificial component designed to replace the missing leg and improve mobility, comfort, stability, and functional performance during walking. In this study, a lightweight prosthetic socket was developed using kenaf fiber reinforced biocomposites and its biomechanical response was investigated in terms of kinematics and kinetics during gait. The angular variations and dynamic forces of both healthy and prosthetic limbs were experimentally analyzed using force plate method under natural body weight conditions. Additionally, the interface pressure between socket and residual limb was evaluated at pressure-sensitive and pressure-tolerance regions using pressure sensor to assess the comfort level of the patient. The results revealed that the developed socket demonstrated improved load-bearing capability, stability, and compatibility during the gait cycle. Furthermore, the prosthetic limb exhibited slightly reduced gait parameters such as cadence, stride length, and walking speed compared to the health limb, primarily due to restricted joint motion. The biomechanical response indicated that, the kinematic response of prosthetic limb in sagittal plane was nearly comparable to the healthy limb while, minor deviations were observed in coronal and transverse planes. The kinetics response of prosthetic limb was found to be optimal with minimal detrimental effects as compared to healthy limb. The pressure distribution between socket-limb interface was maximum in pressure tolerance regions particularly at distal end and tibial end of the stump. Overall, the study demonstrates the feasibility of sustainable natural fiber composites in prosthetic socket design, providing a promising alternative to conventional materials with acceptable biomechanical performance.

Due to increasing sustainability concerns, wood filler-reinforced polymer (WFRP) composite materials have gained prominence as a potential material in various industries such as construction, automotive and consumer products. This real-world application of wood filler-reinforced polymer composites requires well understanding and prediction of important mechanical properties. The conventional experimental methods of material characterization are often resource intensive and time-consuming. Recently, the machine learning (ML) presented a novel and viable avenues for augmenting prediction models, enabling the accurate estimation of mechanical properties with fewer experiments and improved generalization. The current work presents the application of ML techniques for the prediction of tensile properties of WFRP composite. Various models like support vector machine, polynomial regression, and decision trees (DT) are explored for their potential to predict tensile properties based on input variables like filler content, and crosshead speed. These models are very effective and accurate in representing highly intricate and nonlinear interdependencies between material input parameters and its performance. Additionally, the artificial neural network model, in particular, exhibits an excellent capability of predicting tensile strength of composites with the lowest MSE value. The study highlights the efficiency of ML models, demonstrating their potential to enhance material property prediction.

A growing apprehension about global warming has sparked a pursuit among the scientific community to produce ecological friendly substances that may mitigate carbon effects. The atmospheric and ecological features of natural fiber-based composites have had substantial consequences in the field of sustainability. This research investigates how different tool characteristics, such as feed rate and cutting speed, affect the drilling performance of composites based on silanized Corchorus olitorius particles. A number of trails are undertaken to quantify the influence of feed and cutting speed on multiple variables which involves drill force, material removal rate, roundness inaccuracy and surface roughness. The findings demonstrated that the arrangement of drilling has had an immense impact on the emergence of flaws in the vicinity of periphery hole. With an 8 mm drill bit, the lowest feed rate (20 mm/rev) and maximum cutting speed (2000 rpm) resulted in the lowest thrust force (44.25 N) and surface roughness (1.256 μm). On the other hand, maximum values occurred with greater feed rates and lower cutting speeds. In order to identify the potential drilling attributes of established composite substrate, some machine learning models have been devised. Among these models, the support vector machines model has achieved the greatest accuracy (R2 up to 0.951). These findings illustrate the composite’s viability for lightweight residential applications because of its machinability, cost-effectiveness, and satisfactory mechanical performance.

This study presents a comprehensive investigation into passive thermal management of lithium-ion (Li-ion) batteries using beeswax (BW) as a phase change material (PCM), and assesses the effect of cell arrangement on thermal performance under varying discharge rates, and optimized enclosure design. Evaluating inline and staggered configurations at 2C and 5C charge or discharge rates with heat generation rates of 63,690 W/m3 and 104,790 W/m3, simulations show the inline setup providing superior thermal control, reaching lower maximum temperatures of 333.1 K at 2C, and 338 K at 5C compared to the staggered setup where temperatures were 333.8 K at 2C, and 342 K at 5C. BW is effectively absorbing heat, reaching melting fractions up to 70

Natural fibers have piqued the interest of researchers, academics, and manufacturers due to their increased environmental sustainability and biocomparability. As a result, natural fiber-reinforced composites have a significant potential to replace synthetic materials in structural applications. The goal of this research is to create green composites out of organically sourced flax and ramie fibers and a bio-epoxy matrix utilizing a compression mold process. The composites have been fabricated by varying the weight of flax and ramie fibers in ratio of 10

Recently, natural fiber/filler-based composite materials are gaining popularity due to their light weight, ease of procurement and eco-friendliness, and greater modulus and specific strength. The study of mechanical characteristics using Finite Element Methods (FEM) has become progressively essential to quantify the composite’s strength and modulus with different input criteria to avoid experimental complexity. In the present study, the tensile characteristics of the coir filler reinforced composites are evaluated using the Finite Element Method (ANSYS R121) for six different filler weight percentages (0, 2.5, 5, 7.5, 10, and 12.5 wt.

The aim of this study is to evaluate the influence of reinforcing powdered bamboo filler (PBF) on the mechanical and fatigue properties of epoxy-based polymer composites, with a focus on balancing void content and tensile strength. Epoxy composites were fabricated by incorporating varying content of PBF (2.5%, 5%, 7.5%, 10%, and 12.5% by weight) using casting process, at room temperature (32 °C–34 °C) for 24–48 h. The prepared samples were subjected to mechanical testing (tensile strength), fatigue analysis, void content evaluation, and microstructural examination to assess the effects of filler concentration. The specimen with 12.5% PBF exhibited the highest void content (7.75%), while the neat epoxy sample showed the lowest (3.24%). An increasing trend in tensile strength was observed with higher PBF content, peaking at 24.172 MPa for the 12.5% PBF composite. Fatigue resistance improved with filler content; notably, the composite with 10% PBF endured over 10 ^6 fatigue cycles. Microstructural analysis revealed noticeable agglomeration of PBF particles in samples with filler content above 10%. The results suggest that incorporating powdered bamboo filler into epoxy composites can significantly enhance mechanical and fatigue properties, particularly up to a 10% filler concentration. However, excessive filler loading (beyond 10%) may lead to particle agglomeration and increased void content, which could negatively impact performance. These findings provide valuable insights for optimizing natural filler content in sustainable composite material design. The noted enhancements in tensile strength and fatigue life indicate that these composites may be appropriate for lightweight structural applications, especially in non-load-bearing scenarios.

The utilization of agro-food waste natural fillers as a reinforcement for developing biodegradable composites have gained much attention in research society for sustainable engineering application. The aim of this study is to develop sustainable and biodegradable composites from banana wastages filler. The composites are fabricated by varying the weight percentages of banana fillers (0, 2.5, 5.0, 7.5, and 10

Phase change materials (PCMs) have garnered increasing interest for thermal energy storage and temperature regulation, particularly in applications such as lithium-ion battery thermal management. Beeswax (BW), a bio-based, sustainable phase change material, offers high latent heat capacity but suffers from low thermal conductivity. This limits its use in high-heat applications like lithium-ion battery thermal management. This study explores enhancing BW performance by incorporating copper foam with varying porosities (90%, 85%, 80%) using a two-temperature equilibrium model. Results show that decreasing porosity significantly boosts thermal conductivity-up to 77.24 W m(-1).K-1 at 80% porosity, a 257-fold increase over pure BW. While this reduces latent heat capacity by 20% due to less BW volume, total energy storage improves by 17% (2,518 J). Latent heat utilization also rises to 72% at 80% porosity, compared to 65% for pure BW. The composite delays melting initiation by 1,250 s, offering extended sensible cooling during thermal spikes. All porosity levels reduced system temperature by similar to 52.85 K versus non-PCM cases, with minor variation among configurations. The 80%-85% porosity range offers an optimal balance of conductivity, energy absorption, and melting behavior, making copper foam-BW composites a strong candidate for advanced battery thermal regulation.

Recently, the development of cost‐effective, zero‐carbon‐footprint and multifunctional sustainable materials has been a major concern for researchers and scientists. Thus, the present work addresses the development and characterization of hybrid polymer composites integrating jute microfillers and graphene nanoplatelets (GNPs) with epoxy resin matrix. Jute, recognized for its high tensile strength and biodegradability, and GNPs, prized for their superior thermal conductivity and mechanical qualities, with greater surface interfacial, are mixed to improve the tribomechanical and viscoelastic properties of the composites. The composites are produced by varying the GNP weight percentages (0.2–1.0 wt%) with 5% of jute filler reinforcements. The results revealed that the addition of 0.6 wt% GNPs greatly increased the interfacial interaction between fillers and matrix with higher mechanical strength, stiffness and thermal stability and improved viscoelastic properties. Moreover, the addition of 0.2 wt% GNPs in the fabricated composites led to the highest resistance of tribological characteristics (wear and friction) under the influence of increasing load and sliding distances. Additionally, machine learning techniques have been employed to forecast the wear and frictional behavior of the hybrid composites. The support vector machine (SVM) method stood out from the others due to its higher performance. Through the balance of robustness and environmental sustainability, this research validates the prospective of jute–GNP–epoxy hybrid composites for sophisticated engineering applications. © 2025 Society of Chemical Industry.

Bamboo has acquired the interest of scientists due to its benefits over synthetic fibres. It is completely renewable, non-abrasive, eco-friendly, low-cost, and biodegradable. The article focuses on the filler content and normal load and how they affect wear on the bamboo filler reinforced polymer composite. Bamboo powder content varied from 0 to 12.5 wt.

Natural fibers have received a lot of attention from academia as well as industry in the context of sustainable materials. Since they are more environmentally friendly than traditional synthetic materials, their physico-mechanical and frictional properties such as porosity, moisture absorption, high strength, modulus, toughness, and wear resistivity make them appropriate for a variety of industrialized applications where issues involving a significant quantity of dumping must be taken into account. The paper introduces an attempt to use epoxy-based composites reinforced with wood dust for various applications. The composites are prepared with various wood filler stacks (0, 2.5, 5, 7.5, 10, and 12.5 wt%) embedded with epoxy resin and subjected to tensile and flexural testing. The highest ultimate tensile strength achieved at 7.5 wt% wood dust support is 22 MPa, whereas the highest flexural modulus is 0.48 GPa at 12.5 wt% composites. The composite's wear properties is examined under dry, wet, and heated contact conditions using a pin-on-disk (POD) machine. In dry condition, coefficient of friction (COF) varies from 0.10 to 0.38 whereas, in wet condition, the value of COF decreased by 70-83 %. In heated state, the COF is increased by up to 15 % when varying the temperature from 40 degrees C to 80 degrees C. The composite exhibits better wear behavior in the lower filler support than in the higher filler support due to the sturdy connection between the matrix and filler. On the other hand, the wet state's tribological performance is superior to the dry and heated states. During surface morphology analysis, it is found that various voids, crack formation, wear debris, and thin transfer layer formation take place on the composite.

The proper handling of agricultural waste has become a major concern on a global scale. Although agro-wastes are often burned, it can actually be strengthened and used in composite materials to create bioplastics. Rice husk is a type of crop residue that represents a significant source of agricultural waste. It is a highly abundant agricultural waste material that serves as an excellent alternative for reinforcement of composites purposes. Therefore, this work deals with the characterization of the tribological performance of NaOH-treated rice husk-based epoxy composites. The composites were fabricated at different weight fractions (2.5, 5, 7.5, 10, and 12.5

Naturally derived fibers/fillers-based polymers have gained much attention in many industrial applications due to the requirement for renewable and biodegradable components. Machining is sometimes needed to simplify the assembly of pieces in a finished product. Here, this article reports how drill machining affects polymer composites made with 5 wt.% jute filler that has undergone alkaline treatment. The experimental tests have been conducted to explore the impact of tool bit diameter, cutting speed and feed on the various generated responses (thrust force, surface roughness, delamination peel-up and delamination push-out). The results reveal that the appropriate responses are achieved when the cutting speed of the tool is at its maximum while the feed and tool diameter are at their minimal amounts. The response surface methodology (RSM) and support vector machine (SVM) algorithms have been devised to anticipate the drilling performance of produced composites, and both strategies have shown high agreement with experimentally acquired findings. However, the ML tool algorithm proven more reliable than RSM models because of the superior correlation of determination coefficients. [GRAPHICS] .

Natural fibre reinforced polymer matrix composites have gained significant importance due to their bio-degradable nature and sustainable availability. Hemp is one of the most widely researched natural fibres due to its appreciable mechanical and wear properties. Filler reinforced composites are found to solve the problems of delamination and fibre pull-out, as seen in fibre reinforced composites. This article focuses on the study of the mechanical and wear properties of hemp filler reinforced epoxy composites for 0, 2.5, 5, 7.5 wt percent filler loading. The hemp filler reinforced composites showed maximum tensile and flexural strengths at 7.5

The recent surge in demand for bio-based materials in various engineering frontiers has placed biocomposites in the limelight for extensive research. This need is vital in applications including automotive, aerospace, marine, and other related fields which can achieve large-scale biodegradability. However, biocomposites do not live up to the strength and thermal parameters of conventional composites. These drawbacks often restrict their applicability in demanding applications like the ones mentioned above. Among the different strength parameters, the crashworthiness parameters are of prime importance to automotive applications. Therefore, in this study, a comprehensive review of crashworthiness analyses is carried out to determine the relevance and importance of choosing the right biocomposites for automotive applications. The chapter emphasizes imparting the significance of each of the parameters and their values for various biocomposites. This study also attempts to offer a comparative outlook on the various external factors and control parameters that influence the crashworthiness of biocomposites. It is concluded that biocomposites hold great potential when it comes to crashworthiness applications. However, they require effective post-processing, better fiber-matrix interactions, improved matrix materials, and modified fibers to extend their biodegradability and strength in automotive parts.

Researchers and academics are increasingly favoring natural fibres for incorporation into polymer composites on account of their ecological compatibility and longevity. The aim of this comparative study is to identify the optimal natural filler by AHP-TOPSIS approach by analyzing the tribological performance of three distinct natural fillers: coir, bamboo, and wood reinforced polymer composite. These filler materials are pre-treated by alkali treatment to increase the interlinking properties between filler and polymer. The outcome of these treatments on the composites' physical and mechanical properties are investigated. Using a Pin-on-disk (POD) machine under dry, wet, and heated sliding contact conditions, different natural fillers' effects on polymer wear and friction are examined. The wear rate and coefficient of friction (COF) were quantified as a function of the sliding distance (0-2000 m) under various normal loads (5-40 N). It was observed from the different experimental results that coir filler reinforced composite shows best wear resistance property whereas wood filler reinforced composite shows the least wear resistance composite. Results revealed that lower filler support and low load show better wear resistant property compared to the higher filler support and high load condition. When seen through a microscope, the worn surfaces of the composite material exhibit micro and macro fissures, as well as debonding and plastic deformation. The coir filler-based composite was found to be the best alternative using the AHP-TOPSIS method, with a closeness coefficient of 0.770023.

The correct treatment of waste from agriculture has become a serious challenge on a global magnitude. As agro-wastes are often incinerated, they may be toughened and used in composite materials to produce bioplastics. The current research paper explores the impact of incorporating corn-husk filler-based thermoset composite, focusing on its tribological effects. Different weight content of corn-husk particulates (ranging from 0, 2, 4, 6, and 8