Properties Of Polymer Composites Research Articles

The Study of Composite Materials Properties Based on Polymers and Nano-Additives from Industrial Wastes from Kazakhstan.

This research is aimed at studying the properties of polymer anticorrosion coatings based on ED-20 resin widely used in practice and industrial wastes. In this work, three basic types of nanoscale nanofillers were chosen: dispersed particles-microsilica, microspheres obtained at Kazakh enterprises, and carbon nanotubes. Physicochemical research methods were used in the research: a laser analyzer for studying the dispersibility of industrial waste and spectrometric research methods. The properties of materials were investigated by standardized methods. The obtained results show that the introduction of microsilica and microspheres obtained at Kazakhstani enterprises, used as additives, improves both the physical and mechanical properties of epoxy composites compared to the standard (control) material. The results of experiments have shown that the optimal content of additives of microsilica and microspheres provides an improvement in the physical and mechanical properties of epoxy composites in comparison with the standard (control) material. Studies have shown that the introduction of microspheres into ED-20 polymer increases impact toughness. The introduction of microsilica into the matrix contributes to the increase of elastic modulus. Experimental studies of optical properties of samples of carbon composite polymer films based on polystyrene (PS) with additives of carbon nanotubes C60 and C70 and multilayer carbon nanotubes were also carried out. The experimental results obtained for the optical properties of polymer composites based on basic polymers from solid waste and carbon nanotubes showed that the optical properties of polymer composites undergo noticeable changes.

Advanced polymer composites and polymer hybrids for cartilage tissue engineering

AbstractThe repair and regeneration of cartilage is a challenge for scientists and clinical surgery. Achieving cell adhesion and regeneration, anti‐inflammatory, lubrication, targeted drug delivery and controlled release simultaneously in cartilage treatment are the goals of researchers. Polymer composites and hybrids have the potential to realize above functions in cartilage tissue engineering. This review refers to cartilage injuries, current clinical techniques, and their benefits and limitations, focusing on the most relevant and state of art of advanced polymers for cartilage tissue engineering. The frontier applications of multifunctional polymer composites and hybrids in cartilage tissue engineering are discussed in depth, including polymer scaffold, polymer bio‐lubricant, and zwitterionic polymer for drug delivery and sustained drug release. A summary of comprehensive properties of polymers such as processability, mechanical properties, biocompatibility, biodegradability, hydrophilicity, cytotoxicity, etc., and their mechanisms are analyzed. Furthermore, some key challenges and outstanding concerns on polymer‐based materials for cartilage tissue engineering are presented followed by future perspectives.Highlights The state of art of advanced polymers for cartilage tissue engineering. The advanced bionic property and mechanism of polymer composites and hybrids. Polymers for scaffold, biolubricant, drug delivery, sustained drug release. Future perspectives on polymer composites, hybrids‐based cartilage materials.

Comparison of Mechanical Property Simulations with Results of Limited Flexural Tests of Different Multi-Layer Carbon Fiber-Reinforced Polymer Composites.

This article is focused on the experimental study of flexural properties in different multi-layer carbon fiber-reinforced polymer (CFRP) composites and correlations with the results of finite element method (FEM) simulations of mechanical properties. The comparison of the results shows the possibility of reducing the number of experimental specimens for testing. The experimental study of flexural properties for four types of carbon fiber-reinforced polymer matrix composites with twill weaves (2 × 2) was carried out. As input materials, pre-impregnated carbon laminate GG 204 T and GG 630 T (prepreg) and two types of carbon fiber fabrics (GG 285 T and GG 300 T (fabric)) were used. Multi-layer samples were manufactured from two types of prepregs and two types of fabrics, which were hand-impregnated during sample preparation. The layers were stacked using same orientation. All specimens for flexural test were cut with the longer side in the weft direction. Pre-impregnated carbon laminates were further impregnated with resin DT 121H. Carbon fabrics were hand-impregnated with epoxy matrix LG 120 and hardener HG 700. To fulfill the aim of this research, finite element method (FEM)-based simulations of mechanical properties were performed. The FEM simulations and analysis were conducted in Hexagon's MSC Marc Mentat 2022.3 and Digimat 2022.4 software. This paper presents the results of actual experimental bending tests and the results of simulations of bending tests for different composite materials (mentioned previously). We created material models for simulations based on two methods-MF (Mean Field) and FE (Finite Element), and the comparative results show better agreement with the MF model. The composites (GG 285 T and GG 300 T) showed better flexural results than composites made from pre-impregnated carbon laminates (GG 204 T and GG 630 T). The difference in results for the hand-impregnated laminates was about 15% higher than for prepregs, but this is still within an acceptable tolerance as per the reported literature. The highest percentage difference of 14.25% between the simulation and the real experiment was found for the software tool Digimat FE 2022.4-GG 630 T composite. The lowest difference of 0.5% was found for the software tool Digimat MF 2022.4-GG 204 T composite. By comparing the results of the software tools with the results of the experimental measurements, it was found that the Digimat MF 2022.4 tool is closer to the results of the experimental measurements than the Digimat FE 2022.4 tool.

Nano‐enhanced epoxy sandwich composites: Investigating mechanical properties for future aircraft construction

AbstractThe aviation sector is continually seeking ways to reduce the weight of aircraft structures without compromising their mechanical integrity. Lightweight materials, such as advanced epoxy sandwich composites with hybrid nanostructures, have the potential to significantly contribute to fuel efficiency, thereby addressing environmental concerns and operational costs. This research investigates the mechanical properties of hybrid sandwich polymer composites filled with silica nanoparticles (SNiPs). Epoxy isocyanate (PU) foam sandwich composites were fabricated with kevlar fiber, carbon fiber, and glass fiber, constructed by alternating inclined interply bidirectional fiber and foam layers. SNiPs were introduced into the composite system at varying percentages, such as 0, 2, 4, and 6 wt%. The study employs a systematic approach, incorporating experimental testing, to assess key mechanical parameters, including tensile strength, flexural strength, and shear strength. The test results indicate that the incorporation of SNiPs improved the mechanical properties of the composites, leading to enhanced strength, toughness, and modulus of elasticity. Incorporation of composite laminates with 4 wt% SiNPs resulted in improved three‐point bending, tensile, shear, and torsional strengths, with maximum values of ca. 64, ca. 5, ca. 2 MPa, and ca. 22 Nm, respectively. The findings contribute to the ongoing pursuit of materials that can meet the stringent demands of modern aviation, ultimately paving the way for advancements in aircraft construction and design.

The Effect of Self-Healing Microcapsules in Corrosion Testing on Magnesium AZ31 Alloy and Fibre Metal Laminates

Fibre metal laminates (FMLs) are the most interesting composite materials of the past decade. They possess the properties of both polymer composites and metallic alloys. However, there is a problem with corrosion when the outer layers are made of aluminium or magnesium. The electrochemical changes that occur during the corrosion process and the mechanisms associated with the corrosion phenomenon are still being investigated. Recently, self-healing phenomena have emerged as a useful approach to prevent corrosion. However, there is limited research on the combination of FMLs and self-healing layers. Therefore, the main purpose of this article is to evaluate the self-healing ability of a magnesium/PEO layer based on microcapsules in a corrosion environment. It was observed that the corrosion mechanism in magnesium alloys is very complex. However, the use of a barrier layer with PEO treatment and microcapsules yielded positive anti-corrosion results. The FML samples were subjected to a 6-week corrosion test, and the addition of microcapsules to the layers showed positive results. In contrast, the samples without microcapsules exhibited intergranular corrosion. In the future, comprehensive tests using self-healing microcapsules in FMLs could greatly enhance their anti-corrosion properties and improve the integrity of the structure.

Modeling of mechanical properties of wood-polymer composites with Artificial Neural Networks

Mechanical properties (tensile strength (TS), modulus of elasticity in tensile (MET), flexural strength (FS), modulus of elasticity (MOE)) of the material to be obtained depending on the production parameters in the production of high-density polyethylene (HDPE) wood-polymer composites with Scots pine wood flour additive were predicted using Artificial Neural Networks (ANN) model and without destructive testing. In the first stage of the study, an ANN model was developed using data from 56 different studies in the literature on the mechanical properties of wood polymer composites. In the second stage, in order to determine the reliability of the model, output values were estimated using input parameters that had not been used in training and testing of the model. Based on the same input parameters, test specimens were produced and mechanical tests were performed. The results obtained from the experiments and ANN model were compared by considering the mean absolute percentage error (MAPE) value. The coefficient of determination (R2) values obtained in the training and testing phase of the ANN models were all higher than 0.90. In this way, the mechanical properties of the wood polymer composite were successfully predicted by the ANN model. Because most of the MAPE values obtained from the mechanical tests were below 10%, the model was considered a reliable model.

Tribological performance of functional coated fiber reinforced additively manufactured polymer composite

Additive manufacturing has witnessed an upward trend in utilization across diverse industries in recent years. This study examines the tribological properties of polymer composites produced using additive manufacturing. The polymer composites were produced using the fusion deposition modeling process. Subsequently, they undergo thermal spray coating and spin coating processes that deposit hafnium carbide particles onto their surface. The wear test studies were conducted at three distinct temperature levels in accordance with the ASTM standard procedure. The findings demonstrated that the application of a ceramic particle coating led to a substantial decrease in the specific wear rates. Additionally, there were observed differences in the wear rates depending on the specific methods used for applying the coating. The application of thermal coating shown high efficacy in reducing wear rates and safeguarding the underlying materials against material loss. The uncoated carbon fiber reinforced polylactic acid (PLA-CF) material showed a slightly significant amount of material degradation as the test chamber temperature increased, in comparison to the coated specimens. The average specific wear rate of the thermally coated carbon fiber reinforced polylactic acid specimen at a temperature of 70 °C is 0.000156 kg Nm−1.

3D-Networks Based Polymer Composites for Multifunctional Thermal Management and Electromagnetic Protection: A Mini Review

3D-Networks Based Polymer Composites for Multifunctional Thermal Management and Electromagnetic Protection: A Mini Review

Study on Mechanical Properties of Polymer Composites Filled with Nano Egg-shell Powder

Polymeric materials, when reinforced with synthetic fibers like glass, carbon, and aramid, offer notable advantages including increased stiffness and strength-to-weight ratio compared to conventional materials such as wood, concrete, and steel. Among these options, glass fiber stands out due to its affordability and widespread availability. Glass fiber reinforced polymer composites exhibit moderate mechanical properties, which can be significantly enhanced by incorporating nano fillers like eggshell powder. This study explores the utilization of nano eggshell powder as well as methods for effectively integrating nano fillers into polymer composites to create value-added products. Four types of composites, varying in weight proportions of nano eggshell powders, were prepared using the hand lay-up technique for mechanical and thermal characterizations. Various mechanical properties including tensile strength, flexural strength, impact behavior, as well as thermal properties via TGA and DMA analysis were investigated. The results indicate that incorporating the optimal amount of nano fillers significantly improves the overall strength of glass fiber reinforced composite materials, leading to cost savings of over 30%. This suggests that nano eggshell fillers hold great potential in composite manufacturing, particularly for substituting high-cost glass fibers in low load-bearing applications.

Unveiling the Influential Factors and Heavy Industrial Applications of Graphene Hybrid Polymer Composites

Graphene hybrid-filler polymer composites have emerged as prominent materials that revolutionize heavy industries. This review paper encapsulates an in-depth analysis of different influential factors, such as filler/graphene type, aspect ratios, dispersion methods, filler-matrix compatibility, fiber orientation, synergistic effects, different processing techniques, and post-curing conditions, which affect the processing and properties of graphene hybrid polymer composites, as well as their resultant applications. Additionally, it discusses the substantial role of graphene reinforcement with other fillers, such as carbon nanotubes, silica, nano-clays, and metal oxides, to produce functionalized hybrid polymer composites with synergistically enhanced tailored properties, offering solutions for heavy industries, including aerospace, automotive, electronics, and energy harvesting. This review concludes with some suggestions and an outlook on the future of these composite materials by emphasizing the need for continued research to fully optimize their potential.

Highly enhanced microwave absorption of carbon nanotube/nickel/styrene-butadiene-styrene composite with segregated structure

High-performance microwave absorption (MA) polymer composites are highly required in electromagnetic protection. Although the desirable MA performance of many MA absorbers is obtained, its loading of obtaining optimal MA performance still is too high, which is not beneficial to the mechanical properties of polymer composites. In this work, based on the concept of segregated structure, the selective distribution of carbon nanotube/nickel (CNT/Ni) particles was successfully achieved in the styrene-butadiene-styrene (SBS) matrix via hot-compression molding. The CNT/Ni/SBS composites with segregated structure present an excellent MA performance when the filler content is only 5 wt%, including the minimum reflection loss (RLmin) of −42.7 dB and effective absorption bandwidth (EAB) of 6.6 GHz, which shows 27.3 % and 8.2 % increases in comparison to the optimal MA performance of the composites with randomly dispersed structure (10 wt%). In addition, the elongation at break and tensile strength of CNT/Ni/SBS composites can reach 1222 % and 14.3 MPa, respectively, showing great application potential as flexible MA materials. The efficient method provides a promising way to improve the function efficiency of MA absorbers and develop high-performance MA polymer composites with low filler loading in the future.

Optimized random forest model for predicting flexural properties of sustainable composites

AbstractIn an era of technological advancements, the quest for sustainable products has taken a center stage. The utilization of natural fiber reinforced polymer composites has become crucial in the manufacturing of eco‐friendly products due to their low cost, renewability, biodegradability, and comparable properties to synthetic composites. Coir‐based composites have been utilized in roofing, composite panels, furniture, and bio‐based insulation applications, providing enhanced strength and sustainability. In the current investigation, an exploratory data analysis (EDA) was conducted to understand the relationship between the various input variables and the flexural properties of short coir polymer composites (SCPCs). The data analysis revealed that manufacturing process had a significant impact on the flexural properties of SCPCs. Based on the insights gained from the EDA, an optimized Random Forest prediction model was developed to predict the flexural properties. Genetic algorithm approach for hyperparameter optimization led to lower objective loss in contrast to Bayesian optimized Random Forest model. The model's performance was subsequently evaluated through holdout validation, and the outcome demonstrated the model's proficiency in accurately predicting the properties. The developed model can be used as a tool for optimizing the design of SCPCs for specific applications, by predicting the flexural properties of the composites.Highlights Flexural behavior of short coir polymer composites was analyzed and modeled. Manufacturing process has the highest impact on the flexural properties. Random forest model predicted the flexural properties with high accuracy. Genetic algorithm optimized model further enhanced the model performance. The developed framework provides insights into designing biocomposites.

Mechanical Bonding Properties of Solderable Anisotropic Polymer Composite containing Low-Melting-Point and High-Melting-Point Solder Fillers

In this papers, to enhance the mechanical bonding properties of solderable anisotropic polymer composites (SAPCs) containing low-melting-point solder filler only, a new low-melting-point solder and high-melting-point solder mixed filler filled SAPCs (LH-SAPCs) was proposed, and the influence of the high-melting-point solder filler on the conduction path formation and mechanical bonding properties of the LH-SAPC were investigated. Two types of LH-SAPC were synthesized by adding high-melting-point solder within the low-melting-point solder/high-melting-point solder mixed filler at mixing ratios of 0 and 50 vol% (the volume fraction of low-melting-point solder/high-melting-point solder mixed filler in the polymer composite was 20%), and a bonding test was conducted using QFP. The results exhibited that the LH-SAPC containing high-melting-point solder formed a wide and stable conduction path due to the proper selective conduction path formation behavior by the interaction between molten low-melting-point solder and solid-state high-melting-point solder fillers within the polymer composite with low viscosity condition. Furthermore, the mechanical bonding properties of the LH-SAPC joints containing high-melting-point solder were enhanced compared to that of LH-SAPC containing low-melting-point solder only owing to the precipitation hardening and dispersion strengthening effects due to the increase of fine Bi-rich, Cu<sub>6</sub>Sn<sub>5</sub>, and Ag<sub>3</sub>Sn intermetallic compound particles inside the conduction path.

Purification of Iranian bentonite for organoclay synthesis for use in clay–polymer composites

Abstract Polymer-based composites modified with organoclay are economically beneficial candidates for a variety of applications. Different types of impurities accompany montmorillonite phases in various bentonites, which impact the quality and cost of organoclays and final composites. To obtain organoclays for clay composite applications, eight Iranian raw bentonites from different geographical locations were selected as the candidates and characterized by X-ray diffraction (XRD). Sample IB was chosen due to its high purity and lower cristobalite content than the other samples. It was purified by centrifugation or sedimentation methods using a sodium hexametaphosphate (NaHMP) dispersant. The cation-exchange capacity (CEC) was measured for bentonite before and after purification by sedimentation, and it showed a significant increase from 6.944 to 12.128 eq g–1, confirming successful purification. Organoclays were prepared using purified bentonite (sedimentation method) with two surfactants (cetyltrimethylammonium bromide and octadecylamine), and the amount of octadecylamine was optimized. Purified bentonite and organoclay were characterized by XRD, scanning electron microscopy (SEM) and X-ray fluorescence. The results indicate that most of the impurities were removed after purification, and the interlayer space of organoclays increased to 35 Å in the optimized sample prepared with an amount of octadecylamine that was twice the CEC in purified bentonite. The prepared organoclay was used to improve low-density polyethylene (LDPE) polymer properties. The clay–polymer composite properties were studied by field emission SEM, thermogravimetric analysis and tensile strength tests. The organoclay was fully dispersed in the LDPE matrix and in the sample with 5 wt.% of organoclay, where Ti (the temperature at which 10% of the sample is decomposed) and T50% (the midpoint of degradation) were 17°C and 13°C greater than those of polyethylene, respectively. Additionally, the sample residue with 5 wt.% of organoclay at 600°C was 43.4%. The tensile strength of polyethylene increased from 8.67 to 9.03 MPa in the sample with 4 wt.% of organoclay.

Nanoscale brick and mortar strategy for mechanically strong multifunctional composites with extremely high filler-loading

To achieve the best physico-chemical properties of polymer composites, the concentration of fillers should be maximized in many cases. However, at extremely high concentrations of fillers, the discontinuity of the polymer matrix results in poor mechanical properties. To overcome this problem, we propose an efficient protocol to improve the mechanical strength significantly, even at an extremely high concentration of microscale fillers (graphite flakes, 95 wt%). Since the mechanical strength of the polymer composite strongly depends on both the homogeneous distribution of the polymer matrix around microscale fillers and the adhesion between them, we increased the mechanical strength of the composite by the preparation of a hybrid filler decorated with polymer nanoparticles. The decorated polymer nanoparticles eventually turned to the matrix during hot-pressing process like a mortar between bricks. Systematic studies on the mechanical strength as well as electrical and thermal conductivities of the composites revealed that both the precisely controlled size of the polymer nanoparticles and even distribution of them on the hybrid fillers were critical variables to enhance the material's properties above. The newly developed polymer composites with superior physical properties exhibited good electromagnetic interference shielding (EMI shielding effectiveness >80 dB in X-band, thickness ∼ 1.5 mm), making them suitable as electric heaters.

Micro/nano fillers for value‐added polymer composites: A comprehensive review

AbstractThe need for new sustainable engineering materials using polymer composites is evolving every day. Researchers are in a race to develop value‐added products from natural renewable sources and discarded waste materials. Studies indicate several hurdles while trying to provide ecologically friendly materials for product manufacturing over the years. Natural materials are more readily available, biodegradable, more affordable, have less processing health hazards, and are more environmentally friendly than synthetic materials. As the price of commercial polymers decreased, the incorporation of fillers became increasingly necessary for technical reasons.. The market for polymers can actually be expanded by appropriately combining fillers and polymers to produce a wide range of qualities in these two components. This review provides an overview on a variety of organic and inorganic fillers which were incorporated into the polymer composites and their influence on the physical, chemical, mechanical, thermal, and electrical properties of polymer composites by various characterization methods and their In fact, it is possible to achieve a wide range of qualities in these two components by appropriately combining polymers and fillers, which expands the market for which polymers may be employed.application scopes. This review aims to thoroughly examine and assess various polymer and filler combinations, with a particular emphasis on their potential suitability for a range of engineering and industrial applications. These encompass microelectronics, biomedical fields, flexible electronics, flame retardant uses, food packaging, automotive and aerospace sectors, as well as applications within the construction industry for structural and semi‐structural purposes.Highlights New polymer composite engineering materials with long‐term sustainability Value‐added product development from renewable resources and discarded waste materials. Provide information to select appropriate reinforcements for composite manufacturing. Diverse discussion on the application of fillers and their composites.

Prevention of Leakage in Machine Learning Prediction for Polymer Composite Properties.

Machine learning (ML) has facilitated property prediction for intricate materials by integrating materials and experimental features such as processing and measurement conditions. However, ML models designed for material properties have often disregarded a common issue of "leakage," resulting in an overestimation of model performance and a decrease in model transferability. This issue can arise from biases inherent in multiple data points obtained from the same experimental group. We provide a critical examination and prevention method of leakage in property prediction for polymer composites. Our proposed method utilizes data partitioning based on the experimental group to ensure that data from the same group are not mixed in both the training and test sets. Evaluation results highlight that the conventional random partitioning unintentionally inflates ML performance through the misuse of experimental features for leaking data bias within the same experimental group rather than explaining the physical causality. In contrast, the proposed method enables the leakage-free utilization of experimental features to improve prediction accuracy while ensuring model transferability. Specifically, when integrating experimental features with polymer and filler features, the conventional method overestimates the prediction performance of electrical conductivity in reducing RMSE by 26% depending on leakage, whereas the proposed method achieves a reduction in RMSE by 5% without leakage. These findings offer valuable guidance for the effective utilization of experimental features in data-driven materials science.

Engineering properties of hybrid polymer composites produced with different unsaturated polyesters and hybrid epoxy

In this study, the mechanical properties of hybrid polymer composites produced with different unsaturated polyesters and hybrid epoxy resins are investigated. The composites were produced by blending unsaturated polyester resins (i.e., orthophthalic, isophthalic, and terephthalic) and bisphenol-A-based epoxy-vinyl ester resin to produce single, binary and ternary blends. In doing this, a total of 14 different combinations were produced. The results show that the binary and ternary polymer blends tend to improve almost all the tested properties of the polymer composites. Further, the fourier-transform infrared spectroscopy (FT-IR) and scanning electron microscopy (SEM) results confirmed that the reason for enahcned properties is due to better crosslinking and longer chains of polymers produced in binary and ternary mixtures. The absence of peaks determining the styrene polymerization character for all mixtures also demonstrates that the polymerization reaction takes place in all mixtures. It is also believed that the binary and ternary resin mixtures have developed higher energy absorption compared to single resin composites. All of the mentioned has been achieved while the gelation temperatures of the hybrid resin mixtures were not changed significantly and they began gelation at the expected temperature values. In addition to the gelation, peak exotherm temperatures, and barcol hardness values demonstrated that all mixtures achieved sufficient curing. The result of this study is significant and point to the great potential of producing high performance polymer composites through the use of binary or ternary resin mixtures.

A machine learning-enabled prediction of damage properties for fiber-reinforced polymer composites under out-of-plane loading

For understanding the damage morphology in fiber-reinforced plastics under out-of-plane loading, engineers/ and designers mostly rely on experimental investigations and numerical models, which could be costly in terms of resources and computational requirements. Thus, pragmatic predictive approaches that can offer ready-to-use tools for material optimization have gained traction in recent years. This paper proposes a machine learning model, developed with the use of previous experiments, to predict the damage behaviour of E-glass fiber-reinforced plastics in sandwich structures and laminates. The focus is on quasi-static indentation with different indenter geometries, using acoustic signals for damage monitoring. A total of 10 optimal-performing regression algorithms were employed to develop the prediction models. The developed models based on total energy gave acceptable results for all specimens (R-squared value: 0.9932 – 0.9999), while prediction models using force produced less accurate results (R-squared value: 0.8693) for a sandwich structure subjected to a conical indenter. Results showed that energy absorption of composites provided the most reliable data for the development of predictive models. The load profiles could also be used when the contact area is limited (e.g., for hemispherical and conical indenters). The best-performing model for higher surface areas of the indenter increased was k-NN, thanks to its ability to capture complex and nonlinear relationships between the input features and the target variable. Overall, the developed model could provide more autonomy and control for the material optimisation of composite structures for industrial applications with reduced time and cost constraints.

Novel enhancement of interfacial interaction and properties in biodegradable polymer composites using green chemically treated spent coffee ground microfiller

This study investigates the potential of utilizing green chemically treated spent coffee grounds (SCGs) as micro biofiller reinforcement in Poly-3-hydroxybutyrate-co-3-hydroxyvalerate (PHBV) biopolymer composites. The aim is to assess the impact of varying SCG concentrations (1 %, 3 %, 5 %, and 7 %) on the functional, thermal, mechanical properties and biodegradability of the resulting composites with a PHBV matrix. The samples were produced through melt compounding using a twin-screw extruder and compression molding. The findings indicate successful dispersion and distribution of SCGs microfiller into PHBV. Chemical treatment of SCG microfiller enhanced the interfacial bonding between the SCG and PHBV, evidenced by higher water contact angles of the biopolymer composites. Field Emission Scanning Electron Microscopy (FE-SEM) confirmed the successful interaction of treated SCG microfiller, contributing to enhanced mechanical characteristics. A two-way ANOVA was conducted for statistical analysis. Mass losses observed after burying the materials in natural soil indicated that the composites degraded faster than the pure PHBV polymer suggesting that both composites are biodegradable, particularly at high levels of spent coffee grounds (SCG). Despite the possibility of agglomeration at higher concentrations, SCG incorporation resulted in improved functional properties, positioning the green biopolymer composite as a promising material for sustainable packaging and diverse applications.