Search Results (1,447)

The food packaging sector widely relies on polymeric materials, and as sustainability concerns grow, commodity polymers need to be replaced with innovative and more sustainable materials. Thermoplastic polyurethane (TPU) is a versatile elastomeric polymer characterized by flexibility, strength, chemical and abrasion resistance, and biocompatibility. However, it presents some limitations, notably in terms of functional properties (such as barrier properties). The use of nano-sized renewable fillers, such as cellulose nanocrystals (CNCs), may improve these properties, extending the applicability range of TPU. In this work, bio-based TPU nanocomposites were obtained by adding commercial silane-modified cellulose nanocrystals (Si−O−CNC) at different contents (1–5 wt.%). The nanocomposites were produced via melt mixing followed by compression molding and were characterized in terms of their chemical (FTIR), morphological, thermal, mechanical, rheological, wettability, and barrier properties (i.e., water vapor permeability, WVP and oxygen transmission rate, OTR). The presence of Si−O−CNC promoted hydrogen-bonding interactions with the TPU matrix, affecting the microphase separation and organization of the hard segments. These microstructural changes improved thermal stability, reduced WVP and OTR, and increased tensile properties at lower nanofiller contents (1–3 wt.%). At higher contents, partial nanofiller aggregation was observed, leading to a reduction in mechanical performance. Overall, these results suggest that TPU/Si−O−CNC nanocomposites have promising potential as sustainable food packaging materials. Full article

Powder Bed Fusion-Laser Beam/Polymer (PBF-LB/P) is a key additive manufacturing technology widely used in aerospace, but its process parameters are difficult to optimize for thermoplastic composites due to poor powder flowability and unstable melting regions. To address this challenge, this paper develops discrete element and finite element models to systematically determine the PBF process window for both powder spreading and sintering stages, with verified reliability. In the spreading stage, the powder layer performance is evaluated through surface profile, density, and uniformity. The effects of reinforcement phase, spreading speed, and layer thickness are analyzed, establishing reasonable spreading parameter windows. It is found that the optimal layer thickness for PEEK powder is determined to be 0.13 mm, while that for PEEK/CF composite powder is 0.12 mm. At the optimal layer thickness, the powder bed exhibits desirable properties, which minimize its adverse influence on the sintering process and serve as a prerequisite for subsequently establishing the sintering process window. For the sintering stage, sufficient sintering constraint criteria are established, and a systematic determination method is proposed. By analyzing microscopic sintering mechanisms and characterizing the effects of laser power, scanning speed, and hatching space on melt pool dimensions and temperature, a reasonable sintering process window can be efficiently determined. It is found that within the process window, the PEEK specimens achieved a maximum relative density of 99.31% and exhibited a tensile strength 13.1% higher than that of specimens processed outside the window, demonstrating a clear superiority. Full article

Artificial intelligence (AI) and machine learning (ML) algorithms possess the capability to accelerate the design of novel materials; however, their advancement in materials science is severely hindered by a fundamental deficit of experimental data, commonly referred to as data starvation. Unlike solution-based chemistry, where high-throughput (HT) technologies are a well-established standard, the automated synthesis of solid materials—particularly polymers and multicomponent composites—poses an extreme engineering challenge. Furthermore, the traditional, manual research model is inherently flawed by human bias, notably the systematic non-publication of negative results, which deprives AI models of critical boundary information regarding the design space. This paper is the first in a three-part review series defining the architecture of a fully automated, unbiased “data factory” for closed-loop discovery. This section focuses on the physical foundations of the HT workflow: experimental planning, automated synthesis, and material management. Emphasis is placed on the paradigm shift from classical, discrete Design of Experiments (DoE) to the novel concept of Continuous Gradient DoE. It reviews how robotic platforms utilizing precise gravimetric and volumetric feeders, integrated with extruders and in-line capillary rheology, enable the seamless, high-throughput manufacturing of thermoplastics and composites. Moreover, an innovative approach to sample logistics is presented, redefining classical storage patterns through the implementation of Continuous Material Management. This encompasses direct physical tagging (e.g., inkjet marking on continuous filaments or films), spool-based transport systems, and precise, real-time metadata mapping. As demonstrated, the integration of these systems yields an order-of-magnitude increase in productivity (generating tens of thousands of novel material variants annually), a radical reduction in unit costs, and the production of terabytes of standardized, machine-readable data. Establishing this reliable hardware and analytical infrastructure represents the essential first step toward unlocking the full potential of artificial intelligence in advanced materials engineering. Full article

For the impact-resistance evaluation of thermoplastics, the DuPont impact test is widely used to replicate multiaxial stress states inherent in actual product environments. However, conventional evaluation methods remain constrained by probabilistic pass/fail judgments or empirical calculations of absorbed energy. Consequently, quantifying the “material-specific fracture criterion,” which is indispensable for high-fidelity computer-aided engineering (CAE) analysis, persists as an important challenge. While our previous works established the derivation of CES from uniaxial tensile tests, the core originality of this study lies in extending this mechanical framework to the dynamic and multiaxial stress states of the DuPont impact test. By integrating a mathematical model with the probabilistic results of the staircase method, we enable for the first time the quantitative identification of material-specific fracture thresholds directly from standard drop-weight impact configurations. For this study, a novel mechanical model for deformation and fracture behavior in the DuPont impact test is constructed. Then a quantitative evaluation method is proposed for the “Critical Expansion Stress (CES),” a material-specific threshold triggering fracture under multiaxial stress. Specifically, using thermoplastic materials of five types and seven grades (including PP, POM, PS, ABS, and PC), the surface impact energy absorbed per unit volume was calculated via the DuPont impact test using the staircase method, accounting for size effects. Furthermore, microscopic parameters (shear modulus G and critical void volume fraction f0) were identified theoretically based on the mechanical properties obtained from short-beam shear tests. These parameters were integrated into a mathematical model to derive the CES. Comparing the derived CES with the true-stress-based uniaxial tensile strength, which incorporates the necking behavior during large deformations, revealed a distinct correlation governed by their mechanical relation (the 1:3 rule) based on the theoretical definition of hydrostatic stress. For the highly ductile polymer exhibiting significant strain hardening, this correlation holds universally when evaluated at the initial plastic flow stage prior to massive molecular orientation. The proposed method serves as a practical quantitative screening tool for evaluating the surface impact characteristics of plastic materials, providing an accessible framework for identifying material-specific fracture thresholds. Full article

In the context of increasing environmental awareness and the transition toward a circular material economy, the development of sustainable polymeric materials has become a key focus of industrial research. Within this framework, thermoplastic elastomers (TPEs) represent a promising class of materials that combine the elasticity of rubbers with the processability and recyclability of thermoplastics. Their ability to incorporate recycled content further enhances their potential for reducing environmental impact in advanced automotive applications. This study investigates styrenic thermoplastic elastomers (TPS) based on a SEPS (Styrene–Ethylene–Propylene–Styrene) and polypropylene matrix containing over 50% recycled content, with the aim of evaluating the influence of recycled material on structure and performance. TGA, DSC, and ATR-FTIR analyses revealed comparable degradation behavior and similar chemical features between virgin and recycled compounds, while minor differences were possibly related to variations in the plasticizer fraction and polymer-oil interactions. These differences did not significantly compromise the mechanical integrity of the recycled materials under the conditions investigated. Mechanical tests (tensile, tear, hardness, compression set) confirmed that recycled TPS maintains mechanical performance comparable to virgin formulations, while accelerated weathering resulted in minimal color variation and excellent surface appearance retention. Overall, TPS with high recycled content exhibit stable thermal, chemical, and mechanical behavior, confirming their suitability as sustainable alternatives for automotive components. Full article

Battery housings are critical structural and safety components in electric vehicles, fulfilling multiple functions related to mechanical protection, crashworthiness, thermal management, fire resistance, electromagnetic shielding, and integration of battery modules into the vehicle body. While metallic housings, particularly aluminum and steel, remain dominant in industrial applications, increasing attention is being given to composite materials as lightweight alternatives capable of improving energy efficiency and extending driving range. However, the growing use of composites in battery enclosures raises important questions regarding recyclability, end-of-life management, and compatibility with circular economy principles. This review critically examines the current state of the art in composite materials used for electric vehicle battery housings, with particular emphasis on glass- and carbon-fiber-reinforced thermoplastics, thermoset composites, sandwich structures, and hybrid multi-material systems. The paper discusses the functional requirements imposed on battery housings and analyzes how these requirements influence material selection and design strategies. Particular attention is devoted to recycling pathways applicable to composite battery enclosures, including mechanical recycling, thermal treatment, chemical recycling, and reuse-oriented approaches, as well as to the limitations associated with mixed-material assemblies, adhesives, coatings, and integrated functions. The review also addresses circular design strategies for battery housings, including design for disassembly, material traceability, modularity, and the incorporation of recycled polymers and secondary reinforcements into new housing systems. Current research gaps are identified in the integration of structural performance, fire safety, manufacturability, and recyclability within a single design framework. The analysis shows that thermoplastic composites currently offer the most promising route toward circular battery enclosures, while thermoset-based systems still face significant challenges in high-value recycling. The paper concludes by outlining future research directions required for the development of lightweight, safe and recyclable composite battery housings aligned with sustainable mobility and circular economy goals. Full article

The impact of force field models on the thermal and mechanical characteristics of polyimides was comprehensively examined for the first time. Polyimides (PI) are heterocyclic polymers with outstanding thermal and chemical stabilities and excellent dielectric properties. In this study, we used all-atom molecular dynamics (MD) simulations to examine how the flexibility of the dianhydride fragment affects the thermal and mechanical properties of three polyimides: PMDA-ODA, ODPA-ODA, and R-ODA. The considered polyimides have different dianhydride fragments based on pyromellitic acid (PMDA), tetracarboxylic acid diphenyl oxide (ODPA) and 1,3-bis(3′,4-dicarboxyphenoxy)benzene acid (R), with a constant diamine: 4,4′-oxydianiline (ODA). Models were built using five classical force fields (OPLS-AA, Amber/GAFF, Gromos, Charmm/CGenFF, and UFF). For each polyimide, eight models were generated using different force fields and charge schemes: (i) OPLS-AA with 1.14*CM1A charges, (ii) OPLS-AA with HF/6-31G* (RESP) charges, (iii) GAFF with AM1-BCC charges, (iv) GAFF with HF/6-31G* (RESP) charges, (v) CGenFF (version 4.6) with native charges, (vi) CGenFF (version 5.0) with native charges, (vii) Gromos54a7 with native charges, and (viii) UFF with QEq charges. The difference in the chemical structures of the polyimide repeating unit leads to differences in the thermodynamic and kinetic flexibilities that affect the thermal and mechanical properties. Simulations of glass transition temperatures (T_g) for three polyimides PMDA-ODA, ODPA-ODA, and R-ODA mostly replicate the experimental order T_g(PMDA-ODA) > T_g(ODPA-ODA) > T_g(R-ODA), except for the CGenFF (version 4.6) force field. The experimental density ratio ρ(PMDA-ODA) > ρ(ODPA-ODA) > ρ(R-ODA) is most accurately replicated by OPLS-AA (RESP) and CGenFF (version 5.0) polyimide models. The coefficients of thermal expansion (CTE) correspond with the experimental trend, exhibiting an increase in the following order: PMDA-ODA < ODPA-ODA < R-ODA. Gromos54a7 precisely delineates both the ratio and absolute values CTE for all polymers. OPLS-AA (RESP), OPLS-AA (CM1A), CGenFF (version 4.6), and UFF (QEq) models replicate PMDA-ODA’s CTE, while GAFF (RESP) and GAFF (AM1-BCC) models replicate ODPA-ODA and R-ODA CTE values. The ratio between the simulated values of Young’s modulus, yield strength, and strain-hardening modulus followed the sequence PMDA-ODA > ODPA-ODA > R-ODA for the OPLS-AA (RESP) and CGenFF (version 5.0) models. Full article

To address prevalent industrial challenges, including the high cost of fabricating microstructures via photolithography and 3D printing, impurity residues easily generated by conventional physical/chemical pore-forming techniques, and the limited sensitivity of regular capacitive sensors, this paper innovatively proposes an integrated low-temperature in situ gas foaming strategy using ammonium bicarbonate for the fabrication of porous TPU-based ionic gels. Relying on the complete gaseous decomposition property of ammonium bicarbonate upon heating, a three-dimensionally interconnected continuous porous network is spontaneously constructed inside the polymer matrix. Thermoplastic polyurethane (TPU) is selected as the continuous polymer phase, and [EMIM][TFSI] imidazolium ionic liquid is blended as the ion source to synthesize composite ionic gel substrates. A PDMS composite slurry filled with graphene is employed to prepare flexible substrates, followed by low-temperature oxygen plasma surface modification to introduce polar functional groups such as hydroxyl and carboxyl onto electrode surfaces. A standard sandwich-structured ionic pressure sensor with the configuration of “top modified electrode—porous ionic gel dielectric layer—bottom modified electrode” is finally assembled. The porous framework and modified electrodes constitute a dual synergistic enhancement system: the porous structure markedly reduces the equivalent elastic modulus of the gel and improves its compressive deformation capacity; polar-modified electrodes optimize the interfacial compatibility between electrodes and gels, shorten ion migration paths and lower interfacial contact resistance. Systematic calibration of multiple batches of parallel samples reveals that the as-fabricated sensor achieves a high sensitivity of 25.3 kPa⁻¹ across the full measuring range from 0 to 1000 kPa with a linear fitting coefficient R² = 0.992. The loading response time and unloading recovery time of the device are 60 ms and 80 ms respectively, with a performance degradation of less than 3% after 1000 consecutive loading–unloading cycles, featuring low hysteresis error and excellent signal repeatability. Multi-scenario in vivo wearable tests on human subjects verify that the device can precisely capture subtle fluctuations of radial artery pulse and periodic laryngeal deformation during swallowing, distinguish characteristic waveform patterns of various English words according to differences in vocal cord vibration, and accurately detect bending motions when attached to finger joints. The entire fabrication process adopts common chemical raw materials and standard laboratory equipment without expensive micro-nano processing facilities, featuring convenient raw material procurement and high process fault tolerance, which enables large-area coating-based mass production. This work delivers a novel technical route for the low-cost large-scale production of high-performance ionic flexible sensors and bears significant industrialization reference value for applications in wearable medical monitoring, bionic robotic electronic skin, flexible human–machine interactive touch panels and other related fields. Full article

Recently, there has been a significant expansion of additive technologies, especially Fused Filament Fabrication (FFF). This article aims to upgrade a commercial 3D printer to develop viscous polymeric materials, as this option is not currently available. The FFF method is primarily used with thermoplastics and elastomers in filament form. However, materials derived from various water-soluble acrylates offer significant potential, with advantages including environmental friendliness and desirable mechanical and visual properties. The possibility of using a viscous polymer as a carrier for metal material prior to sintering is also a significant factor. The aim of the text is to present the preparation of a 3D printer suitable for printing the above materials. The main requirement was to modify the selected printer with minimal interference with HW and SW. We mainly focused on adjusting the print head. A new prototype for the printing of viscous polymeric materials was visualized. Furthermore, the individual components were designed and printed; a functional system capable of processing these materials was assembled. Full article

Recycled thermoplastics offer a promising route for valorizing industrial residues and developing thermoplastic-bonded wood-based panels without added formaldehyde-based resins. In this study, experimental wood–polymer composite boards were produced from recycled acrylonitrile–butadiene–styrene (ABS) edge-banding waste used as the polymer matrix and industrial wood fibers used as the lignocellulosic reinforcement. The boards were manufactured at target densities of 800–1200 kg·m⁻³ and wood fiber contents of 10–30%, followed by the evaluation of selected physical and mechanical properties, including water absorption, thickness swelling, modulus of elasticity and bending strength. Thermogravimetric analysis of the recycled ABS edge-banding material and qualitative optical microscopy of the board surfaces were used to support, but not independently prove, the interpretation of the composite structure. The recycled ABS waste enabled the formation of compact boards, with density exerting the strongest influence on water resistance and bending performance. The regression models indicated a balanced region at 21.84 wt.% wood fibers and 1134 kg·m⁻³, corresponding to predicted water absorption of 1.62%, thickness swelling of 3.22%, modulus of elasticity of 2931 N·mm⁻² and bending strength of 22.20 N·mm⁻². Optical microscopy suggested a more continuous ABS-rich surface in the most homogeneous specimens, whereas local accumulations of fine particles and areas of limited polymer coverage were observed on the opposite surface. These findings demonstrate the potential of recycled ABS edge-banding waste for wood–polymer board production, while indicating that additional feedstock cleaning and sieving should be investigated in subsequent work to improve furnish uniformity and structural homogeneity. Full article

Usually, particle morphology and surface treatment are adjusted to achieve high conductivity in highly filled conductive polymer composites. Here, we demonstrate that this key property can be further improved by keeping the particle contact regions free of polymer using an extension of the capillary suspension concept. If the secondary liquid is chosen such that it remains in the contact areas between conductive particles during solidification of the polymer phase, then the composite conductivity substantially increases. For both a thermoset and a thermoplastic model system including 40 vol.% silver particles in the paste, the conductivity was more than doubled compared to the respective binary system, reaching conductivity values up to (4.3 ± 0.2) × 10⁶ Sm⁻¹. SEM images clearly show the polymer-free contact regions in samples with enhanced conductivity. However, conductivity only increases if the secondary fluid is removed after solidification of the polymer phase. Thus, the capillary suspension concept can be used for a controlled modification of particle–particle contacts and represents a generic, viable strategy for enhancing conductivity in highly filled polymer composites. The concept helps to save precious (silver) resources and may find application in various fields of printed electronics, e.g., metallization of thermosensitive solar cells. Full article

Optimizing the injection molding of short-fiber-reinforced thermoplastics (SFRTs) is a persistent challenge due to the complex interplay between processing parameters and final mechanical performance. To address this, we developed and validated a machine learning (ML) pipeline to maximize both the tensile strength and Charpy impact resistance in polyamide 6 with 30% glass fiber (PA6-GF30). Through a designed experimental campaign, we systematically varied four key process parameters—melt temperature (260–300 °C), injection pressure (600–1000 bar), packing pressure (400–800 bar), and cooling time (15–35 s). The resulting dataset was used to train and compare three different regression models: Random Forest (RF), Gradient Boosting (GB), and Support Vector Regression (SVR). Our findings indicate that the Gradient Boosting (GB) algorithm yielded the most reliable predictions, significantly outperforming the other evaluated models. Further analysis using SHAP (Shapley Additive exPlanations) identified packing pressure as the dominant factor influencing tensile strength (contributing approximately 40% to the prediction), while melt temperature emerged as the key driver for impact resistance (around 35% contribution). By integrating our best-performing GB model with a multi-objective genetic algorithm, we identified an optimal set of parameters that simultaneously enhances both mechanical properties. Among the evaluated models (Random Forest, Support Vector Regression, and Gradient Boosting), the Gradient Boosting algorithm achieved the highest predictive accuracy. Compared to the baseline condition (280 °C melt temperature, 800 bar injection pressure, 600 bar packing pressure, 25 s cooling time), experimental validation of these optimized settings demonstrated substantial improvement: tensile strength increased from 145 MPa to 171 MPa (an 18% enhancement), and impact resistance rose from 45 kJ/m² to 55 kJ/m² (a 22% gain). This work establishes that an integrated ML and optimization framework can serve as a transformative approach for high-precision manufacturing of advanced engineering polymers. The primary novelty of this work lies in the development of a fully integrated, bias-free methodological framework that explicitly couples physical interpretability with multi-objective optimization, bridging the critical gap between black-box predictions and actionable industrial insights. Full article

This study investigates the influence of PLA flowability and talc content on the performance of compostable thermoplastic starch/poly(butylene succinate) (TPS/PBS)-based systems for rigid applications. Different PLA grades with varying melt flow index (PLA23, PLA8 and PLA70) and talc contents (0, 5 and 10 wt%) were incorporated. Twelve formulations were compounded by twin-screw extrusion and processed by injection moulding. FTIR confirmed the coexistence of TPS, PBS and PLA phases without evidence of chemical interactions. Morphological analysis showed that PLA flowability plays a key role in phase distribution, with higher-flow PLA promoting improved dispersion and interfacial adhesion, while talc addition (5 and 10 wt%) increased structural heterogeneity; at higher loadings, particularly, DSC analysis revealed that talc acted as a nucleating agent for the PBS phase, increasing crystallisation temperatures from approximately 73 °C to 81 °C depending on formulation. Mechanical results showed that Young’s modulus increased from approximately 1.4 GPa to 2.7 GPa with decreasing PLA flowability and increasing talc content. Formulations containing low-flow PLA reached tensile strengths close to 32 MPa, although elongation at break decreased to values near 2%. In contrast, high-flow PLA formulations exhibited a more balanced mechanical response, with elongation values up to approximately 8%, associated with improved phase dispersion. Hybrid PLA systems showed intermediate behaviour, reaching elongations up to 22% while maintaining modulus values around 1.8 GPa. Talc provided additional reinforcement but reduced deformation capacity. HDT values remained relatively constant, indicating limited improvement in thermomechanical resistance despite increased stiffness. These results demonstrate that the combined control of PLA molecular characteristics and talc content enables tuning of the mechanical and thermomechanical performance of TPS/PBS/PLA/talc systems for rigid packaging applications. Full article

Waste-to-energy (WtE) systems are frequently proposed as complementary waste-management strategies; however, their climate performance depends on the interaction between thermodynamic efficiency, material circularity, and electricity-system characteristics. Existing life-cycle assessments generally provide static comparisons between landfill and WtE but rarely identify the operating conditions under which WtE remains environmentally competitive. To address this gap, a parametric life cycle–energy framework was developed by integrating attributional LCA with an analytical energy model capable of evaluating critical efficiency thresholds under varying recovery rates and electricity-grid conditions. Four representative thermoplastics (PET, HDPE, PP, and LDPE) were evaluated using ReCiPe 2016 Midpoint (H) in SimaPro under Mexican electricity conditions ($E{F}_{\mathrm{grid}}=0.444$ kg CO₂eq/kWh). Results indicate that total life-cycle climate impacts are dominated by upstream polymer production, whereas end-of-life management contributes only marginally to overall GWP. Critical-efficiency analysis revealed strong sensitivity to both recovery rate and electricity-grid carbon intensity. For PET, the minimum efficiency required for WtE to outperform landfill increased from 13.1% to 73.5% across the evaluated scenarios, whereas HDPE remained competitive at efficiencies below 1.3%. Monte Carlo simulations (10,000 realizations) further demonstrated that avoided emissions decline systematically with increasing recovery rates, with LDPE exhibiting the highest mean avoided emissions (1735 kg CO₂eq) and PET the lowest (811 kg CO₂eq). These results demonstrate that WtE climate performance is governed primarily by residual waste availability and electricity-system evolution rather than thermodynamic efficiency alone. Consequently, WtE should be interpreted as a transitional residual-waste management strategy whose long-term climate relevance decreases as material circularity and electricity-grid decarbonization advance. Full article

The rapid growth in the use of carbon fiber-reinforced polymers (CFRPs) and fused-deposition-modeled (FDM) polylactic acid (PLA) has generated substantial non-biodegradable and thermoplastic waste streams, creating urgent needs for scalable recycling and valorization strategies. This study develops and evaluates an integrated route that chemically recovers carbon fibers (CFs) from CFRP waste and converts them into high-performance reinforcements for recycled PLA matrices. CFRP fragments were pre-swollen in acetic acid (120 °C, 1 h), then depolymerized by means of oxidation with 1 M KMnO₄ (100 °C, 2 h), washed, dried (100 °C, 24 h), and size-reduced by means of cryogenic milling. Recycled CFs (treated) and untreated CFRP fragments were blended with 3D-printing PLA waste at 10, 20 and 30 wt.% via melt mixing (175 °C, 5 min, 70 rpm) and molded into ASTM D638 dog-bone specimens. Materials were characterized via XRD, FTIR, Raman, SEM and mechanical testing. XRD and Raman confirmed retention of the graphitic backbone after treatment; FTIR and Raman revealed oxygen-containing surface functionalization consistent with oxidation, while SEM showed effective removal of epoxy and improved fiber surface cleanliness. Compared with neat PLA (tensile strength 45.4 MPa; modulus 2.6 GPa; elongation 6.3%), composites reinforced with chemically recycled CFs exhibited marked mechanical enhancement: at 30 wt.% treated CF, the tensile strength increased to 102.6 MPa (+126%), elastic modulus to 11.7 GPa (+350%), and toughness to 250.3 MPa, while ductility decreased to 2.9%. Equivalent composites with untreated CFRP exhibited smaller gains (30 wt.%: tensile 87.3 MPa; modulus 10.3 GPa), highlighting the benefit of epoxy removal and surface activation for fiber–matrix adhesion. The proposed chemical recycling pathway is operationally simple and cost-effective, produces reusable CFs with preserved graphitic structure and enhanced surface chemistry, and enables the fabrication of high-performance, waste-derived PLA composites suitable for structural and engineering applications. This work demonstrates a viable waste-to-value approach that advances circularity for both CFRP and 3D-printing polymer waste streams. Full article