Effect of Additive on Crystallization and Mechanical Properties of Polymer Blends of Poly(Lactic Acid) and Poly[(Butylene Succinate)-co-Adipate]

AbstractThe effect of additive on crystallization and mechanical properties of poly(lactic acid) (PLA) and poly(butylene succinate-co-adipate) (PBSA) blend was studied. PLA and PBSA were blended in a twin screw extruder, which incorporated poly(butylene adipate-co-terephthalate) (PBAT) as an additive in PLA/PBSA blend. The ratio of PLA/PBSA was 80/20. The contents of PBAT were varied from 0 to 50 wt%. The thermal properties and crystallization behavior of PLA/PBSA/PBAT blends were analyzed by differential scanning calorimetry. The effect of PBAT contents on non-isothermal crystallization kinetic of the composites was investigated by using Avrami equation. Tensile strength and impact performance of the PLA/PBSA/PBAT blends decreased when increasing PBAT contents. It can be noted that the addition of 20 wt% PBAT showed the maximum impact performance of the PLA/PBSA blends

Improvement of Interlayer Adhesion and Heat Resistance of Biodegradable Ternary Blend Composite 3D Printing

Poly(lactic acid) (PLA) filaments have been the most used in fused deposition modeling (FDM) 3D printing. The filaments, based on PLA, are continuing to be developed to overcome brittleness, low heat resistance, and obtain superior mechanical performance in 3D printing. From our previous study, the binary blend composites from PLA and poly(butylene adipate-co-terephthalate) (PBAT) with nano talc (PLA/PBAT/nano talc) at 70/30/10 showed an improvement in toughness and printability in FDM 3D printing. Nevertheless, interlayer adhesion, anisotropic characteristics, and heat resistance have been promoted for further application in FDM 3D printing. In this study, binary and ternary blend composites from PLA/PBAT and poly(butylene succinate) (PBS) with nano talc were prepared at a ratio of PLA 70 wt. % and blending with PBAT or PBS at 30 wt. % and nano talc at 10 wt. %. The materials were compounded via a twin-screw extruder and applied to the filament using a capillary rheometer. PLA/PBAT/PBS/nano talc blend composites were printed using FDM 3D printing. Thermal analysis, viscosity, interlayer adhesion, mechanical properties, and dimensional accuracy of binary and ternary blend composite 3D prints were investigated. The incorporation of PBS-enhanced crystallinity of the blend composite 3D prints resulted in an improvement to mechanical properties, heat resistance, and anisotropic characteristics. Flexibility of the blend composites was obtained by presentation of PBAT. It should be noted that the core–shell morphology of the ternary blend influenced the reduction of volume shrinkage, which obtained good surface roughness and dimensional accuracy in the ternary blend composite 3D printing

Improvement of Interlayer Adhesion and Heat Resistance of Biodegradable Ternary Blend Composite 3D Printing

Poly(lactic acid) (PLA) filaments have been the most used in fused deposition modeling (FDM) 3D printing. The filaments, based on PLA, are continuing to be developed to overcome brittleness, low heat resistance, and obtain superior mechanical performance in 3D printing. From our previous study, the binary blend composites from PLA and poly(butylene adipate-co-terephthalate) (PBAT) with nano talc (PLA/PBAT/nano talc) at 70/30/10 showed an improvement in toughness and printability in FDM 3D printing. Nevertheless, interlayer adhesion, anisotropic characteristics, and heat resistance have been promoted for further application in FDM 3D printing. In this study, binary and ternary blend composites from PLA/PBAT and poly(butylene succinate) (PBS) with nano talc were prepared at a ratio of PLA 70 wt. % and blending with PBAT or PBS at 30 wt. % and nano talc at 10 wt. %. The materials were compounded via a twin-screw extruder and applied to the filament using a capillary rheometer. PLA/PBAT/PBS/nano talc blend composites were printed using FDM 3D printing. Thermal analysis, viscosity, interlayer adhesion, mechanical properties, and dimensional accuracy of binary and ternary blend composite 3D prints were investigated. The incorporation of PBS-enhanced crystallinity of the blend composite 3D prints resulted in an improvement to mechanical properties, heat resistance, and anisotropic characteristics. Flexibility of the blend composites was obtained by presentation of PBAT. It should be noted that the core–shell morphology of the ternary blend influenced the reduction of volume shrinkage, which obtained good surface roughness and dimensional accuracy in the ternary blend composite 3D printing

Influence of Ambient Temperature and Crystalline Structure on Fracture Toughness and Production of Thermoplastic by Enclosure FDM 3D Printer

Fused deposition modeling (FDM) 3D printing has printed thermoplastic materials layer-by-layer to form three dimensional products whereby interlayer adhesion must be well controlled to obtain high mechanical performance and product integrity. This research studied the effects of ambient temperatures and crystalline structure on the interlayer adhesion and properties of thermoplastic FDM 3D printing. Five kinds of poly(lactic acid) (PLA) filaments, both commercially available and the laboratory-made, were printed using the enclosure FDM 3D printer. The ambient temperatures were set by the temperature-controlled chamber from room temperature to 75 °C with and without a cooling fan. The interlayer adhesion was characterized by the degree of entanglement density, morphology, and fracture toughness. In addition, PLA filament with high crystallinity has induced heat resistance, which could prevent filament clogging and successfully print at higher chamber temperatures. The ambient temperature increased with increased chamber temperature and significantly increased when printed without a cooling fan, resulting in improved interlayer bonding. The crystalline structure and dynamic mechanical properties of the 3D printed products were promoted when the chamber temperature was increased without a cooling fan, especially in PLA composites and PLA containing a high content of L-isomer. However, although the additives in the PLA composite improved crystallinity and the degree of entanglement density in the 3D-printed products, they induced an anisotropic characteristic that resulted in the declination of the interlayer bonding in the transverse orientation products. The increasing of chamber temperatures over 40 °C improved the interlayer bonding in pristine PLA products, which was informed by the increased fracture toughness. Further, it can be noted that the amorphous nature of PLA promotes molecular entanglement, especially when printed at higher chamber temperatures with and without a cooling fan

Properties of 3D Printable Poly(lactic acid)/Poly(butylene adipate-co-terephthalate) Blends and Nano Talc Composites

Biodegradable poly(lactic acid) (PLA) filaments have been widely used in the fused deposition modeling (FDM) 3D printing technology. However, PLA has low toughness and low thermal resistance that affects printability and restricts its industrial applications. In this study, PLA was compounded with 0 to 40 wt% of poly(butylene adipate-co-terephthalate) (PBAT) and varied content of nano talc at 0 to 40 wt% in a twin screw extruder. The compounds were reextruded to filaments using a capillary rheometer. PLA/PBAT blends and their composite filaments were printed with a FDM 3D printing machine. Morphology, rheological behaviour, thermal characteristic, surface roughness, and mechanical property of 3D printing of the blends and the composites were investigated. Complex viscosity of the blends and the composites increased with increase of the PBAT and the nano talc contents. The incorporation of the nano talc enhanced crystallization temperature and reduced the coefficient of volume expansion of the composites. It was found that the PLA/PBAT blends and composites were excellent in both printability and dimension stability at PBAT content 10-30 wt% and nano talc up to 10 wt%. Interestingly, it was possible to print the composite filaments at an angle up to 75° during the overhang test without a supporter. From the vertical specimens, the surface roughness improved due to the incorporation of the nano talc. Tensile strength of the blends and the composites decreased, whereas elongation at break increased when the PBAT and the nano talc contents were increased. The reduction of tensile strength was attributed to agglomeration of the PBAT dispersed phase and less adhesion between the nano talc and the matrix. It can be noted that the composite 3D printing product showed superior elongation at break up to 410% by adding nano talc 1 wt%. This result suggests that the ductile 3D printable PLA/PBAT blend and the PLA/PBAT-nano talc composite products can be prepared, which shows potential for the commercialized scale

Development of a Machine Learning Model to Predict the Color of Extruded Thermoplastic Resins

The conventional method for the color-matching process involves the compounding of polymers with pigments and then preparing plaques by using injection molding before measuring the color by an offline spectrophotometer. If the color fails to meet the L*, a*, and b* standards, the color-matching process must be repeated. In this study, the aim is to develop a machine learning model that is capable of predicting offline color using data from inline color measurements, thereby significantly reducing the time that is required for the color-matching process. The inline color data were measured using an inline process spectrophotometer, while the offline color data were measured using a bench-top spectrophotometer. The results showed that the Bagging with Decision Tree Regression and Random Forest Regression can predict the offline color data with aggregated color differences (dE) of 10.87 and 10.75. Compared to other machine learning methods, Bagging with Decision Tree Regression and Random Forest Regression excel due to their robustness, ability to handle nonlinear relationships, and provision of insights into feature importance. This study offers valuable guidance for achieving Bagging with Decision Tree Regression and Random Forest Regression to correlate inline and offline color data, potentially reducing time and material waste in color matching. Furthermore, it facilitates timely corrections in the event of color discrepancies being observed via inline measurements