Enhanced PLA/PEG filaments for sustainable high-performance 3D printing using PLA synthesized from commercial lactic acid
Source abstract
Abstract
Abstract Additive manufacturing has incorporated renewable polymers, such as polylactic acid (PLA), but its low mechanical and thermal properties require the addition of 20% to 40% w/w of additives, which can reduce tensile strength by up to 60% and material degradation temperatures by 10 to 20 °C. This research seeks to reduce the use of commercial PLA additives by developing 3D printing filaments that incorporate a compatible plasticizer, polyethylene glycol (PEG), and synthesized PLA (PLA-R), in a lesser extent. The study presents the synthesis of filaments for fused filament fabrication (FFF) using a blend of commercial PLA, PLA-R obtained from 90% pure lactic acid, and PEG. The study focused on the evaluation of three blend ratios: these are pelletized and extruded using a single-screw extruder to produce filaments with a target diameter of 1.75 mm. Mechanical and thermal performance were evaluated using tensile testing and thermogravimetric analysis (TGA). The optimal formulation contains 80% commercial PLA, 15% PEG, and 5% PLA-R, resulting in a consistent filament diameter. This formulation was used to fabricate Dogbone samples on a desktop 3D printer using FFF. These samples were subsequently analyzed using tensile testing and scanning electron microscopy (SEM), demonstrating their improved properties and suitability for additive manufacturing. Graphical abstract Development of PLA-Based Filament for 3D Printing, Divided into Four Stages – (1) Ring Opening Polymerization of PLA-R; (2) Development of polymer blends; (3) Obtaining Filament by Extrusion; 4) 3D Printing by Fused Filament Fabrication Method.
Source: crossref · Quality: baseline
Research context
OpenAlex topics: Additive Manufacturing and 3D Printing Technologies · biodegradable polymer synthesis and properties · Polymer Foaming and Composites
SciVX discovery tags are terminology-based. OpenAlex topics are source-provided classifications.
References (45)
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