Processing–Structure–Degradation Relationships in Additively Manufactured and Cast PLA/PCL Blends

IF 5.2 3区 材料科学 Q2 MATERIALS SCIENCE, MULTIDISCIPLINARY
Fatemeh Sadat Mahdavi, Arunachalam Ramanathan, Xiao Sun, Dhanush Patil, Varunkumar Thippanna, Libin Yang, Sri Vaishnavi Thummalapalli, M. Taylor Sobczak, Chao Sui, Zhengfu Huang, Tiantian Li, Qixuan Xiang, Ian Doran, James Jaraczewski, Manlilang Luo, Jacob Houston, Nathan Newton, Kate Hwang, Robert Loos, Mike Parker, Haley Dayton, Mark Remmert, Gajanan Bhat, Smriti Rai, Kenan Song
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Abstract

This study explores the effects of varying polylactic acid (PLA) and polycaprolactone (PCL) blend ratios on the rheological properties, printability, and structural performance of scaffolds fabricated by electrohydrodynamic writing(EHD). The blends were prepared in weight ratios of 100/0, 90/10, 80/20, 70/30, 60/40, 50/50, and 0/100 (PLA/PCL) and systematically evaluated to determine their influence on ink viscosity, extrusion behavior, scaffold fidelity, and mechanical integrity. The results demonstrate that increasing PCL content reduces viscosity, enhancing extrudability and enabling finer resolution in printed structures. However, this requires careful optimization of printing pressure and nozzle diameter to maintain structural stability. Intermediate blends (e.g., 70/30 or 60/40) demonstrated the best balance between printability, mechanical strength, and controlled degradation, making them promising for tissue engineering applications. The study highlights the advantages of EHD as a precision additive manufacturing technique, enabling controllable degradation behavior through tuning of degradation kinetics via blend composition. Overall, this work demonstrates that optimizing PLA/PCL blend composition enables the fabrication of mechanically robust biopolymer structures with controlled degradation profiles, reinforcing their potential for food packaging, biomedical devices, or even the patient-specific tissue regeneration.

Abstract Image

增材制造和铸造PLA/PCL共混物的加工-结构-降解关系
本研究探讨了不同的聚乳酸(PLA)和聚己内酯(PCL)混合比例对电流体动力书写(EHD)支架流变性能、可打印性和结构性能的影响。以重量比为100/0、90/10、80/20、70/30、60/40、50/50和0/100 (PLA/PCL)制备共混物,并系统评估其对油墨粘度、挤出行为、支架保真度和机械完整性的影响。结果表明,增加PCL含量可降低黏度,提高挤压性,使印刷结构具有更精细的分辨率。然而,这需要仔细优化印刷压力和喷嘴直径,以保持结构稳定性。中间混合物(例如70/30或60/40)在可打印性、机械强度和可控降解之间表现出最佳平衡,使其在组织工程应用中具有前景。该研究强调了EHD作为一种精密增材制造技术的优势,通过调节混合成分的降解动力学,实现了可控制的降解行为。总的来说,这项工作表明,优化PLA/PCL共混组合物可以制造具有控制降解特征的机械坚固的生物聚合物结构,增强其在食品包装,生物医学设备甚至患者特异性组织再生方面的潜力。
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来源期刊
Macromolecular Materials and Engineering
Macromolecular Materials and Engineering 工程技术-材料科学:综合
CiteScore
7.30
自引率
5.10%
发文量
328
审稿时长
1.6 months
期刊介绍: Macromolecular Materials and Engineering is the high-quality polymer science journal dedicated to the design, modification, characterization, processing and application of advanced polymeric materials, including membranes, sensors, sustainability, composites, fibers, foams, 3D printing, actuators as well as energy and electronic applications. Macromolecular Materials and Engineering is among the top journals publishing original research in polymer science. The journal presents strictly peer-reviewed Research Articles, Reviews, Perspectives and Comments. ISSN: 1438-7492 (print). 1439-2054 (online). Readership:Polymer scientists, chemists, physicists, materials scientists, engineers Abstracting and Indexing Information: CAS: Chemical Abstracts Service (ACS) CCR Database (Clarivate Analytics) Chemical Abstracts Service/SciFinder (ACS) Chemistry Server Reaction Center (Clarivate Analytics) ChemWeb (ChemIndustry.com) Chimica Database (Elsevier) COMPENDEX (Elsevier) Current Contents: Physical, Chemical & Earth Sciences (Clarivate Analytics) Directory of Open Access Journals (DOAJ) INSPEC (IET) Journal Citation Reports/Science Edition (Clarivate Analytics) Materials Science & Engineering Database (ProQuest) PASCAL Database (INIST/CNRS) Polymer Library (iSmithers RAPRA) Reaction Citation Index (Clarivate Analytics) Science Citation Index (Clarivate Analytics) Science Citation Index Expanded (Clarivate Analytics) SciTech Premium Collection (ProQuest) SCOPUS (Elsevier) Technology Collection (ProQuest) Web of Science (Clarivate Analytics)
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