Comparative Evaluation of Rigid and Compliant 3D-Printed Lung Models for Particle Deposition Performance
Year: 2025
Type: conference-paper
Abstract: Accurately modeling how inhaled particles deposit within the respiratory tract remains a key challenge in respiratory health research. This study evaluates the suitability of several rigid 3D printing materials for constructing anatomically inspired second-generation bronchial airway models, focusing on how material surface characteristics influence particle deposition behavior. Airway constructs were fabricated using five materials—bioresin (photopolymer), polylactic acid (PLA), carbon fiber-reinforced PLA, polyethylene terephthalate glycol (PETG), and thermoplastic polyurethane (TPU)— a specific type of thermoplastic elastomer (TPE), using stereolithography and fused deposition modeling techniques. Each material’s surface roughness (Ra) was quantified using profilometry, and deposition efficiency was assessed through controlled aerosol exposure experiments. Although deposition did not scale linearly with roughness, a general trend emerged: higher surface roughness tended to increase deposition. Bioresin, exhibiting the second highest roughness (Ra ≈ 35 μm), showed the highest deposition in the second-generation bronchial airway models with 2.68% of the total aerosol deposited, while smoother materials such as carbon fiber PLA and PETG demonstrated no deposition. These findings underscore the critical role of surface texture in influencing airflow and particle-wall interactions, especially in the context of respiratory diseases that alter airway morphology. This comparative analysis offers new insights into material selection for developing rigid airway phantoms and underscores the complex, non-linear role of surface roughness in particle transport. The results lay a foundation for future efforts to decouple geometry, flow behavior, and surface properties—guiding the design of next-generation lung phantoms for aerosol therapy, pollutant exposure, and drug delivery studies.
Institution: Rochester Institute of Technology
Language: English
Subfield: Pulmonary and Respiratory Medicine
Field: Medicine
Domain: Health Sciences
Open Access status: hybrid
OpenAlex ID: W7131064321