Advisor(s)
Vinoy Thomas
Committee Member(s)
Haibin Ning
Jololian Leon
Ramana Reddy
Robin Foley
School
School of Engineering
Document Type
Dissertation
Department (new version)
Materials Engineering
Date of Award
9-11-2025
Abstract
The current dissertation presents an overarching pipeline for the development and production of custom-made scaffolds for periodontal tissue regeneration using finite element analysis (FEA), machine learning (ML), and additive manufacturing (AM).CAD anatomically realistic scaffolds were generated from CT-based maxilla and mandible models. The FEA simulation results under masticatory (100 N), parafunctional (500–550 N), and traumatic (800–850 N) loads showed region-specific distribution of stresses and strains, which guided structural reinforcement strategies. Over 1000 3D-printed PCL scaffolds were printed using various pore diameters (200–300 µm) and filament diameters. Five ML models were constructed for predicting print quality based on process factors. Classification accuracy in scaffold quality was high, at >93%, for the Random Forest and XG Boost models, which showed that filament diameter, chamber temperature, and extruder temperature were significant variables according to SHAP analysis. Dimensional analysis showed <8% deviation in filament and pore dimensions. Thermal analysis confirmed thermal stability with degradation onset above 300°C and crystallinity between 27-40%.Mechanical testing showed that 3-layered scaffolds had a maximum tensile strength of 7.13 MPa, while Swelling and degradation studies for 3 months showed controlled resorption (13–25%) depending on structure. Surface was functionalized by 2% GELMA and 4–5% Casein, augmenting hydrophilicity (contact angle was reduced from 62° to 33°) as well as supporting protein adhesion. Cell cultures with RPE cells showed >85% enhanced viability and adhesion on GELMA-functionalized scaffolds. This work presents a robust digital-to-biological process that allows the creation of biocompatible, mechanically stable, and patient-specific scaffolds for innovative periodontal therapy.
ProQuest ID
Recommended Citation
Pemmada, Rakesh, "Leveraging Computational Modelling/Simulation, Machine Learning, And Additive Manufacturing For Customized Design Of Periodontal And Bone Tissue Scaffolds" (2025). All ETDs from UAB. 7405.
https://digitalcommons.library.uab.edu/etd-collection/7405
