Banca de QUALIFICAÇÃO: MILLENA DE CASSIA SOUSA E SILVA

Uma banca de QUALIFICAÇÃO de MESTRADO foi cadastrada pelo programa.
DISCENTE: MILLENA DE CASSIA SOUSA E SILVA
DATA: 29/02/2024
HORA: 08:00
LOCAL: Banca Remota
TÍTULO: Tailoring mechanical properties of bioprinted GelMA scaffolds with multilayers of PLA/Laponite nanocomposite fibers
PALAVRAS-CHAVES: nanocomposites; bioprinting; scaffold; tissue engineering; laponite
PÁGINAS: 20
GRANDE ÁREA: Engenharias
ÁREA: Engenharia de Materiais e Metalúrgica
SUBÁREA: Materiais Não-Metálicos
ESPECIALIDADE: Polímeros, Aplicações
RESUMO:

This study focuses on fabricating and evaluating hybrid scaffolds of bioprinted GelMA hydrogels reinforced with multilayers of Poly(Lactic Acid) (PLA)/Laponite (LAP) microfibrous membranes. PLA microfibers with varying amounts of LAP (0, 1.0, 2.5, and 5%) were synthesized using rotary-jet spinning and were subjected to oxygen plasma treatment. Scanning electron microscopy (SEM), Fourier transform infrared spectroscopy (FTIR), and x-ray diffraction (XRD) were utilized for morphological and compositional analyses. Their mechanical properties were evaluated via uniaxial tensile testing, highlighting improved mechanical strength by incorporating LAP, particularly in the PLA/ LAP 2.5% group. Then, the microfibrous membranes were integrated into bioprinted GelMA hydrogel layers, creating GelMA-PLA/LAP hybrid scaffolds, whose interaction and integrity were confirmed through SEM. Mechanical assessment via uniaxial compression tests demonstrated a significant enhancement in the mechanical properties of the hybrid scaffolds attributed to the inclusion of microfibrous membranes. These findings underscore the potential utility of GelMA-PLA/LAP scaffolds in tissue engineering applications by capitalizing on the mechanical reinforcement imparted by PLA/LAP microfibrous layers.

MEMBROS DA BANCA:
Presidente - 1397472 - ANDERSON DE OLIVEIRA LOBO
Interno - 1570906 - BARTOLOMEU CRUZ VIANA NETO
Externo à Instituição - FRANCILIO DE CARVALHO OLIVEIRA - UNINOVAFAPI