Random lasing detection of structural transformation and compositions in silk fibroin scaffolds

Sung Yeun Yang, Soocheol Kim, Hye In Shin, Seung Ho Choi, Young L. Kim, Chulmin Joo, Won Hyoung Ryu

Research output: Contribution to journalArticle

3 Citations (Scopus)

Abstract

In tissue engineering, microstructure and material composition of tissue scaffolds have major influences on the proliferation and differentiation of cells in the scaffolds. However, once tissue scaffolds implanted, it is extremely difficult to monitor the change of their microstructure and compositions during tissue regeneration. Here, we report how random lasing can be utilized to non-invasively monitor the structure and composition of scaffolds. We hypothesize that morphological and compositional change of silk fibroin (SF) scaffolds can be conveniently detected based on random lasing responses. Engineered SF scaffolds with hydroxyapatite (HAP) nanoparticles and controlled pore alignment were fabricated, and their random lasing responses were analyzed depending on the concentration of HAP nanoparticles and the degree of internal pore alignment. We also examined the real-time random lasing responses of porous SF scaffolds by applying a compressive force to the scaffolds. Introduction of HAP nanoparticles lowered the lasing thresholds and narrowed the random lasing (RL) width dramatically, which is likely due to the increase in heterogeneity in both refractive index and physical arrangement within the SF and HAP composites. The strong dependency of RL response on pore alignment was also measured and validated by numerical calculation with the finite element method (FEM). Finally, real-time monitoring of RL on compressed scaffolds demonstrated the possibility of using RL as a monitoring tool for structural change of SF scaffolds in vivo. [Figure not available: see fulltext.].

Original languageEnglish
Pages (from-to)289-297
Number of pages9
JournalNano Research
Volume12
Issue number2
DOIs
Publication statusPublished - 2019 Feb 1

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All Science Journal Classification (ASJC) codes

  • Materials Science(all)
  • Electrical and Electronic Engineering

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