Development of computational models to predict the toxicity of advanced materials
by
 
Bilgi, Eyüp, author.

Title
Development of computational models to predict the toxicity of advanced materials

Author
Bilgi, Eyüp, author.

Personal Author
Bilgi, Eyüp, author.

Physical Description
xvi, 214 leaves: illustrarions, charts; 29 cm + 1 computer laser optical disc.

Abstract
The aim of this study is to harness computational power to enhance existing knowledge on NM safety and to optimize the use of existing nanotoxicity data. The primary goal is to support the safe(r)-by-design concept, necessitating early integration of safety considerations into NM design through structural manipulation strategies. This thesis focuses on three case studies: zinc oxide, silver, and gold NP, using data manually collected from the literature. Analyses with zinc oxide and silver NP revealed a correlation between their toxicity and both internal (intrinsic properties, size, shape, surface charge) and external (cell and analysis-related properties) factors. For zinc oxide, it was found that coating had significant influence on cell viability, with a critical threshold identified at 20 µg/ml concentration and 10 nm size. Similarly, for silver NPs, concentration, size, and exposure time were significant factors. Coating with organic macromolecules increased cell viability, whereas green-synthesized NPs (using bacteria, plant extracts, algae) decreased it. The gold NP study highlighted that ensemble methods were more effective in elucidating complex relationships, with cellular uptake linked to particle size, zeta potential, concentration, and exposure time. Overall, this thesis contributes to safer-by-design strategies, crucial for developing commercially viable and safe NMs. The findings advocate for a broader toxicity evaluation approach, considering various physicochemical aspects and experimental procedures. The complex interactions observed suggest that advanced algorithms are necessary for accurate modeling, supporting the optimization of experimental parameters in NP engineering for biomedical applications.

Subject Term
Nanostructured materials -- Toxicology
 
Biomedical materials.
 
Machine learning
 
Artificial intelligence

Added Author
Öksel Karakuş, Ceyda,
 
Bedir, Erdal,

Added Corporate Author
İzmir Institute of Technology. Materials Science and Engineering.

Added Uniform Title
Thesis (Doctoral)-- İzmir Institute of Technology: Materials Science and Engineering.
 
İzmir Institute of Technology: Materials Science and Engineering. (Doctoral).

Electronic Access
Access to Electronic Versiyon.


LibraryMaterial TypeItem BarcodeShelf NumberStatus
IYTE LibraryThesisT002878RA1270.N36 D48 2023Tez Koleksiyonu
IYTE LibrarySupplementary CD-ROMROM4019RA1270.N36 D48 2023 EK.1Tez Koleksiyonu