A computational and experimental framework for tissue engineering scaffold design and characterisation
A computational and experimental framework for tissue engineering scaffold design and characterisation
批准号:
2573181
负责人:
金额:
$0.0万
依托单位:
依托单位国家:
英国
项目类别:
Studentship
财政年份:
2021
资助国家:
英国
项目状态:
未结题
起止时间:
2021 至 --
中文摘要
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英文摘要
Mechanobiology research is for understanding the role of mechanics in cell physiology and pathology. It will have implications for studying cellular physiology and pathology and to guide the strategy for regenerating both the structural and functional features of tissue (such as bone / cartilage). In mechanobiological studies in vitro, a dynamic micro-mechanical environment is usually applied to cells via bioreactors. Porous scaffolds are commonly used for housing the cells in a three-dimensional (3D) culturing environment. Such scaffolds usually have different pore geometries (e.g. with different pore shapes, pore dimensions and porosities). These pore geometries can affect the internal micro-mechanical environment that the cells experience when loaded in the bioreactor. Therefore, to adjust the applied micro-mechanical environment on cells, researchers can tune either the applied load and/or the design of the scaffold pore geometries. To benefit the tissue engineering / organoids fields for cellular mechanobiology research by optimising the mechanical stimulation on cells within scaffolds, this PhD project aims to develop a computational and experimental framework for designing tissue engineering scaffold geometry and characterising its influence on the internal micro-mechanical environment. To carry out the PhD project, computer-aided design / computer-aided engineering (CAD/CAE) approach will be used for creating scaffold geometries and simulating the internal micro-mechanical environment. In addition, experimental measurement will be setup for validating the simulation results by measuring the flow within scaffolds, for example. Afterwards, many simulations will be run on various scaffold geometries to create a "big data". Finally, a data-driven optimisation technique will be used for processing the "big data" to build up a automatic design framework. This framework is expected to be applied to scaffold geometric design for various tissue engineering applications (e.g. bone, cartilage).
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