Enhanced mixing efficiency for a novel 3D Tesla micromixer for Newtonian and non-Newtonian fluids  被引量:1

在线阅读下载全文

作  者:Abdellah AAZMI Zixian GUO Haoran YU Weikang LV Zengchen JI Huayong YANG Liang MA 

机构地区:[1]State Key Laboratory of Fluid Power and Mechatronic Systems,Zhejiang University,Hangzhou 310058,China [2]School of Mechanical Engineering,Zhejiang University,Hangzhou 310058,China

出  处:《Journal of Zhejiang University-Science A(Applied Physics & Engineering)》2023年第12期1065-1078,共14页浙江大学学报(英文版)A辑(应用物理与工程)

基  金:supported by the National Key Research and Development Program of China(No.2018YFA0703000);the National Natural Science Foundation of China(No.52275294).

摘  要:The fabrication of constructs with gradients for chemical,mechanical,or electrical composition is becoming critical to achieving more complex structures,particularly in 3D printing and biofabrication.This need is underscored by the complexity of in vivo tissues,which exhibit heterogeneous structures comprised of diverse cells and matrices.Drawing inspiration from the classical Tesla valve,our study introduces a new concept of micromixers to address this complexity.The innovative micromixer design is tailored to enhance the re-creation of in vivo tissue structures and demonstrates an advanced capability to efficiently mix both Newtonian and non-Newtonian fluids.Notably,our 3D Tesla valve micromixer achieves higher mixing efficiency with fewer cycles,which represents a significant improvement over the traditional mixing method.This advance is pivotal for the field of 3D printing and bioprinting,and offers a robust tool that could facilitate the development of gradient hydrogel-based constructs that could also accurately mimic the intricate heterogeneity of natural tissues.

关 键 词:MICROMIXING 3D printing Non-Newtonian fluids Computational fluid dynamics 

分 类 号:TB126[理学—工程力学] TH69[理学—力学]

 

参考文献:

正在载入数据...

 

二级参考文献:

正在载入数据...

 

耦合文献:

正在载入数据...

 

引证文献:

正在载入数据...

 

二级引证文献:

正在载入数据...

 

同被引文献:

正在载入数据...

 

相关期刊文献:

正在载入数据...

相关的主题
相关的作者对象
相关的机构对象