Spreading behavior of cell-laden droplets in 3D bioprinting process

基质(水族馆) 缩放比例 材料科学 体积热力学 过程(计算) 纳米技术 计算机科学 物理 几何学 热力学 海洋学 数学 地质学 操作系统
作者
Xinxing Chen,Aidan P. O’Mahony,Tracie Barber
出处
期刊:Journal of Applied Physics [American Institute of Physics]
卷期号:133 (1) 被引量:2
标识
DOI:10.1063/5.0130063
摘要

3D droplet-based bioprinting technology is an innovative and time-saving additive manufacturing method, which enables spatial patterning of biological materials and biochemical and living cells for multiple clinical and research applications. Understanding the criteria that control droplet spreading behavior during droplet impact is of great importance in controlling printing resolution and optimizing the printing performance. In this experimental work, the spreading of 3D printed cell-laden droplets was studied with side and bottom view images. The droplets contain 1×107 cells/ml input cell concentration and corresponding Φ=0.52% cell volume fraction and impact onto a flat hydrophilic substrate, a pre-printed droplet, and a pre-printed thin liquid film. The cell-laden droplet impact morphology, the maximum spreading factor, and the cell distribution under different printing conditions (89<We<365,174<Re<414) in a 3D bioprinting process were characterized. It was found that on the hydrophilic flat substrate, the cells homogeneously distributed into a disk structure. The maximum spreading factor, βmax, can be well described by the correlation formulas based on the energy balance and volume conservation. A power-law scaling formula was found to describe the maximum spreading in terms of the Weber number for cell-laden droplet impact on both pre-printed droplets and thin liquid films, where βmax∝We0.25. Input cell concentration, up to 1×107 cells/ml, was found to have negligible effect on the maximum droplet spreading factor in a 3D bioprinting process.
最长约 10秒,即可获得该文献文件

科研通智能强力驱动
Strongly Powered by AbleSci AI
科研通是完全免费的文献互助平台,具备全网最快的应助速度,最高的求助完成率。 对每一个文献求助,科研通都将尽心尽力,给求助人一个满意的交代。
实时播报
1秒前
1秒前
科研通AI5应助hu970采纳,获得10
1秒前
1秒前
艺玲发布了新的文献求助10
2秒前
咚咚咚完成签到,获得积分10
2秒前
芋圆Z.完成签到,获得积分10
2秒前
atad2发布了新的文献求助10
2秒前
li梨完成签到,获得积分10
2秒前
3秒前
晏小敏完成签到,获得积分10
3秒前
爆米花应助风中寄云采纳,获得10
4秒前
屹舟发布了新的文献求助10
4秒前
Dou完成签到,获得积分10
4秒前
白泯完成签到,获得积分10
5秒前
1ssd发布了新的文献求助10
5秒前
667发布了新的文献求助10
5秒前
小二郎应助辰柒采纳,获得10
6秒前
7秒前
7秒前
clear完成签到,获得积分20
7秒前
7秒前
orixero应助congguitar采纳,获得10
7秒前
Evan完成签到,获得积分10
7秒前
YANG发布了新的文献求助10
8秒前
8秒前
123发布了新的文献求助10
8秒前
sunzhiyu233发布了新的文献求助10
9秒前
Raul完成签到 ,获得积分10
9秒前
9秒前
伯尔尼圆白菜完成签到,获得积分10
9秒前
9秒前
10秒前
10秒前
10秒前
buuyoo完成签到,获得积分10
10秒前
科研通AI5应助魏煜佳采纳,获得10
10秒前
LLxiaolong完成签到,获得积分10
10秒前
11秒前
11秒前
高分求助中
Continuum Thermodynamics and Material Modelling 3000
Production Logging: Theoretical and Interpretive Elements 2700
Social media impact on athlete mental health: #RealityCheck 1020
Ensartinib (Ensacove) for Non-Small Cell Lung Cancer 1000
Unseen Mendieta: The Unpublished Works of Ana Mendieta 1000
Bacterial collagenases and their clinical applications 800
El viaje de una vida: Memorias de María Lecea 800
热门求助领域 (近24小时)
化学 材料科学 生物 医学 工程类 有机化学 生物化学 物理 纳米技术 计算机科学 内科学 化学工程 复合材料 基因 遗传学 物理化学 催化作用 量子力学 光电子学 冶金
热门帖子
关注 科研通微信公众号,转发送积分 3527699
求助须知:如何正确求助?哪些是违规求助? 3107752
关于积分的说明 9286499
捐赠科研通 2805513
什么是DOI,文献DOI怎么找? 1539954
邀请新用户注册赠送积分活动 716878
科研通“疑难数据库(出版商)”最低求助积分说明 709759