A Novel Cryogenic Approach to 3D Printing Cytocompatible, Conductive, Hydrogel-Based Inks

材料科学 墨水池 3D打印 3d打印 组织工程 导电体 纳米技术 挤压 电导率 数字光处理 生物医学工程 复合材料 计算机科学 化学 计算机视觉 物理化学 投影机 医学
作者
Aida Shoushtari Zadeh Naseri,Cormac Fay,Andrew Nattestad,Gregory Ryder,Sepidar Sayyar,Zhilian Yue,Xiao Liu,David L. Officer,Gordon G. Wallace
出处
期刊:3D printing and additive manufacturing [Mary Ann Liebert, Inc.]
卷期号:11 (2): 447-459 被引量:3
标识
DOI:10.1089/3dp.2022.0169
摘要

In the field of tissue engineering and regenerative medicine, developing cytocompatible 3D conductive scaffolds that mimic the native extracellular matrix is crucial for the engineering of excitable cells and tissues. In this study, a custom cryogenic extrusion 3D printer was developed, which afforded control over both the ink and printing surface temperatures. Using this approach, aqueous inks were printed into well-defined layers with high precision. A conductive hydrogel ink was developed from chitosan (CS) and edge-functionalised expanded graphene (EFXG). Different EFXG:CS ratios (between 60:40 and 80:20) were evaluated to determine both conductivity and printability. Using the novel customized cryogenic 3D printer, conductive structures of between 2 and 20 layers were produced, with feature sizes as small as 200 μm. The printed structures are mechanically robust and are electrically conducting. The highest Young's modulus and conductivity in a hydrated state were 2.6 MPa and ∼45 S/m, respectively. Cytocompatibility experiments reveal that the developed material supports NSC-34 mouse motor neuron-like cells in terms of viability, attachment, and proliferation. The distinctive mechanical and electrical properties of the 3D-printed structures would make them good candidates for the engineering of 3D-structured excitable cells. Moreover, this novel printing setup can be used to print other hydrogel-based inks with high precision and resolution.

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
无限凛发布了新的文献求助10
刚刚
justonce发布了新的文献求助10
1秒前
邪恶韩孜发布了新的文献求助10
1秒前
2秒前
高大荔枝发布了新的文献求助10
2秒前
kingdom金田一完成签到,获得积分20
2秒前
思源应助Ashore采纳,获得10
4秒前
5秒前
5秒前
5秒前
6秒前
胡萝卜发布了新的文献求助10
6秒前
gww发布了新的文献求助10
6秒前
9秒前
9秒前
9秒前
李lll发布了新的文献求助10
9秒前
yuii完成签到,获得积分10
10秒前
爆米花应助邪恶韩孜采纳,获得10
11秒前
12秒前
12秒前
gww完成签到,获得积分10
12秒前
justonce完成签到,获得积分10
12秒前
科研通AI2S应助LNdOjk采纳,获得10
13秒前
Owen应助温婉的凝雁采纳,获得10
15秒前
陌路发布了新的文献求助30
15秒前
Akim应助高LL采纳,获得10
15秒前
楠D发布了新的文献求助10
18秒前
20秒前
21秒前
大个应助岸久舞若衣采纳,获得10
22秒前
会撒娇的绮兰完成签到,获得积分10
23秒前
田様应助坚定青槐采纳,获得10
23秒前
希望天下0贩的0应助lee采纳,获得10
23秒前
烟花应助humble采纳,获得10
25秒前
26秒前
wyl发布了新的文献求助10
26秒前
岸久舞若衣完成签到,获得积分20
26秒前
26秒前
27秒前
高分求助中
(应助此贴封号)【重要!!请各用户(尤其是新用户)详细阅读】【科研通的精品贴汇总】 10000
Chemistry and Physics of Carbon Volume 18 800
The Organometallic Chemistry of the Transition Metals 800
The formation of Australian attitudes towards China, 1918-1941 640
Signals, Systems, and Signal Processing 610
全相对论原子结构与含时波包动力学的理论研究--清华大学 500
Elevating Next Generation Genomic Science and Technology using Machine Learning in the Healthcare Industry Applied Machine Learning for IoT and Data Analytics 400
热门求助领域 (近24小时)
化学 材料科学 医学 生物 纳米技术 工程类 有机化学 化学工程 生物化学 计算机科学 物理 内科学 复合材料 催化作用 物理化学 光电子学 电极 细胞生物学 基因 无机化学
热门帖子
关注 科研通微信公众号,转发送积分 6443580
求助须知:如何正确求助?哪些是违规求助? 8257418
关于积分的说明 17586894
捐赠科研通 5502274
什么是DOI,文献DOI怎么找? 2900939
邀请新用户注册赠送积分活动 1877987
关于科研通互助平台的介绍 1717534