4.8 Article

Hands-Off Preparation of Monodisperse Emulsion Droplets Using a Poly(dimethylsiloxane) Microfluidic Chip for Droplet Digital PCR

期刊

ANALYTICAL CHEMISTRY
卷 87, 期 8, 页码 4134-4143

出版社

AMER CHEMICAL SOC
DOI: 10.1021/ac503169h

关键词

-

资金

  1. JSPS KAKENHI Grant [13250199]
  2. Ministry of Education, Culture, Sports, Science and Technology, Japan [S0901039]
  3. Grants-in-Aid for Scientific Research [25410153] Funding Source: KAKEN

向作者/读者索取更多资源

A fully autonomous method of creating highly monodispersed emulsion droplets with a low sample dead volume was realized using a degassed poly(dimethylsiloxane) (PDMS) microfluidic chip possessing a simple T-junction channel geometry with two inlet reservoirs for oil and water to be loaded and one outlet reservoir for the collection of generated droplets. Autonomous transport of oil and water phases in the channel was executed by permeation of air confined inside the outlet reservoir into the degassed PDMS. The only operation required for droplet creation was simple pipetting of oil and aqueous solutions into the inlet reservoirs. Long-lasting fluid transport in the current system enabled us to create ca. 51,000 monodispersed droplets (with a coefficient of variation of <3% for the droplet diameter) in 80 min with a maximum droplet generation rate of ca. 12 Hz using a PDMS chip that had been degassed overnight. With multiple time-course measurements, the reproducibility in the current method of droplet preparation was confirmed, with tunable droplet sizes achieved simply by changing the cross-sectional dimensions of the microchannel. Furthermore, it was verified that the resultant droplets could serve as microreactors for digital polymerase chain reactions. This hands-free technique for preparing monodispersed droplets in a very facile and inexpensive fashion is intended for, but not limited to, bioanalytical applications and is also applicable to material syntheses.

作者

我是这篇论文的作者
点击您的名字以认领此论文并将其添加到您的个人资料中。

评论

主要评分

4.8
评分不足

次要评分

新颖性
-
重要性
-
科学严谨性
-
评价这篇论文

推荐

暂无数据
暂无数据