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Digitally programmable microfluidic automaton for multiscale combinatorial mixing and sample processing

delete2013-01-01
delete70
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OA
AI
E
Erik C. Jensen
A
Amanda M. Stockton
T
Thomas N. Chiesl
J
Jungkyu Kim
A
Abhisek Ranjan Bera
R
Richard A. Mathies *
DOI:10.1039/c2lc40861adelete
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摘要

摘要

En 中文
A digitally programmable microfluidic Automaton consisting of a 2-dimensional array of pneumatically actuated microvalves is programmed to perform new multiscale mixing and sample processing operations. Large (mu L-scale) volume processing operations are enabled by precise metering of multiple reagents within individual nL-scale valves followed by serial repetitive transfer to programmed locations in the array. A novel process exploiting new combining valve concepts is developed for continuous rapid and complete mixing of reagents in less than 800 ms. Mixing, transfer, storage, and rinsing operations are implemented combinatorially to achieve complex assay automation protocols. The practical utility of this technology is demonstrated by performing automated serial dilution for quantitative analysis as well as the first demonstration of on-chip fluorescent derivatization of biomarker targets (carboxylic acids) for microchip capillary electrophoresis on the Mars Organic Analyzer. A language is developed to describe how unit operations are combined to form a microfluidic program. Finally, this technology is used to develop a novel microfluidic 6-sample processor for combinatorial mixing of large sets (>2(6) unique combinations) of reagents. The digitally programmable microfluidic Automaton is a versatile programmable sample processor for a wide range of process volumes, for multiple samples, and for different types of analyses.
Keyword:
CAPILLARY-ELECTROPHORESIS MICRODEVICE
CARBONACEOUS BIOMARKERS
CHIP
CAPTURE
DILUTE
VALVES

期刊

L
Lab on a Chip
IF:
5.4
论文数:
9.0K
被引数:
3.3W

机构

U
University of California Berkeley
学者数:
3.5W
论文数: 2.8W
被引数: 11.3W
University of California System 封面图
University of California System
学者数:
37.5W
论文数: 33.8W
被引数: 6.6K
引用论文

引用论文

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