Generalized serial dilution module for monotonic and arbitrary microfluidic gradient generators

Generalized serial dilution module for monotonic and arbitrary microfluidic gradient generators
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DOI:
10.1039/b813582g
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发表时间:
2009-01-01
期刊:
影响因子:
6.1
通讯作者:
Oh, Kwang W.
Oh, Kwang W.
中科院分区:
工程技术1区
文献类型:
--
作者:
Lee, Kangsun;Kim, Choong;Oh, Kwang W.

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In this paper, we propose a generalized serial dilution module for universal microfluidic concentration gradient generators including N cascaded-mixing stages in a stepwise manner. Desired concentrations were generated by means of controlled volumetric mixing ratios of two merging solutions in each stage. The flow rates were adjusted by controlling channel length, which is proportional to fluidic resistance in each channel. A generalized mathematical model for generating any complex concentration and output flow rate gradients is presented based on the fact that there is an analogy between microfluidic circuits and electrical circuits. The pressure drop corresponds to a voltage drop, the flow rate to an electrical current, and the flow resistance to an electrical resistance. A simple equivalent electrical circuit model was generalized, and in the model each channel segment was represented by an electrical resistance. As a result of the mathematical modelling, the only variable parameter in the generalized serial dilution module was the channel length. By the use of the generalized serial dilution module with N 4, three types of microfluidic gradient generators for linear, logarithmic and Gaussian gradients were successfully designed and tested. The proposed strategy is capable of generating universal monotonic gradients with a single module or arbitrary gradients with multiple modules ranging from linear to complex non-linear shapes of concentration gradients as well as arbitrary output flow rate gradients in a stepwise manner. The simple universal gradient generation technology using the generalized serial dilution module will find widespread use in the greater chemical and biological community, and address many challenges of gradient-dependent phenomena.