Adaptive Microfluidic Networks for Optimal Transport
用于最佳传输的自适应微流体网络
基本信息
- 批准号:490727199
- 负责人:
- 金额:--
- 依托单位:
- 依托单位国家:德国
- 项目类别:Research Grants
- 财政年份:
- 资助国家:德国
- 起止时间:
- 项目状态:未结题
- 来源:
- 关键词:
项目摘要
Flow transport in complex networks is abundant in biology and engineering, from the vasculature of animals, to the hyphal networks of fungi, to the random porous media making up batteries. It has long been thought that biological network morphologies were optimised to minimise the energetic cost associated to viscous flow dissipation in their branches. However, another possibility, raised recently is for these networks to be optimal for mass exchange, or perfusion. We then need not only to have a network that covers space efficiently, but also whose morphology leads to an even flow of chemicals (catalysts, nutrients, oxygen,...) throughout all its tubes, so that all parts of the network receive the same amount of chemical. Living systems continuously adapt their network morphology in response to stimuli; local feedback coupled to the presence of global flows leads to self-organised structures optimal for perfusion. In contrast, fluid velocities in engineered networks of random media differ from tube to tube, and follow an overall exponential distribution. Transport through these porous media is inefficient, being limited to a few fast lanes. The current strategy to optimize flow in porous media is to build, branch by branch, an optimized network morphology. The aim of our project is to combine theory, simulations and experiments to generate adaptive microfluidic networks whose morphology self-organises in response to signals, leading to network morphologies optimal for perfusion. In addition to its fundamental interest, the outcome of this project has a wide range of applications, from the design and cooling of efficient batteries, to the production of enhanced chemical reactors having high transport efficiency and a large reaction surface, contributing to having a cleaner, more affordable energy.
复杂网络中的流动输运在生物学和工程学中非常丰富,从动物的脉管系统到真菌的菌丝网络,再到组成电池的随机多孔介质。长期以来,人们一直认为生物网络形态被优化,以最大限度地减少与其分支中的粘性流耗散相关的能量成本。然而,最近提出的另一种可能性是这些网络对于质量交换或灌注是最佳的。然后,我们不仅需要有一个有效覆盖空间的网络,而且其形态导致化学物质(催化剂,营养素,氧气......)的均匀流动。在所有的管道中,这样网络的所有部分都接收相同数量的化学物质。生命系统不断地调整其网络形态以响应刺激;局部反馈与全局流的存在相结合,导致最适合灌注的自组织结构。相比之下,随机介质的工程网络中的流体速度在管与管之间不同,并且遵循总体指数分布。通过这些多孔介质的运输效率很低,仅限于几条快速通道。目前优化多孔介质中流动的策略是逐分支建立优化的网络形态。我们的项目的目的是联合收割机理论,模拟和实验相结合,以产生自适应的微流体网络,其形态自组织响应信号,导致最佳的网络形态灌注。除了其根本利益之外,该项目的成果还具有广泛的应用,从高效电池的设计和冷却到具有高传输效率和大反应表面的增强型化学反应器的生产,有助于获得更清洁,更实惠的能源。
项目成果
期刊论文数量(0)
专著数量(0)
科研奖励数量(0)
会议论文数量(0)
专利数量(0)
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Professorin Dr. Karen Alim其他文献
Professorin Dr. Karen Alim的其他文献
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{{ truncateString('Professorin Dr. Karen Alim', 18)}}的其他基金
Dynamic patterns of the plant growth regulator auxin
植物生长调节剂生长素的动态模式
- 批准号:
356728468 - 财政年份:2017
- 资助金额:
-- - 项目类别:
Research Units
Kollektive Bewegung von zusammenhängenden Zellen
连接细胞的集体运动
- 批准号:
195142051 - 财政年份:2011
- 资助金额:
-- - 项目类别:
Research Fellowships
Fluid flows controlling morphology: How flows coordinate the collective behaviour of protrusions for directed migration
流体流动控制形态:流动如何协调突起的集体行为以进行定向迁移
- 批准号:
443740179 - 财政年份:
- 资助金额:
-- - 项目类别:
Research Grants
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