Fluctuations of the number of adsorbed micro/nanoparticles in sensors for measurement of particle concentration in air and liquid environments
Fluctuations of the number of adsorbed micro/nanoparticles in sensors for measurement of particle concentration in air and liquid environments
复制标题
用于测量空气和液体环境中颗粒浓度的传感器中吸附的微/纳米颗粒数量的波动
DOI：
10.2298/ciceq140219011j
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发表时间：
2014
影响因子：
1.2
通讯作者：
M. Frantlović
中科院分区：
文献类型：
--
作者：
I. Jokić;Z. Djuric;K. Radulović;M. Frantlović
吸附粒子数涨落的理论模型
在空气和液体中工作的环境传感器中的微米/纳米颗粒，
提出，考虑到质量传递过程的影响，
传感器反应室中的目标颗粒。的表达式
相应吸附-脱附噪音的总功率，以及
相应的信噪比也被导出。提出的分析
表明，转移过程可以有显着的影响，
传感器限制性能。对波动的影响
频谱和信噪比是在不同的值下估计的
目标颗粒浓度、功能化位点表面密度，以及
吸附和解吸速率常数（值选自
对应于真实的条件的范围）。分析提供了
传感器设计和操作条件优化指南
给定的目标物质和传感器功能化，以便
减小传质的影响，从而提高最终的
性能（例如最小可检测信号、信噪比）
用于粒子探测的传感器。我们进行的计算表明，
有可能将信噪比提高两个数量级
通过使用消除传质的优化，
影响力的社会[Projekat Ministarstva nauke，Srbije，br. TR32008]
A theoretical model of fluctuations of the number of adsorbed
micro/nanoparticles in environmental sensors operating in air and liquids is
presented, taking into account the effects of the mass transfer processes of
the target particles in a sensor reaction chamber. The expressions for the
total power of the corresponding adsorption-desorption noise, and for the
corresponding signal-to-noise ratio are also derived. The presented analysis
shows that the transfer processes can have a significant influence on the
sensors limiting performance. The influence on both the fluctuations
spectrum and the signal-to-noise ratio is estimated at different values of
target particles concentration, functionalization sites surface density, and
adsorption and desorption rate constants (the values are chosen from the
ranges corresponding to real conditions). The analysis provides the
guidelines for optimization of sensor design and operating conditions for
the given target substance and sensor functionalization, in order to
decrease the influence of the mass transfer, thus improving the ultimate
performance (e.g. minimal detectable signal, signal-to-noise ratio) of
sensors for particle detection. The calculations we performed show that it
is possible to increase the signal-to-noise ratio for as much as two orders
of magnitude by using the optimization that eliminates the mass transfer
influence. [Projekat Ministarstva nauke Republike Srbije, br. TR32008]