利用结构表征技术分析线性微透析探针的质量输运

Kho Chun Min , Zainal Arifin Ahmad , Siti Kartini Enche Ab Rahim , Norazharuddin Shah Abdullah
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摘要

微透析是一种广泛用于采样和监测目的的分离技术。微透析需要一个(微透析)探针插入到指定的研究区域。分离过程是通过使用附着在微透析孔上的选择性半透膜完成的。尽管是一种成熟的技术,仍然存在关于微透析探针性能的问题。最大的问题是,通过微透析采样收集的溶质浓度仅代表采样点原始浓度的20-30%。这个问题可以通过理解微透析探针及其周围的质量传递现象来解决。一种简单而可持续的分析质量传输的方法是使用计算模型。在本文中,一个数学框架,表示葡萄糖恢复从静态介质使用线性设计的微透析探针进行了描述。合理地选择了控制方程、边界条件和操作参数。用不同的扩散系数描述了质量在静止介质、半透膜和探针腔内的输运。随后,研究了一些确定的参数对总采收率的影响。利用扫描电镜成像技术研究微透析膜的物理特性,从而估算扩散系数值。讨论了不同扩散系数值对总采收率的影响。
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Mass Transport Analysis in Linear Microdialysis Probes Utilizing Structural Characterization Technique

Microdialysis is a separation technique widely used for sampling and monitoring purposes. Microdialysis requires a (microdialysis) probe to be inserted to the designated area of study. Separation procedure is completed by using a selective semi-permeable membrane attached to the microdialysis proe. Despite being a well-established technique, there are still issues regarding the performance of the microdialysis probe. The biggest issue is arguably that the concentration of solutes collected via microdialysis sampling represents only 20-30% of the original concentration from the sampling site. This issue can be resolved by understanding mass transport phenomena within the microdialysis probe and its surroundings. One straightforward, yet sustainable way to analyze mass transport is through the use of computational modelling. In this paper, a mathematical framework, representing glucose recovery from a quiescent media using a microdialysis probe of linear design was described. Governing equations, boundary conditions and operational parameters were justifiably selected. Different diffusion coefficients were used to describe the mass transport through the quiescent media, semi-permeable membrane and the probe's lumen. Subsequently, the influence of some identified parameters, on the overall recovery is examined. Scanning electron microscopy imaging was used to study the physical characteristics of the microdialysis membrane, thus being utilized to estimate the diffusion coefficient values. The impact of using different diffusion coefficient values on the overall recovery was also discussed.

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