用于 PCR 应用的基于模型的频率自适应微波加热技术

IF 3 Q2 ENGINEERING, ELECTRICAL & ELECTRONIC IEEE Journal of Electromagnetics RF and Microwaves in Medicine and Biology Pub Date : 2024-04-11 DOI:10.1109/JERM.2024.3383225
Matko Martinic;Dominique Schreurs;Tomislav Markovic;Bart Nauwelaers
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引用次数: 0

摘要

聚合酶链式反应(PCR)技术广泛应用于各种学科,主要是生物学和医学,已成为过去 100 年中最重要的发现之一。然而,市售 PCR 仪器的主要缺点是热循环速度慢。另一方面,快速高效的微波(MW)加热为大幅缩短 PCR 实验所需时间提供了可行的解决方案。在这项研究中,我们采用了互补分环谐振器(CSRR),将其与容积为 5.4 美元/毫升的微流体结构相结合,用作频率约为 3.75 GHz 的微波加热器。由此产生的装置具有极佳的温度均匀性,加热和冷却速率分别高达 19 美元/秒和 18.6 美元/秒。此外,还研究了基于模型的频率自适应兆瓦加热,其基础是在兆瓦加热过程中由于样品温度升高而产生的最佳加热频率偏移,与固定频率加热相比,应用功率降低了 1.2 W,加热效率提高了 8%。
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Model-Based Frequency Adaptive Microwave Heating for PCR Applications
With widespread applications in a variety of disciplines, mainly biology and medicine, Polymerase Chain Reaction (PCR) technology has established itself as one of the most significant discoveries of the last 100 years. However, the primary drawback of commercially available PCR instruments is their slow thermal cycling. On the other hand, rapid and efficient microwave (MW) heating offers a viable solution to drastically decrease the time needed for PCR experiments. In this study, we utilize a Complementary Split Ring Resonator (CSRR), operating as a microwave heater at around 3.75 GHz when combined with a microfluidic structure with a 5.4 $\mu$ l volume. The resulting device exhibits excellent temperature uniformity with high heating and cooling rates of 19 $^\circ$ C/s and 18.6 $^\circ$ C/s, respectively. Furthermore, model-based frequency-adaptive MW heating was investigated based on optimal heating frequency shift due to the temperature increase of the sample during MW heating, yielding 1.2 W lower applied power and an 8% higher heating efficiency when compared to fixed-frequency heating.
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来源期刊
CiteScore
5.80
自引率
9.40%
发文量
58
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Front Cover Table of Contents IEEE Journal of Electromagnetics, RF, and Microwaves in Medicine and Biology About this Journal IEEE Journal of Electromagnetics, RF and Microwaves in Medicine and Biology Publication Information Models of Melanoma Growth for Assessment of Microwave-Based Diagnostic Tools
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