Mathematical Approximation for Quantifying Noise Level in Silicon- and Nonsilicon-Based Chips for DNA Detection

Abstract

The growing importance of DNA and RNA characterization through solid-state nanopores emphasizes the need for a comprehensive understanding of the principles that govern DNA and RNA detection. While semiconductors have been widely utilized in these studies, the fundamental rationale of designating them as the prime choice for DNA and RNA topology characterization remains unclear. This paper explores the electrical properties of semiconductor chips, metals, and insulators, elucidating specific features that make semiconductors conducive to detecting DNA and RNA translocation. Despite the conceptual simplicity of the detection mechanism, a notable drawback in these methodologies lies in the generation of unwanted noise caused by fluctuations in the ionic current, as recorded by the amplifier. This noise, stemming from statistical fluctuations in the signal itself, introduces discrepancies in enumerating molecules traversing the nanopore, hindering the accurate determination of the true topological characteristics of lengthy polymer molecules such as DNA. Efforts to mitigate noise generation by exploring the configuration of silicon-based membranes have been undertaken. However, despite these endeavors, a precise mathematical quantification of noise levels remains insufficiently explored. This work further investigates factors influencing noise reduction and compares theoretical and experimental noise levels. The primary objective of this study is to validate the precision of mathematical approximations for noise levels across a range of silicon-based chips, providing insights into the fundamental factors contributing to noise reduction. Ultimately, our investigation introduces alternative materials to semiconductors for nanopore fabrication. These materials are poised to enhance detection capacity by virtue of lower noise levels, presenting promising prospects for enhanced DNA and RNA characterization. Importantly, due to lower noise levels, these materials present an unprecedented opportunity for the realtime investigation of DNA and RNA topology. This eliminates the need for both data recording and the use of supplementary software to filter out the noise to detect the translocation event.