基于Tcad仿真的分栅介电调制结高灵敏度分栅绝缘子减少Hfo2 TFET变化的设计与性能评估

Q4 Mathematics Philippine Statistician Pub Date : 2022-12-31 DOI:10.17762/msea.v71i4.1672
Rajkumar Mandal, Debasis Mukherjee
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引用次数: 0

摘要

最近在微生物学方面的一些发现使纳米生物分子的可靠鉴定和对它们的广泛分析成为必要。为了充分理解活细胞内发生的任何奇怪行为,必须发现和分析各种蛋白质,包括DNA、生物素-链亲和素、氨基酸以及许多类型的细菌和病毒。快速测试和检测是防止未被发现的生物危害消灭人类和其他陆地生物的必要步骤。几十年前,开发一种准确、价格合理的生物传感器一直是科学家们的难题。与昂贵的实验室传感器和检测方法相比,基于fet的实验室芯片纳米生物传感器似乎是一个很有前途的替代品。由于其尺寸,价格合理,功耗低,弹性,响应时间更快,灵敏度更高,因此比传统的批量传感器更可靠。由于其精度、适应性和与嵌入式系统的兼容性,具有纳米腔的介质调制FET生物传感器正在成为一个有前途的研究领域,可以产生有用的生物分析数据。作为传统掺杂ttfet器件的替代方案,使用电荷等离子体sige异质结双栅ttfet,可以生产无标签生物传感器,绕过对传统半导体的需求,传统半导体需要大量的热预算并且容易受到随机掺杂波动(RDFs)的影响。研究了介电常数(k)、正负电荷密度、栅极功函数和空腔尺寸的变化对生物传感器性能的影响,以更好地了解这些因素对生物传感器性能的影响。这些参数改变了生物传感器的电特性,提高了检测效率。还讨论了这些因素如何影响器件的漏极电流、电场、表面电位、亚阈值摆幅(SS)、绝缘体与金属膜(ION/IOFF)比和电子隧穿率(ETR)。并对漏极电流的灵敏度进行了研究。对于所提出的结构是否用于带电分子或中性分子没有限制。在较低的电源电压下,SG-DM电流JLFET的灵敏度很高,测量值为1.2 *10^3,电位灵敏度为1.4 V。结果表明,SG-DM [2] JLFET功耗小,灵敏度高,具有良好的应用潜力。
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Design and Performance Assessment of Split Gate Dielectric Modulated Junction less TFET Variation of Hfo2 by the Divided Gate Insulator for High Sensitivity Using Tcad Simulation
A number of more recent discoveries in microbiology have made reliable identification of nano-biomolecules and extensive analyses of them necessary. A variety of proteins, including DNA, biotin-streptavidin, amino acids, as well as many types of bacteria and viruses, must be found and analyzed in order to fully comprehend any odd behavior occurring inside of live cells. Rapid testing and detection are essential steps in preventing undiscovered biohazards from eradicating the human race and other terrestrial living things. Since many decades ago, developing an accurate, affordable biosensor has been a struggle for scientists [1]. When compared to pricey laboratory-based sensors and detection methods, FET-based lab-on-chip nano biosensors appear to be a promising substitute. It is significantly more dependable than conventional bulk sensors because of its size, affordability, low power consumption, resilience, faster response time, and better sensitivity [1]. Due to their precision, adaptability, and compatibility with embedded systems, dielectrically modulated FET biosensors with Nano cavities are emerging as a promising research area that can yield useful data on bio-analyses. As an alternative to conventionally doped TFET devices, using a charge plasma SiGe-heterojunction double gate TFET, a label-free biosensor can be produced, bypassing the need for conventional semiconductors, which require a large thermal budget and are susceptible to random dopant fluctuations (RDFs). The effect of changing the dielectric constant (k), the positive and negative charge density, the gate work function, and the cavity size has been investigated to better understand how these factors affect the performance of the proposed biosensor. These parameters modify the biosensor's electric characteristics, improving detection [2]. There is also discussion of how these factors influence the device's drain current, electric field, surface potential, sub-threshold swing (SS), insulator-to-metal film (ION/IOFF) ratio, and electron tunneling rate (ETR). The sensitivity of the drain current in the proposed biosensor is also investigated. There is no restriction on whether or whether the proposed structure is used for charged or neutral molecules.Under lower supply voltages, it is discovered that the SG-DM current JLFET's sensitivity is high, measuring 1.2 *10^3, with a potential sensitivity of 1.4 V. A result, the SG-DM [2] JLFET exhibits good application potential while consuming little power and having ahigh sensitivity.
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来源期刊
Philippine Statistician
Philippine Statistician Mathematics-Statistics and Probability
CiteScore
0.50
自引率
0.00%
发文量
92
期刊介绍: The Journal aims to provide a media for the dissemination of research by statisticians and researchers using statistical method in resolving their research problems. While a broad spectrum of topics will be entertained, those with original contribution to the statistical science or those that illustrates novel applications of statistics in solving real-life problems will be prioritized. The scope includes, but is not limited to the following topics:  Official Statistics  Computational Statistics  Simulation Studies  Mathematical Statistics  Survey Sampling  Statistics Education  Time Series Analysis  Biostatistics  Nonparametric Methods  Experimental Designs and Analysis  Econometric Theory and Applications  Other Applications
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