Dataset Information

Random telegraph noise from resonant tunnelling at low temperatures.

ABSTRACT: The Random Telegraph Noise (RTN) in an advanced Metal-Oxide-Semiconductor Field-Effect Transistor (MOSFET) is considered to be triggered by just one electron or one hole, and its importance is recognised upon the aggressive scaling. However, the detailed nature of the charge trap remains to be investigated due to the difficulty to find out the exact device, which shows the RTN feature over statistical variations. Here, we show the RTN can be observed from virtually all devices at low temperatures, and provide a methodology to enable a systematic way to identify the bias conditions to observe the RTN. We found that the RTN was observed at the verge of the Coulomb blockade in the stability diagram of a parasitic Single-Hole-Transistor (SHT), and we have successfully identified the locations of the charge traps by measuring the bias dependence of the RTN.

SUBMITTER: Li Z

PROVIDER: S-EPMC5762822 | biostudies-other | 2018 Jan

REPOSITORIES: biostudies-other

ACCESS DATA

Publications

Random telegraph noise from resonant tunnelling at low temperatures.

Li Zuo Z Sotto Moïse M Liu Fayong F Husain Muhammad Khaled MK Yoshimoto Hiroyuki H Sasago Yoshitaka Y Hisamoto Digh D Tomita Isao I Tsuchiya Yoshishige Y Saito Shinichi S

Scientific reports 20180110 1

The Random Telegraph Noise (RTN) in an advanced Metal-Oxide-Semiconductor Field-Effect Transistor (MOSFET) is considered to be triggered by just one electron or one hole, and its importance is recognised upon the aggressive scaling. However, the detailed nature of the charge trap remains to be investigated due to the difficulty to find out the exact device, which shows the RTN feature over statistical variations. Here, we show the RTN can be observed from virtually all devices at low temperature ...[more]

PMID: 29321552

Similar Datasets

Project description:Evolution requires phenotypic variation in a population of organisms for selection to function. Gene regulatory processes involved in organismal development affect the phenotypic diversity of organisms. Since only a fraction of all possible phenotypes are predicted to be accessed by the end of development, organisms may evolve strategies to use environmental cues and noise-like fluctuations to produce additional phenotypic diversity, and hence to enhance the speed of adaptation. We used a generic model of organismal development --gene regulatory networks-- to investigate how different levels of noise on gene expression states (i.e. phenotypes) may affect access to new, unique phenotypes, thereby affecting phenotypic diversity. We studied additional strategies that organisms might adopt to attain larger phenotypic diversity: either by augmenting their genome or the number of gene expression states. This was done for different types of gene regulatory networks that allow for distinct levels of regulatory influence on gene expression or are more likely to give rise to stable phenotypes. We found that if gene expression is binary, increasing noise levels generally decreases phenotype accessibility for all network types studied. If more gene expression states are considered, noise can moderately enhance the speed of discovery if three or four gene expression states are allowed, and if there are enough distinct regulatory networks in the population. These results were independent of the network types analyzed, and were robust to different implementations of noise. Hence, for noise to increase the number of accessible phenotypes in gene regulatory networks, very specific conditions need to be satisfied. If the number of distinct regulatory networks involved in organismal development is large enough, and the acquisition of more genes or fine tuning of their expression states proves costly to the organism, noise can be useful in allowing access to more unique phenotypes.

Dataset Information

Random telegraph noise from resonant tunnelling at low temperatures.

Publications

Random telegraph noise from resonant tunnelling at low temperatures.

Similar Datasets

OmicsDI is part of the ELIXIR infrastructure

Tweets