An Ultra-Sensitive Biosensor to Investigate Random Telegraph Noise in Human Breast Cancer Cells

Breast cancer is a leading cause of death in women worldwide, and yet its pathophysiology is poorly understood. Although single-cell studies have highlighted the contribution of membrane depolarisation to the proliferation of breast cancer, dynamic signalling at a network level has not been extensively researched. It is urgent therefore to decode the intercellular signalling patterns linked to metastasis, particularly at a cell cohort level. This paper introduces a novel strategy for conducting such recordings on highly metastatic MDA-MB-231 cells, via an ultra-low noise biosensor based on a large electrode area which maximises the Helmholtz double-layer capacitance. The extracellular sensitivity of our biosensor allows the detection of pA-level random telegraph signal (RTS) noise superimposed with an omnipresent 1/f noise. The RTS noise is validated and modelled using a Markov chain. The analysis of slow cooperative potentials across the large area electrode suggests the involvement of cohort calcium signalling, and the 1/f noise analysis suggests a strong contribution of resting membrane noise. Overall, this work shows the potential of the new recording platform and statistical analysis for better understanding and predicting the underlying signalling mechanisms of metastatic breast cancer cells. In future, this platform could highlight the effects of compounds, or drugs, on the underlying activity of cancer cell cohorts in a clinical setting.

Effect of Interface Traps on the RTS Noise Behavior of Junctionless Nanowires

This work presents a study on the effects of single interface traps throughout the Junctionless Nanowire Transistor (JNT). The results are obtained by analyzing the Random Telegraph Signal noise of the device, which consists of an exception of the generation-recombination noise. The results obtained are mostly from numerical simulation, validated through experimental data. As in physical devices, it is impossible to obtain a single trap in specific locations, we have used a distribution of traps with similar characteristics in a way that they behave like a single trap. The results show the behave considering a set of traps distributions, using an exponential model. The traps are distributed from the conduction band to the valence band. Keywords– JNT; RTS Noise; G-r Noise; Interface Traps.

An Analysis of Random Telegraph Signal Noise in a Precise Analog Circuit

We analyzed the gain error issue and non-linearity issue of a precise Analog-to-Digital Converter (ADC) and found the root cause to be Random Telegraph Signal (RTS) noise in bipolar devices. The RTS noise produced nearly 1mV abrupt changes in a band-gap reference voltage, and affected ADC and other circuits where the reference voltage was used. We developed a new measurement method enabling us to detect RTS noise in bipolar with higher signal-to-noise ratio than traditional methods. We also developed an algorithm to extract RTS occurrence frequency and average magnitude. The RTS characterization capability has helped us invent a new bipolar structure and develop new processes to minimize RTS noise.

Investigation of 1/f Noise and Superimposed RTS Noise in Ti–Au/n-Type GaAs Schottky Barrier Diodes

Low frequency noise characteristics of Schottky diodes are investigated. Two noise components were found in experimental noise records: random telegraph signal (RTS), caused by burst noise, and 1/f Gaussian noise. The noise is sampled and recorded on a PC. Then, in addition to the spectrum, the probability density function (pdf) of the total noise is analyzed. In the case of the mixture of the burst noise and Gaussian (1/f) noise, the pdf has two maxima separated by a local minimum. Extraction of burst noise component from Gaussian noise background was performed using the pdf, standard signal detection theory, and advanced signal-processing techniques. It is concluded that the RTS noise and 1/f noise have different physical origins in Schottky diodes. The raw noise is split into two components. One appeared to be burst noise with a Lorentzian-like spectral shape. The other component is 1/f noise. Having extracted 1/f noise, we have studied the dependence of noise spectral values on the current across the diode.