A thermalization energy analysis of the threshold voltage shift in amorphous indium gallium zinc oxide thin film transistors under simultaneous negative gate bias and illumination

It has been previously observed that thin film transistors (TFTs) utilizing an amorphous indium gallium zinc oxide (a-IGZO) semiconducting channel suffer from a threshold voltage shift when subjected to a negative gate bias and light illumination simultaneously. In this work, a thermalization energy analysis has been applied to previously-published data on negative bias under illumination stress (NBIS) in a-IGZO TFTs. A barrier to defect conversion is extracted of 0.65 – 0.75 eV, which is consistent with reported energies of oxygen vacancy migration. The attempt-to-escape frequency is extracted to be 106 – 107 s–1 which suggests a weak localization of carriers in band tail states over a 20 – 40 nm distance. Models for the NBIS mechanism based on charge trapping are reviewed and a defect pool model is proposed in which two distinct distributions of defect states exist in the a-IGZO band gap: these are associated with states that are formed as neutrally charged and 2+ charged oxygen vacancies at the time of film formation. In this model, threshold voltage shift is not due to a defect creation process, but to a change in the energy distribution of states in the band gap upon defect migration as this allows a state formed as a neutrally charged vacancy to be converted into one formed as a 2+ charged vacancy and vice versa. Carrier localization close to the defect migration site is necessary for the conversion process to take place, and such defect migration sites are associated with conduction and valence band tail states. Under negative gate bias stressing, the conduction band tail is depleted of carriers, but the bias is insufficient to accumulate holes in the valence band tail states, and so no threshold voltage shift results. It is only under illumination that the quasi Fermi level for holes is sufficiently lowered to allow occupation of valence band tail states. The resulting charge localization then allows a negative threshold voltage shift, but only under conditions of simultaneous negative gate bias and illumination, as observed experimentally as the NBIS effect.This work was supported by the European Community’s 7th Framework Programme under grant agreement NMP3-LA-2010-246334.Copyright 2014 American Institute of Physics. This article may be downloaded for personal use only. Any other use requires prior permission of the author and the American Institute of Physics

Gene therapy restores vision in rd1 mice after removal of a confounding mutation in Gpr179

The rd1 mouse with a mutation in the Pde6b gene was the first strain of mice identified with a retinal degeneration. However, AAV-mediated gene supplementation of rd1 mice only results in structural preservation of photoreceptors, and restoration of the photoreceptor-mediated a-wave, but not in restoration of the bipolar cell-mediated b-wave. Here we show that a mutation in Gpr179 prevents the full restoration of vision in rd1 mice. Backcrossing rd1 with C57BL6 mice reveals the complete lack of b-wave in a subset of mice, consistent with an autosomal recessive Mendelian inheritance pattern. We identify a mutation in the Gpr179 gene, which encodes for a G-protein coupled receptor localized to the dendrites of ON-bipolar cells. Gene replacement in rd1 mice that are devoid of the mutation in Gpr179 successfully restores the function of both photoreceptors and bipolar cells, which is maintained for up to 13 months. Our discovery may explain the failure of previous gene therapy attempts in rd1 mice, and we propose that Grp179 mutation status should be taken into account in future studies involving rd1 mice

A thermalization energy analysis of the threshold voltage shift in amorphous indium gallium zinc oxide thin film transistors under positive gate bias stress

Thin film transistors (TFTs) employing an amorphous indium gallium zinc oxide (a-IGZO) channel layer exhibit a positive shift in the threshold voltage under the application of positive gate bias stress (PBS). The time and temperature dependence of the threshold voltage shift was measured and analysed using the thermalization energy concept. The peak energy barrier to defect conversion is extracted to be 0.75 eV and the attempt-to-escape frequency is extracted to be 107 s−1. These values are in remarkable agreement with measurements in a-IGZO TFTs under negative gate bias illumination stress (NBIS) reported recently (Flewitt and Powell, J. Appl. Phys. 115, 134501 (2014)). This suggests that the same physical process is responsible for both PBS and NBIS, and supports the oxygen vacancy defect migration model that the authors have previously proposed.The research leading to these results has received funding from the European Community’s 7th Framework Programme under grant agreement NMP3-LA-2010-246334. Financial support of the European Commission is therefore gratefully acknowledged. The work has also received funding from FEDER through the COMPETE 2020 Programme and National Funds through FCT–Portuguese Foundation for Science and Technology under the Project No. UID/CTM/50025/2013.This is the author accepted manuscript. The final version is available from AIP Publishing via http://dx.doi.org/10.1063/1.494324

Robust artificial neural networks and outlier detection. Technical report

Large outliers break down linear and nonlinear regression models. Robust regression methods allow one to filter out the outliers when building a model. By replacing the traditional least squares criterion with the least trimmed squares criterion, in which half of data is treated as potential outliers, one can fit accurate regression models to strongly contaminated data. High-breakdown methods have become very well established in linear regression, but have started being applied for non-linear regression only recently. In this work, we examine the problem of fitting artificial neural networks to contaminated data using least trimmed squares criterion. We introduce a penalized least trimmed squares criterion which prevents unnecessary removal of valid data. Training of ANNs leads to a challenging non-smooth global optimization problem. We compare the efficiency of several derivative-free optimization methods in solving it, and show that our approach identifies the outliers correctly when ANNs are used for nonlinear regression

UK Immunotherapy Study: reanalysis by a combined symptom and medication score

Reanalysis of UK22 subcutaneous immunotherapy trial according to WAO/EAACI recommendations revealed clinically relevant improvements at both doses. Starting at the lower dose should enable efficacy with lower risk of adverse events