Low voltage thin film transistors based on solution-processed In2O3:W. A remarkably stable semiconductor under negative and positive bias stress

We have investigated solution-processed tungsten-doped crystalline indium oxide (In2O3:W) as a function of the W content and their implementation in TFTs also employing spray coated Y2O3 gate dielectrics, and gold source and drain contacts. We showed that tungsten doping practically has no effect on the optical band gap whereas it shifts up the Urbach tail energy of In2O3:W films. The TFT performance employing In2O3:W channels also seems to decline at high tungsten concentration. Negative and positive bias stress under (dark) ambient conditions of TFTs employing In2O3:W(0.1 at%) showed remarkable improvement in their stability characteristics compared to the un-doped ones. This is evidenced by significantly smaller changes of the threshold voltage and subthreshold swing with insignificant change of the electron mobility that was practically unaffected under negative bias voltage. The negative bias stress results were interpreted in terms of the higher W-O bond dissociation energy compared to that of In-O, and the consequent oxygen vacancy suppression. However the positive bias stability results in a reduced accumulation of electrons in the back channel due to atmospheric oxygen absorption. The results presented in this report demonstrate the potential for stable, low operational voltage, high performance metal oxide-based TFTs employing gate dielectrics also grown from solutions, at low manufacturing cost

A prototype telepresence robot for use in the investigation of ebola and lassa virus threatened villages in Nigeria

The article investigates the idea of low-cost, telepresence-based mobile robots for eventual use within villages and rural areas in Nigeria, where diseases such as the Ebola Virus Disease (EVD) and Lassa Haemorrhagic Fever (LHF) are common, yet human intervention is constrained due to the great risk of transmission through bodily fluids. To illustrate the concept and practical issues arising, a systems design approach is taken to identify some of the engineering requirements; and, in the focus of this article, a prototype has been developed at Lancaster University. The robotic device is semi-humanoid in that the upper half features two 7-DOF manipulators, designed in part to resemble human operation, while the lower half consists of a four-wheeled base, prioritising ease of operation and reliability over the flexibility offered by a leg-based system

Localising and identifying radionuclides via energy-resolved angular photon responses

A technique for the in-situ localisation of radioactivity is described whereby the energy-resolved angular photon response of a collimated inorganic scintillation detector is used to derive the spatial arrangement of a variety of radioactive source configurations. The influence of photon radiation (X- and γ ray) incident on the collimated detector is expressed mathematically, by way of a sinc transform embedded to a dynamic linear regression model, to increase the spatial accuracy of the localisation. This approach is tested experimentally with two pairs of like radionuclides, two pairs of different combinations of radionuclides and three different radionuclides to demonstrate its combined isotopic discrimination and spatial localisation capabilities. A fit based on the model referred to above is observed to reproduce the data for the combined X- and γ-ray regions of interest effectively. This allows for increased resolution via interpolation between the data which is observed to improve location accuracy significantly. This research is relevant to applications in autonomous robotic exploration tasks and for the characterisation of contaminated environments associated with nuclear legacies and radiological emergencies

Use of Gaussian process regression for radiation mapping of a nuclear reactor with a mobile robot

Collection and interpolation of radiation observations is of vital importance to support routine operations in the nuclear sector globally, as well as for completing surveys during crisis response. To reduce exposure to ionizing radiation that human workers can be subjected to during such surveys, there is a strong desire to utilise robotic systems. Previous approaches to interpolate measurements taken from nuclear facilities to reconstruct radiological maps of an environment cannot be applied accurately to data collected from a robotic survey as they are unable to cope well with irregularly spaced, noisy, low count data. In this work, a novel approach to interpolating radiation measurements collected from a robot is proposed that overcomes the problems associated with sparse and noisy measurements. The proposed method integrates an appropriate kernel, benchmarked against the radiation transport code MCNP6, into the Gaussian Process Regression technique. The suitability of the proposed technique is demonstrated through its application to data collected from a bespoke robotic system used to conduct a survey of the Joz̆ef Stefan Institute TRIGA Mark II nuclear reactor during steady state operation, where it is shown to successfully reconstruct gamma dosimetry estimates in the reactor hall and aid in identifying sources of ionizing radiation