R&D Paths of Pixel Detectors for Vertex Tracking and Radiation Imaging

This report reviews current trends in the R&D of semiconductor pixellated sensors for vertex tracking and radiation imaging. It identifies requirements of future HEP experiments at colliders, needed technological breakthroughs and highlights the relation to radiation detection and imaging applications in other fields of science.Comment: 17 pages, 2 figures, submitted to the European Strategy Preparatory Grou

Photovoltaic technologies

Photovoltaics is already a billion dollar industry. It is experiencing rapid growth as concerns over fuel supplies and carbon emissions mean that governments and individuals are increasingly prepared to ignore its current high costs. It will become truly mainstream when its costs are comparable to other energy sources. At the moment, it is around four times too expensive for competitive commercial production. Three generations of photovoltaics have been envisaged that will take solar power into the mainstream. Currently, photovoltaic production is 90% first-generation and is based on silicon wafers. These devices are reliable and durable, but half of the cost is the silicon wafer and efficiencies are limited to around 20%. A second generation of solar cells would use cheap semiconductor thin films deposited on low-cost substrates to produce devices of slightly lower efficiency. A number of thin-film device technologies account for around 5–6% of the current market. As second-generation technology reduces the cost of active material, the substrate will eventually be the cost limit and higher efficiency will be needed to maintain the cost-reduction trend. Third-generation devices will use new technologies to produce high-efficiency devices. Advances in nanotechnology, photonics, optical metamaterials, plasmonics and semiconducting polymer sciences offer the prospect of cost-competitive photovoltaics. It is reasonable to expect that cost reductions, a move to second-generation technologies and the implementation of new technologies and third-generation concepts can lead to fully cost- competitive solar energy in 10–15 years

OXIDATION OF SILICON - THE VLSI GATE DIELECTRIC

Silicon dominates the semiconductor industry for good reasons. One factor is the stable, easily formed, insulating oxide, which aids high performance and allows practical processing. How well can these virtues survive as new demands are made on integrity, on smallness of feature sizes and other dimensions, and on constraints on processing and manufacturing methods? These demands make it critical to identify, quantify and predict the key controlling growth and defect processes on an atomic scale.The combination of theory and novel experiments (isotope methods, electronic noise, spin resonance, pulsed laser atom probes and other desorption methods, and especially scanning tunnelling or atomic force microscopies) provide tools whose impact on models is just being appreciated. We discuss the current unified model for silicon oxidation, which goes beyond the traditional descriptions of kinetic and ellipsometric data by explicitly addressing the issues raised in isotope experiments. The framework is still the Deal-Grove model, which provides a phenomenology to describe the major regimes of behaviour, and gives a base from which the substantial deviations can be characterized. In this model, growth is limited by diffusion and interfacial reactions operating in series. The deviations from Deal-Grove are most significant for just those first tens of atomic layers of oxide which are critical for the ultra-thin oxide layers now demanded. Several features emerge as important. First is the role of stress and stress relaxation. Second is the nature of the oxide closest to the Si, both its defects and its differences from the amorphous stoichiometric oxide further out, whether in composition, in network topology, or otherwise. Thirdly, we must consider the charge states of both fixed and mobile species. In thin films with very different dielectric constants, image terms can be important; these terms affect interpretation of spectroscopies, the injection of oxidant species and relative defect stabilities. This has added importance now that P-b concentrations have been correlated with interfacial stress. This raises further issues about the perfection of the oxide random network and the incorporation of interstitial species like molecular oxygen.Finally, the roles of contamination, particles, metals, hydrocarbons etc are important, as is interface roughness. These features depend on pre-gate oxide cleaning and define the Si surface that is to be oxidized which may have an influence on the features listed above

Recent Progress on 3D Silicon Detectors

3D silicon detectors, in which the electrodes penetrate the sensor bulk perpendicular to the surface, have recently undergone a rapid development from R\&D over industrialisation to their first installation in a real high-energy-physics experiment. Since June 2015, the ATLAS Insertable B-Layer is taking first collision data with 3D pixel detectors. At the same time, preparations are advancing to install 3D pixel detectors in forward trackers such as the ATLAS Forward Proton detector or the CMS-TOTEM Proton Precision Spectrometer. For those experiments, the main requirements are a slim edge and the ability to cope with non-uniform irradiation. Both have been shown to be fulfilled by 3D pixel detectors. For the High-Luminosity LHC pixel upgrades of the major experiments, 3D detectors are promising candidates for the innermost pixel layers to cope with harsh radiation environments up to fluences of $2\times10^{16}$\,n$_{eq}$/cm$^2$ thanks to their excellent radiation hardness at low operational voltages and power dissipation as well as moderate temperatures. This paper will give an overview on the recent developments of 3D detectors related to the projects mentioned above and the future plans.Comment: Proceedings of the 24th International Workshop on Vertex Detectors, 1-5 June 2015, Santa Fe, US

Scalable Microfabrication Procedures for Adhesive-Integrated Flexible and Stretchable Electronic Sensors.

New classes of ultrathin flexible and stretchable devices have changed the way modern electronics are designed to interact with their target systems. Though more and more novel technologies surface and steer the way we think about future electronics, there exists an unmet need in regards to optimizing the fabrication procedures for these devices so that large-scale industrial translation is realistic. This article presents an unconventional approach for facile microfabrication and processing of adhesive-peeled (AP) flexible sensors. By assembling AP sensors on a weakly-adhering substrate in an inverted fashion, we demonstrate a procedure with 50% reduced end-to-end processing time that achieves greater levels of fabrication yield. The methodology is used to demonstrate the fabrication of electrical and mechanical flexible and stretchable AP sensors that are peeled-off their carrier substrates by consumer adhesives. In using this approach, we outline the manner by which adhesion is maintained and buckling is reduced for gold film processing on polydimethylsiloxane substrates. In addition, we demonstrate the compatibility of our methodology with large-scale post-processing using a roll-to-roll approach

On-the-fly Data Assessment for High Throughput X-ray Diffraction Measurement

Investment in brighter sources and larger and faster detectors has accelerated the speed of data acquisition at national user facilities. The accelerated data acquisition offers many opportunities for discovery of new materials, but it also presents a daunting challenge. The rate of data acquisition far exceeds the current speed of data quality assessment, resulting in less than optimal data and data coverage, which in extreme cases forces recollection of data. Herein, we show how this challenge can be addressed through development of an approach that makes routine data assessment automatic and instantaneous. Through extracting and visualizing customized attributes in real time, data quality and coverage, as well as other scientifically relevant information contained in large datasets is highlighted. Deployment of such an approach not only improves the quality of data but also helps optimize usage of expensive characterization resources by prioritizing measurements of highest scientific impact. We anticipate our approach to become a starting point for a sophisticated decision-tree that optimizes data quality and maximizes scientific content in real time through automation. With these efforts to integrate more automation in data collection and analysis, we can truly take advantage of the accelerating speed of data acquisition