Characterisation of AMS H35 HV-CMOS monolithic active pixel sensor prototypes for HEP applications

Monolithic active pixel sensors produced in High Voltage CMOS (HV-CMOS) technology are being considered for High Energy Physics applications due to the ease of production and the reduced costs. Such technology is especially appealing when large areas to be covered and material budget are concerned. This is the case of the outermost pixel layers of the future ATLAS tracking detector for the HL-LHC. For experiments at hadron colliders, radiation hardness is a key requirement which is not fulfilled by standard CMOS sensor designs that collect charge by diffusion. This issue has been addressed by depleted active pixel sensors in which electronics are embedded into a large deep implantation ensuring uniform charge collection by drift. Very first small prototypes of hybrid depleted active pixel sensors have already shown a radiation hardness compatible with the ATLAS requirements. Nevertheless, to compete with the present hybrid solutions a further reduction in costs achievable by a fully monolithic design is desirable. The H35DEMO is a large electrode full reticle demonstrator chip produced in AMS 350 nm HV-CMOS technology by the collaboration of Karlsruher Institut f\"ur Technologie (KIT), Institut de F\'isica d'Altes Energies (IFAE), University of Liverpool and University of Geneva. It includes two large monolithic pixel matrices which can be operated standalone. One of these two matrices has been characterised at beam test before and after irradiation with protons and neutrons. Results demonstrated the feasibility of producing radiation hard large area fully monolithic pixel sensors in HV-CMOS technology. H35DEMO chips with a substrate resistivity of 200$\Omega$ cm irradiated with neutrons showed a radiation hardness up to a fluence of $10^{15}$n$_{eq}$cm$^{-2}$ with a hit efficiency of about 99% and a noise occupancy lower than $10^{-6}$ hits in a LHC bunch crossing of 25ns at 150V

Test beam measurement of the first prototype of the fast silicon pixel monolithic detector for the TT-PET project

The TT-PET collaboration is developing a PET scanner for small animals with 30 ps time-of-flight resolution and sub-millimetre 3D detection granularity. The sensitive element of the scanner is a monolithic silicon pixel detector based on state-of-the-art SiGe BiCMOS technology. The first ASIC prototype for the TT-PET was produced and tested in the laboratory and with minimum ionizing particles. The electronics exhibit an equivalent noise charge below 600 e- RMS and a pulse rise time of less than 2 ns, in accordance with the simulations. The pixels with a capacitance of 0.8 pF were measured to have a detection efficiency greater than 99% and, although in the absence of the post-processing, a time resolution of approximately 200 ps

Prototyping of an HV-CMOS demonstrator for the High Luminosity-LHC upgrade

HV-CMOS sensors can offer important advantages in terms of material budget, granularity and cost for large area tracking systems in high energy physics experiments. This article presents the design and simulated results of an HV-CMOS pixel demonstrator for the High Luminosity-LHC. The pixel demonstrator has been designed in the 0.35 μm HV-CMOS process from ams AG and submitted for fabrication through an engineering run. To improve the response of the sensor, different wafers with moderate to high substrate resistivities are used to fabricate the design. The prototype consists of four large analog and standalone matrices with several pixel flavours, which are all compatible for readout with the FE-I4 ASIC. Details about the matrices and the pixel flavours are provided in this article

New label-free methods for protein relative quantification applied to the investigation of an animal model of Huntington Disease

Spectral Counts approaches (SpCs) are largely employed for the comparison of protein expression profiles in label-free (LF) differential proteomics applications. Similarly, to other comparative methods, also SpCs based approaches require a normalization procedure before Fold Changes (FC) calculation. Here, we propose new Complexity Based Normalization (CBN) methods that introduced a variable adjustment factor (f), related to the complexity of the sample, both in terms of total number of identified proteins (CBN(P)) and as total number of spectral counts (CBN(S)). Both these new methods were compared with the Normalized Spectral Abundance Factor (NSAF) and the Spectral Counts log Ratio (Rsc), by using standard protein mixtures. Finally, to test the robustness and the effectiveness of the CBNs methods, they were employed for the comparative analysis of cortical protein extract from zQ175 mouse brains, model of Huntington Disease (HD), and control animals (raw data available via ProteomeXchange with identifier PXD017471). LF data were also validated by western blot and MRM based experiments. On standard mixtures, both CBN methods showed an excellent behavior in terms of reproducibility and coefficients of variation (CVs) in comparison to the other SpCs approaches. Overall, the CBN(P) method was demonstrated to be the most reliable and sensitive in detecting small differences in protein amounts when applied to biological samples

New label-free methods for protein relative quantification applied to the investigation of an animal model of Huntington Disease

Spectral Counts approaches (SpCs) are largely employed for the comparison of protein expression profiles in label-free (LF) differential proteomics applications. Similarly, to other comparative methods, also SpCs based approaches require a normalization procedure before Fold Changes (FC) calculation. Here, we propose new Complexity Based Normalization (CBN) methods that introduced a variable adjustment factor (f), related to the complexity of the sample, both in terms of total number of identified proteins (CBN(P)) and as total number of spectral counts (CBN(S)). Both these new methods were compared with the Normalized Spectral Abundance Factor (NSAF) and the Spectral Counts log Ratio (Rsc), by using standard protein mixtures. Finally, to test the robustness and the effectiveness of the CBNs methods, they were employed for the comparative analysis of cortical protein extract from zQ175 mouse brains, model of Huntington Disease (HD), and control animals (raw data available via ProteomeXchange with identifier PXD017471). LF data were also validated by western blot and MRM based experiments. On standard mixtures, both CBN methods showed an excellent behavior in terms of reproducibility and coefficients of variation (CVs) in comparison to the other SpCs approaches. Overall, the CBN(P) method was demonstrated to be the most reliable and sensitive in detecting small differences in protein amounts when applied to biological samples

Novel high-speed monolithic silicon detector for particle physics

This contribution presents simulation results, implementation, and first tests of a monolithic detector developed at KIT. It consists of a sensor diode tightly integrated with an analogue front-end based on SiGe (Silicon-Germanium) SG13G2 130 nm BiCMOS technology produced at the Leibniz Institute for High Performance Microelectronics (IHP). The pixel size is 100 μm × 100 μm, and the nwell charge collection node dimensions were reduced to 10 μm × 10 μm. We investigate the influence of this approach on sensor performance, spatial resolution via charge sharing and timing behaviour

A monolithic ASIC demonstrator for the Thin Time-of-Flight PET scanner

Time-of-flight measurement is an important advancement in PET scanners to improve image reconstruction with a lower delivered radiation dose. This article describes the monolithic ASIC for the TT-PET project, a novel idea for a high-precision PET scanner for small animals. The chip uses a SiGe Bi-CMOS process for timing measurements, integrating a fully-depleted pixel matrix with a low-power BJT-based front-end per channel, integrated on the same 100 µm thick die. The target timing resolution of the scanner is 30 ps RMS for electrons from the conversion of 511 keV photons. The system will include 1.6 million channels across almost 2000 different chips. A full-featured demonstrator chip with a 3×10 matrix of 500×500 µm2 pixels was fabricated to validate each block. Its design and experimental results are presented here. © 2019 CERN

Tourism income and economic growth in Greece: Empirical evidence from their cyclical components

This paper examines the relationship between the cyclical components of Greek GDP and international tourism income for Greece for the period 1976–2004. Using spectral analysis the authors find that cyclical fluctuations of GDP have a length of about nine years and that international tourism income has a cycle of about seven years. The volatility of tourism income is more than eight times the volatility of the Greek GDP cycle. VAR analysis shows that the cyclical component of tourism income is significantly influencing the cyclical component of GDP in Greece. The findings support the tourism-led economic growth hypothesis and are of particular interest and importance to policy makers, financial analysts and investors dealing with the Greek tourism industry