Science, Technology and Innovation


Advanced Scientific Instrumentation

AdvSciInstExperimental particle physics and multidisciplinary experimental research frequently relies on scientific instrumentation with consistently increasing data collection capacities, with many channels operating at high working frequencies. This results in massive amounts of data: the Multidisciplinary Laboratory (MLab) specializes in developing new instruments and methods based on modern technology to efficiently and effectively deal with this extreme data production rate.
MLab research activity focused on the development of advanced scientific instrumentation for novel particle detectors and multidisciplinary experimental projects, including X-ray analytical instruments and techniques for cultural heritage and high channel count systems for electrophysiology.

Ongoing research
Advanced Instrumentation and Methods for Novel Particle Detectors

COMPASS Experiment at CERN

COMPASS Experiment at CERNMLab is currently participating in upgrading the data acquisition and processing system of the COMPASS spectrometer at CERN. Working with INFN Trieste and the Technical University of Munich (TUM), MLab develops systems to support COMPASS's experimental results on hadronic structure. In particular, the collaboration focuses on the development of a new generation of trigger-less data acquisition and real-time feature extraction architecture based on Field-Programmable Gate Array (FPGA) for the particle detectors of the "COMPASS Beyond 2020" experiment.

System-on-Chip based data acquisition platform

System-on-Chip based data acquisition platformMLab is involved in a research and development project on large area photon detection, using multi pattern gassous photomultipliers (MPGD). In collaboration with INFN Trieste, this project aims at developing a distributed network of HV systems for thick-GEM gaseous detectors of UV photons. As part of this project, a custom data acquisition board able to manage 8-bit data resolution at 500 MHz sampling rate has been designed and produced by MLab and INFN Trieste.

A replica of the system prototype developed at MLab has been given on loan to the University of San Carlos, Guatemala, where is being used as a data acquisition platform for high resolution time stamping in cosmic ray detection in the context of the Latin American Giant Observatory (LAGO) project.

High Performance X-Ray Spectroscopy

High Performance X-Ray SpectroscopyMLab is collaborating with INFN Trieste and ELETTRA on a project focusing on the development of novel solid-state detectors, based on silicon drift chamber technology for high-resolution spectroscopy of low-energy X-ray photons. This kind of silicon drift detector (SDD) provides spatial, timing, and spectroscopic information for applications in various fields such as soft X-ray astrophysics, environment monitoring, and advanced light sources (e.g. synchrotrons and free electron lasers).

The group has also contributed to the characterisation and testing of the XAFS Fluorescence Detector System based on 64 SDDs for the SESAME Synchrotron Light Source in Amman, Jordan to be completed and delivered to SESAME.

Ongoing research
Scientific Instrumentation for Multidisciplinary Experimental Research

HiCCE: High Channel Count for Electrophysiology

HiCCE: High Channel Count for ElectrophysiologyHigh-density electrophysiological instrumentation is gaining wider use in many fields, as a tool for investigating and understanding the workings of the brain. But the cost of this tool can be prohibitive for many laboratories, particularly in developing countries. HiCCE is an open-hardware and open-source project aimed at providing high-performance, low-cost research instrumentation for electrophysiology. As an Open Science project, all information and plans will be publicly available, as a resource for anyone to interested in related research questions, removing cost as a barrier to research.

SoC-FPGA Cluster Architecture for Supercomputing

SoC-FPGA Cluster Architecture for SupercomputingTechnologies that can compute large amounts of data in quickly without high power demands are in high demand, with standard computing facilities reaching their limits. Programmable Systems on Chip (SoC) technologies offer a way forward with the possibility of parallelising critical computing tasks at high processing speed, based on tightly interconnected FPGA fabrics with high-performance multi-core processors. Although systems based on this kind of complex devices can deliver a great number of computational services with low latency responses and high throughput online data processing, they are still difficult to exploit.

This research project is focused on new methodologies and hardware/software architectures for efficient implementation of clusters of SoC-FPGA for supercomputing of interest in both science and engineering. The research plan foresees hardware prototyping, FPGA design and software development.

Electromyography measurement system based on cEMG sensors and reconfigurable hardware

MLab is collaborating with the Department of Electrical, Electronic and Systems Engineering of the Universiti Kebangsaan Malaysia to develop a wireless capacitive electromyography (EMG) measurement system with reconfigurable hardware and digital filter in order to monitor muscle activity. The increasing number of people with musculoskeletal diseases, such as chronic lower back pain, myopathy, and fibromyalgia requires innovative monitoring and treatment concepts. Challenges for this project include designing a compact and low power consumption wireless cEMG sensor, small and compact power supply, high sampling rate and resolution filter module, high signal-to-noise ratio performance, and dynamic filtering capability.

Ongoing research
Nuclear Instrumentation in collaboration with IAEA NSIL

Nuclear instrumentation for radiation monitoring and digital pulse processing

Adv3The aim of the collaborative project is to develop a compact radiation monitor, spectrometer and multi-channel analyser based on novel detectors and modern FPGA technology.

The use of artificial neural networks in nuclear instrumentation such as the classification of the signal pulse shape for real time identification of ionizing particles will be explored. The project foresees the development of a hardware prototype based on FPGA-Multi-processor devices to be used as an experimental high-performance platform for training and optimization of machine learning based methods for nuclear applications.

X-ray instrumentation for spectrometry

NucThe aim of the collaborative project is to develop a transportable XRF and related techniques spectrometer and scanner for quantitative elemental analysis, and to meet most of the spatially resolved measurements needed for the characterization of cultural heritage objects and other kinds of samples.