Istituto Nazionale di Ricerca Metrologica
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Stability study and uncertainty evaluation of CO2 certified reference materials for greenhouse gases monitoring
Full text linkThe continuous rising in the concentration of carbon dioxide (CO2) in the atmosphere is one of the main causes of
the increase in the greenhouse effect and global warming. To monitor the alarming scenario and to provide
Governments and decision makers with reliable emission data, gaseous certified reference materials (CRMs) at
atmospheric CO2 amount fraction are needed. This paper describes two independent metrological traceability
paths established at INRiM for the preparation of this kind of CRMs. The aim of this publication is to show a
method for evaluating the uncertainty associated with CRM stability and to demonstrate that there is no significant
trend in the results over time. Such CRMs are produced as an intermediate step towards the development
of novel generation CRMs certified also for the isotopic composition
The measurand in ISO GPS verification
Full text linkA clear definition of the measurand is an essential precondition for measuring. When verifying conformity to ISO GPS tolerances (verification), the measurand is often unclear, particularly for geometrical tolerances. The tolerance zone is a portion of space whereas the measurand is a scalar quantity, and many such quantities may be derived from the same portion of space.
We propose a unified derivation of the measurand in ISO GPS verification matching the designer’s intent. Different types of tolerances are considered, from the easiest to the least obvious as to the derivation of the measurand
A Bayesian statistical method for large-scale MEMS-based sensors calibration: a case study on 100 digital accelerometers
Full text linkLow-cost sensors and in particular micro-electro-mechanical systems (MEMS) devices are widely used in many applications, including consumer electronics, healthcare, automotive, and industrial automation. Their large-scale production (typically in the order of millions per week in a single factory) would require the calibration of a huge number of devices that would be costly and time-consuming. A solution can be found in the use of statistical methods in order to (at least partially) substitute for the typical calibration procedures. In this work, we propose a Bayesian method to statistically calibrate large batches of sensors using probabilistic models and prior knowledge. The method involves experimentally calibrating only a small sample of sensors, then infer the number of reliable sensors in the entire batch and assign an appropriate uncertainty to all the sensors. Therefore, it can be considered as a statistical calibration of the batch. The Bayesian nature of this approach allows reducing the number of experimental calibrations by incorporating the prior knowledge coming from the previous calibration of a 'benchmark' batch, which is performed 'once and for all' and is representative of the whole production process. The application and validation of the method are performed through the calibration of 100 digital MEMS accelerometers. Validation results showed an acceptable agreement between experimental-based bootstrap and theoretical values, with relative differences within +/- 7%
Data for: Analysis of spin-squeezing generation in cavity-coupled atomic ensembles with continuous measurements
No full textInfluence of coil geometry, supply conditions and nanoparticle heating properties on magnetic hyperthermia in mouse models
Full text linkFor in vivo magnetic hyperthermia tests, which are typically conducted on small animal models, one of the objectives is the design of alternating current (AC) magnetic field applicators able to guarantee an effective activation of magnetic nanoparticles (MNPs). During therapy application, it is critical to optimize heat deposition due to MNPs and minimize side effects in healthy tissues. For an accurate treatment planning, it is required to carefully select the geometry of the applicator coils and their location with respect to the body, as a function of the position and size of the tumour target region. Additionally, one should preliminary estimate the impact of experimental conditions on the MNP heating efficiency and thus on their capability to induce a temperature increase in tissues. Biophysical constraints have also to be taken into account in the choice of AC magnetic field parameters (frequency and amplitude), to avoid eddy current effects as much as possible. In this study, we present realistic simulations of preclinical tests on a mouse model, evaluating thermal response under various experimental conditions. We investigate different field applicator configurations, including helical, Helmholtz and pancake coils, while also analysing the role of the amplitude and frequency of the supply current, as well as of the type and administered dose of MNPs. The temperature increase in tissues, resulting from the heating effects due to AC magnetic field exposure and MNP activation, is calculated by means of in-house finite element models that solve the low -frequency electromagnetic field problem and the bioheat transfer equation. This in silico approach, which is applicable to any type of field applicators and MNPs, has been demonstrated to provide useful insights for the optimization of in vivo experiments, enabling the design of safer and more effective treatments
Arctic metrology: case study for air temperature measurements at Ny-Ålesund, Svalbard
Full text linkEmerging Spatiotemporal Dynamics in Multiterminal Neuromorphic Nanowire Networks Through Conductance Matrices and Voltage Maps
No full textSelf-organizing memristive nanowire (NW) networks are promising candidates for neuromorphic-type data processing in a physical reservoir computing framework because of their collective emergent behavior, which enables spatiotemporal signal processing. However, understanding emergent dynamics in multiterminal networks remains challenging. Here experimental spatiotemporal characterization of memristive NW networks dynamics in multiterminal configuration is reported, analyzing the activation and relaxation of network's global and local conductance, as well as the inherent spatial nonlinear transformation capabilities. Emergent effects are analyzed i) during activation, by investigating the spatiotemporal dynamics of the electric field distribution across the network through voltage mapping; ii) during relaxation, by monitoring the evolution of the conductance matrix of the multiterminal system. The multiterminal approach also allowed monitoring the spatial distribution of nonlinear activity, demonstrating the impact of different network areas on the system's information processing capabilities. Nonlinear transformation tasks are experimentally performed by driving the network into different conductive states, demonstrating the importance of selecting proper operating conditions for efficient information processing. This work allows a better understanding of the local nonlinear dynamics in NW networks and their impact on the information processing capabilities, providing new insights for a rational design of self-organizing neuromorphic systems
Quantification of PFAS in rice and maize: Validation of a UHPLC-HRMS/MS isotopic dilution approach in support to food safety
Full text link: In the present work, an analytical method for the quantification of per and poly fluoroalkyl substances (PFAS) in rice and maize has been developed and then validated with a metrological approach. PFAS are a group of human-made chemicals used in a variety of industries and consumer products for their water- and grease-resistant properties. Studies have shown that PFAS can contaminate soil and water, and there is concern about their bioaccumulation in edible plants, fruits, and cereals. The presence of PFAS has been identified in rice and other food products, including maize, as indicated by studies and scientific literature. This is particularly alarming since some PFAS have been associated with adverse health effects and rice and maize account for over 20% of the annual food intake worldwide. Despite this evidence, the regulation currently in place is not covering cereal matrices and limits of quantification for matrices encompassed by the current legislation are defined for a small group of PFAS. In this study an UHPLC-HRMS/MS based method was validated, obtaining a LOQ (Limit Of Quantification) ranging between 2 ng/kg and 32 ng/kg and robustness in line with EU guidelines and recommendation for PFAS in food. Additionally, a metrological approach was employed to estimate the uncertainty budget, utilizing modeling and experimental methods, and comparing the outcomes, aiming to characterize with high accuracy PFAS in rice and maize and support control bodies to assess contamination in suspected areas. A comparison of uncertainty of different approaches was conducted after applying the method to 30 real samples
The project ‘Metrology for Static and Dynamic Characterization of Supercapacitors’ – MetSuperCap
No full textSupercapacitors (SCs) represent an environmentally friendly technology, that can replace batteries or work with them in high power density applications. To support the increasing use of SCs, accurate characterization is required also under operating conditions. In addition, validated circuital and software models are needed to identify the SCs behavior in dynamic applications. Along slower but highly accurate methods, novel quick, traceable, and effective measurement techniques are required to evaluate SCs State of Charge (SoC) and State of Health (SoH) and to promote the uptake of SCs in consumer electronics, energy, transport, aerospace and in many other applications. The MetSuperCap project aims to improve the characterization of SCs by providing an accurate identification of their parameters in the laboratory and under operational conditions
Detection Efficiency Characterization for Free-Space Single-Photon Detectors: Measurement Facility and Wavelength-Dependence Investigation
Full text linkIn this paper, we present an experimental apparatus for the measurement of the detection efficiency of free-space single-photon detectors based on the substitution method. We extend the analysis to account for the wavelength dependence introduced by the transmissivity of the optical window in front of the detector's active area. Our method involves measuring the detector's response at different wavelengths and comparing it to a calibrated reference detector. This allows us to accurately quantify the efficiency variations due to the optical window's transmissivity. The results provide a comprehensive understanding of the wavelength-dependent efficiency, which is crucial for optimizing the performance of single-photon detectors in various applications, including quantum communication and photonics research. This characterization technique offers a significant advancement in the precision and reliability of single-photon detection efficiency measurements