Veronica Sberveglieri

Dr. Veronica Sberveglieri

CNR-IBBR Via Madonna del Piano 10, Sesto Fiorentino, Firenze, Italy
orcid

Research Focus & Metrics

Academic Career Length

18Years (2009-Present)

(Calculated once Scilit publication data is synced: current year − year of first publication + 1)

Representative Publications

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29 March 2017 in Sensors
Verified
Journal Article
Open access
PDF file
Andrea PonzoniAndrea Ponzoni
Andrea Ponzoni
CBCamilla Baratto
Camilla Baratto
NCNicola Cattabiani
Nicola Cattabiani
MFMatteo Falasconi
Matteo Falasconi
Vardan GalstyanVardan Galstyan
Vardan Galstyan
Dario ZappaDario Zappa
Dario Zappa
This work reports the recent results achieved at the SENSOR Lab, Brescia (Italy) to address the selectivity of metal oxide based gas sensors. In particular, two main strategies are being developed for this purpose: (i) investigating different sensing mechanisms featuring different response spectra that may be potentially integrated in a single device; (ii) exploiting the electronic nose (EN) approach. The former has been addressed only recently and activities are mainly focused on determining the most suitable configuration and measurements to exploit the novel mechanism. Devices suitable to exploit optical (photoluminescence), magnetic (magneto-optical Kerr effect) and surface ionization in addition to the traditional chemiresistor device are here discussed together with the sensing performance measured so far. The electronic nose is a much more consolidated technology, and results are shown concerning its suitability to respond to industrial and societal needs in the fields of food quality control and detection of microbial activity in human sweat.

1 March 2013 in Sensors and Actuators B: Chemical
Verified
Journal Article
Closed access
Elisabetta CominiElisabetta Comini
Elisabetta Comini
CBCamilla Baratto
Camilla Baratto
ICIsabella Concina
Isabella Concina
Guido FagliaGuido Faglia
Guido Faglia
MFMatteo Falasconi
Matteo Falasconi
Giorgio SberveglieriGiorgio Sberveglieri
Giorgio Sberveglieri

14 April 2018 in Chemosensors
Verified
Journal Article
Open access
PDF file
Vardan GalstyanVardan Galstyan
Vardan Galstyan
MBManohar Prasad Bhandari
Manohar Prasad Bhandari
Veronica SberveglieriVeronica Sberveglieri
Veronica Sberveglieri
Giorgio SberveglieriGiorgio Sberveglieri
Giorgio Sberveglieri
Elisabetta CominiElisabetta Comini
Elisabetta Comini
Metal oxide materials have been applied in different fields due to their excellent functional properties. Metal oxides nanostructuration, preparation with the various morphologies, and their coupling with other structures enhance the unique properties of the materials and open new perspectives for their application in the food industry. Chemical gas sensors that are based on semiconducting metal oxide materials can detect the presence of toxins and volatile organic compounds that are produced in food products due to their spoilage and hazardous processes that may take place during the food aging and transportation. Metal oxide nanomaterials can be used in food processing, packaging, and the preservation industry as well. Moreover, the metal oxide-based nanocomposite structures can provide many advantageous features to the final food packaging material, such as antimicrobial activity, enzyme immobilization, oxygen scavenging, mechanical strength, increasing the stability and the shelf life of food, and securing the food against humidity, temperature, and other physiological factors. In this paper, we review the most recent achievements on the synthesis of metal oxide-based nanostructures and their applications in food quality monitoring and active and intelligent packaging.

12 December 2012 in Sensors
Verified
Journal Article
Open access
PDF file
Andrea PonzoniAndrea Ponzoni
Andrea Ponzoni
Elisabetta CominiElisabetta Comini
Elisabetta Comini
ICIsabella Concina
Isabella Concina
Matteo FerroniMatteo Ferroni
Matteo Ferroni
MFMatteo Falasconi
Matteo Falasconi
Giorgio SberveglieriGiorgio Sberveglieri
Giorgio Sberveglieri
In this work we report on metal oxide (MOX) based gas sensors, presenting the work done at the SENSOR laboratory of the CNR-IDASC and University of Brescia, Italy since the 80s up to the latest results achieved in recent times. In particular we report the strategies followed at SENSOR during these 30 years to increase the performance of MOX sensors through the development of different preparation techniques, from Rheotaxial Growth Thermal Oxidation (RGTO) to nanowire technology to address sensitivity and stability, and the development of electronic nose systems and pattern recognition techniques to address selectivity. We will show the obtained achievement in the context of selected applications such as safety and security and food quality control.

1 February 2015 in Sensors and Actuators B: Chemical
Verified
Journal Article
Closed access
EGEmanuela Gobbi
Emanuela Gobbi
MFMatteo Falasconi
Matteo Falasconi
GZGiulia Zambotti
Giulia Zambotti
Veronica SberveglieriVeronica Sberveglieri
Veronica Sberveglieri
Andrea PulvirentiAndrea Pulvirenti
Andrea Pulvirenti
Giorgio SberveglieriGiorgio Sberveglieri
Giorgio Sberveglieri

26 April 2012 in IEEE Sensors Journal
Verified
Journal Article
Closed access
ICIsabella Concina
Isabella Concina
MFMatteo Falasconi
Matteo Falasconi
Veronica SberveglieriVeronica Sberveglieri
Veronica Sberveglieri
This paper presents three different applications of an electronic nose (EN) based on a metal oxide sensor array, in order to illustrate the broad spectrum of potential uses of the technique in food quality control. The following scenarios are considered: 1) the screening of a typical error that may occur during the processing of tomato pulp, which leads to sensory damage of the product; 2) the detection of microbial contamination by Alicyclobacillus spp. (ACB) affecting soft drinks; and 3) the proof of evidence of extra virgin olive oil fraudulently adulterated with hazelnut oil. In each case, the EN is able to identify the spoiled product by means of the alterations in the pattern of volatile compounds, reconstructed by principal component analysis of the sensor responses.