Project Description: The aim of this research is the development of EIS methods for the non-destructive estimation of fruit quality evolution during its on-plant and post-harvest ripening. The project focuses on three interconnected research areas:
► The development of a handheld impedance analyzer, with a focus on the size and cost reduction and on the enhancement of the portability of the system, to obtain on-field measurements comparable with the commercially available bench-top instruments.
► The development of custom-made, biocompatible and non-destructive contact electrodes using a combination of printing techniques (i.e. spray coating, screen printing, dispense printing, etc…) on flexible and stretchable substrates (PET, Kapton, PDMS, Fabric).
► The analysis of the impedance output, in terms of its general evolution, influence of the frequency range and the fitting on equivalent circuits. Furthermore, the application of machine learning algorithms for the correlation of the fruit quality parameters with the impedance data will be evaluated.
Project Description: The project aims at the development of low-cost electrochemical biosensor for the detection of food toxicants (Mycotoxin, Heavy Metals and Antibiotic residuals) from food products. It mainly involves the following activities:
► Development of electrochemical, ion-selective membrane and molecularly imprinted polymer based biosensors.
► Detection of mycotoxin (AFM1 and OTA), heavy metal and antibiotic residuals from different food sources on a real-time basis.
► Low and improved limit of detection, high sensitivity and selectivity due to use of specific antibodies and selective membrane using nanomaterials.
Project Description: The aim of this research is interfacing biology and electronics, in order to develop low-cost printed biosensors for fast detection of food-borne hazards. This project focuses on detection and quantification of biogenic amines, as their presence in food constitutes a potential public health concern due to their physiological and toxicological effects.
Biosensors, fabricated with printing techniques (such as screen printing, inkjet printing, dispense printing, 3D printing) on mechanically flexible substrates, functionalized with nanoparticles (such as carbon nanotubes, silver nanoparticles etc.) and immobilized with antibodies for specific detection are promising analytical tools for fast and low-cost analysis. Furthermore, selectivity, reproducibility, mechanical and time stability need to be evaluated to be able to implement biosensors in the food safety analysis and moving toward industrial-scale manufacturing.
Main research areas includes:
► Flexible and printed biosensor
► Simultaneous detection of food hazards
Project Description: Currently food waste is a major problem (30% of all food produced is wasted) and 50% of this waste is produced when the food is packed. This waste is mainly due to the oxidation of lipids and proteins and microbial spoilage. During the food spoilage, the food starts releasing gases (NH3, TMA, and DMA). By detecting the presence of these three gases we can detect the spoilage at the initial stage when the food is still consumable. Therefore, if we want to reduce the food waste, we have to increase the shelf-life of food products by reducing the spoilage rate (oxidation and microbial spoilage), thus reducing these two phenomena is mandatory. In order to achieve this:
► We will develop a gas sensor array for NH3, TMA, and DMA detection which will monitor the headspace of the packaging and coat the inner-side of the package with smart materials incorporated with antioxidant and antimicrobial agents.
► Then when the presence of the analyte is detected the sensor will send an electrical signal to the smart materials.
► Under the electrical stimulation induced by the sensor the volatile agents loaded inside will be realized and stops or reduce the spoilage rate of the food.
In this way the sensor and the smart materials they work together in a closed system and extend the shelf life of the food product as long as possible.
Project Description: The aim of this research project, conducted in collaboration with the researchers of the Center of Materials and Microsystem (CMM) at Fondazione Bruno Kessler (FBK), is to develop a flexible and printed gas, temperature and humidity sensor employing different printing techniques suitable for the deposition on flexible substrates, and to finally build a flexible printed sensors array. Different prototypes of the sensors will be developed and characterized, focusing on metal oxide (MOx)-coated carbon nanotubes (CNTs) as a sensing material. The sensing material is deposited on microheaters developed at FBK in Trento using spray deposition, whereas the CNTs are coated with the MOx using magnetron sputtering. The sensitivity of different materials and preparations will be studied in relation to sensitivity to different gases.
Project Description: This Ph.D. thesis project aims at fabricating carbon nanotube-based field-effect transistor (CNTFET) biosensors on flexible substrates to detect typical additives used in industrial beverages and wine. In particular, CNTFETs will be first designed and fabricated using different deposition techniques and patterning steps. Subsequently, to develop biosensors sensitive to the abovementioned analytes, selective and specific enzymes will be immobilized and used to react with the analytes. Characterization of material morphology and electrical performance will be observed on both CNTFETs and CNTFET-based biosensors. As a final goal of the project, a CNTFET biosensor array will be developed to monitor the different additives at the same time on a real-time basis. This biosensor array will help to detect all these carcinogenic additives with low detection limit, allowing broad-range employment in the field of food quality monitoring in the beverage sectors.
Project Description: The human gut microbiota produces a great number of metabolites including gases such as H2, CH4, NH3 and CO2. The real-time monitoring of the presence and concentration of these gases along the different regions of the human Gastrointestinal (GI) tract is a potential assessment tool to correlate and understand the effects of different phenomena inside our body, including the effect of different diets, the development of food products, the use of prebiotic and probiotics on the microbial community activity and composition.
► To fabricate and test a single CNT gas sensor under a chamber control conditions
► To fabricate and test an array of CNT-based gas sensor under a chamber control condition and in a single SHIME bioreactor
► To evaluate the performance of the array CNT-based gas sensor on a SHIME experimental setup
Project Description: Single-Photon Avalanche Diodes (SPAD) are one of the most promising Si-based optical sensors for their low-cost mass production, small size, low power consumption and low working bias. By contrary, SPADs have low sensitivity to long-wavelength photons (>Near-IR), limiting their possible applications. In this research project, conducted in collaboration with the researchers of the Center of Materials and Microsystem (CMM) at Fondazione Bruno Kessler (FBK) in Trento, to overcome this problem is suggested to couple a Si-based SPAD with a metallic nano-grating supporting Surface Plasmon Polaritons (SPPs). Therefore, confining incident photons in the superficial layer of the device, increasing the absorption probability. The project is composed of three parts:
► Simulation of different nano-grating structure
► Production in clean rooms laboratories of the optimal structure on a SPAD
► Electro-optical characterization to evaluate the enhancement
Project Description: The recent achievements in flexible electronics have made it possible to integrate the modular sensors and actuators in the form of smart wearables. The applications of such smart wearables vary from controlling (prosthetics) to monitoring (vital signs) purpose. The use of smart wearables has been discussed in sports and rescuing activities. The issue with such smart wearables is its energy requirement. While batteries can limit the duration of working, we need to find out the ways to make the wearable self-sufficient on its energy needs. This project in collaboration with EURAC Research is mainly focused to develop flexible and integrate-able energy harvesting and energy storing devices. This will be done by performing the following tasks:
► Developing an energy harvesting device based on Triboelectric phenomenon
► Energy storing devices based on flexible super-capacitors
► Integrating the devices with sensors in a smart wearable
Project Description: Precision Agriculture is a concept of Smart Farm Management, in order to increase crop yield and reduce the environmental impacts, primarily cause by over-fertilization and over-flooding. Currently, Normalized Difference Vegetation Index (NDVI) mapping is a key tool for Precision Agriculture, due to its ability to provide information about the rate of vegetation. Nevertheless, state-of-the-art NDVI maps do not allow visualization of soil areas based on pH and irregular distribution of nutrients across the land. Therefore farmers can detect crop stress only based on the rate of vegetation, but they can’t quickly diagnose whether stress is due to pests or low levels of soil nutrients. This is why the primary aim of this PhD project is to develop a low-cost wireless sensors system. To develop a complete sensors system (which will consist of PH, Moisture, Humidity and NPK sensors ) below mentioned points will be considered:
► Biodegradable material as a substrate will be utilized for the sake of preventing negative environmental impacts.
► The interdigitated electrode (IDEs) structure will be simulated in COMSOL Multiphysics while the antenna designing & simulation will be done in CST Microwave studio for energy harvesting and communication.
► For sensors fabrication, inkjet and screen printing techniques will be used.
Project Description: Over the past few years, wearable technology has emerged as a major component of the lifestyle and fitness markets, mostly in the form of smart bands and smartwatches. Nevertheless, state-of-the-art measurement systems for the evaluation of athletic performance still rely on bulky and cumbersome instrumentation. Being part of the “STEX” project, in collaboration with Microgate Srl, this PhD project is aimed at the design, fabrication and characterization of real-time wearable solutions to monitor the muscles’ activity, to provide immediate feedback to the athlete about their physiological status. Three approaches will be pursued: monitoring of the respiratory rate using strain sensors, analysis of sweat using biochemical sensors and analysis of the gas emitted from the skin using gas sensors. Such sensors will be fabricated combining conventional microfabrication technologies and printing techniques, in the form of low-cost, non-invasive, sensitive and selective sensing platforms that will be ultimately integrated in textiles and garments.
The main parts of the project will be:
► Design and characterization of the sensors in laboratory environment
► Integration of such sensors in wearable platforms
► Validation of the wearable platforms through human trials in real-life situations
Project Description: The interest of the agri-food sector for a non-destructive and rapid technique for monitoring food quality and safety is increasing and electrical impedance spectroscopy (EIS) has shown great potential in this direction. The aim of this project development is a portable, real-time and low-cost EIS method to assess and manage critical variables in food manufacturing processes and in storage context.
The project consists of following steps:
► To correlate the impedance response to fruit quality parameters and fruit changes using a commercial benchtop impedance analyzer
► To improve an already existing portable, real-time and low-cost prototype EIS-based glove for the evaluation of fruit quality, fabricated using flexible spray-coated electrodes, to allow noninvasive assessment of critical variables in field and during storage
► Application of statistical methods and machine learning for a more accurate evaluation of impedance spectroscopy parameters
► To correlate the impedance response of others food matrices to quality parameters using a commercial benchtop impedance analyzer.