Ultra conformable and multimodal tactile sensors based on organic field-effect transistors

Cognitive psychology is the branch of psychology related to all the processes by which sensory input is transformed, processed and used. Academic and industrial research has always invested time and resources to develop devices capable to simulate the behavior of the organs where the perceptions are located. In recent years, in fact, there have been numerous discoveries related to new materials, and new devices, capable of reproducing, in a reliable manner, the sensory behavior of humans. Particular interest in scientific research has been aimed at understanding and reproducing of man's tactile sensations. It is known that, through the receptors of the skin, it is possible to detect sensations such as pain, changes in pressure and/or temperature. The development of tactile sensor technology had a significant increase in the last years of 1970s, thanks to the important surveys of Stojiljkovic, Harmon and Lumelsky who presented the firsts prototype of sensors for artificial skin applications, and summarized the main characteristics and requirements of tactile sensors. Recently, organic electronics has been deeply investigated as technology for the fabrication of tactile sensors using biocompatible materials, which can be deposited and processed on ultra flexible and ultra conformable substrates. In general, the most attractive property of these materials is mainly related to their high mechanical flexibility, which is mandatory for artificial skin applications. The main object of this PhD research activity was the development and optimization of an innovative technology for the realization of physical sensors able to detect pressure and temperature variations, which can be applied in the field of biomedical engineering and biorobotics. By exploiting the particular characteristics of the employed materials, such as mechanical flexibility, the proposed sensors are very suitable to be integrated with flexible structures (for example plastics) as a pressure and temperature sensor, and therefore, ideal for the realization of an artificial skin like. In Chapter 1, the basics of humans somatosensory system will be introduced: after a brief description of tactile thermoreceptors, mechanoreceptors and nociceptors, a definition of electronic skin and its characteristics will be provided. In Chapter 2, a wide analysis of the state of the art will be reported. Several and different examples of tactile sensor (in inorganic and organic technology) will be presented, underlining advantages and disadvantages for each approach. In Chapter 3, the firsts experimental results, obtained in the first part of my PhD program, will be presented. All the steps of the fabrication process of the devices will be described, as well as the measurement setup used for the electrical characterization of the sensors. In Chapter 4, the sensor structure optimization will be presented. It will be demonstrated how the presented devices are able to sense simultaneously thermal and mechanical stimuli. Moreover, it will be demonstrated that, thanks to an alternative and innovative fabrication process, the sensors can be transferred directly on skin, thus proving the suitability of the proposed sensor architecture for tactile applications

Time- and frequency-resolved fluorescence with a single TCSPC detector via a Fourier-transform approach

We introduce a broadband single-pixel spectro-temporal fluorescence detector, combining time-correlated single photon counting (TCSPC) with Fourier transform (FT) spectroscopy. A birefringent common-path interferometer (CPI) generates two time-delayed replicas of the sample’s fluorescence. Via FT of their interference signal at the detector, we obtain a two-dimensional map of the fluorescence as a function of detection wavelength and emission time, with high temporal and spectral resolution. Our instrument is remarkably simple, as it only requires the addition of a CPI to a standard single-pixel TCSPC system, and it shows a readily adjustable spectral resolution with inherently broad bandwidth coverag

Time- and frequency-resolved fluorescence with a single TCSPC detector via a Fourier-transform approach

We introduce a broadband single-pixel spectro-temporal fluorescence detector, combining time-correlated single photon counting (TCSPC) with Fourier transform (FT) spectroscopy. A birefringent common-path interferometer (CPI) generates two time-delayed replicas of the sample's fluorescence. Via FT of their interference signal at the detector, we obtain a two-dimensional map of the fluorescence as a function of detection wavelength and emission time, with high temporal and spectral resolution. Our instrument is remarkably simple, as it only requires the addition of a CPI to a standard single-pixel TCSPC system, and it shows a readily adjustable spectral resolution with inherently broad bandwidth coverage

Correction: Printed, cost-effective and stable poly(3-hexylthiophene) electrolyte-gated field-effect transistors

Correction for 'Printed, cost-effective and stable poly(3-hexylthiophene) electrolyte-gated field-effect transistors' by Davide Blasi et al., J. Mater. Chem. C, 2020, DOI: 10.1039/d0tc03342a

Chitosan gated organic transistors printed on ethyl cellulose as a versatile platform for edible electronics and bioelectronics

Edible electronics is an emerging research field targeting electronic devices that can be safely ingested and directly digested or metabolized by the human body. As such, it paves the way to a whole new family of applications, ranging from ingestible medical devices and biosensors, to smart labelling for food quality monitoring and anti-counterfeiting. Being a newborn research field, many challenges need to be addressed to realize fully edible electronic components. In particular, an extended library of edible electronic materials is required, with suitable electronic properties depending on the target device and compatible with large-area printing processes, to allow scalable and cost-effective manufacturing. In this work, we propose a platform for future low-voltage edible transistors and circuits that comprises an edible chitosan gating medium and inkjet printed inert gold electrodes, compatible with low thermal budget edible substrates, such as ethylcellulose. We report the compatibility of the platform, characterized by critical channel features as low as 10 µm, with different inkjet printed carbon-based semiconductors, including biocompatible polymers present in the picograms range per device. A complementary organic inverter is also demonstrated with the same platform as a proof-of-principle logic gate. The presented results offer a promising approach to future low-voltage edible active circuitry, as well as a testbed for non-toxic printable semiconductors

A Single-Molecule Bioelectronic Portable Array for Early Diagnosis of Pancreatic Cancer Precursors

A cohort of 47 patients is screened for pancreatic cancer precursors with a portable 96-well bioelectronic sensing-array for single-molecule assay in cysts fluid and blood plasma, deployable at point-of-care (POC). Pancreatic cancer precursors are mucinous cysts diagnosed with a sensitivity of at most 80% by state-of-the-art cytopathological molecular analyses (e.g., KRASmut DNA). Adding the simultaneous assay of proteins related to malignant transformation (e.g., MUC1 and CD55) is deemed essential to enhance diagnostic accuracy. The bioelectronic array proposed here, based on single-molecule-with-a-large-transistor (SiMoT) technology, can assay both nucleic acids and proteins at the single-molecule limit-of-identification (LOI) (1% of false-positives and false-negatives). It comprises an enzyme-linked immunosorbent assay (ELISA)-like 8 × 12-array organic-electronics disposable cartridge with an electrolyte-gated organic transistor sensor array, and a reusable reader, integrating a custom Si-IC chip, operating via software installed on a USB-connected smart device. The cartridge is complemented by a 3D-printed sensing gate cover plate. KRASmut, MUC1, and CD55 biomarkers either in plasma or cysts-fluid from 5 to 6 patients at a time, are multiplexed at single-molecule LOI in 1.5 h. The pancreatic cancer precursors are classified via a machine-learning analysis resulting in at least 96% diagnostic-sensitivity and 100% diagnostic-specificity. This preliminary study opens the way to POC liquid-biopsy-based early diagnosis of pancreatic-cancer precursors in plasma.</p

A Single-Molecule Bioelectronic Portable Array for Early Diagnosis of Pancreatic Cancer Precursors

A cohort of 47 patients is screened for pancreatic cancer precursors with a portable 96-well bioelectronic sensing-array for single-molecule assay in cysts fluid and blood plasma, deployable at point-of-care (POC). Pancreatic cancer precursors are mucinous cysts diagnosed with a sensitivity of at most 80% by state-of-the-art cytopathological molecular analyses (e.g., KRASmut DNA). Adding the simultaneous assay of proteins related to malignant transformation (e.g., MUC1 and CD55) is deemed essential to enhance diagnostic accuracy. The bioelectronic array proposed here, based on single-molecule-with-a-large-transistor (SiMoT) technology, can assay both nucleic acids and proteins at the single-molecule limit-of-identification (LOI) (1% of false-positives and false-negatives). It comprises an enzyme-linked immunosorbent assay (ELISA)-like 8 × 12-array organic-electronics disposable cartridge with an electrolyte-gated organic transistor sensor array, and a reusable reader, integrating a custom Si-IC chip, operating via software installed on a USB-connected smart device. The cartridge is complemented by a 3D-printed sensing gate cover plate. KRASmut, MUC1, and CD55 biomarkers either in plasma or cysts-fluid from 5 to 6 patients at a time, are multiplexed at single-molecule LOI in 1.5 h. The pancreatic cancer precursors are classified via a machine-learning analysis resulting in at least 96% diagnostic-sensitivity and 100% diagnostic-specificity. This preliminary study opens the way to POC liquid-biopsy-based early diagnosis of pancreatic-cancer precursors in plasma.</p

NEMO-SN1 Abyssal Cabled Observatory in the Western Ionian Sea

The NEutrinoMediterranean Observatory—Submarine Network 1 (NEMO-SN1) seafloor observatory is located in the central Mediterranean Sea, Western Ionian Sea, off Eastern Sicily (Southern Italy) at 2100-m water depth, 25 km from the harbor of the city of Catania. It is a prototype of a cabled deep-sea multiparameter observatory and the first one operating with real-time data transmission in Europe since 2005. NEMO-SN1 is also the first-established node of the European Multidisciplinary Seafloor Observatory (EMSO), one of the incoming European large-scale research infrastructures included in the Roadmap of the European Strategy Forum on Research Infrastructures (ESFRI) since 2006. EMSO will specifically address long-term monitoring of environmental processes related to marine ecosystems, marine mammals, climate change, and geohazards

Event reconstruction for KM3NeT/ORCA using convolutional neural networks

The KM3NeT research infrastructure is currently under construction at two locations in the Mediterranean Sea. The KM3NeT/ORCA water-Cherenkov neutrino detector off the French coast will instrument several megatons of seawater with photosensors. Its main objective is the determination of the neutrino mass ordering. This work aims at demonstrating the general applicability of deep convolutional neural networks to neutrino telescopes, using simulated datasets for the KM3NeT/ORCA detector as an example. To this end, the networks are employed to achieve reconstruction and classification tasks that constitute an alternative to the analysis pipeline presented for KM3NeT/ORCA in the KM3NeT Letter of Intent. They are used to infer event reconstruction estimates for the energy, the direction, and the interaction point of incident neutrinos. The spatial distribution of Cherenkov light generated by charged particles induced in neutrino interactions is classified as shower- or track-like, and the main background processes associated with the detection of atmospheric neutrinos are recognized. Performance comparisons to machine-learning classification and maximum-likelihood reconstruction algorithms previously developed for KM3NeT/ORCA are provided. It is shown that this application of deep convolutional neural networks to simulated datasets for a large-volume neutrino telescope yields competitive reconstruction results and performance improvements with respect to classical approaches

Event reconstruction for KM3NeT/ORCA using convolutional neural networks

The KM3NeT research infrastructure is currently under construction at two locations in the Mediterranean Sea. The KM3NeT/ORCA water-Cherenkov neutrino de tector off the French coast will instrument several megatons of seawater with photosensors. Its main objective is the determination of the neutrino mass ordering. This work aims at demonstrating the general applicability of deep convolutional neural networks to neutrino telescopes, using simulated datasets for the KM3NeT/ORCA detector as an example. To this end, the networks are employed to achieve reconstruction and classification tasks that constitute an alternative to the analysis pipeline presented for KM3NeT/ORCA in the KM3NeT Letter of Intent. They are used to infer event reconstruction estimates for the energy, the direction, and the interaction point of incident neutrinos. The spatial distribution of Cherenkov light generated by charged particles induced in neutrino interactions is classified as shower-or track-like, and the main background processes associated with the detection of atmospheric neutrinos are recognized. Performance comparisons to machine-learning classification and maximum-likelihood reconstruction algorithms previously developed for KM3NeT/ORCA are provided. It is shown that this application of deep convolutional neural networks to simulated datasets for a large-volume neutrino telescope yields competitive reconstruction results and performance improvements with respect to classical approaches