Photoactive (supra)molecular devices in double layer membranes

Biological systems are complex and highly organized architectures governed by non-covalent interactions responsible for the regulation of essential tasks in all living organisms. These systems are a constant source of inspiration for supramolecular chemists aiming to design multicomponent molecular assemblies able to perform elaborated tasks, thanks to the role and action of the components that constitute them. Artificial supramolecular systems exploit non-covalent interactions to mimic naturally occurring events. In this context, stimuli-responsive supramolecular systems have attracted attention due to the possibility to control macroscopic effects through modifications at the nanoscale. This thesis is divided in three experimental chapters, characterized by a progressive increase in molecular complexity. Initially, the preparation and studies of liposomes functionalized with a photoactive guest such as azobenzene in the bilayer were tackled, in order to evaluate the effect of such photochrome on the vesicle properties. Subsequently, the synthesis and studies of thread-like molecules comprising an azobenzene functionality was reported. Such molecules were conceived to be intercalated in the bilayer membrane of liposomes with the aim to be used as components for photoresponsive transmembrane molecular pumps. Finally, a [3]rotaxane was developed and studied in solution. This system is composed of two crown ether rings interlocked with an axle containing three recognition sites for the macrocycles, i.e. two pH-switchable ammonium stations and a permanent triazolium station. Such molecule was designed to achieve a change in the ratio between the recognition sites and the crown ethers as a consequence of acid-base inputs. This leads to the formation of rotaxanes containing a number of recognition sites respectively larger, equal or lower than the number of interlocked rings and connected by a network of acid-base reactions.

Wireless solutions for the industrial internet of things

The fourth industrial revolution is paving the way for Industrial Internet of Things applications where industrial assets (e.g., robotic arms, valves, pistons) are equipped with a large number of wireless devices (i.e., microcontroller boards that embed sensors and actuators) to enable a plethora of new applications, such as analytics, diagnostics, monitoring, as well as supervisory, and safety control use-cases. Nevertheless, current wireless technologies, such as Wi-Fi, Bluetooth, and even private 5G networks, cannot fulfill all the requirements set up by the Industry 4.0 paradigm, thus opening up new 6G-oriented research trends, such as the use of THz frequencies. In light of the above, this thesis provides (i) a broad overview of the main use-cases, requirements, and key enabling wireless technologies foreseen by the fourth industrial revolution, and (ii) proposes innovative contributions, both theoretical and empirical, to enhance the performance of current and future wireless technologies at different levels of the protocol stack. In particular, at the physical layer, signal processing techniques are being exploited to analyze two multiplexing schemes, namely Affine Frequency Division Multiplexing and Orthogonal Chirp Division Multiplexing, which seem promising for high-frequency wireless communications. At the medium access layer, three protocols for intra-machine communications are proposed, where one is based on LoRa at 2.4 GHz and the others work in the THz band. Different scheduling algorithms for private industrial 5G networks are compared, and two main proposals are described, i.e., a decentralized scheme that leverages machine learning techniques to better address aperiodic traffic patterns, and a centralized contention-based design that serves a federated learning industrial application. Results are provided in terms of numerical evaluations, simulation results, and real-world experiments. Several improvements over the state-of-the-art were obtained, and the description of up-and-running testbeds demonstrates the feasibility of some of the theoretical concepts when considering a real industry plant.

On the motion planning & control of nonlinear robotic systems

In the last decades, we saw a soaring interest in autonomous robots boosted not only by academia and industry, but also by the ever in- creasing demand from civil users. As a matter of fact, autonomous robots are fast spreading in all aspects of human life, we can see them clean houses, navigate through city traffic, or harvest fruits and vegetables. Almost all commercial drones already exhibit unprecedented and sophisticated skills which makes them suitable for these applications, such as obstacle avoidance, simultaneous localisation and mapping, path planning, visual-inertial odometry, and object tracking. The major limitations of such robotic platforms lie in the limited payload that can carry, in their costs, and in the limited autonomy due to finite battery capability. For this reason researchers start to develop new algorithms able to run even on resource constrained platforms both in terms of computation capabilities and limited types of endowed sensors, focusing especially on very cheap sensors and hardware. The possibility to use a limited number of sensors allowed to scale a lot the UAVs size, while the implementation of new efficient algorithms, performing the same task in lower time, allows for lower autonomy. However, the developed robots are not mature enough to completely operate autonomously without human supervision due to still too big dimensions (especially for aerial vehicles), which make these platforms unsafe for humans, and the high probability of numerical, and decision, errors that robots may make. In this perspective, this thesis aims to review and improve the current state-of-the-art solutions for autonomous navigation from a purely practical point of view. In particular, we deeply focused on the problems of robot control, trajectory planning, environments exploration, and obstacle avoidance.

Chemiluminescence – based bioanalytical devices for astrobiological, food safety and clinical applications

At the intersection of biology, chemistry, and engineering, biosensors are a multidisciplinary innovation that provide a cost-effective alternative to traditional laboratory techniques. Due to their advantages, biosensors are used in medical diagnostics, environmental monitoring, food safety and many other fields. The first part of the thesis is concerned with learning the state of the art of paper-based immunosensors with bioluminescent (BL) and chemiluminescent (CL) detection. The use of biospecific assays combined with CL detection and paper-based technology offers an optimal approach to creating analytical tools for on-site applications and we have focused on the specific areas that need to be considered more in order to ensure a future practical implementation of these methods in routine analyses. The subsequent part of the thesis addresses the development of an autonomous lab-on-chip platform for performing chemiluminescent-based bioassays in space environment, exploiting a CubeSat platform for astrobiological investigations. An origami-inspired microfluidic paper-based analytical device has been developed with the purpose of assesses its performance in space and to evaluate its functionality and the resilience of the (bio)molecules when exposed to a radiation-rich environment. Subsequently, we designed a paper-based assay to detect traces of ovalbumin in food samples, creating a user-friendly immunosensing platform. To this purpose, we developed an origami device that exploits a competitive immunoassay coupled with chemiluminescence detection and magnetic microbeads used to immobilize ovalbumin on paper. Finally, with the aim of exploring the use of biomimetic materials, an hydrogel-based chemiluminescence biosensor for the detection of H2O2 and glucose was developed. A guanosine hydrogel was prepared and loaded with luminol and hemin, miming a DNAzyme activity. Subsequently, the hydrogel was modified by incorporating glucose oxidase enzyme to enable glucose biosensing. The emitted photons were detected using a portable device equipped with a smartphone's CMOS (complementary metal oxide semiconductor) camera for CL emission detection.

Graphene-based bioelectronic interfaces and devices and interpretative models targeting glial cells

Bioelectronic interfaces have significantly advanced in recent years, offering potential treatments for vision impairments, spinal cord injuries, and neurodegenerative diseases. However, the classical neurocentric vision drives the technological development toward neurons. Emerging evidence highlights the critical role of glial cells in the nervous system. Among them, astrocytes significantly influence neuronal networks throughout life and are implicated in several neuropathological states. Although they are incapable to fire action potentials, astrocytes communicate through diverse calcium (Ca2+) signalling pathways, crucial for cognitive functions and brain blood flow regulation. Current bioelectronic devices are primarily designed to interface neurons and are unsuitable for studying astrocytes. Graphene, with its unique electrical, mechanical and biocompatibility properties, has emerged as a promising neural interface material. However, its use as electrode interface to modulate astrocyte functionality remains unexplored. The aim of this PhD work was to exploit Graphene-oxide (GO) and reduced GO (rGO)-coated electrodes to control Ca2+ signalling in astrocytes by electrical stimulation. We discovered that distinct Ca2+dynamics in astrocytes can be evoked, in vitro and in brain slices, depending on the conductive/insulating properties of rGO/GO electrodes. Stimulation by rGO electrodes induces intracellular Ca2+ response with sharp peaks of oscillations (“P-type”), exclusively due to Ca2+ release from intracellular stores. Conversely, astrocytes stimulated by GO electrodes show slower and sustained Ca2+ response (“S-type”), largely mediated by external Ca2+ influx through specific ion channels. Astrocytes respond faster than neurons and activate distinct G-Protein Coupled Receptor intracellular signalling pathways. We propose a resistive/insulating model, hypothesizing that the different conductivity of the substrate influences the electric field at the cell/electrolyte or cell/material interfaces, favouring, respectively, the Ca2+ release from intracellular stores or the extracellular Ca2+ influx. This research provides a simple tool to selectively control distinct Ca2+ signals in brain astrocytes in neuroscience and bioelectronic medicine.