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Lithium-oxygen batteries, with their very high energy density (3500 Wh kg -1 ), could represent a real breakthrough in the envisioned strategies towards more efficient energy storage solutions for a less and less carbonated energy mix. However, the problems associated with this technology are numerous. A first one is linked to the high reactivity of the lithium metal anode, while a second one is linked to the highly oxidative environment created by the cell's O 2 saturation. Keeping in mind the necessity for greener materials in future energy storage solutions, in this work an innovative lithium protective membrane is prepared based on chitosan, a polysaccharide obtained from the deacetylation reaction of chitin. Chitosan was methacrylated through a simple, one-step reaction in water and then cross-linked by UV-induced radical polymerization. The obtained membranes were successively activated in liquid electrolyte and used as a lithium protection layer. The cells prepared with protected lithium were able to reach a higher full discharge capacity, and the chitosan's ability to slow down degradation processes was verified by post-mortem analyses. Moreover, in long cycling conditions, the protected lithium cell performed more than 40 cycles at 0.1 mA cm -2 , at a fixed capacity of 0.5 mAh cm -2 , retaining 100% coulombic efficiency, which is more than twice the lifespan of the bare lithium cell.

Every year millions of people worldwide undergo surgical interventions, with the occurrence of mild or severe post-treatment consequences meaning that rehabilitation plays a key role in modern medicine. Considering the cases of burns and plastic surgery, the pressing need for new materials that can be used for wound patches or body fillers and are able to sustain tissue regeneration and promote cell adhesion and proliferation is clear. The challenges facing next-generation implant materials also include the need for improved structural properties for cellular organization and morphogenic guidance together with optimal mechanical, rheological, and topographical behavior. Herein, we propose for the first time a sodium alginate hydrogel obtained by a thiol-yne reaction, easily synthesized using carbodiimide chemistry in a two-step reaction. The hydrogels were formed in all cases within a few minutes of light irradiation, showing good self-standing properties under solicitation. The mechanical, rheological, topographical, and swelling properties of the gels were also tested and reported. Lastly, no cytotoxicity was detected among the hydrogels. Soluble extracts in culture media allowed cell proliferation, and no differences between samples were detected in terms of metabolic activity and DNA content. These results suggest the potential use of these cytocompatible hydrogels in tissue engineering and regenerative medicine.

In this study, new photocurable biobased hydrogels deriving from chitosan and gelatin are designed and tested as sorbents for As(V) and Pb(II) removal from water. Those renewable materials were modified by a simple methacrylation reaction in order to make them light processable. The success of the reaction was evaluated by both 1 H-NMR and FTIR spectroscopy. The reactivity of those formulations was subsequently investigated by a real-time photorheology test. The obtained hydrogels showed high swelling capability reaching up to 1200% in the case of methacrylated gelatin (GelMA). Subsequently, the Z-potential of the methacrylated chitosan (MCH) and GelMA was measured to correlate their electrostatic surface characteristics with their adsorption properties for As(V) and Pb(II). The pH of the solutions proved to have a huge influence on the As(V) and Pb(II) adsorption capacity of the obtained hydrogels. Furthermore, the effect of As(V) and Pb(II) initial concentration and contact time on the adsorption capability of MCH and GelMA were investigated and discussed. The MCH and GelMA hydrogels demonstrated to be promising sorbents for the removal of heavy metals from polluted waters.

Even if still at an early stage of development, non-invasive continuous glucose monitoring (NI-CGM) sensors represent a promising technology for optimizing diabetes therapy. Recent studies showed that the Multisensor provides useful information about glucose dynamics with a mean absolute relative difference (MARD) of 35.4% in a fully prospective setting. Here we propose a method that, exploiting the same Multisensor measurements, but in a retrospective setting, achieves a much better accuracy. Data acquired by the Multisensor during a long-term study are retrospectively processed following a two-step procedure. First, the raw data are transformed to a blood glucose (BG) estimate by a multiple linear regression model. Then, an enhancing module is applied in cascade to the regression model to improve the accuracy of the glucose estimation by retrofitting available BG references through a time-varying linear model. MARD between the retrospectively reconstructed BG time-series and reference values is 20%. Here, 94% of values fall in zone A or B of the Clarke Error Grid. The proposed algorithm achieved a level of accuracy that could make this device a potential complementary tool for diabetes management and also for guiding prediabetic or nondiabetic users through life-style changes.

In diabetes research, non-invasive continuous glucose monitoring (NI-CGM) devices represent a new and appealing frontier. In the last years, some multi-sensor devices for NI-CGM have been proposed, which exploit several sensors measuring phenomena of different nature, not only for measuring glucose related signals, but also signals reflecting some possible perturbing processes (temperature, blood perfusion). Estimation of glucose levels is then obtained combining these signals through a mathematical model which requires an initial calibration step exploiting one reference blood glucose (RBG) sample. Even if promising results have been obtained, especially in hospitalized volunteers, at present the temporal accuracy of NI-CGM sensors may suffer because of environmental and physiological interferences. The aim of this work is to develop a general methodology, based on Monte Carlo (MC) simulation, to assess the robustness of the calibration step used by NI-CGM devices against these disturbances. The proposed methodology is illustrated considering two examples: the first concerns the possible detrimental influence of sweat events, while the second deals with calibration scheduling. For implementing both examples, 45 datasets collected by the Solianis Multisensor system are considered. In the first example, the MC methodology suggests that no further calibration adjustments are needed after the occurrence of sweat events, because the "Multisensor+model" system is able to deal with the disturbance. The second case study shows how to identify the best time interval to update the model's calibration for improving the accuracy of the estimated glucose. The methodology proposed in this work is of general applicability and can be helpful in making those incremental steps in NI-CGM devices development needed to further improve their performance.

Monitoring glucose concentration in the blood is essential in the therapy of diabetes, a pathology which affects about 350 million people around the World (three million in Italy), causes more than four million deaths per year and consumes a significant portion of the budget of national health systems (10% in Italy). In the last 15 years, several sensors with different degree of invasiveness have been proposed to monitor glycemia in a quasi-continuous way (up to 1 sample/min rate) for relatively long intervals (up to 7 consecutive days). These continuous glucose monitoring (CGM) sensors have opened new scenarios to assess, off-line, the effectiveness of individual patient therapeutic plans from the retrospective analysis of glucose time-series, but have also stimulated the development of innovative on-line applications, such as hypo/hyper-glycemia alert systems and artificial pancreas closed-loop control algorithms. In this review, we illustrate some significant Italian contributions, both from industry and academia, to the growth of the CGM sensors research area. In particular, technological, algorithmic and clinical developments performed in Italy will be discussed and put in relation with the advances obtained in the field in the wider international research community.