Valentina Margaria

Microwave-Assisted Synthesis of Reduced Graphene Oxide/SnO2 Nanocomposite for Oxygen Reduction Reaction in Microbial Fuel Cells

We report on an easy, fast, eco-friendly, and reliable method for the synthesis of reduced graphene oxide/SnO2 nanocomposite as cathode material for application in microbial fuel cells (MFCs). The material was prepared starting from graphene oxide that has been reduced to graphene during the hydrothermal synthesis of the nanocomposite, carried out in a microwave system. Structural and morphological characterizations evidenced the formation of nanocomposite sheets, with SnO2 crystals of few nanometers integrated in the graphene matrix. Physico-chemical analysis revealed the formation of SnO2 nanoparticles, as well as the functionalization of the graphene by the presence of nitrogen atoms. Electrochemical characterizations put in evidence the ability of such composite to exploit a cocatalysis mechanism for the oxygen reduction reaction, provided by the presence of both SnO2 and nitrogen. In addition, the novel composite catalyst was successfully employed as cathode in seawater-based MFCs, giving electrical performances comparable to those of reference devices employing Pt as catalyst.

Quantifying Forearm Muscle Activity during Wrist and Finger Movements by Means of Multi-Channel Electromyography

The study of hand and finger movement is an important topic with applications in prosthetics, rehabilitation, and ergonomics. Surface electromyography (sEMG) is the gold standard for the analysis of muscle activation. Previous studies investigated the optimal electrode number and positioning on the forearm to obtain information representative of muscle activation and robust to movements. However, the sEMG spatial distribution on the forearm during hand and finger movements and its changes due to different hand positions has never been quantified. The aim of this work is to quantify 1) the spatial localization of surface EMG activity of distinct forearm muscles during dynamic free movements of wrist and single fingers and 2) the effect of hand position on sEMG activity distribution. The subjects performed cyclic dynamic tasks involving the wrist and the fingers. The wrist tasks and the hand opening/closing task were performed with the hand in prone and neutral positions. A sensorized glove was used for kinematics recording. sEMG signals were acquired from the forearm muscles using a grid of 112 electrodes integrated into a stretchable textile sleeve. The areas of sEMG activity have been identified by a segmentation technique after a data dimensionality reduction step based on Non Negative Matrix Factorization applied to the EMG envelopes. The results show that 1) it is possible to identify distinct areas of sEMG activity on the forearm for different fingers; 2) hand position influences sEMG activity level and spatial distribution. This work gives new quantitative information about sEMG activity distribution on the forearm in healthy subjects and provides a basis for future works on the identification of optimal electrode configuration for sEMG based control of prostheses, exoskeletons, or orthoses. An example of use of this information for the optimization of the detection system for the estimation of joint kinematics from sEMG is reported.

Music translation of tertiary protein structure: auditory patterns of the protein folding

We have translated genome-encoded protein sequence into musical notes and created a polyphonic harmony taking in account its tertiary structure. We did not use a diatonic musical scale to obtain a pleasant sound, focusing instead on the spatial relationship between aminoacids closely placed in the 3- dimensional protein folding. In this way, the result is a musical translation of the real morphology of the protein, that opens the challenge to bring musical harmony rules into the proteomic research field.