RESUMEN
Strain engineering is an efficient tool to tune and tailor the electrical and optical properties of 2D materials. The built-in strain can be tuned during the synthesis process of a two-dimensional semiconductor, such as molybdenum disulfide, by employing different growth substrates with peculiar thermal properties. In this work, we demonstrate that the built-in strain of MoS2 monolayers, grown on a SiO2/Si substrate by liquid precursor chemical vapor deposition, is mainly dependent on the size of the monolayer. In fact, we identify a critical size equal to 20 µm, from which the built-in strain increases drastically. The built-in strain is the maximum for a 60 µm sized monolayer, leading to 1.2% tensile strain with a partial release of strain close to the monolayer triangular vertexes due to the formation of nanocracks. These findings also imply that the standard method for evaluation of the number of layers based on the Raman mode separation can become unreliable for highly strained monolayers with a lateral size above 20 µm.
RESUMEN
Many efforts have been spent in the last decade for the development of nanoscale synaptic devices integrated into neuromorphic circuits, trying to emulate the behavior of natural synapses. The study of brain properties with the standard approaches based on biocompatible electrodes coupled to conventional electronics, however, presents strong limitations, which in turn could be overcame by the in-situ growth of neuronal networks coupled to memristive devices. To meet this challenging task, here two different chips were designed and fabricated for culturing neuronal cells and sensing their electrophysiological activity. The first chip was designed to be connected to an external memristor, while the second chip was coated with TiO2 films owning memristive properties. The biocompatibility of chips was preliminary analyzed by culturing the hybrid motor-neuron cell line NSC-34 and by measuring the electrical activity of cells interfacing the chip with a standard patch-clamp setup. Next, neurons were seeded on chips and their activity measured with the same setup. For both cell types total current and voltage responses were evoked and recorded with optimal results with no breakdowns. In addition, an external stimulation was applied to cells through chip electrodes, being effective and causing no damage or pitfalls to the cells. Finally, the whole bio-hybrid system, i.e. the chip interconnected with a commercial memristor, was tested with promising results. Spontaneous electrical activity of neurons grown on the chip was indeed present and this signal was collected and sent to the memristor, changing its state. Taken together, we demonstrated the ability of memristor to work with a synaptic/plastic response together with natural systems, opening the way for the further implementation of basic computing elements able to perform both storage and processing of data, as in natural neurons.
Asunto(s)
Redes Neurales de la Computación , Neuronas/citología , Animales , Electrodos , Electrónica , Ratones , Neuronas/metabolismo , Sinapsis/metabolismo , Células Tumorales CultivadasRESUMEN
The Hummers' method for graphite oxide (GO) preparation has been applied to graphite nanoplatelets, in order to achieve higher reaction yield and faster kinetics. Aqueous GO solutions have been used to produce uniform GO films on a polyethylene terephthalate substrate, generating graphene patterns in a controlled way (widths of a few tens of microns). The reduction of GO deposited on the polymeric substrate has been performed by using a Nd:YVO4 continuous-wave frequency-duplicated laser. Spectroscopic and diffractometric characterizations (FT-IR, visible-NIR, Raman, XPS, and XRD) have shown that the reduction process induced by the laser annealing technique is mainly due to dehydration of the GO layers. It has been obtained by means of a suitable laser optical apparatus, a controlled reduction of GO without damaging the substrate, and precise writing of micro-tracks that can be used as electrically and thermally conductive patterns.