G. Di Francia

Porous silicon in solar cells: a review and a description of its application as an AR coating

In this paper, we first review the potential applications of porous Si in solar cell structures. Then we describe the fabrication of this material by both electrochemical and chemical etching methods, providing some guidelines for a better comprehension of the influence of each process parameter. After that, the properties of porous Si in terms of morphology, structure, photoluminescence, and electroluminescence emissions are summarized together with their actual photovoltaic applications. The results of our study specifically address the creation of an antireflection (AR) coating for polycrystalline Si based solar cells. We have demonstrated the feasibility of a very efficient porous Si AR layer, prepared by a simple, cost effective, chemical etching method. The formation of a porous Si layer about 0.5 μm thick on the polycrystalline wafer results in an effective reflectance coefficient Reff lower than 5% in the wavelength region from 350 to 1150 nm. The drastic reduction of the optical losses is controllable by the process parameters and is almost independent of the starting substrate.

Gas detection with a porous silicon based sensor

Abstract Porous silicon (PS) layers with 60% porosity and 80 μm thick were prepared from n-type silicon wafer. We present the sensitivity of PS photoluminescence to 250 ppm of carbon monoxide. Besides the variation of conductivity of the device due to presence of organic vapors such as chloroform, methanol, ethanol and toluene have been carried out.

Wireless Sensor Networks for Distributed Chemical Sensing: Addressing Power Consumption Limits With On-Board Intelligence

Chemicals detection and quantification is extremely important for ensuring safety and security in multiple application domains like smart environments, building automation, etc. Characteristics of chemical signal propagation make single point of measure approach mostly inefficient. Distributed chemical sensing with wireless platforms may be the key for reconstructing chemical images of sensed environment but its development is currently hampered by technological limits on solid-state sensors power management. We present the implementation of power saving sensor censoring strategies on a novel wireless electronic nose platform specifically designed for cooperative chemical sensing and based on TinyOS. An on-board sensor fusion component complements its software architecture with the capability of locally estimate air quality and chemicals concentrations. Each node is hence capable to decide the informative content of sampled data extending the operative lifespan of the entire network. Actual power savings are modeled and estimated with a measurement approach in experimental scenarios.

Gold-catalysed porous silicon for NOx sensing

Abstract Porous silicon (PS), obtained by electrochemical anodization of an n-type silicon wafer, was catalysed by sputtering gold onto the surface (4, 8, 15 and 40-nm nominal thickness). Investigation by Rutherford backscattering spectroscopy (RBS) and by electron microscopy showed that gold did not form a continuous layer, but rather formed clusters penetrating into the pores of PS by about 1 μm. A variation of the sample conductivity in the presence of a few parts per million of NO2 and NO was recorded at room temperature. We demonstrated that, as a result of Au catalysation, PS is suitable for sensing nitrogen oxides with negligible influence by interfering gases such as CO, CH4 or methanol. Indeed, we found that humidity appreciably affected the response.

Evaluation of the thermal conductivity of porous silicon layers by an optical pump-probe method

Measurements of the thermal conductivity for free-standing porous silicon layers were performed by means of an optical pump-probe experimental set-up. By transient heating due to laser pumping, a refractive index modulation was induced in the sample and, solving the heat propagation equation for inside the solid film, it is shown that the time decay of the nonlinear transmittance can be related to the thermal conductivity. The optical technique demonstrated here is contactless, quite simple and does not require much effort in data analysis, and is therefore very useful for thin-film characterization. The thermal conductivities of the porous silicon samples, whose porosities lay in the range 60-70%, were taken into account, and we found good agreement with results obtained with different techniques.

Nonlinear optical refraction of free-standing porous silicon layers

Measurements of the nonlinear refractive index of free-standing porous silicon samples by means of the Z-scan technique are reported. A sensitive enhancement of the optical nonlinearity is found with respect to bulk silicon. The results are in agreement with a simple theoretical model which is also presented and discussed, that attributes the enhancement to quantum confinement of carriers. The negative sign of nonlinear refractive index suggests that optical Stark effect gives the dominating contribution to the nonlinearity. It is also found that the nonlinearity is mainly refractive, which is very promising in order to use porous silicon for nonlinear optical applications such as power limiting or optical switching.

Semi-Supervised Learning Techniques in Artificial Olfaction: A Novel Approach to Classification Problems and Drift Counteraction

Semi-supervised learning is a promising research area aiming to develop pattern recognition tools capable to exploit simultaneously the benefits from supervised and unsupervised learning techniques. These can lead to a very efficient usage of the limited number of supervised samples achievable in many artificial olfaction problems like distributed air quality monitoring. We believe it can also be beneficial in addressing another source of limited knowledge we have to face when dealing with real world problems: concept and sensor drifts. In this paper we describe the results of two artificial olfaction investigations that show semi-supervised learning techniques capabilities to boost performance of state-of-the art classifiers and regressors. The use of semi-supervised learning approach resulted in the effective reduction of drift-induced performance degradation in long-term on-field continuous operation of chemical multisensory devices.

A calibrated graphene-based chemi-sensor for sub parts-per-million NO2 detection operating at room temperature

Here, we present a room temperature operating chemi-sensor based on a graphene film that shows sensitivity to NO2 up to a 50 parts-per-billion (ppb) with extremely limited interference from relative humidity and can be also calibrated in a sub-parts-per-million (ppm) range with a response and recovery time of few seconds. The device has been fabricated using as active material, a solution of graphene nanosheets suspended in N-methyl-pyrrolidone drop casted on an alumina substrate with gold interdigitated electrodes. The derivative of the device response is found to be univocally correlated to NO2 concentrations from 100 ppb up to 1000 ppb and the sensor can therefore be calibrated in this same range.

Sensitivity of Porous Silicon Photoluminescence to Low Concentrations of CH4 and CO

In this paper we report the sensitivity of porous silicon photoluminescence (PL) to diluted mixtures of methane and carbon monoxide in synthetic air. We also investigate the separate effect of synthetic air, purified nitrogen and relative humidity on both photoluminescence and conductance (G). Porous silicon samples have been prepared from n-type silicon substrates. We find that PL intensity and G decrease in synthetic air with respect to their values in N2. Presence of carbon monoxide reduces the PL intensity while methane provokes the opposite behaviour. The dependence of the PL spectra on methane and carbon monoxide concentrations has been investigated. The observed effects can be related to gas induced modifications in porous surface and suggest that porous silicon can be employed in gas sensor technology.

Characterization of Nanoparticles in Seawater for Toxicity Assessment Towards Aquatic Organisms

The fate and the behaviour of nanoparticles in seawater, which is the ultimate sink for any release of nanoparticles, is a very important issue for the assessment of their environmental impact. Despite this concern, only few studies regarding the ecotoxic effect of NPs upon marine organisms were conducted. In this work the dispersion behaviour of NPs in a seawater matrix has been investigated and their physicochemical properties characterized. The ecotoxicological impact towards marine organisms of several nanoparticles has been also examined.