On the thermal and thermodynamic (In)stability of methylammonium lead halide perovskites

The interest of the scientific community on methylammonium lead halide perovskites (MAPbX3, X = Cl, Br, I) for hybrid organic-inorganic solar cells has grown exponentially since the first report in 2009. This fact is clearly justified by the very high efficiencies attainable (reaching 20% in lab scale devices) at a fraction of the cost of conventional photovoltaics. However, many problems must be solved before a market introduction of these devices can be envisaged. Perhaps the most important to be addressed is the lack of information regarding the thermal and thermodynamic stability of the materials towards decomposition, which are intrinsic properties of them and which can seriously limit or even exclude their use in real devices. In this work we present and discuss the results we obtained using non-ambient X-ray diffraction, Knudsen effusion-mass spectrometry (KEMS) and Knudsen effusion mass loss (KEML) techniques on MAPbCl3, MAPbBr3 and MAPbI3. The measurements demonstrate that all the materials decompose to the corresponding solid lead (II) halide and gaseous methylamine and hydrogen halide, and the decomposition is well detectable even at moderate temperatures (~60 °C). Our results suggest that these materials may be problematic for long term operation of solar devices

Nanostructured semiconductor materials for dye-sensitized solar cells

Since O'Regan and Grätzel's first report in 1991, dye-sensitized solar cells (DSSCs) appeared immediately as a promising low-cost photovoltaic technology. In fact, though being far less efficient than conventional silicon-based photovoltaics (being the maximum, lab scale prototype reported efficiency around 13%), the simple design of the device and the absence of the strict and expensive manufacturing processes needed for conventional photovoltaics make them attractive in small-power applications especially in low-light conditions, where they outperform their silicon counterparts. Nanomaterials are at the very heart of DSSC, as the success of its design is due to the use of nanostructures at both the anode and the cathode. In this review, we present the state of the art for both n-type and p-type semiconductors used in the photoelectrodes of DSSCs, showing the evolution of the materials during the 25 years of history of this kind of devices. In the case of p-type semiconductors, also some other energy conversion applications are touched upon. © 2017 Carmen Cavallo et al

A neural network approach to human posture classification and fall detection using RGB-D camera

In this paper, we describe a human posture classification and a falling detector module suitable for smart homes and assisted living solutions. The system uses a neural network that processes the human joints produced by a skeleton tracker using the depth streams of an RGB-D sensor. The neural network is able to recognize standing, sitting and lying postures. Using only the depth maps from the sensor, the system can work in poor light conditions and guarantees the privacy of the person. The neural network is trained with a dataset produced with the Kinect tracker, but it is also tested with a different human tracker (NiTE). In particular, the aim of this work is to analyse the behaviour of the neural network even when the position of the extracted joints is not reliable and the provided skeleton is confused. Real-time tests have been carried out covering the whole operative range of the sensor (up to 3.5 m). Experimental results have shown an overall accuracy of 98.3% using the NiTE tracker for the falling tests, with the worst accuracy of 97.5%

A Human Activity Recognition System Based on Dynamic Clustering of Skeleton Data

Human activity recognition is an important area in computer vision, with its wide range of applications including ambient assisted living. In this paper, an activity recognition system based on skeleton data extracted from a depth camera is presented. The system makes use of machine learning techniques to classify the actions that are described with a set of a few basic postures. The training phase creates several models related to the number of clustered postures by means of a multiclass Support Vector Machine (SVM), trained with Sequential Minimal Optimization (SMO). The classification phase adopts the X-means algorithm to find the optimal number of clusters dynamically. The contribution of the paper is twofold. The first aim is to perform activity recognition employing features based on a small number of informative postures, extracted independently from each activity instance; secondly, it aims to assess the minimum number of frames needed for an adequate classification. The system is evaluated on two publicly available datasets, the Cornell Activity Dataset (CAD-60) and the Telecommunication Systems Team (TST) Fall detection dataset. The number of clusters needed to model each instance ranges from two to four elements. The proposed approach reaches excellent performances using only about 4 s of input data (~100 frames) and outperforms the state of the art when it uses approximately 500 frames on the CAD-60 dataset. The results are promising for the test in real context

Solid solutions of rare earth cations in mesoporous anatase beads and their performances in dye-sensitized solar cells

Solid solutions of the rare earth (RE) cations Pr3+, Nd3+, Sm3+, Gd3+, Er3+ and Yb3+ in anatase TiO2 have been synthesized as mesoporous beads in the concentration range 0.1-0.3% of metal atoms. The solid solutions were have been characterized by XRD, SEM, diffuse reflectance UV-Vis spectroscopy, BET and BJH surface analysis. All the solid solutions possess high specific surface areas, up to more than 100 m2/g. The amount of adsorbed dye in each photoanode has been determined spectrophotometrically. All the samples were tested as photoanodes in dye-sensitized solar cells (DSSCs) using N719 as dye and a nonvolatile, benzonitrile based electrolyte. All the cells were have been tested by conversion efficiency (J-V), quantum efficiency (IPCE), electrochemical impedance spectroscopy (EIS) and dark current measurements. While lighter RE cations (Pr3+, Nd3+) limit the performance of DSSCs compared to pure anatase mesoporous beads, cations from Sm3+ onwards enhance the performance of the devices. A maximum conversion efficiency of 8.7% for Er3+ at a concentration of 0.2% has been achieved. This is a remarkable efficiency value for a DSSC employing N719 dye without co-adsorbents and a nonvolatile electrolyte. For each RE cation the maximum performances are obtained for a concentration of 0.2% metal atoms. © 2015, Nature Publishing Group. All rights reserved

Corrigendum: On the thermal and thermodynamic (in)stability of methylammonium lead halide perovskites

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A Cloud Robotics Solution to Improve Social Assistive Robots for Active and Healthy Aging

Technological innovation in robotics and ICT represents an effective solution to tackle the challenge of providing social sustainable care services for the ageing population. The recent introduction of cloud technologies is opening new opportunities for the provisioning of advanced robotic services based on the cooperation of a number of connected robots, smart environments and devices improved by the huge cloud computational and storage capability. In this context, this paper aims to investigate and assess the potentialities of a cloud robotic system for the provisioning of assistive services for the promotion of active and healthy ageing. The system comprised two different smart environments, located in Italy and Sweden, where a service robot is connected to a cloud platform for the provisioning of localization based services to the users. The cloud robotic services were tested in the two realistic environments to assess the general feasibility of the solution and demonstrate the ability to provide assistive location based services in a multiple environment framework. The results confirmed the validity of the solution but also suggested a deeper investigation on the dependability of the communication technologies adopted in such kind of systems

Enabling Global Robot Navigation Based on a Cloud Robotics Approach

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