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

Risk-based clustering for near misses identification in integrated deterministic and probabilistic safety analysis

In integrated deterministic and probabilistic safety analysis (IDPSA), safe scenarios and prime implicants (PIs) are generated by simulation. In this paper, we propose a novel postprocessing method, which resorts to a risk-based clustering method for identifying Near Misses among the safe scenarios. This is important because the possibility of recovering these combinations of failures within a tolerable grace time allows avoiding deviations to accident and, thus, reducing the downtime (and the risk) of the system. The postprocessing risk-significant features for the clustering are extracted from the following: (i) the probability of a scenario to develop into an accidental scenario, (ii) the severity of the consequences that the developing scenario would cause to the system, and (iii) the combination of (i) and (ii) into the overall risk of the developing scenario. The optimal selection of the extracted features is done by a wrapper approach, whereby a modified binary differential evolution (MBDE) embeds a K-means clustering algorithm. The characteristics of the Near Misses scenarios are identified solving a multiobjective optimization problem, using the Hamming distance as a measure of similarity. The feasibility of the analysis is shown with respect to fault scenarios in a dynamic steam generator (SG) of a nuclear power plant (NPP)

Transient identification by clustering based on Integrated Deterministic and Probabilistic Safety Analysis outcomes

open3noIn this work, we present a transient identification approach that utilizes clustering for retrieving scenarios information from an Integrated Deterministic and Probabilistic Safety Analysis (IDPSA). The approach requires: (i) creation of a database of scenarios by IDPSA; (ii) scenario post-processing for clustering Prime Implicants (PIs), i.e., minimum combinations of failure events that are capable of leading the system into a fault state, and Near Misses, i.e., combinations of failure events that lead the system to a quasi-fault state; (iii) on-line cluster assignment of an unknown developing scenario. In the step (ii), we adopt a visual interactive method and risk-based clustering to identify PIs and Near Misses, respectively; in the on-line step (iii), to assign a scenario to a cluster we consider the sequence of events in the scenario and evaluate the Hamming similarity to the sequences of the previously clustered scenarios. The feasibility of the analysis is shown with respect to the accidental scenarios of a dynamic Steam Generator (SG) of a NPP.Di Maio, Francesco; Vagnoli, Matteo; Zio, EnricoDI MAIO, Francesco; Vagnoli, Matteo; Zio, Enric

Determination of prime implicants by differential evolution for the dynamic reliability analysis of non-coherent nuclear systems

open4We present an original computational method for the identification of prime implicants (PIs) in non-coherent structure functions of dynamic systems. This is a relevant problem for dynamic reliability analysis, when dynamic effects render inadequate the traditional methods of minimal cut-set identification. PIs identification is here transformed into an optimization problem, where we look for the minimum combination of implicants that guarantees the best coverage of all the minterms. For testing the method, an artificial case study has been implemented, regarding a system composed by five components that fail at random times with random magnitudes. The system undergoes a failure if during an accidental scenario a safety-relevant monitored signal raises above an upper threshold or decreases below a lower threshold. Truth tables of the two system end-states are used to identify all the minterms. Then, the PIs that best cover all minterms are found by Modified Binary Differential Evolution. Results and performances of the proposed method have been compared with those of a traditional analytical approach known as Quine-McCluskey algorithm and other evolutionary algorithms, such as Genetic Algorithm and Binary Differential Evolution. The capability of the method is confirmed with respect to a dynamic Steam Generator of a Nuclear Power Plant.Di Maio, Francesco; Baronchelli, Samuele; Vagnoli, Matteo; Zio, EnricoDI MAIO, Francesco; Baronchelli, Samuele; Vagnoli, Matteo; Zio, Enric

Radiation Reaction Effects on Electron Nonlinear Dynamics and Ion Acceleration in Laser-solid Interaction

Radiation Reaction (RR) effects in the interaction of an ultra-intense laser pulse with a thin plasma foil are investigated analytically and by two-dimensional (2D3P) Particle-In-Cell (PIC) simulations. It is found that the radiation reaction force leads to a significant electron cooling and to an increased spatial bunching of both electrons and ions. A fully relativistic kinetic equation including RR effects is discussed and it is shown that RR leads to a contraction of the available phase space volume. The results of our PIC simulations are in qualitative agreement with the predictions of the kinetic theory

Computed tomography findings of pneumatosis and portomesenteric venous gas in acute bowel ischemia.

BACKGROUND: To use more representative sample size to evaluate whether computed tomography (CT) scan evidence of the concomitant presence of pneumatosis and portomesenteric venous gas is a predictor of transmural bowel necrosis. METHODS: Data from 208 patients who were referred for a diagnosis of bowel ischemia were retrospectively reviewed. Only patients who underwent a surgical intervention following a diagnosis of bowel ischemia who also had a post-operative histological confirmation of such a diagnosis were included. Patients were split into two groups according to the presence of histological evidence of transmural bowel ischemia (case group) or partial bowel ischemia (control group). CT images were reviewed for findings of ischemia, including mural thickening, pneumatosis, bowel distension, portomesenteric venous gas and arterial or venous thrombi. RESULTS: A total of 248 subjects who underwent surgery for bowel ischemia were identified. Among the 208 subjects enrolled in our study, transmural bowel necrosis was identified in 121 subjects (case group), and partial bowel necrosis was identified in 87 subjects (control group). Based on CT findings, including mural thickening, bowel distension, pneumatosis, pneumatosis plus portomesenteric venous gas and presence of thrombi or emboli, there were no significant differences between the case and control groups. The concomitant presence of pneumatosis and porto-mesenteric venous gas showed an odds ratio of 1.95 (95%CI: 0.491-7.775, P = 0.342) for the presence of transmural necrosis. The presence of pneumatosis plus porto-mesenteric venous gas exhibited good specificity (83%) but low sensitivity (17%) in the identification of transmural bowel infarction. Accordingly, the positive and negative predictive values were 60% and 17%, respectively. CONCLUSION: Although pneumatosis plus porto-mesenteric venous gas is associated with bowel ischemia, we have demonstrated that their co-occurrence cannot be used as diagnostic signs of transmural necrosis

Corticobasal syndrome: neuroimaging and neurophysiological advances

Corticobasal degeneration (CBD) is a neurodegenerative condition characterized by 4R-tau protein deposition in several brain regions that clinically manifests itself as a heterogeneous atypical parkinsonism typically expressing in the adulthood. The prototypical clinical phenotype of CBD is corticobasal syndrome (CBS). Important insights into the pathophysiological mechanisms underlying motor and higher cortical symptoms in CBS have been gained by using advanced neuroimaging and neurophysiological techniques. Structural and functional neuroimaging studies often showed asymmetric cortical and subcortical abnormalities, mainly involving perirolandic and parietal regions and basal ganglia structures. Neurophysiological investigations including electroencephalography and somatosensory evoked potentials provided useful information on the origin of myoclonus and on cortical sensory loss. Transcranial magnetic stimulation demonstrated heterogeneous and asymmetric changes in the excitability and plasticity of primary motor cortex and abnormal hemispheric connectivity. Neuroimaging and neurophysiological abnormalities in multiple brain areas reflect the asymmetric neurodegeneration, leading to the asymmetric motor and higher cortical symptoms in CBS. This article is protected by copyright. All rights reserved