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

C60bioconjugation with proteins: Towards a palette of carriers for all pH ranges

The high hydrophobicity of fullerenes and the resulting formation of aggregates in aqueous solutions hamper the possibility of their exploitation in many technological applications. Noncovalent bioconjugation of fullerenes with proteins is an emerging approach for their dispersion in aqueous media. Contrary to covalent functionalization, bioconjugation preserves the physicochemical properties of the carbon nanostructure. The unique photophysical and photochemical properties of fullerenes are then fully accessible for applications in nanomedicine, sensoristic, biocatalysis and materials science fields. However, proteins are not universal carriers. Their stability depends on the biological conditions for which they have evolved. Here we present two model systems based on pepsin and trypsin. These proteins have opposite net charge at physiological pH. They recognize and disperse C60in water. UV-Vis spectroscopy, zeta-potential and atomic force microscopy analysis demonstrates that the hybrids are well dispersed and stable in a wide range of pH's and ionic strengths. A previously validated modelling approach identifies the protein-binding pocket involved in the interaction with C60. Computational predictions, combined with experimental investigations, provide powerful tools to design tailor-made C60@proteins bioconjugates for specific applications

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

Usable Security. A Systematic Literature Review

Usable security involves designing security measures that accommodate users’ needs and behaviors. Balancing usability and security poses challenges: the more secure the systems, the less usable they will be. On the contrary, more usable systems will be less secure. Numerous studies have addressed this balance. These studies, spanning psychology and computer science/engineering, contribute diverse perspectives, necessitating a systematic review to understand strategies and findings in this area. This systematic literature review examined articles on usable security from 2005 to 2022. A total of 55 research studies were selected after evaluation. The studies have been broadly categorized into four main clusters, each addressing different aspects: (1) usability of authentication methods, (2) helping security developers improve usability, (3) design strategies for influencing user security behavior, and (4) formal models for usable security evaluation. Based on this review, we report that the field’s current state reveals a certain immaturity, with studies tending toward system comparisons rather than establishing robust design guidelines based on a thorough analysis of user behavior. A common theoretical and methodological background is one of the main areas for improvement in this area of research. Moreover, the absence of requirements for Usable security in almost all development contexts greatly discourages implementing good practices since the earlier stages of development

Finite reservoirs and irreversibility corrections to Hamiltonian systems statistics

We consider several Hamiltonian systems perturbed by external agents, that preserve their Hamiltonian structure. We investigate the corrections to the canonical statistics resulting from coupling such systems with possibly large but finite reservoirs, and from the onset of processes breaking the time reversal symmetry. We analyze exactly solvable oscillators systems, and perform simulations of relatively more complex ones. This indicates that the standard statistical mechanical formalism needs to be adjusted, in the ever more investigated nano-scale science and technology. In particular, the hypothesis that heat reservoirs be considered infinite and be described by the classical ensembles is found to be critical when exponential quantities are considered, since the large size limit may not coincide with the infinite size canonical result. Furthermore, process-dependent emergent irreversibility affects ensemble averages, effectively frustrating, on a statistical level, the time reversal invariance of Hamiltonian dynamics, that is used to obtain numerous results

The use of dynamical networks to detect the hierarchical organization of financial market sectors

Two kinds of filtered networks: minimum spanning trees (MSTs) and planar maximally filtered graphs (PMFGs) are constructed from dynamical correlations computed over a moving window. We study the evolution over time of both hierarchical and topological properties of these graphs in relation to market fluctuations. We verify that the dynamical PMFG preserves the same hierarchical structure as the dynamical MST, providing in addition a more significant and richer structure, a stronger robustness and dynamical stability. Central and peripheral stocks are differentiated by using a combination of different topological measures. We find stocks well connected and central; stocks well connected but peripheral; stocks poorly connected but central; stocks poorly connected and peripheral. It results that the Financial sector plays a central role in the entire system. The robustness, stability and persistence of these findings are verified by changing the time window and by performing the computations on different time periods. We discuss these results and the economic meaning of this hierarchical positioning

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

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