Monolithic Perovskite/Silicon Tandems with >28% Efficiency: Role of Silicon-Surface Texture on Perovskite Properties

Textured silicon wafers used in silicon solar cell manufacturing offer superior light trapping, which is a critical enabler for high-performance photovoltaics. A similar optical benefit can be obtained in monolithic perovskite/silicon tandem solar cells, enhancing the current output of the silicon bottom cell. Yet, such complex silicon surfaces may affect the structural and optoelectronic properties of the overlying perovskite films. Here, through extensive characterization based on optical and microstructural spectroscopy, it is found that the main effect of such substrate morphology lies in an altering of the photoluminescence response of the perovskite, which is associated with thickness variations of the perovskite, rather than lattice strain or compositional changes. With this understanding, the design of high-performance perovskite/silicon tandems is rationalized, yielding certified power conversion efficiencies of >28%.     

Differential evolution and differential ant-stigmergy on dynamic optimisation problems

Many real-world optimisation problems are of dynamic nature, requiring an optimisation algorithm which is able to continuously track a changing optimum over time. To achieve this, we propose two population-based algorithms for solving dynamic optimisation problems (DOPs) with continuous variables: the self-adaptive differential evolution algorithm (jDE) and the differential ant-stigmergy algorithm (DASA). The performances of the jDE and the DASA are evaluated on the set of well-known benchmark problems provided for the special session on Evolutionary Computation in Dynamic and Uncertain Environments. We analyse the results for five algorithms presented by using the non-parametric statistical test procedure. The two proposed algorithms show a consistently superior performance over other recently proposed methods. The results show that both algorithms are appropriate candidates for DOPs.     

On-line motion synthesis and adaptation using a trajectory database

Autonomous robots cannot be programmed in advance for all possible situations. Instead, they should be able to generalize the previously acquired knowledge to operate in new situations as they arise. A possible solution to the problem of generalization is to apply statistical methods that can generate useful robot responses in situations for which the robot has not been specifically instructed how to respond. In this paper we propose a methodology for the statistical generalization of the available sensorimotor knowledge in real-time. Example trajectories are generalized by applying Gaussian process regression, using the parameters describing a task as query points into the trajectory database. We show on real-world tasks that the proposed methodology can be integrated into a sensory feedback loop, where the generalization algorithm is applied in real-time to adapt robot motion to the perceived changes of the external world.     

Statistical optimisation of the exopolysaccharide production by Lactobacillus fermentum Lf2 and analysis of its chemical composition

Lactobacillus fermentum Lf2 produces high amounts of exopolysaccharides (EPS) (~1 g/L) with demonstrated functional and technological roles when applied as a food ingredient in dairy matrices, properties that made these EPS interesting in comparison with other similar molecules from lactic acid bacteria (LAB). Those characteristics encouraged us to optimise the production. The EPS extract is composed of a high molecular mass β‐glucan and a medium molecular mass heteroglycan. In the present work, the optimal conditions that doubled the EPS yield using a semidefined medium (SDM, 0.63% yeast nitrogen base, 0.53% bacto casitone, 0.53% ammonium citrate, 6.25% sucrose, pH 6.5) were found by means of response surface methodology (RSM). The chemical characterisation indicated that under optimised conditions the synthesis of the heteroglycan was favoured compared with that of the β‐glucan.     

Influence of ionic strength and HPMC viscosity grade on drug release and swelling behavior of HPMC matrix tablets

Matrix tablets containing paracetamol and hydroxypropyl methylcellulose (HPMC 2906) of different viscosity grades (50, 400, 1500, and 4000 mPa·s) were evaluated for drug release and change in matrix tablet mass [ΔM (%)] after exposure to 0.09, 0.15, 0.31, and 0.52M ionic strengths of dissolution media. At 0.09 and 0.15M ionic strength, drug‐release profiles reflected the extended release characteristic; in addition the increase in ΔM was slow and continuous within first few hours. At 0.31M the higher viscosity grade matrices showed extensive initial swelling and the loss of extended release whereas at 0.52M a similar tablet performance is observed for the matrices of all viscosity grades. Notably, when extensive increase in ΔM occurs in the very beginning of exposure to medium the loss of extended release from the matrix is expected. © 2016 Wiley Periodicals, Inc. J. Appl. Polym. Sci. 2016 , 133, 43604.     

Mental illness and the impact of believing others know about it.

Reports 2 studies measuring the impact upon 30 male inpatients and 29 male outpatients of believing others have become aware of their psychiatric history. Ss thought the interest was in determining if another person would behave the same toward mental patients and controls. 1/2 the Ss were told the other person knew they were patients and the remainder that he believed them to be nonpatients. Believing others were aware of their status caused Ss to feel less appreciated, to find a task more difficult, and to perform more poorly, and they were perceived as more tense, anxious, and poorly adjusted by an O. (20 ref.) (PsycINFO Database Record (c) 2010 APA, all rights reserved)