Upper bounds for solar thermophotovoltaic efficiency

The main components of thermophotovoltaic (TPV) devices are the primary lens (or mirror), the absorber, the PV cell, and a photon recuperator system. A theory integrating all these components is used in this paper to analyse a particular type of TPV device (plane disk absorber and PV cell). The TPV efficiency is maximized by using three optimization parameters, namely absorber, PV cell temperatures, and cell voltage. Almost ideal operation conditions are envisaged and upper bounds are obtained for the TPV efficiency. They are strongly dependent on PV cell bandgap and radiation concentration. Preliminary results suggest the existence of an optimum solar radiation concentration ratio. The improvement in thermal design quality allows the usage of PV cells based on wide bandgap semiconductors.     

Bead-based polymerase chain reaction on a microchip

We present a bead-based approach to microfluidic polymerase chain reaction (PCR), enabling fluorescent detection and sample conditioning in a single microchamber. Bead-based PCR, while not extensively investigated in microchip format, has been used in a variety of bioanalytical applications in recent years. We leverage the ability of bead-based PCR to accumulate fluorescent labels following DNA amplification to explore a novel DNA detection scheme on a microchip. The microchip uses an integrated microheater and temperature sensor for rapid control of thermal cycling temperatures, while the sample is held in a microchamber fabricated from (poly)dimethylsiloxane and coated with Parylene. The effects of key bead-based PCR parameters, including annealing temperature and concentration of microbeads in the reaction mixture, are studied to achieve optimized device sensitivity and detection time. The device is capable of detecting a synthetically prepared section of the Bordetella pertussis genome in as few as 10 temperature cycles with times as short as 15?min. We then demonstrate the use of the procedure in an integrated device; capturing, amplifying, detecting, and purifying template DNA in a single microfluidic chamber. These results show that this method is an effective method of DNA detection which is easily integrated in a microfluidic device to perform additional steps such as sample pre-conditioning.     

Invariant diagrams with data refinement

Invariant based programming is an approach where we start to construct a program by first identifying the basic situations (pre- and post-conditions as well as invariants) that could arise during the execution of the algorithm. These situations are identified before any code is written. After that, we identify the transitions between the situations, which will give us the flow of control in the program. Data refinement is a technique of building correct programs working on concrete data structures as refinements of more abstract programs working on abstract data types. We study in this paper data refinement for invariant based programs and we apply it to the construction of the classical Deutsch–Schorr–Waite graph marking algorithm. Our results are formalized and mechanically proved in the Isabelle/HOL theorem prover.     

Density related properties of bark insulation boards bonded with tannin hexamine resin

Building owners are increasingly interested in a healthy and sustainable living environment, which is a trend favoring ecological building materials with outstanding structural physical parameters. Insulation boards from particles of larch bark (Larix decidua Mill.) bonded with a formaldehyde-free tannin resin were pressed and evaluated for their mechanical and physical properties. It could be shown that light (target density 250 kg/m³) boards can be pressed, and their thermal conductivity is low (0.065–0.09 W/(m*K)). With regard to mechanical characteristics, the influence of panel density was studied, and it was found that a certain compaction (ρ ≥ 400 kg/m³) is necessary to meet the requirements of the relevant standard. Interestingly, the resin amount did not influence the mechanical board properties as strongly as expected, and panel density is the most important variable in this respect. The study proved that tree bark cannot only be used for substantially upgraded insulation panels but can also be bonded with a formaldehyde free tannin resin.     

Effect of P2O5 on the Structural and Magnetic Properties of Magnetite‐Based Glass‐Ceramics

The specific morphology and magnetic properties of magnetite‐based glass‐ceramics obtained by crystallization of Fe‐containing borosilicate glassmelts in the presence of P₂O₅ as nucleating agent are investigated. We found that the distribution of the tiny nanoparticles of magnetite determines the low temperature response to magnetic field. The observed effects are discussed with respect to the following factors: (1) the existence of a multimodal size distribution of the tiny grains as revealed by Mössbauer spectroscopy, magnetometry, and high‐resolution electron microscopy; (2) the existence of a disordered layer at the grain surface which is driven by field in a magnetically ordered state; and (3) the interplay between the relaxation mechanisms in different temperature ranges.     

Prediction of the crack condition of highway pavements using machine learning models

Departments of Transportation regularly evaluate the condition of pavements through visual inspections, nondestructive evaluations, image recognition models and learning algorithms. The above methodologies, though efficient, have drawn attention due to their subjective errors, uncertainties, noise effects and overfitting. To improve on the outcomes of the shallow learning models already used in pavement crack prediction, this paper reports on an investigation of the use of recursive partitioning and artificial neural networks (ANN; deep learning frameworks) in predicting the crack rating of pavements. Explanatory variables such as the average daily traffic and truck factor, roadway functional class, asphalt thickness, and pavement condition time series data are employed in the model formulation. Overall, it is observed that the recursive partitioning (regression tree – R² > 0.8 and classification tree – R² > 0.6) and ANN (continuous response – R² > 0.8 and categorical response – R² > 0.6) are compelling machine learning models for the prediction of the crack ratings based on their goodness-of-fit statistics, mean absolute deviation (MAD < 0.4) and the root mean square errors (RMSE between 0.30 and 0.65).     

Electrochemical impedance spectroscopy and corrosion behaviour of Al2O3-Ni nano composite coatings

In this paper, the results on the electrochemical impedance spectroscopy and corrosion properties of electrodeposited nanostructured Al₂O₃-Ni composite coatings are presented. The nanocomposite coatings were obtained by codeposition of alumina nanoparticles (13 nm) with nickel during plating process. The coating thickness was 50 μm on steel support and an average of nano Al₂O₃ particles inside of coatings at 15 vol.% was present. The structure of the coatings was investigated by scanning electron microscopy (SEM). It has been found that the codeposition of Al₂O₃ particles with nickel disturbs the nickel coating's regular surface structure. The electrochemical behavior of the coatings in the corrosive solutions was investigated by polarization potentiodynamic and electrochemical impedance spectroscopy methods. As electrochemical test solutions 0.5 M sodium chloride and 0.5 M potassium sulphate were used in a three electrode open cell. The corrosion potential is shifted to more negative values for nanostructured coatings in 0.5 M sodium chloride. The polarization resistance in 0.5 M sodium chloride decreases in 24 h, but after that increases slowly. In 0.5 M potassium sulphate solution the polarization resistance decreases after 2 h and after 30 h of immersion the polarization resistance is higher than that of the beginning value. The corrosion rate calculated by polarization potentiodynamic curves obtained after 30 min from immersion in solution is smaller for nanostructured coatings in 0.5 M potassium sulphate (4.74 μm/year) and a little bit bigger in 0.5 M sodium chloride (5.03 μm/year).     

Computing global and diffuse solar hourly irradiation on clear sky. Review and testing of 54 models

Fifty-four broad band models for computation of global and diffuse irradiance on horizontal surface are shortly presented and tested. The input data for these models consist of surface meteorological data, atmospheric column integrated data and data derived from satellite measurements. The testing procedure is performed for two meteorological stations in Romania (South-Eastern Europe). The testing procedure consists of forty-two stages intended to provide information about the sensitivity of the models to various sets of input data. There is no model to be ranked “the best” for all sets of input data. Very simple models as well as more complex models may belong to the category of “good models”. The best models for solar global radiation computation are, on equal-footing, ESRA3, Ineichen, METSTAT and REST2 (version 81). The second best models are, on equal-footing, Bird, CEM and Paulescu & Schlett. The best models for solar diffuse radiation computation are, on equal-footing, ASHRAE2005 and King. The second best model is MAC model. The best models for computation of both global and diffuse radiation are, on equal-footing, ASHRAE 1972, Biga, Ineichen and REST2 (version 81). The second best is Paulescu & Schlett model.