Impact of mechanical stress on barium titanate-based positive temperature coefficient resistive material

The sensitivity toward mechanical stress of barium titanate-based positive temperature coefficient resistor material was investigated by determining the resistance change with application of uniaxial stress from room temperature to 200 °C, which is well above the Curie temperature T_C. Using the Landau–Ginsburg–Devonshire theory the resistance increases in the paraelectric state, the negligible impact of stress close to T_C and the observed increase in T_C with increasing stress could be rationalized. For the ferroelectric state, the stress-related resistance increase was attributed to ferroelasticity, a change in bulk permittivity and interfacial stress inducing a piezoelectric potential. The obtained results are also discussed with respect to recent endeavors to tune properties of potential barriers in piezoelectric semiconductors by mechanical stress.     

Comparison of direct electrocaloric characterization methods exemplified by 0.92 Pb(Mg1/3Nb2/3)O3‐0.08 PbTiO3 multilayer ceramics

Electrocaloric device structures have been developed as multilayer ceramics (MLCs) based on fundamental research carried out on PMN‐8PT bulk ceramics. Two different MLC structures were prepared with nine layers each and layer thicknesses of 86 μm and 39 μm. The influence of the device design on its properties has been characterized by microstructural, dielectric, ferroelectric, and direct electrocaloric measurement. For direct characterization two different methods, ie temperature reading (thermistor and thermocouple) and heat flow measurement (differential scanning calorimetry), were used. A comparison of results revealed a highly satisfactory agreement between the different methods. This study confirms that MLCs are promising candidates for implementation into energy‐efficient electrocaloric cooling systems providing large refrigerant volume and high electrocaloric effect. Due to their micron‐sized active layers, they allow for the application of high electric fields under low operation voltages. We measured a maximum electrocaloric temperature change of ΔT=2.67 K under application/withdrawal of an electric field of ΔE=16 kV mm^?1, which corresponds to operation voltages below 1.5 kV.     

Predicting piezometric water level in dams via artificial neural networks

The safety control of dams is based on measurements of parameters of interest such as seepage flows, seepage water clarity, piezometric levels, water levels, pressures, deformations or movements, temperature variations, loading conditions, etc. Interpretation of these large sets of available data is very important for dam health monitoring and it is based on mathematical models. Modelling seepage through geological formations located near the dam site or dam bodies is a challenging task in dam engineering. The objective of this study is to develop a feedforward neural network (FNN) model to predict the piezometric water level in dams. An improved resilient propagation algorithm has been used to train the FNN. The measured data have been compared with the results of FNN models and multiple linear regression (MLR) models that have been widely used in analysis of the structural dam behaviour. The FNN and MLR models have been developed and tested using experimental data collected during 9 years. The results of this study show that FNN models can be a powerful and important tool which can be used to assess dams.     

Soundness verification for conceptual workflow nets with data: Early detection of errors with the most precision possible

A conceptual workflow model specifies the control flow of a workflow together with abstract data information. This model is later on refined by adding specific data information, resulting in an executable workflow which is then run on an information system. It is desirable that correctness properties of the conceptual workflow are transferable to its refinements. In this paper, we present classical workflow nets extended with data operations as a conceptual workflow model. For these nets, we develop a novel technique to verify soundness. An executable workflow is sound if from every reachable state it is always possible to terminate properly. Our technique allows us to analyze a conceptual workflow and to conclude whether there exists at least one sound refinement of it, and whether any refinement of a conceptual workflow model is sound. The positive answer to the first question in combination with the negative answer to the second question means that sound and unsound refinements for the conceptual workflow in question are possible.     

Electrospun PEO/rGO Scaffolds: The Influence of the Concentration of rGO on Overall Properties and Cytotoxicity

Reduced graphene oxide (rGO) is one of the graphene derivatives that can be employed to engineer bioactive and/or electroactive scaffolds. However, the influence of its low and especially high concentrations on scaffolds’ overall properties and cytotoxicity has yet to be explored. In this study, polyethylene oxide (PEO)-based scaffolds containing from 0.1 to 20 wt% rGO were obtained by electrospinning. Morphological, thermal and electrical properties of the scaffolds were characterized by SEM, Raman spectroscopy, XRD, DSC and electrical measurements. The diameter of the fibers decreased from 0.52 to 0.19 µm as the concentration of rGO increased from 0.1 wt% to 20 wt%. The presence of rGO above the percolation threshold (5.7 wt%) resulted in a significantly reduced electrical resistivity of the scaffolds. XRD and Raman analysis revealed delamination of the graphene layers (interlayer spacing increased from 0.36 nm to 0.40–0.41 nm), and exfoliation of rGO was detected for the samples with an rGO concentration lower than 1 wt%. In addition, an evident trend of increasing cell viability as a function of the rGO concentration was evidenced. The obtained results can serve as further guidance for the judicious selection of the rGO content incorporated into the PEO matrix for constructing electroactive scaffolds.     

Ultrasensitive proteomics using high-efficiency on-line micro-SPE-nanoLC-nanoESI MS and MS/MS

Ultrasensitive nanoscale proteomics approaches for characterizing proteins from complex proteomic samples of <50 ng of total mass are described. Protein identifications from 0.5 pg of whole proteome extracts were enabled by ultrahigh sensitivity (<75 zmol for individual proteins) achieved using high-efficiency (peak capacities of approximately 10(3)) 15-microm-i.d. capillary liquid chromatography separations (i.e., using nanoLC, approximately 20 nL/min mobile-phase flow rate at the optimal linear velocity of approximately 0.2 cm/s) coupled on-line with a micro-solid-phase sample extraction and a nanoscale electrospray ionization interface to a 11.4-T Fourier transform ion cyclotron resonance (FTICR) mass spectrometer (MS). Proteome measurement coverage improved as sample size was increased from as little as 0.5 pg of sample. It was found that a 2.5-ng sample provided 14% coverage of all annotated open reading frames for the microorganism Deinococcus radiodurans, consistent with previous results for a specific culture condition. The estimated detection dynamic range for detected proteins was 10(5)-10(6). An improved accurate mass and LC elution time two-dimensional data analysis methodology, used to both speed and increase the confidence of peptide/protein identifications, enabled identification of 872 proteins/run from a single 3-h nanoLC/FTICR MS analysis. The low-zeptomole-level sensitivity provides a basis for extending proteomics studies to smaller cell populations and potentially to a single mammalian cell. Application with ion trap MS/MS instrumentation allowed protein identification from 50 pg (total mass) of proteomic samples (i.e., approximately 100 times larger than FTICR MS), corresponding to a sensitivity of approximately 7 amol for individual proteins. Compared with single-stage FTICR measurements, ion trap MS/MS provided a much lower proteome measurement coverage and dynamic range for a given analysis time and sample quantity.