Zeitschriftenaufsätze

For industrial processes, operating conditions tend to be time varying, leading to the time-varying nonstationary characteristics. In this paper, an active nonstationary variables selection-based just-in-time co-integration analysis and slow feature analysis monitoring approach is proposed to explore the real-time variations in dynamic processes. To this end, by analyzing the time-varying stationarity of online data, active nonstationary variables are selected. Meanwhile, a just-in-time strategy is used to update the offline model. On this basis, co-integration analysis and slow feature analysis are developed for extracting long-run equilibrium relationships and slowly varying features. A comprehensive statistic is generated by Bayesian inference to monitor the operation status. With the active nonstationary information extraction, the proposed method emphasizes the online nonstationary characteristics, which allows the monitoring model to effectively capture the dynamic variations. Two case studies on benchmark processes show the advantages and feasibility of the proposed method.

V-groove nanopatterning of Si substrates has recently demonstrated promise for achieving high-quality III-V-on-Si epitaxy while providing a lower-cost processing route than chemo-mechanical polishing to produce epi-ready planar wafers. A key factor in determining the crystalline quality of III-V buffer layers is the Si surface structure and its chemical composition. Unlike planar Si surfaces, the surfaces of V-grooves prior to growth have not been studied in detail. Here, we study the surface of V-groove Si prepared for GaP nucleation via X-ray photoelectron spectroscopy and low-energy electron diffraction. We identify several pretreatments, using both 830˚C and 1000˚C annealing under an As background pressure, as being suitable for deoxidizing and cleaning the V-groove Si surface. The V-groove Si was found to behave similarly to reference Si(0 0 1) and Si(1 1 1) planar samples, demonstrating that in situ techniques such as reflection anisotropy spectroscopy can be used on reference samples to infer the state of the V-groove surface, and indicating that the extensive research on planar Si surfaces can be directly applied to V-grooves.

For the characterization of the mechanical deformation of materials at microscopic length scales, image processing of a high-quality surface pattern was used. We imprinted speckle patterns onto a thin polymer film attached to the surface of flat and curved metal substrates using flexible molds and soft-thermal nanoimprint lithography. High optical contrast was achieved by mixing black dye into the film generating high absorption in the elevated structures, and by adding titania nanoparticles as fillers to the recessed areas to induce diffuse scattering. For accessing resolution suitable to detect deformation at an individual grain level, the structure sizes were scaled down from 20 μm to 2 μm. For both structure sizes imaging was tested using a digital image correlation setup, that enables 3D imaging of samples with angles of up to 10˚ of inclination.

In following paper we propose method of energetic description for active microcantilevers. Microelectromechanical devices (MEMS), to which the microcantilevers belong, are becoming part of energy generation and transformation systems. Therefore efficiency of said devices becomes significant parameter. In our approach we described the method to estimate the efficiency based on the measured parameters of a cantilever and it’s effective movement under actuation. We have conducted measurements an calculations for series of cantilevers actuated electrothermally and electromagnetically. Acquired results are in line with predicted properties of examined MEMS’. Method is suited for description of microcantilevers, assessment of utility and comparison in case of common application. [2022-0043]

Cyanobacteria are fast-growing, genetically accessible, photoautotrophs. Therefore, they have attracted interest as sustainable production platforms. However, the lack of techniques to systematically optimize cultivation parameters in a high-throughput manner is holding back progress towards industrialization. To overcome this bottleneck, here we introduce a droplet-based microfluidic platform capable of one- (1D) and two-dimension (2D) screening of key parameters in cyanobacterial cultivation. We successfully grew three different unicellular, biotechnologically relevant, cyanobacteria: Synechocystis sp. PCC 6803, Synechococcus elongatus UTEX 2973 and Synechococcus sp. UTEX 3154. This was followed by a highly-resolved 1D screening of nitrate, phosphate, carbonate, and salt concentrations. The 1D screening results suggested that nitrate and/or phosphate may be limiting nutrients in standard cultivation media. Finally, we use 2D screening to determine the optimal N:P ratio of BG-11. Application of the improved medium composition in a high-density cultivation setup led to an increase in biomass yield of up to 15.7%. This study demonstrates that droplet-based microfluidics can decrease the volume required for cyanobacterial cultivation and screening up to a thousand times while significantly increasing the multiplexing capacity. Going forward, microfluidics have the potential to play a significant role in the industrial exploitation of cyanobacteria.