The catalytic hydrogenation of the LOHC compound dibenzyltoluene (H0-DBT) was investigated by 1 H NMR spectroscopy in order to elucidate the reaction pathway of its charging process with hydrogen in the
Our
contribution demonstrates that the combination of additive
manufacturing and electrophoretic deposition offers great potential
for the future manufacturing of tailor-made catalytic structures for
continuous flow applications. A new protocol for the controlled and
homogeneous coating of both electrodes of interpenetrating porous
open cell structures (interPOCS) with layers of boehmite is presented.
Moreover, it has been found that by applying different coating voltages
in an electrophoretic deposition (EPD) process, the properties of
the obtained coating can be fine-tuned with respect to layer thickness,
density, and porosity. This offers very interesting options for optimizing
the catalysis-relevant properties from two sides by the use of the
special interPOCS support design and by adjusting the coating through
the parameters of the EPD coating process.
The purpose of this article is to summarize recent research results for constructing nonparametric multivariate control charts with main focus on data depth-based control charts. Data depth provides dimension reduction to high-dimensional problems in a completely nonparametric way. Several depth measures including Tukey depth are shown to be particularly effective for purposes of statistical process control in case that the data deviate normality assumption. For detecting small or moderate shifts in the process target mean, the multivariate version of the exponentially weighted moving average chart is generally robust to non-normal data, so that nonparametric alternatives may be less often required.for the sample size n of the subgroup. The UCL is used to monitor future subgroups in Phase II. If the underlying input data are from the multivariate normal distribution, then the T 2 statistic is appropriate, and the multivariate problem can be conveniently reduced to a single-variable test. Along with the normality assumption, Hotelling's T 2 control chart relies Appl. Stochastic Models Bus. Ind. 2016, 32 660-676Figure 4. T 2 control chart and nonparametric Q-chart for an example with 20 periods (subgroups of n = 4) of observed p = 5 variate data. The process becomes out of control after 10 periods (upper control limits are presented by the dashed lines).
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