Random processes of the diffusion type have the property that microscopic fluctuations of the trajectory make possible the identification of certain statistical parameters from one continuous observation. The paper deals with the construction of parameter estimates when observations are made at discrete but very dense time points.
Intrinsically conducting polymer polypyrrole/polyester textile composites were prepared by in situ chemical oxidative polymerization of polypyrrole on a polyester fabric. As an oxidizing agent ferric chloride was used, p-toluenesulfonic acid was used as a dopant. Polymerization conditions (concentration of monomer, polymerization time and temperature) were investigated and optimized by the help of Design of experiment methodology to obtain fabric with electromagnetic shielding efficiency at least 12 dB for frequency 1.5 GHz. Moreover, weight increase, macroscopic color shade of images and scanning electron microscopy images of samples were evaluated. It was found that all selected factors and their interactions have statistically significant effect on resulting electromagnetic shielding effectiveness, whereas monomer concentration has the highest positive influence. Experimental data were used to derive an empirical model linking the output and inputs. Optimized parameters (polymerization temperature 6.7℃, polymerization time 10 h and monomer concentration 5.8 g/l) for creating polypyrrole/polyester textile composite with electromagnetic shielding ability higher than 12 dB were successfully verified.
The development of new fluorescent molecules and dyes requires precise determination of their emission efficiency, which ultimately defines the potential of the developed materials. For this, the photoluminescence quantum yield (QY) is commonly used, given by the ratio of the number of emitted and absorbed photons, where the latter can be determined by subtraction of the transmitted signal by the sample and by a blank reference. In this work, we show that when the measurement uncertainty is larger than 10% of the absorptance of the sample, the QY distribution function becomes skewed, which can result in underestimated QY values by more than 200%. We demonstrate this effect in great detail by simulation of the QY methodology that implements an integrating sphere, which is widely used commercially and for research. Based on our simulations, we show that this effect arises from the non-linear propagation of the measurement uncertainties. The observed effect applies to the measurement of any variable defined as Z = X/Y , with Y = U − V , where X, U and V are random, normally distributed parameters. For this general case, we derive the analytical expression and quantify the range in which the effect can be avoided.
Random processes of the diffusion type have the property that microscopic fluctuations of the trajectory make possible the identification of certain statistical parameters from one continuous observation. The paper deals with the construction of parameter estimates when observations are made at discrete but very dense time points.
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