Erratum: Kiselev, I., et al. On the Temporal Stability of Analyte Recognition with an E-Nose Based on a Metal Oxide Sensor Array in Practical Applications. Sensors 2018, 18, 550.

The authors wish to make the following corrections to this paper [...].

Long Slender Piezo-Resistive Silicon Microprobes for Fast Measurements of Roughness and Mechanical Properties inside Micro-Holes with Diameters below 100 µm.

During the past decade, piezo-resistive cantilever type silicon microprobes for high-speed roughness measurements inside high-aspect-ratio microstructures, like injection nozzles or critical gas nozzles have been developed. This article summarizes their metrological properties for fast roughness and shape measurements including noise, damping, tip form, tip wear, and probing forces and presents the first results on the measurement of mechanical surface parameters. Due to the small mass of the cantilever microprobes, roughness measurements at very high traverse speeds up to 15 mm/s are possible. At these high scanning speeds, considerable wear of the integrated silicon tips was observed in the past. In this paper, a new tip-testing artefact with rectangular grooves of different width was used to measure this wear and to measure the tip shape, which is needed for morphological filtering of the measured profiles and, thus, for accurate form measurements. To reduce tip wear, the integrated silicon tips were replaced by low-wear spherical diamond tips of a 2 µm radius. Currently, a compact microprobe device with an integrated feed-unit is being developed for high-speed roughness measurements on manufacturing machines. First measurements on sinusoidal artefacts were carried out successfully. Moreover, the first measurements of the elastic modulus of a polymer surface applying the contact resonance measurement principle are presented, which indicates the high potential of these microprobes for simultaneous high-speed roughness and mechanical parameter measurements.

On the Temporal Stability of Analyte Recognition with an E-Nose Based on a Metal Oxide Sensor Array in Practical Applications.

The paper deals with a functional instability of electronic nose (e-nose) units which significantly limits their real-life applications. Here we demonstrate how to approach this issue with example of an e-nose based on a metal oxide sensor array developed at the Karlsruhe Institute of Technology (Germany). We consider the instability of e-nose operation at different time scales ranging from minutes to many years. To test the e-nose we employ open-air and headspace sampling of analyte odors. The multivariate recognition algorithm to process the multisensor array signals is based on the linear discriminant analysis method. Accounting for the received results, we argue that the stability of device operation is mostly affected by accidental changes in the ambient air composition. To overcome instabilities, we introduce the add-training procedure which is found to successfully manage both the temporal changes of ambient and the drift of multisensor array properties, even long-term. The method can be easily implemented in practical applications of e-noses and improve prospects for device marketing.