Introduction The selective detection with high spatio-temporal resolution of hydrocarbons leakage as a result of pipelines inconsistency is a valid industrial demand [1]. Perspectives are associated with deployment of distributed networks of chemical sensors, transferring data on ambience pollution to the data processing center [2]. Miniature micromachined metal oxide semiconductor gas sensors possess a great perspective of practical use in this regard, however their long term operation in real atmosphere conditions requires improvement [3]. In this work we demonstrate improved selectivity of propane vs. methane detection in low concentrations in the ambient air of highly urbanized location by the SnO2-based semiconductor gas sensors with the modulated working temperature, using statistical analysis of “sensor response/sensor working temperature” shape representation. The obtained results of gases discrimination with artificial neural network (ANN) machine learning algorithm, used such pre-treated data as input samples, demonstrate advantages over similar classification methods without signal pre-processing, or pre-processing with previously reported methods of PCA, wavelet transformation and polynomial curve approximation. Sensor fabrication, data collection and processing Three SnO2-based materials have been used – pure SnO2, gold-modified SnO2 and bimetallic Au and Pd modified SnO2. The gas sensing materials synthesis via single step flame spray pyrolysis technique and sensors fabrication has been reported in a recent paper [4]. A fixed air flow from outside of the building of the Department of Chemistry of Moscow State University through PTFE sensor chamber was used as a background. Methane or propane were admixed to the background air flow through precise mass-flow controllers in three different concentrations from certified gas bottles. Sensors were operated in a working temperature modulation mode between 500 oC and 150 oC with period length of 60 sec. Sensitive layer resistance was measured with the 10 Hz frequency. Collected data was separated in two parts: first, collected in December 2018 was used for data processing algorithms training. Second, collected during January and February 2019, was used for the testing of elaborated data processing models. The total data set of 22440 measurement cycles,11220 of which represent an ambient air, while two data subsets of 5610 measurement cycles represent same air with admixture of methane or propane, were used for processing. The multilayer perceptron ANN-model with 2 hidden dense layers has been used for data processing model development and gases discrimination. The batch normalization and dropout techniques were implemented to avoid model overfitting. According to statistical shape analysis approach, each characteristic point of sensor response is characterized by certain gas sensor working temperature and sensitive layer resistance. All characteristic points of each single measurement cycle during analysis are converted into Kendall’s pre-shape space with removed translation and scaling factor, but with remaining rotation as well as the shape. During further processing the data samples are projected onto the unit-sphere with a pole of mean shape of sensor responses towards air without additives. Later inverse transformation of data samples leads to icon representation of response shape, eliminating possible effects of sensor baseline and response amplitude drift. Results and Conclusions Direct application of collected data to artificial neural network algorithm for methane vs. propane selective detection without any pre-processing gives a decent level of accuracy (Fig.1). However, it can be seen by the rise of discrimination error after normalization of data samples, that the main component of the sensors response, used by algorithm for gases discrimination, is of amplitude nature. It means, that the developed signal processing model may work in unstable manner when any additional gas is involved in the measurements. The use of statistical shape analysis allows to significantly improve the accuracy of discrimination of methane vs. propane in comparison with other pre-processing techniques. The remained error of gases identification is mostly related to the single day of measurements, which is associated with urban air pollution during winter heating season. References [1] L.E. Mujica; M. Ruiz; J.M. Mejia, Leak Detection and Localization on Hydrocarbon Transportation Lines by Combining Real-time Transient Model and Multivariate Statistical Analysis. Struct Hlth Monit 2015, 2350-2357. doi: 10.12783/SHM2015/292 [2] D. Spirjakin; A.M. Baranov; A. Somov; V. Sleptsov, Investigation of heating profiles and optimization of power consumption of gas sensors for wireless sensor networks. Sensor Actuat a-Phys 2016, 247, 247-253, doi:10.1016/j.sna.2016.05.049. [3] Collier-Oxandale, A.M.; Thorson, J.; Halliday, H.; Milford, J.; Hannigan, M. Understanding the ability of low-cost MOx sensors to quantify ambient VOCs. Atmos Meas Tech 2019, 12, 1441-1460, doi:10.5194/amt-12-1441-2019. [4] Krivetskiy, V.; Zamanskiy, K.; Beltyukov, A.; Asachenko, A.; Topchiy, M.; Nechaev, M.; Garshev, A.; Krotova, A.; Filatova, D.; Maslakov, K., et al. Effect of AuPd Bimetal Sensitization on Gas Sensing Performance of Nanocrystalline SnO2 Obtained by Single Step Flame Spray Pyrolysis. Nanomaterials-Basel 2019, 9, doi:10.3390/nano9050728. Figure 1
Continuous monitoring of greenhouse gases with high spatio-temporal resolution has lately become an urgent task because of tightening environmental restrictions. It may be addressed with an economically efficient solution, based on semiconductor metal oxide gas sensors. In the present work, CO2 detection in the relevant concentration range and ambient conditions was successfully effectuated by fine-particulate La2O3-based materials. Flame spray pyrolysis technique was used for the synthesis of sensitive materials, which were studied with X-ray diffraction (XRD), Fourier-transform infrared spectroscopy (FTIR), diffuse reflectance infrared Fourier transform spectroscopy (DRIFTs) and low temperature nitrogen adsorption coupled with Brunauer–Emmett–Teller (BET) effective surface area calculation methodology. The obtained materials represent a composite of lanthanum oxide, hydroxide and carbonate phases. The positive correlation has been established between the carbonate content in the as prepared materials and their sensor response towards CO2. Small dimensional planar MEMS micro-hotplates with low energy consumption were used for gas sensor fabrication through inkjet printing. The sensors showed highly selective CO2 detection in the range of 200–6667 ppm in humid air compared with pollutant gases (H2 50 ppm, CH4 100 ppm, NO2 1 ppm, NO 1 ppm, NH3 20 ppm, H2S 1 ppm, SO2 1 ppm), typical for the atmospheric air of urbanized and industrial area.
Introduction The detection of volatile organic compounds (VOCs), such as acetone, ethanol or formaldehyde is a relevant practical task [1]. Enhanced sensitivity towards such gases has been reported periously for ZnO based nanomaterials, modified with Co3O4 phase [1-3]. However, the reported techniques of such nanocomposites fabrication are usually involve several stages, are time and labor consuming and barely scalable [1-5]. In this work we demonstrate facile single step synthesis and improved sensitivity towards wide range of gases in dry and humid air conditions of ZnO-Co3O4 nanocomposites. Long term stability of obtained nanoparticle materials gas sensor response is demonstrated. Materials synthesis, characterization and sensor measurements A series of ZnO based materials were obtained by flame spray pyrolysis technique, described elsewhere [6]. Zn (II) and Co (II) 2-ethylhexanoates were taken as a precursors, which were diluted in toluene in 1:4 ratio by volume. Toluene also served as a fuel. Co (II) 2-ethylhexanoate has been taken in a calculated amount to form 1, 5 and 20% mol Co containing nanocomposite based on ZnO. Mixture of precursors and fuel was fed with 3 ml/min pace to a spray nozzle, where it was dispersed with 3 ml/min oxygen flow at a pressure drop of 3 bar. The nano-powders, forming during synthesis, were collected on a glass fiber filter 75 cm above the nozzle with the use of vacuum pump. During separate synthetic procedure the obtained materials were directly deposited on ceramic alumina plates, fixed at 19 cm above the nozzle on water-cooled surface. Plates were equipped with platinum contacts on one side and platinum heating element on the other, used by us in the previous work [6]. Micro-hotplates with the deposited sensitive element were welded in TO-8 case and used in further gas sensor measurements as is. One sample of alumina plate with deposit for each material were passed through 24h annealing at 500 oC and then used in sensor measurements alongside the sensors with as prepared sensitive films. Powders of synthesized materials were investigated by XRD, BET, TEM with EDX mapping, EPR techniques. Real chemical composition of obtained samples was investigated by ICP-MS method. The interaction of obtained nanoparticulate matter with VOC molecules was studied by in situ DRIFTs and Raman spectroscopy, as well as thermo-programmed desorption, coupled with mass-spectrometry. Results and Conclusions Increase in Co content leads to increase in sensor response towards VOCs, particularly oxygen-containing acetone and methanol (Fig. 1). At the same time this effect is observed only for the material with lowest Co content in case of hydrogen detection. Moreover, the sensor response towards methanol and propane decreases once sensor working temperature exceeds 400 oC in case of nanocomposite with highest Co content. TEM micrograph with EDX mapping shows uniform distribution of Co over ZnO matrix. XRD analysis indicates formation of separate Co3O4 phase in case of material with 20 % mol Co content, while EPR results give a cue for formation of both Co (II) substitutional defect in ZnO matrix as well as Co3O4 phase formation. This allows to conclude that introduction of Co in ZnO based nanocomposite has both electrical and chemical beneficial effects on metal oxide gas sensor performance, especially towards oxygen-containing VOCs. Thermal annealing at 500 oC prior to gas sensor measurements leads to response decrease of thus prepared sensitive layers, however, the resulting response is preserved over long-term operation even in high humidity conditions. Gas sensor, fabricated on the basis of sensitive layers without pre-annealing step, demonstrate slow drift of response value during long-term operation. References [1] Y. Sun, Z. Wang, W. Wang, G. Li, P. Li, K. Lian, W. Zhang, S. Zhuiykov, J. Hu, L. Chen, Electrospinning preparation of Pd@Co3O4-ZnO composite nanofibers and their highly enhanced VOC sensing properties, Materials Research Bulletin 2019, 109, 255-264. doi:10.1016/j.materresbull.2018.10.001 [2] L. Zhang, X. Jing, J. Liu, J. Wang, Y. Sun, Facile synthesis of mesoporous ZnO/Co3O4 microspheres with enhanced gas-sensing for ethanol, Sensors and Actuators B: Chemical, 2015, 221, 1492-1498. doi:10.1016/j.snb.2015.07.113. [3] S. Bai, J. Guo, X. Shu, X. Xiang, R. Luo, D. Li, A. Chen, C. C. Liu, Surface functionalization of Co3O4 hollow spheres with ZnO nanoparticles for modulating sensing properties of formaldehyde, Sensors and Actuators B: Chemical, 2017, 245, 359-368. doi:10.1016/j.snb.2017.01.102. [4] X. Gao, F. Li, R. Wang, T. Zhang, A formaldehyde sensor: Significant role of p-n heterojunction in gas-sensitive core-shell nanofibers, Sensors and Actuators B: Chemical, 2018, 258, 1230-1241. doi:10.1016/j.snb.2017.11.088. [5] J. Sun, L. Sun, S. Bai, H. Fu, J. Guo, Y. Feng, R. Luo, D. Li, A. Chen, Pyrolyzing Co/Zn bimetallic organic framework to form p-n heterojunction of Co3O4/ZnO for detection of formaldehyde, Sensors and Actuators B: Chemical, 2019, 285, 291-301, doi: org/10.1016/j.snb.2018.12.080. [6] Krivetskiy, V.; Zamanskiy, K.; Beltyukov, A.; Asachenko, A.; Topchiy, M.; Nechaev, M.; Garshev, A.; Krotova, A.; Filatova, D.; Maslakov, K., et al. Effect of AuPd Bimetal Sensitization on Gas Sensing Performance of Nanocrystalline SnO2 Obtained by Single Step Flame Spray Pyrolysis. Nanomaterials-Basel 2019, 9, doi:10.3390/nano9050728. Figure 1
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