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Tin dioxide is the most commonly used material in commercial gas sensors based on semiconducting metal oxides. Despite intensive efforts, the mechanism responsible for gas-sensing effects on SnO(2) is not fully understood. The key step is the understanding of the electronic response of SnO(2) in the presence of background oxygen. For a long time, oxygen interaction with SnO(2) has been treated within the framework of the "ionosorption theory". The adsorbed oxygen species have been regarded as free oxygen ions electrostatically stabilized on the surface (with no local chemical bond formation). A contradiction, however, arises when connecting this scenario to spectroscopic findings. Despite trying for a long time, there has not been any convincing spectroscopic evidence for "ionosorbed" oxygen species. Neither superoxide ions O(2)(-), nor charged atomic oxygen O,(-) nor peroxide ions O(2)(2-) have been observed on SnO(2) under the real working conditions of sensors. Moreover, several findings show that the superoxide ion does not undergo transformations into charged atomic oxygen at the surface, and represents a dead-end form of low-temperature oxygen adsorption on reduced metal oxide.

The mechanistic description of gas sensing on inorganic, organic, and polymeric materials is of great scientific and technological interest. The understanding of surface and bulk reactions responsible for gas-sensing effects will lead to increased selectivity and sensitivity in the chemical determination of gases and thus to the development of better sensors. In recent years, spectroscopic tools have been developed to follow the physicochemical processes taking place in an active sensing element in real time and under operating conditions. Thus, the monitoring of the processes in "living" gas sensors is no longer an unsolvable problem. This Review gives an overview of in situ and operando spectroscopic techniques for the study of gas-sensing mechanisms on solid-state sensors.

Anisotropy is a basic property of single crystals. Dissimilar facets/surfaces have different geometric and electronic structure that results in dissimilar functional properties. Several case studies unambiguously demonstrated that the gas sensing activity of metal oxides is determined by the nature of surfaces exposed to ambient gas. Accordingly, a control over crystal morphology, i.e. over the angular relationships, size and shape of faces in a crystal, is required for the development of better sensors with increased selectivity and sensitivity in the chemical determination of gases. The first step toward this nanomorphological control of the gas sensing properties is the design and synthesis of well-defined nanocrystals which are uniform in size, shape and surface structure. These materials possess the planes of the symmetrical set {hkl} and must therefore behave identically in chemical reactions and adsorption processes. Because of these characteristics, the form-controlled nanocrystals are ideal candidates for fundamental studies of mechanisms of gas sensing which should involve (i) gas sensing measurements on specific surfaces, (ii) their atomistic/quantum chemical modelling and (ii) spectroscopic information obtained on same surfaces under operation conditions of sensors.

This Editorial is intended for materials scientists interested in performing machine learning-centered research. We cover broad guidelines and best practices regarding the obtaining and treatment of data, feature engineering, model training, validation, evaluation and comparison, popular repositories for materials data and benchmarking datasets, model and architecture sharing, and finally publication.In addition, we include interactive Jupyter notebooks with example Python code to demonstrate some of the concepts, workflows, and best practices discussed. Overall, the data-driven methods and machine learning workflows and considerations are presented in a simple way, allowing interested readers to more intelligently guide their machine learning research using the suggested references, best practices, and their own materials domain expertise. File list (2) download file view on ChemRxiv BestPractices_submitted.pdf (2.22 MiB) download file view on ChemRxiv BestPractices paper-SI.pdf (3.00 MiB)

A nonaqueous approach that involves the reaction of tungsten isopropoxide with benzyl alcohol leads to tungsten oxide nanowire bundles without the use of any additional structure‐directing templates. The bundles consist of crystalline nanowires with highly uniform diameters of about 1 nm and aspect ratios exceeding 500 (see picture). Gas‐sensing tests show a high sensitivity to NO2.

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The simultaneous measurements of conductance and work function changes induced by gaseous ambient have been performed on α-Fe2O3 thick film polycrystalline samples kept at 280 °C and exposed to different gaseous atmospheres. The switching from n- to p-type conductivity on α-Fe2O3 is shown to have an electronic origin, which is due to the oxygen adsorption and formation of a surface inversion layer and, therefore, to the inversion of the surface conduction type. The modeling of the n–p switching is described in terms of conductance dependence on the band bending induced by gaseous ambient.