A microfabricated physical sensor for atmospheric mercury monitoring

Abstract A new microfabricated physical sensor for elemental gaseous mercury (Hg 0 ) determinations has been developed and experimentally tested by the authors. Hg 0 represents 90-99% of atmospheric mercury forms. The sensor is based on the technique of resistivity variation of thin gold film, characterised by high selectivity and absence of optical parts. The sensor consists of four identical thin gold film resistors mounted in Wheatstone bridge configuration. Two resistors work as sensitive elements and the others as reference, in order to minimise the influence of temperature variation. The absorption of Hg 0 on the gold film produces a change in the resistivity of the amalgam. Far from the saturation, this change is proportional to the amount of the absorbed Hg 0 . The adsorption behaviour of the sensor deposited by sputtering on two different substrates (glass and Printed Circuit Board (PCB)) have been investigated. The sensors showed to work in a large range of linearity and need a low power during the regeneration process. Sensors on glass and PCB substrates underwent numerous regeneration cycles without inflicting any mechanical or electrical damages to the resistors. The presented experimental results describe the features of both sensors pointing out advantages and drawbacks of the used substrates. The PCB substrate seems to have more suitable characteristics for developing a new mercury 'smart' sensor

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Anti-Allergic Cromones Inhibit Histamine and Eicosanoid Release from Activated Human and Murine Mast Cells by Releasing Annexin A1

PMCID: PMC3601088This is an open-access article distributed under the terms of the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited

How I turned my kitchen in a lab during the pandemic and its (non-)icy outcomes

Unwanted icing has major safety and economic repercussions on human activities, affecting means of transportation, infrastructures, and consumer goods. Compared to the common deicing methods in use today, intrinsically icephobic surfaces can decrease ice accumulation and formation without any active intervention from humans or machines. However, such systems often require complex fabrication methods and can be costly, which limits their applicability. In this study, we report the preparation and characterization of a series of slippery lubricant-infused porous surfaces (SLIPSs) realized by impregnating with silicone oil a candle soot layer deposited on double-sided 3M adhesive tape. Despite the use of common household items, these SLIPSs showed anti-icing performance comparable to other systems described in the literature (ice adhesion < 20 kPa) and a good resistance to mechanical and environmental damages. To improve the overall performances, we explored several design solution involving surface functionalization of the inner pores and the use of fluorinated lubricants. The use of a flexible and functional substrate as tape allowed these devices to be stretchable without suffering significant degradation and highlights how these systems can be easily prepared and applied anywhere needed. In addition, the possibility of deforming the substrate can pave the way for the application of SLIPS technology in mechanical ice removal methodologies, drastically incrementing their performanc

A neural network based intelligent predictive sensor for cloudiness, solar radiation and air temperature

Accurate measurements of global solar radiation and atmospheric temperature, as well as the availability of the predictions of their evolution over time, are important for different areas of applications, such as agriculture, renewable energy and energy management, or thermal comfort in buildings. For this reason, an intelligent, light-weight and portable sensor was developed, using artificial neural network models as the time-series predictor mechanisms. These have been identified with the aid of a procedure based on the multi-objective genetic algorithm. As cloudiness is the most significant factor affecting the solar radiation reaching a particular location on the Earth surface, it has great impact on the performance of predictive solar radiation models for that location. This work also represents one step towards the improvement of such models by using ground-to-sky hemispherical colour digital images as a means to estimate cloudiness by the fraction of visible sky corresponding to clouds and to clear sky. The implementation of predictive models in the prototype has been validated and the system is able to function reliably, providing measurements and four-hour forecasts of cloudiness, solar radiation and air temperature