Single wall carbon nanotubes loaded with Pd and NiPd nanoparticles for H2 sensing at room temperature

Pd and bimetallic Ni50Pd50 nanoparticles protected by polyvinylpyrrolidone (PVP) have been synthesized by the reduction-by-solvent method and deposited on single wall carbon nanotubes (SWCNTs) to be tested as H2 sensors. The SWCNTs were deposited by drop casting from different suspensions. The Pd nanoparticles-based sensors show a very reproducible performance with good sensitivity and very low response times (few seconds) for different H2 concentrations, ranging from 0.2% to 5% vol. H2 in air at atmospheric pressure. The influence of the metal nanoparticle composition, the quality of SWCNTs suspension and the metal loading have been studied, observing that all these parameters play an important role in the H2 sensor performance. Evidence for water formation during the H2 detection on Pd nanoparticles has been found, and its repercussion on the behaviour of the assembled sensors is discussed. The sensor preparation procedure detailed in this work has proven to be simple and reproducible to prepare cost-effective and highly efficient H2 sensors that perform very well under real application conditions.

Contribution to Real-Time Estimation of Crop Phenological States in a Dynamical Framework Based on NDVI Time Series: Data Fusion With SAR and Temperature

In this study, a methodology based in a dynamical framework is proposed to incorporate additional sources of information to normalized difference vegetation index (NDVI) time series of agricultural observations for a phenological state estimation application. The proposed implementation is based on the particle filter (PF) scheme that is able to integrate multiple sources of data. Moreover, the dynamics-led design is able to conduct real-time (online) estimations, i.e., without requiring to wait until the end of the campaign. The evaluation of the algorithm is performed by estimating the phenological states over a set of rice fields in Seville (SW, Spain). A Landsat-5/7 NDVI series of images is complemented with two distinct sources of information: SAR images from the TerraSAR-X satellite and air temperature information from a ground-based station. An improvement in the overall estimation accuracy is obtained, especially when the time series of NDVI data is incomplete. Evaluations on the sensitivity to different development intervals and on the mitigation of discontinuities of the time series are also addressed in this work, demonstrating the benefits of this data fusion approach based on the dynamic systems.