RESUMO
Organometal halide perovskite materials have triggered enormous attention for a wide range of high-performance optoelectronic devices. However, their stability and toxicity are major bottleneck challenges for practical applications. Substituting toxic heavy metal, that is, lead (Pb), with other environmentally benign elements, for example, tin (Sn), could be a potential solution to address the toxicity issue. Nevertheless, even worse stability of Sn-based perovskite material than Pb-based perovskite poses a great challenge for further device fabrication. In this work, for the first time, three-dimensional CH3NH3SnI3 perovskite nanowire arrays were fabricated in nanoengineering templates, which can address nanowire integration and stability issues at the same time. Also, nanowire photodetectors have been fabricated and characterized. Intriguingly, it was discovered that as the nanowires are embedded in mechanically and chemically robust templates, the material decay process has been dramatically slowed down by up to 840 times, as compared with a planar thin film. This significant improvement on stability can be attributed to the effective blockage of diffusion of water and oxygen molecules within the templates. These results clearly demonstrate a new and alternative strategy to address the stability issue of perovskite materials, which is the major roadblock for high-performance optoelectronics.
RESUMO
A new anode material, Ru-SrMo0.9O3-δ, with a perovskite structure and segregated metallic Ru, has been tested in an intermediate-temperature solid oxide fuel cell (IT-SOFC) in an electrolyte-supported configuration giving substantial power densities as high as 840 mW/cm2 at 850 °C using pure H2 as fuel. This material has been prepared by the citrate method and structurally and microstructurally characterized at room temperature by different techniques such as X-ray diffraction (XRD), neutron powder diffraction (NPD), scanning electron microscopy (SEM), and scanning transmission electron microscopy (STEM). NPD was very useful to determine oxygen positions and vacancies, unveiling a cubic and oxygen-deficient perovskite SrMo0.9O3-δ oxide with a Pm-3m space group and potential ionic mobility. On the other hand, SEM and STEM studies have allowed to identify metallic segregated Ru nanoparticles providing the material with an excellent catalytic activity. Other properties such as the thermal expansion coefficient (TEC) and chemical compatibility with other cell components or electrical conductivity have also been studied to understand the excellent performance of this material as anode in IT-SOFC and correlate it with the crystallographic structure.
RESUMO
Solvent treatment is critical to improving the stability of halide perovskite materials that suffer from notorious issues that inhibit their industrial deployment; however, the complicated perovskite virtual design space with different types of solvent modifiers is inaccessible to traditional trial-and-error methods. In this study, machine learning is employed to predict stable multiple solvent-modified perovskite films under hostile conditions, and a complicated quinary solvent system "DMSO + DMF + toluene + NMP + GBL" is effectively identified to significantly improve the optoelectronic stability of CH3NH3PbI3 in water. The "combinatorial solvent design" approach is realized by an extra tree machine learning model, which leads to a prediction dataset containing aqueous stability labels of 6720 new quinary solvent/perovskite systems. Importantly, the accuracy of the machine learning model is verified via photoelectrochemical experiments, achieving an experimental accuracy of 80%. A machine learning-predicted quinary solvent system offers significantly enhanced aqueous stability and 1000 times larger aqueous photocurrents, compared with the control CH3NH3PbI3 film under the same hostile conditions. This study demonstrates the efficacy of machine learning for solvent design toward stable halide perovskite materials under hostile conditions.
RESUMO
The modern development in the agricultural production has huge influential factors being highly beneficial and also includes some health hazards. Under the class of chlorophenols, 2,4,6-trichlorophenol is a widely used chemical which remains as a major pollutant in the environment. The detection of 2,4,6-trichlorophenol was initiated as a controlling measure to decrease the seriousness prevailing in the ecosystem. The electrochemical and UV-vis absorption sensing platform are simple and low-cost detection techniques with precise and sensitive analysis. Cadmium tin oxide integrated with the reduced graphene oxide was employed as a nanohybrid for the construction of the working electrode. The structural and morphological analysis confirmed the high degree of crystallinity of the nanocomposite with nanorod formation. The high surface area, with high charge carrier mobility, and increased electrical conductivity of the material boosted the 2,4,6-trichlorophenol detection. The active surface area was calculated to be 0.068 cm-1, 0.089 cm-1, 0.118 cm-1 and 0.146 cm-1 for all the modified electrodes. The resistance of the electrodes was about 91.4 Ω, 72.9 Ω, 48.8 Ω and 41.6 Ω. The linear range of 2,4,6-trichlorophenol was 0.019 µM-0.299 µM and 1.299 µM-1678.97 µM in electrochemical sensing and 10.99 µM-24.84 µM in UV detection. The obtained limit of detection with the formulation 3σ/SD was about 3.05 nM and 80 nM with sensitivity about 14.01 µA µM-1 cm-2. The real sample detection in environmental real samples showed good recovery results. The specific selectivity, good repeatability, reproducibility and stability analysis proves the good sensing parameters. Thus, the fabricated electrode is highly sufficient of sensing 2,4,6-trichlorophenol. These excellent features of the material can be applied for several other applications which will provide good performances.