95 research outputs found

    Catalytic Ozonation of Toluene Using Chilean Natural Zeolite: The Key Role of Brønsted and Lewis Acid Sites

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    The influence of surface physical-chemical characteristics of Chilean natural zeolite on the catalytic ozonation of toluene is presented in this article. Surface characteristics of natural zeolite were modified by acid treatment with hydrochloric acid and ion-exchange with ammonium sulphate. Prior to catalytic ozonation assays, natural and chemically modified zeolite samples were thermally treated at 623 and 823 K in order to enhance Brønsted and Lewis acid sites formation, respectively. Natural and modified zeolite samples were characterised by N2 adsorption at 77 K, elemental analysis, X-ray fluorescence, and Fourier transform infrared (FTIR) spectroscopy, using pyridine as a probe molecule. The highest values of the reaction rate of toluene oxidation were observed when NH4Z1 and 2NH4Z1 zeolite samples were used. Those samples registered the highest density values of Lewis acid sites compared to other samples used here. Results indicate that the presence of strong Lewis acid sites at the 2NH4Z1 zeolite surface causes an increase in the reaction rate of toluene oxidation, confirming the role of Lewis acid sites during the catalytic ozonation of toluene at room temperature. Lewis acid sites decompose gaseous ozone into atomic oxygen, which reacts with the adsorbed toluene at Brønsted acid sites. On the other hand, no significant contribution of Brønsted acid sites on the reaction rate was registered when NH4Z1 and 2NH4Z1 zeolite samples were use

    Measurement of the cosmic ray spectrum above 4×10184{\times}10^{18} eV using inclined events detected with the Pierre Auger Observatory

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    A measurement of the cosmic-ray spectrum for energies exceeding 4×10184{\times}10^{18} eV is presented, which is based on the analysis of showers with zenith angles greater than 6060^{\circ} detected with the Pierre Auger Observatory between 1 January 2004 and 31 December 2013. The measured spectrum confirms a flux suppression at the highest energies. Above 5.3×10185.3{\times}10^{18} eV, the "ankle", the flux can be described by a power law EγE^{-\gamma} with index γ=2.70±0.02(stat)±0.1(sys)\gamma=2.70 \pm 0.02 \,\text{(stat)} \pm 0.1\,\text{(sys)} followed by a smooth suppression region. For the energy (EsE_\text{s}) at which the spectral flux has fallen to one-half of its extrapolated value in the absence of suppression, we find Es=(5.12±0.25(stat)1.2+1.0(sys))×1019E_\text{s}=(5.12\pm0.25\,\text{(stat)}^{+1.0}_{-1.2}\,\text{(sys)}){\times}10^{19} eV.Comment: Replaced with published version. Added journal reference and DO

    Energy Estimation of Cosmic Rays with the Engineering Radio Array of the Pierre Auger Observatory

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    The Auger Engineering Radio Array (AERA) is part of the Pierre Auger Observatory and is used to detect the radio emission of cosmic-ray air showers. These observations are compared to the data of the surface detector stations of the Observatory, which provide well-calibrated information on the cosmic-ray energies and arrival directions. The response of the radio stations in the 30 to 80 MHz regime has been thoroughly calibrated to enable the reconstruction of the incoming electric field. For the latter, the energy deposit per area is determined from the radio pulses at each observer position and is interpolated using a two-dimensional function that takes into account signal asymmetries due to interference between the geomagnetic and charge-excess emission components. The spatial integral over the signal distribution gives a direct measurement of the energy transferred from the primary cosmic ray into radio emission in the AERA frequency range. We measure 15.8 MeV of radiation energy for a 1 EeV air shower arriving perpendicularly to the geomagnetic field. This radiation energy -- corrected for geometrical effects -- is used as a cosmic-ray energy estimator. Performing an absolute energy calibration against the surface-detector information, we observe that this radio-energy estimator scales quadratically with the cosmic-ray energy as expected for coherent emission. We find an energy resolution of the radio reconstruction of 22% for the data set and 17% for a high-quality subset containing only events with at least five radio stations with signal.Comment: Replaced with published version. Added journal reference and DO

    Measurement of the Radiation Energy in the Radio Signal of Extensive Air Showers as a Universal Estimator of Cosmic-Ray Energy

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    We measure the energy emitted by extensive air showers in the form of radio emission in the frequency range from 30 to 80 MHz. Exploiting the accurate energy scale of the Pierre Auger Observatory, we obtain a radiation energy of 15.8 \pm 0.7 (stat) \pm 6.7 (sys) MeV for cosmic rays with an energy of 1 EeV arriving perpendicularly to a geomagnetic field of 0.24 G, scaling quadratically with the cosmic-ray energy. A comparison with predictions from state-of-the-art first-principle calculations shows agreement with our measurement. The radiation energy provides direct access to the calorimetric energy in the electromagnetic cascade of extensive air showers. Comparison with our result thus allows the direct calibration of any cosmic-ray radio detector against the well-established energy scale of the Pierre Auger Observatory.Comment: Replaced with published version. Added journal reference and DOI. Supplemental material in the ancillary file

    First results from the AugerPrime Radio Detector

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    Update of the Offline Framework for AugerPrime

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    Extraction of the Muon Signals Recorded with the Surface Detector of the Pierre Auger Observatory Using Recurrent Neural Networks

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    We present a method based on the use of Recurrent Neural Networks to extract the muon component from the time traces registered with water-Cherenkov detector (WCD) stations of the Surface Detector of the Pierre Auger Observatory. The design of the WCDs does not allow to separate the contribution of muons to the time traces obtained from the WCDs from those of photons, electrons and positrons for all events. Separating the muon and electromagnetic components is crucial for the determination of the nature of the primary cosmic rays and properties of the hadronic interactions at ultra-high energies. We trained a neural network to extract the muon and the electromagnetic components from the WCD traces using a large set of simulated air showers, with around 450 000 simulated events. For training and evaluating the performance of the neural network, simulated events with energies between 1018.5, eV and 1020 eV and zenith angles below 60 degrees were used. We also study the performance of this method on experimental data of the Pierre Auger Observatory and show that our predicted muon lateral distributions agree with the parameterizations obtained by the AGASA collaboration

    Event-by-event reconstruction of the shower maximum XmaxX_{\mathrm{max}} with the Surface Detector of the Pierre Auger Observatory using deep learning

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