A new effective way to degrade methylene blue by introducing negative ions powder into Fe3O4/H2O2 system to accelerate Fe(III)/Fe(II) transformation

Negative ions powders (NIP) have been widely applied in many fields because of their natural electric field and far infrared radiation, especially in wastewater treatment. In this study, the NIP was first introduced into Fe3O4/H2O2 system to degrade methylene blue (MB). The MB removal was completely achieved at 5 h via a non-photochemical pathway and the degradation rate constant of this system is about 0.565 h−1, which is about 16 times higher than in Fe3O4/H2O2 Fenton-like system (0.035 h−1). In addition, the results of quenching experiments indicate that the electron (e−) and negative oxygen ion (•O2−) are the main reactive species. It was determined that Fe3O4@NIP is the effective component that leads to the activation of H2O2 to produce •OH, which derive from the pathway: NIP acts as an electron donor to reduce Fe(III) into Fe(II). Moreover, NIP can produce negative ions, which is also conductive to degradation. This study suggests a promising direction for the practical application of NIP based catalysis by integrating it with the Fe(III)/Fe(II) transformation process.

Analysis of the Natural Electric Field at Different Sea Depths

The natural electric field at the depth of 0~1500 m in high seas of South China Sea is obtained by using a new type of measuring device. The electric field data in the frequency range of 0.01~0.5 Hz and 0.5~30 Hz are analyzed respectively. The results show that the induced electric field generated by the surface wave (about 0.14 Hz in the experiment) is obvious at the depth of 50 m but can be ignored at the depth greater than 100 m. When the depth increases from 50 m to 1500 m, the peak value of the natural electric field gradually decreases. At the depth of 1000 m, the peak value is 0.04~0.08 uV/m for electric field in 0.01~0.5 Hz, and 0.07~0.1 uV/m for electric field in 0.5~30 Hz. At last, the natural electric field in coastal waters near Sanya City where the water depth is 15 m is measured by means of a sinking device. The results show that, the peak value is about 2~4 uV/m for electric field in 0.01~0.5 Hz and 2 uV/m for electric field in 0.5~30 Hz. By comparing the natural electric field between high seas and coastal waters, we find the latter has a larger peak value than the former at nearly the same water depth. In addition, line spectrum noise often occurs in coastal waters while little line spectrum noise in high seas when the water depth is more than 50 m.

Automatic detection of the electron density from the WHISPER instrument onboard CLUSTER

<p>The Waves of HIgh frequency and Sounder for Probing Electron density by Relaxation (WHISPER) instrument, is part of the Wave Experiment Consortium (WEC) of the CLUSTER mission. The instrument consists basically of a receiver, a transmitter, and a wave spectrum analyzer. It delivers active (sounding) and natural electric field spectra. The characteristic signature of waves indicates the nature of the ambient plasma regime and, combined with the spacecraft position, reveals the different magnetospheric boundaries and regions. The electron density can be deduced from the characteristics of natural waves in natural mode and from the resonance triggered in the sounding mode. The electron density is a parameter of major scientific interest and is also commonly used for the calibration of the particles instruments.</p><p>Until recently, the electron density required a manual intervention consisting in visualizing input parameters from the experiments, such as the WHISPER active/passive spectrograms combined with the dataset from the other instruments onboard CLUSTER.</p><p>Work is being carried out to automatize the detection of the electron density using Machine Learning and Deep Learning methods.</p><p>To automate this process, knowledge of the region (plasma regime) is highly desirable. In order to try to determinate the different plasma regions, a Multi-Layer Perceptron has been implemented. This model consists of three neuronal network dense layers, with some additional dropout to prevent overfitting. For each detected region, a second Multi-Layer perceptron was implemented to determine the plasma frequency. This model has been trained with 100k spectra using the plasma frequency values manually found. The accuracy can reach until 98% in some plasma regions.</p><p>These models of the electron density automated determination are also currently applied on the dataset of the mutual impedance instrument (RPC-MIP) onboarded ROSETTA and will be useful for other space missions such as BepiColombo (especially for PWI/AM<sup>2</sup>P experiment) or JUICE (RPWI/MIME experiment).</p>

The map of permanent natural electric field of Russia

The article describes a direct connection between the natural electric potential and the dynamics of the temperature of volcanoes using the examples of observation of the natural electric potential on the surfaces of volcanoes. If the upper part of the volcano is hotter, positive potential anomalies are recorded, and conversely, if the lower part of the volcanoes is hotter, negative anomalies of the same potential are recorded. At the same time, the temperature processes occurring at great depths, as a rule, are closely related to long-lived deep faults. Therefore, observations of the natural potential over these faults will allow controlling the dynamics of deep temperature processes. Given this new direction of the natural potential method and its effective application in the search for non-ferrous metal ores, there is a need to create the map of the natural electrical potential of Russia. As a result, small-scale map would allow us more precise limitation of ore fields and purposefully search for previously undiscovered deposits of metal ores. In addition, a small-scale map would make it possible to most accurately track the development of deep tectonic fault zones and to study them in relation to volcanic activity and seismic events. In this regard, the method of natural electric potential hodograph is considered as one of the possible ways to predict seismic events.

Method of preview processing of the primary geoelectromagnetic data received from a modified geophysical automatic station

Preliminary processing of primary geophysical data, automatically transmitted from the regime geophysical station to the daily specific files confirmed the feasibility of using such approaches. The purpose of the research is to focus on the choice of simple methods of primary data processing and the development of appropriate mathematical models of the dynamics. The results of preliminary processing of the primary data obtained from the regime geophysical automatic station are submitted. Descriptive statistics and simulation of time series were used as processing methods. The presentation of the results by multidimensional graphs allowed to reveal the phenomenon of coincidence in the first indicators of descriptive statistics, and in the second, the coincidence of the model's coefficients for the daily measurements of the natural electric field

Disturbances of the Natural Electric Field in the Atmosphere Before Technogenic Earthquakes

Modern seismology attaches great importance to the methods of short-term earthquake forecasting. One of these methods is a method based on the registration of disturbances of the atmospheric electric field and the field arising in rocks before earthquakes. Until now, this problem is discussed at the level of hypotheses. The mechanism of perturbations is unclear and the literature does not provide any convincing evidence of the explanation of the observed phenomena – flashes and columns of light, breakdown of electric cables in the earth a few hours before the earthquake and other phenomena. In the present article on the basis of the phenomenon of fast cracks loading discovered in the nineties of the last century [1] the explanation of these phenomena is offered by the solution of a direct problem about an electric field of the hearth of technogenic earthquake in the atmosphere.