Characteristics of fluid inclusions in the Cenozoic volcanic-hosted Kushk-e-Bahram Manto-type Cu deposit of central Iran

The Kushk-e-Bahram Manto-type Cu deposit is located in central Iran, within Eocene to Oligo–Miocene volcanic strata which occur in the central part of the Uremia-Dokhtar Magmatic Arc (UDMA). Propylitization, silicification, argillization and carbonatization are the main types of alteration to have affected the pyroclastic and volcanic rocks. There are high amounts of oxide minerals, including malachite, azurite, hematite, magnetite and goethite. Three types of primary FIs have been determined in the Kushk-e-Bahram deposit, namely; I: two-phase liquid-rich FIs (L+V), II: mono-phase liquid FIs, III: two-phase vapour-rich FIs which have been identified based on petrographical studies. Based on FI studies of co-existing quartz and calcite, homogenization temperatures (Th) must have been between 67 and 228°C, with an average of 158°C. Moreover, salinity is between 14.0–30.3 wt% NaCl, equivalent to a 19.6% average. Fluid density values vary from 0.8 to 1.1 gr/cm3. Based on FI data and related diagrams, the depth of their trapping was estimated to be <200 m and ore formation occurred at pressures of <50 bars. Consequently, mineralogy, host rock and FIs characteristics in the Kushk-e-Bahram deposit are similar to the Manto-type Cu deposits in Mesozoic-Cenozoic volcanic belts of Iran and South America

Critical metals in Iran – geochemistry: exploration and analysis

Critical metals are fundamental to many 21st century processes and technologies. These elements are essential for maintaining and improving future quality of life, including many high-technology yet low-carbon industries. Two factors have been used by the NRC (National Research Council) to rank criticality: the degree to which a commodity is essential and the risk of supply disruption for the commodity (Verplanch and Hitzman, 2016). The European Union has identified twenty critical raw materials as critical metals (Ec, 2015). Many of these critical materials (including Rare Earth Elements (REEs), Platinum Group Elements (PGEs), Magnesium, Niobium, Germanium, Indium, Gallium, Cobalt, Borate, Tungsten, Fluorspar are important for high-technology, environmental protection and military applications, but vulnerable to politically or economically driven fluctuations in supply (Pirajno, 2009; Laznicka, 2010; Charalampides et al., 2015; Fernandez, 2017). Tin, Molybdenum and Lithium) are included as critical metals by several countries (e.g. Australia; Skirrow et al., 2013). Of course a number of other metals, which have not been assessed as critical, are also of significant importance for modern technologies – these include some of the alloy metals such as chromium, nickel and molybdenum

Combination of Machine Learning Algorithms with Concentration-Area Fractal Method for Soil Geochemical Anomaly Detection in Sediment-Hosted Irankuh Pb-Zn Deposit, Central Iran

Prediction of geochemical concentration values is essential in mineral exploration as it plays a principal role in the economic section. In this paper, four regression machine learning (ML) algorithms, such as K neighbor regressor (KNN), support vector regressor (SVR), gradient boosting regressor (GBR), and random forest regressor (RFR), have been trained to build our proposed hybrid ML (HML) model. Three metric measurements, including the correlation coefficient, mean absolute error (MAE), and means squared error (MSE), have been selected for model prediction performance. The final prediction of Pb and Zn grades is achieved using the HML model as they outperformed other algorithms by inheriting the advantages of individual regression models. Although the introduced regression algorithms can solve problems as single, non-complex, and robust regression models, the hybrid techniques can be used for the ore grade estimation with better performance. The required data are gathered from in situ soil. The objective of the recent study is to use the ML model’s prediction to classify Pb and Zn anomalies by concentration-area fractal modeling in the study area. Based on this fractal model results, there are five geochemical populations for both cases. These elements’ main anomalous regions were correlated with mining activities and core drilling data. The results indicate that our method is promising for predicting the ore elemental distribution

Sonophotocatalytic degradation of sulfadiazine by integration of microfibrillated carboxymethyl cellulose with Zn-Cu-Mg mixed metal hydroxide/g-C3N4 composite

This research aimed to prepare a recoverable sonophotocatalyst, in which microfibrillated carboxymethyl cellulose (MFC) acted as the Zn-Cu-Mg-mixed metal hydroxide/graphitic carbon nitride (MMH/g-C3N4) carrier. The characteristics of bare and composite sonophotocatalysts were analyzed by the XRD, FT-IR, BET, DRS, PL and FE-SEM equipped with the EDX mapping. The performance of prepared composites (MMH/g-C3N4@MFC) with various weight ratios of the MMH/g-C3N4 was studied for the sonophotocatalytic degradation of sulfadiazine (SDZ) as the model emerging contaminant. 93% of SDZ was degraded using the most effective catalyst (MMH/gC(3)N(4)@MFC3) with 15% weight ratio of the MMH/g-C3N4 under the desired operating conditions including solution pH of 6.5, SDZ concentration of 0.15 mM and ultrasonic power of 300 W. The MMH addition to the gC(3)N(4) structure increased the separation of charge carriers generated via the visible light or ultrasound irradiations. Moreover, the MMH/g-C3N4 was dispersed uniformly on the MFC and consequently, more active sites were available to form reactive oxygen species (ROS), compared to powder form. Hydroxyl radicals ((OH)-O-center dot) were determined as the main ROS in the SDZ degradation by performing a series of scavenging experiments. Less than 10% decrease in the degradation efficiency of SDZ was observed during five subsequent experiments, which indicated the proper retention of the MMH/g-C3N4 particles in the MFC. The adequate mineralization of SDZ (83% decrease in chemical oxygen demand (COD)) was obtained after 200 min of treatment. Eventually, ten degradation intermediates were identified by the GC-MS analysis and a plausible degradation mechanism for the contaminant was proposed.Peer reviewe

Geochemical Anomaly Detection in the Irankuh District Using Hybrid Machine Learning Technique and Fractal Modeling

Prediction of elemental concentrations is essential in mineral exploration as it plays a vital role in detailed exploration. New machine learning (ML) methods, such as hybrid models, are robust approaches infrequently used concerning other methods in this field; therefore, they have not been examined properly. In this study, a hybrid machine learning (HML) method was proposed based on combining K-Nearest Neighbor Regression (KNNR) and Random Forest Regression (RFR) to predict Pb and Zn grades in the Irankuh district, Sanandaj-Sirjan Zone.. The aim of the proposed study is to employ the hybrid model as a new method for grade distribution. The KNNR-RFR hybrid model results have been applied for the Pb and Zn anomalies classification. The hybrid (KNNR-RFR) method has shown more accurate prediction outputs based on the correlation coefficients than the single regression models with 0.66 and 0.54 correlation coefficients for Pb and Zn, respectively. The KNN-RF results were used to classify Pb and Zn anomalies in the study area. The concentration-area fractal model separated the main anomalous areas for these elements. The Pb and Zn main anomalies were correlated with mining activities and core drilling data. The current study demonstrates that the hybrid model has a substantial potential for the ore elemental distribution prediction. The presented model expresses a promising result and can predict ore grades in similar investigations

The role of ETG modes in JET-ILW pedestals with varying levels of power and fuelling

We present the results of GENE gyrokinetic calculations based on a series of JET-ITER-like-wall (ILW) type I ELMy H-mode discharges operating with similar experimental inputs but at different levels of power and gas fuelling. We show that turbulence due to electron-temperature-gradient (ETGs) modes produces a significant amount of heat flux in four JET-ILW discharges, and, when combined with neoclassical simulations, is able to reproduce the experimental heat flux for the two low gas pulses. The simulations plausibly reproduce the high-gas heat fluxes as well, although power balance analysis is complicated by short ELM cycles. By independently varying the normalised temperature gradients (omega(T)(e)) and normalised density gradients (omega(ne )) around their experimental values, we demonstrate that it is the ratio of these two quantities eta(e) = omega(Te)/omega(ne) that determines the location of the peak in the ETG growth rate and heat flux spectra. The heat flux increases rapidly as eta(e) increases above the experimental point, suggesting that ETGs limit the temperature gradient in these pulses. When quantities are normalised using the minor radius, only increases in omega(Te) produce appreciable increases in the ETG growth rates, as well as the largest increases in turbulent heat flux which follow scalings similar to that of critical balance theory. However, when the heat flux is normalised to the electron gyro-Bohm heat flux using the temperature gradient scale length L-Te, it follows a linear trend in correspondence with previous work by different authors

Spectroscopic camera analysis of the roles of molecularly assisted reaction chains during detachment in JET L-mode plasmas

The roles of the molecularly assisted ionization (MAI), recombination (MAR) and dissociation (MAD) reaction chains with respect to the purely atomic ionization and recombination processes were studied experimentally during detachment in low-confinement mode (L-mode) plasmas in JET with the help of experimentally inferred divertor plasma and neutral conditions, extracted previously from filtered camera observations of deuterium Balmer emission, and the reaction coefficients provided by the ADAS, AMJUEL and H2VIBR atomic and molecular databases. The direct contribution of MAI and MAR in the outer divertor particle balance was found to be inferior to the electron-atom ionization (EAI) and electron-ion recombination (EIR). Near the outer strike point, a strong atom source due to the D+2-driven MAD was, however, observed to correlate with the onset of detachment at outer strike point temperatures of Te,osp = 0.9-2.0 eV via increased plasma-neutral interactions before the increasing dominance of EIR at Te,osp &lt; 0.9 eV, followed by increasing degree of detachment. The analysis was supported by predictions from EDGE2D-EIRENE simulations which were in qualitative agreement with the experimental observations

Shattered pellet injection experiments at JET in support of the ITER disruption mitigation system design

A series of experiments have been executed at JET to assess the efficacy of the newly installed shattered pellet injection (SPI) system in mitigating the effects of disruptions. Issues, important for the ITER disruption mitigation system, such as thermal load mitigation, avoidance of runaway electron (RE) formation, radiation asymmetries during thermal quench mitigation, electromagnetic load control and RE energy dissipation have been addressed over a large parameter range. The efficiency of the mitigation has been examined for the various SPI injection strategies. The paper summarises the results from these JET SPI experiments and discusses their implications for the ITER disruption mitigation scheme

New H-mode regimes with small ELMs and high thermal confinement in the Joint European Torus

New H-mode regimes with high confinement, low core impurity accumulation, and small edge-localized mode perturbations have been obtained in magnetically confined plasmas at the Joint European Torus tokamak. Such regimes are achieved by means of optimized particle fueling conditions at high input power, current, and magnetic field, which lead to a self-organized state with a strong increase in rotation and ion temperature and a decrease in the edge density. An interplay between core and edge plasma regions leads to reduced turbulence levels and outward impurity convection. These results pave the way to an attractive alternative to the standard plasmas considered for fusion energy generation in a tokamak with a metallic wall environment such as the ones expected in ITER.&amp; nbsp;Published under an exclusive license by AIP Publishing