High temperature oxidation behavior of CrMnFeCoNi high-entropy alloy was investigated in oxygen at 600-1100°C by thermogravimetric technique. The composition of each element is 20 at% in an experimental alloy. Oxidation rates observed by mass change measurement were generally smaller in comparison to those of each single element. The values of mass gains were slight larger against those of pure Ni or Ni-based superalloys at the same temperatures in oxygen. Mass gain curves almost obeyed on parabolic rate law, and had larger magnitudes as oxidation temperature increased. X-ray diffraction analysis revealed that the scale formed on the alloys consisted of Mn₂O₃ and Cr₂O₃. Although Mn originally has a larger oxidation rate, that of the CrMnFeCoNi alloy was relatively small because of protective nature of Fe-Cr spinel oxide film. One of the reasons was considered from the viewpoint of thermodynamics that Mn and Cr have larger negative Gibbs free energy change of oxidation reaction among the five elements of the alloy.

Highly mismatched alloys such as GaNAs demonstrate exotic electronic properties such as the splitting of the conduction bands (CB) into E_－ and E＋ sub-bands, and make them promising for novel application. However, the incorporation of nitrogen atoms in the host GaAs severely degrades the electro-optical properties of this alloy with added challenges of the precise control of the compositions. Here we focus on the effect of Sb doping on the compositional and electro-optical properties of GaNAs thin films grown by molecular beam epitaxy. Sb has enhanced the nitrogen incorporation rate significantly, and the precise control of the group-V atoms (N,As,Sb) is performed using a simple equation based on surface reaction model. While there were no distinguishable effect of Sb addition on the electro-optical properties of the E ＋ bands in GaNAs strained layers studied by laser-modulated photo-reflectance (PR) spectroscopy, marked improvement was observed when Sb was added to lattice-matched GaInNAs thin films. It is revealed that the N incorporation rate in both the GaInNAs and GaNAs system is affected by the Sb adatoms in the same manner. PR spectroscopy also revealed that the impact of Sb addition was significant on the epitaxial quality of the overgrown thin films that accompanied increased abruptness around the GaNAs/GaAs heterointerfaces. While deep localized states dominated the photo-luminescence (PL), and Sb showed only marginal impact on the defect distribution and the PL quality, Sb impact was prominent in improving the transport property of the electron mobility that was ascribed to the reduced potential fluctuation of the E_－band. The rate of potential fluctuation reduction was calculated even faster for the E＋ sub-bands.

Hydrogen production using renewable energy is regarded as a key technology to achieve sustainable society. But hydrogen has a low volumetric energy density and it’s difficult to storage and transport. Therefore, ammonia normally produced by the Haber-Bosch process with hydrogen and nitrogen attracts much attention as hydrogen carrier. Although ammonia is toxic, it has a low risk because we can detect it immediately due to its characteristic smell when it leaks. So, a direct ammonia fuel cell (DAFC) that directly generates electricity from ammonia is expected to be a new power generation system. Pt is used as an anode catalyst for ammonia oxidation reaction in DAFC, but an alternative one is required because it is expensive and deactivated by adsorbed N species. In this study, we focused on Pt alloy anodes. We chose Al, Cu and Ni as alloying elements. We have discovered the improvement of ammonia oxidation activity by alloying Pt with other elements. Especially, Pt-11.6at.%Al showed the highest ammonia oxidation current, 7.33 mA cm^-2, and it will be attractive candidate for DAFC.

(Bi_0.5L_0.5)(Fe_0.7Co_0.3)O₃ (L = La, Nd, Sm, Gd, Dy) thin films with ferromagnetism and ferroelectricity were fabricated using pulsed DC sputtering technique to obtain high saturation magnetization, perpendicular magnetic anisotropy and large magnetic Kerr effect. These magnetic properties are very important for realization of high performance magnetic devices driven by electric field. All (Bi_0.5L_0.5)(Fe_0.7Co_0.3)O₃ (L = La, Nd, Sm, Gd, Dy) thin films had relatively high saturation magnetization, perpendicular magnetic anisotropy and magnetic Kerr effect. Especially, (Bi_0.5Nd_0.5)(Fe_0.7Co_0.3)O₃ thin film had a very high saturation magnetization of 140 emu/cm³ (1.40×10⁵ A/m), a high perpendicular magnetic anisotropy of 2.6 at ratio of perpendicular coercivity against in-plane coercivity and (Bi_0.5La_0.5)(Fe_0.7Co_0.3)O₃ thin film had a very high magnetic Kerr rotation angle of 0.72°. These magnetic properties were excellent compared with the case of (Bi_0.5A_0.5)FeO₃ (A = Ca, Sr, Ba) thin films with the maximum value of 90 emu/cm³ (9.0×10⁴ A/m) (for saturation magnetization), 0.8 (for ratio of Perpendicular coercivity against in-plane coercivity) and 0.03° (for magnetic Kerr rotation angle) which were fabricated previously. These magnetic properties are very important for realization of high performance magnetic devices driven by electric field.

Magnetic crystals are physically important to know their intrinsic magnetic properties. Magnetic crystals are also technologically important and their creation has aided crystal growth significantly. Rareearth orthoferrites material (RFeO₃) is one of the major components used in manufacturing sophisticated gadgets. This study focuses on the growth and physical properties of the optically generated RFeO₃ (R=Y, Gd and Sm) single crystals. The floating zone method generates single crystals of 3-20 mm/h in the optical zone. The purity of the grown materials was confirmed from the Powder X-Ray Diffraction (PXRD) analysis. The addition of Gd to YFeO₃ increases the lattice parameters of the material. Magnetic properties of the grown crystal were studied between 20-700 K. At high temperature, two anomalous effects were observed, one at (T_SR=480 K) due to spin reorientation and the other is antiferromagnetic (AFM) to paramagnetic transitions at (T_N= 670 K). Bloch parameter was also calculated. Microhardness value decreases nonlinearly. When the applied load is greater than 1.96 N, there is a transition from palmqvist to median crack due to the plastic deformation of the crystal. Controllable magnetic and mechanical characteristics will help to enhance performance of magnetic devices.

In the present study, we discuss the platinum-group element (PGE) mineralization process in the Merensky Reef of the Limpopo mine, Eastern Limb of the Bushveld Complex, South Africa. The lithologies of an investigated drill core are norite and anorthosite with minor pyroxenite and chromitite. The Merensky Reef is hosted in pyroxenite with two chromitite layers and contains hydrothermal chlorite veinlets. Most of the platinum group minerals (PGMs) are found in interstitial sulfides and in euhedral orthopyroxene such as cooperite ([Pt,Pd,Ni]S), Pd-Au-Ag alloy and moncheite (Pt[Te,Bi]₂). Some PGMs such as kotulskite (Pd[TeBi]) and michenerite (PdBiTe) and hessite (Ag₂Te) are found in sulfide veinlets with alteration minerals. These results indicate that there are two stages of mineralization: magmatic PGE mineralization and later hydrothermal PGE mineralization.

Chrysotile is one of the asbestos types minerals and it is the fibrous form in nature. Also, chrysotile may cause health problems. Accordingly, it is better to be known whether chrysotile exists in a construction site in advance so that constructor can take a counter plan for worker health. However, identifying a small amount of chrysotile is very difficult. In a conventional way, experts quantify the amount of chrysotile by using a microscope and X-ray diffraction analysis. It is time-consuming and depends on individual skills. Speaking of identification techniques, it has been reported hyperspectral imaging and machine learning applications show good performance for mineral identification tasks. In this paper, a prediction model to identify chrysotile is trained with hyperspectral data of fibrous chrysotile and serpentine which is very similar to chrysotile. Finally, the model achieved 99.95% accuracy for test data. Then, the model has tested its identification capability by predicting hyperspectral data of the mixture of both serpentine and chrysotile that was unused in the training procedure and performed potential.

Generation of atmospheric arc plasma with some chemical activity is performed with a transferred type dc arc discharge. A commercially available welding torch is used with argon steam mixture as operation gas. As steam mol percentage increases in the mixture, input power to arc plasma increases and generated plasma appearance clearly changes. Spectroscopy analysis shows that complete dissociation of additional steam leads to increment of H and O radicals in the arc plasma.

Landslide awareness, especially in regions where natural disasters are always happening, is of the most extreme importance. To anticipate the disaster, several statistical methods have been proposed, but it is still unclear which one is more accurate. However, few studies have proposed a dependable method. These strategies are considered rather indiscriminate in this digital world where every study is based on the new technology. Thus, this study endeavors to identify landslides causative factors effectiveness and landslide susceptibility area by the geographic information system (GIS) and frequency ratio (FR) in central parts of Badakhshan province, Afghanistan, which is usually suffering from landslide hazards. The dataset which we have obtained from the Ministry of mines and petroleum of Afghanistan's will be used to track down the expected relationship of the area of the past landslides with landslides' causative variables within the study area for developing the landslide susceptibility map. To determine the major factors' affection to the landslides, spatial databases were constructed from landslides trigger factors related to the landslides those occurred from the data sets. The weight of each factor was estimated by the FR model to analyze their effectiveness in landslides hazard identification and construction of landslides susceptibility map. To verify the results, the constructed susceptibility map was compared with landslides area. The result showed susceptibility mapping of landslides using the GIS and FR model.

To mine in the underground, the method of blasting and blast hole drilling methods are mainly, and widely accepted. The hole drilling methods are done with rotary percussion drill. However, there are problems in terms of difficulty of operating and mining cost resulting from its failure occurs, and thus it is hard for mining companies to find a way of mining underground efficiently, profitability, and safely. From this background, it is necessary to build the early detection system for drill bit failure. This system needs the technology of CNN (Convolutional Neural Network Smart Mining, which is the process of using information, autonomy, and technology to improve safety, reduce operating costs, and improve mine site productivity. In this research, drilling vibration from rotary percussion drill is transmitted as acceleration waveform and used as input data for building the system. The data is collected replacing the kinds of diameter of bit or drilling condition. This data is for developing the model introduced CNN to detect the difference between Normal drilling and the other kinds of drilling with something error. For Firstly, batch of waveform data is input model as training data to make the model recognize the data pattern. Secondly, validation process confirms the correct answer rate against the training data, and then, the test for the model is practiced. Finally, by comparing each accuracy in phase of test from 4 types of models built with different kinds of data and the ideal way of the input waveform data is found.

This study focuses on the human ability to tolerate subtle differences in color and categorize similar colors into a single mass to enhance completely automated public turing test to tell computers and humans apart (CAPTCHA). First, an experiment was conducted to check whether the color selection condition could control the color categorization results. Consequently, it was clarified that when the selection condition was added, the color to be categorized changed, implying the possibility of controlling the categorized result. Subsequently, an investigation was conducted to clarify the range of liquid crystal display colors categorized as major color names. As a result, it was clarified that the hue angle size of the colors categorized by more than half of the participants was sometimes greater than the hue angle size between the primary and complementary colors. It was also clarified that among the categorized colors, there were categorized colors in the two color names. Finally, results from the first and second experiments were collated. It was confirmed that by using the categorized color range and selection conditions, it is possible to obtain an answer with a color name that is different from the original color name. These results suggest that the ability of humans to categorize similar colors into a single mass enhances CAPTCHA.

The enclosed space of an underground mining operation has issues, safety and productivity are concerns of utmost importance. As the danger increases as it goes deeper, there is a need for more technological innovation than now Smart mining is a general term for a new resource development technology that combines mining and ICT (Information and Communication Technology). As an example of smart mining, in this study, an in-situ stress monitoring system was developed, and demonstration test of the system in a mine was conducted. Wireless sensor networks (WSNs) have been proposed as a solution for environmental monitoring, worker position tracking, and additional functions. There are different types of WSN systems including “Wi-Fi” technology. This research proposes a communication system using the “Wi-Fi Ad Hoc, Direct” mode, in which data loggers and mobile terminals (i.e., smartphones) transfer data to each another. Data are transmitted from a fixed underground base unit to a worker’s mobile terminal. Next, these data transferred to a data logger in the surface once the worker leaves the mine. Hence, data wirelessly transmits between the surface and underground locations. Data communication range, transfer speed, and received signal strength indicator (RSSI) in different conditions were measured to verify feasibility of the system.

In recent years deep learning has gained a lot of popularity because of its ability to work on complex tasks. It has been used in many industries to optimize operations and to help in decision-making. Deep neural networks have often been referred to as ‘Black boxes’, that is they take inputs and give outputs with high accuracies without giving an insight into how they work. It is important to demystify deep neural networks to verify that they are looking at the correct patterns. This paper proposes the use of Gradient-Weighted Class Activation Mapping (Grad-CAM) to visualize the behavior of lithology identification models that use drill vibrations as input to a one- dimensional convolutional neural network (1D CNN). The lithology identification models, time acceleration, and frequency model had 99.8% and 99.0% classification accuracy. The models could distinguish between granite and marble rock based on vibration signatures. With the use of Grad-CAM, it was possible to make the 1D CNN models transparent by visualizing the regions of input that were important for predictions. The Grad-CAM results indicated that the lithology identification models successfully learned the significant frequencies contained in each rock's vibration signal.

The income and expenses of a mining project determine the project’s profitability. The income of the cash flow model is calculated by multiplying the selling price of the mineral and the reserves. Expenses represent the outcome-related section of the project. However, these three factors of profit determinants are highly uncertain. Real Option (RO) methodology was developed to account for these uncertainties. To date, the practice of this method has been limited as its application in mining needs to be more adaptable, especially regarding uncertainty drivers. Recently, the trend of RO research has been dominated by the effect of price and geological uncertainty, which affects the income of the mining project. Additionally, no research has been conducted to combine the uncertainties of both the income and expenses of a mining project. The Black Scholes Method and Lattice Valuation are two common RO approaches that measure a project with uncertainty. In this research, the stratified state aggregation (SSA) technique was used to determine the value of a mining project which considering economic, geological, and technical uncertainty. The SSA simulation approach is based on a Monte Carlo simulation. It is flexible in method construction, particularly in its adaptability to real-world uncertainties. The case study was conducted at a tin mining project at PT Timah Tbk, Indonesia, a short-term mine planning underwater mining projects. Price and cost uncertainty drivers have been calculated using the nature logarithmic of the historical data, while geological uncertainty has been measured using conditional simulation.In summary, uncertainties in mining can be modeled using RO; hence the SSA approach is conducted to evaluate multi-uncertainty as well as multi-stage mining. The incorporation of the uncertainty measurement is demonstrated, especially the income and expenses of cash flow parameters. Moreover, these uncertainties can be overcome by the management's flexibility to either hold or abandon the project.

A pre-treatment method for upgrading gold from a polymetallic gold-zinc-lead ore by flotation was studied. X-ray diffraction analysis of the gold sulfide ore showed that quartz, calcite, pyrite, sphalerite, and galena are the main constituents of the ore. The composition of the polymetallic ore contained 6.49 ppm Au, 3.48% Zn, 1.25% Pb, 17.98% Fe, and 20.36% S. Due to the complexity of the polymetallic ore, the gold recovery is generally low. The objective of this study is to develop a primary flotation process to recover gold in a bulk sulfide concentrate. The effects of particle size, collector type, flotation time, and the slurry pH on the recoveries and grades of gold, zinc, and lead were investigated. The developed flotation process consisted of rougher, scavenger, and cleaner stages. High recovery of gold was found to be linked with a high recovery of Pb which was achieved by the utilization of a mixture of collector AERO 7249 and PAX. The gold flotation kinetics were fast with more than 50% of gold recovered within 5 minutes of flotation. Under optimized flotation conditions with rougher, scavenger, and cleaner stages, a total gold recovery of 88.36 % and a final gold grade of 60.97 ppm were obtained. A total gold enrichment ratio of 9.4 was achieved, confirming the viability of the flotation method in upgrading the gold from the polymetallic sulfide ore prior to further processing.

The Raman spectral patterns of analyzed natural titanomagnetite samples revealed peaks at 670-680 cm^-1, 544-603 cm^-1, 407-495 cm^-1 and 373-392 cm^-1 that correspond to the A_1g, T_2g (2), T_2g (3) and E_g vibrational modes of the spinel Fd3m space group. Previous studies of titanomagnetite Raman spectra patterns have suggested the behavior of these peaks reflect the distribution of Fe²⁺-O, Fe³⁺-O and Ti⁴⁺-O bonds within the titanomagnetite crystal structure. The peak intensities of each vibrational modes are observed to be relative, reflecting the re-distribution of Fe²⁺ and Fe³⁺ in both the tetrahedral and octahedral sites as a function of Ti concentration. Existing titanomagnetite Raman spectroscopy studies are limited to analysis of synthetic titanomagnetite. In this study, Raman spectral patterns from natural titanomagnetite i.e., magnetite-ulvöspinel solid solution samples were analyzed to determine behavior of Raman spectrum peak positions and intensities due to changing content of Ti⁴⁺, Fe²⁺ and Fe³⁺.