• Journal of Nuclear Fuel Cycle and Waste Technology(JNFCWT)
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• v.19 no.2
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• pp.187-196
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• 2021

Chemical equilibrium calculations for multicomponent aqueous systems involving the reductive dissolution of magnetite (Fe₃O₄) with oxalic acid (H₂C₂O₄) were performed using the HSC Chemistry® version 9. They were conducted with an aqueous solution model based on the Pitzer's approach of one molality aqueous solution. The change in the amounts and activity coefficients of species and ions involved in the reactions as well as the solution pH at equilibrium was calculated while changing the amounts of raw materials (Fe₃O₄ and H₂C₂O₄) and the system temperature from 25℃ to 125℃. In particular, the conditions under which Fe₃O₄ is completely dissolved at high temperatures were determined by varying the raw amount of H₂C₂O₄ and the temperature for a given raw amount of Fe₃O₄ fed into the aqueous solution. When the raw amount of H₂C₂O₄ added was small for a given raw amount of Fe₃O₄, no undissolved Fe₃O₄ was present in the solution and the pH of the solution increased significantly. The formation of ferrous oxalate complex (FeC₂O₄) was observed. The equilibrium amount of FeC₂O₄ decreased as the raw amount of H₂C₂O₄ increased.

• Korean Journal of Materials Research
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• v.33 no.5
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• pp.175-188
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• 2023

Water electrolysis holds great potential as a method for producing renewable hydrogen fuel at large-scale, and to replace the fossil fuels responsible for greenhouse gases emissions and global climate change. To reduce the cost of hydrogen and make it competitive against fossil fuels, the efficiency of green hydrogen production should be maximized. This requires superior electrocatalysts to reduce the reaction energy barriers. The development of catalytic materials has mostly relied on empirical, trial-and-error methods because of the complicated, multidimensional, and dynamic nature of catalysis, requiring significant time and effort to find optimized multicomponent catalysts under a variety of reaction conditions. The ultimate goal for all researchers in the materials science and engineering field is the rational and efficient design of materials with desired performance. Discovering and understanding new catalysts with desired properties is at the heart of materials science research. This process can benefit from machine learning (ML), given the complex nature of catalytic reactions and vast range of candidate materials. This review summarizes recent achievements in catalysts discovery for the hydrogen evolution reaction (HER) and oxygen evolution reaction (OER). The basic concepts of ML algorithms and practical guides for materials scientists are also demonstrated. The challenges and strategies of applying ML are discussed, which should be collaboratively addressed by materials scientists and ML communities. The ultimate integration of ML in catalyst development is expected to accelerate the design, discovery, optimization, and interpretation of superior electrocatalysts, to realize a carbon-free ecosystem based on green hydrogen.

• Economic and Environmental Geology
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• v.50 no.2
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• pp.85-96
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• 2017

Gold mineralization of Samjeong and Yongjang gold mines in Uichang area shows characteristics of Bonanza-type gold deposits. Ores are mainly developed along the contact parts between quartz vein and arkosic sandstone beds(Fe-rich bed) in sedimentary rock. Electrum, silver sulfide and sulfate minerals are mainly in the ores. On the other hand, gold mineralization is less developed in cherty rock and andesitic rock than arkosic sandstone. The study highlights characteristics of gold precipitation in the deposit on the basis of numerical modelling of the reactions between the assumed hydrothermal ore fluids with multicomponent heterogeneous equilibrium calculations. Aqueous species, gases and minerals, containing electrum are included in the calculations. The reaction result between hydrothermal ore fluids and arkosic sandstone show that pH increasing in the ore-forming fluid would trigger precipitation of quartz, chlorite, sericite, chalcopyrite, galena, pyrite, electrum, actinolite and feldspar. The numerical modelling also illustrates the drastic increase of pH and desulfidation lead to precipitation of electrum. Ag/Au ratios in the ore vary with pH conditions and subsequently precipitation of silver-bearing sulfides such as acanthite and polybasite. The modelling of the reaction between andesitic rock and ore-forming fluid shows that mineral assemblages of the case are analogous to ones of the reaction between arkosic sandstone and fluid except the latter has little portion of electrum. The abovementioned modelling results suggest that gold-silver mineralization is bounded by host rocks at the study area.