• 방사성폐기물학회지
• /
• 제19권2호
• /
• pp.187-196
• /
• 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.

• 한국재료학회지
• /
• 제33권5호
• /
• pp.175-188
• /
• 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.

• 자원환경지질
• /
• 제50권2호
• /
• pp.85-96
• /
• 2017

의창지역의 삼정광산과 용장광산의 금광화작용은 보난자(Bonanza)형 금광상의 특성을 나타낸다. 광상은 퇴적암 내의 장석질 사암과 석영맥의 접촉부에서 주로 산출되며, 금과 은을 함유하는 광물은 에렉트럼과 더불어 은황화광물 및 황산염광물로 산출된다. 반면, 광상의 모암이 쳐트질 암석과 안산암인 경우에는 금광화작용이 장석질 사암의 경우보다 미약하게 발달된다. 이 연구에서는 금의 침전 특성을 파악하기 위하여 열수용액과 장석질 사암 및 안산암간의 수치모델링에 의한 다성분 다상계 평형계산을 실시하였다. 모델링에서는 함금은 광물인 에렉트럼 및 수용액상 또는 기상 원소들이 사용되었다. 반응경로 모델링 결과, pH가 증가함에 따라 석영, 녹니석, 견운모, 황동석, 방연석, 황철석, 에렉트럼, 양기석과 장석이 침전되었다. 또한, 에렉트럼은 모암과 광화용액 간의 반응에 의한 급격한 pH 증가와 탈황화작용에 의해 침전되었음을 확인하였다. 금 은비는 용액의 pH 조건이나 아칸다이트와 폴리바사이트와 같은 은황화 광물 침전에 의해 변화되었다. 한편, 안산암과 열수용액과의 반응에서 침전된 광물은 열수용액과 장석질 사암과의 반응에서 침전된 광물과 유사하지만 상대적으로 적은 양의 에렉트럼이 침전되었다. 이러한 연구결과로 미루어 볼 때 의창지역 보난자형 금광화작용의 부광대는 모암 규제에 의해 형성되었다고 판단된다.