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    ์„ ํƒ์  ์‚ฐํ™” ์—ด์ฒ˜๋ฆฌ ๊ธฐ์ˆ ์„ ๋ฐ”ํƒ•์œผ๋กœ ์ ‘๊ทผํ•œ ํ•ฉ๊ธˆ์˜ ํ‘œ๋ฉด ์‚ฐํ™”์ธต ๊ฐœ์งˆ์— ๋Œ€ํ•œ ์—ฐ๊ตฌ

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    ํ•™์œ„๋…ผ๋ฌธ(๋ฐ•์‚ฌ) -- ์„œ์šธ๋Œ€ํ•™๊ต๋Œ€ํ•™์› : ๊ณต๊ณผ๋Œ€ํ•™ ์žฌ๋ฃŒ๊ณตํ•™๋ถ€, 2023. 2. ํ™ฉ๋†๋ฌธ.Fe-Si-Cr ๊ณ„๋Š” ์—๋„ˆ์ง€ ๋ณ€ํ™˜์žฅ์น˜์ธ ์ธ๋•ํ„ฐ ์ฝ”์–ด์— ์ฃผ๋กœ ์‚ฌ์šฉ๋˜๋Š” ํ•ฉ๊ธˆ๊ณ„์ด๋ฉฐ ๋ณต์žกํ•œ ํ˜•์ƒ์ œ์กฐ์™€ ๋“ฑ๋ฐฉ์˜ ์ž๊ธฐ์  ํŠน์„ฑ์„ ๊ฐ€์ง€๋Š” ์žฅ์ ์ด ์žˆ๋Š” ๋ถ„๋ง์„ ์‚ฌ์šฉํ•˜์—ฌ ๋ถ„๋ง ์•ผ๊ธˆ ๊ณต์ •์„ ํ†ตํ•ด ์ธ๋•ํ„ฐ ์ฝ”์–ด๋กœ ์ œ์กฐํ•˜๊ฒŒ๋œ๋‹ค. ์ฝ”์–ด์˜ ์‚ฌ์šฉํ™˜๊ฒฝ๊ณผ ์—๋„ˆ์ง€ ์ €์žฅ๋Ÿ‰์„ ๊ณ ๋ คํ•  ๋•Œ, ๋ถ„๋ง๊ฐ„์˜ ์ ˆ์—ฐ์ธต์„ ์น˜๋ฐ€ํ•˜๊ณ  ๊ท ์ผํ•˜๊ฒŒ ํ˜•์„ฑํ•˜๋Š” ๊ฒƒ์ด ํ•„์ˆ˜์ ์ด๋‹ค. ํ•˜์ง€๋งŒ ๊ธฐ์กด์˜ ์ธ๋•ํ„ฐ ์ฝ”์–ด ์ œ์กฐ ๊ณต์ •์—์„œ ์ ˆ์—ฐ์ธต์„ ํ˜•์„ฑํ•˜๋Š” ๋ฐฉ์‹์€ ์Šต์‹๊ณต์ •์„ ์ ์šฉํ•˜์—ฌ ์ฃผ๋กœ ์ œ์กฐ๋˜์—ˆ๋‹ค. ๋”ฐ๋ผ์„œ ๋ถ„๋ง ํ‘œ๋ฉด์— ๋ถˆ๊ท ์ผํ•œ ์ ˆ์—ฐ์ธต์ด ํ˜•์„ฑ๋˜๊ฒŒ ๋˜๊ณ  ์ด์— ๋”ฐ๋ผ ์ž์„ฑํŠน์„ฑ ๋ฐ ์ ˆ์—ฐํŠน์„ฑ์˜ ์ €ํ•˜๊ฐ€ ์ง€์†์ ์œผ๋กœ ๋ฐœ์ƒํ•˜๋Š” ๋ฌธ์ œ๊ฐ€ ๋ฐœ์ƒํ•˜๊ณ  ์žˆ๋Š” ์ƒํ™ฉ์ด๋‹ค. ๋”ฐ๋ผ์„œ ๊ธฐ์ƒ ๋ฐฉ์‹์œผ๋กœ ์„ ํƒ์ ์œผ๋กœ ์ ˆ์—ฐํŠน์„ฑ์ด ์šฐ์ˆ˜ํ•œ ์›์†Œ๋งŒ์„ ์‚ฐํ™”์‹œํ‚ค๊ฒŒ ๋œ๋‹ค๋ฉด ๋ถ„๋ง ํ‘œ๋ฉด์— ์น˜๋ฐ€ํ•˜๊ณ  ์šฐ์ˆ˜ํ•œ ์ ˆ์—ฐํŠน์„ฑ์„ ๊ฐ€์ง€๋Š” ์ ˆ์—ฐ์ธต์„ ํ˜•์„ฑํ•  ์ˆ˜ ์žˆ๊ฒŒ ๋œ๋‹ค. ์ด๋Ÿฌํ•œ ์—ด์ฒ˜๋ฆฌ ๊ธฐ์ˆ ์„ ์„ ํƒ์  ์‚ฐํ™” ์—ด์ฒ˜๋ฆฌ ๊ธฐ์ˆ ์ด๋ผ๊ณ  ํ•œ๋‹ค. ์„ ํƒ์  ์‚ฐํ™” ์—ด์ฒ˜๋ฆฌ ๊ธฐ์ˆ ์€ ํ•ฉ๊ธˆ์„ ๊ตฌ์„ฑํ•˜๋Š” ์›์†Œ์˜ ์‚ฐํ™” ๊ตฌ๋™๋ ฅ์ด ๋‹ค๋ฆ„์„ ์ด์šฉํ•˜์—ฌ ์—ด์ฒ˜๋ฆฌ ์‹œ ์‚ฐํ™”ํฌํ…์…œ์„ ์ œ์–ดํ•˜์—ฌ ํŠน์ • ์›์†Œ๋งŒ์„ ์‚ฐํ™”์‹œํ‚ค๋Š” ๊ฒƒ์„ ๊ฐ€๋Šฅํ•˜๊ฒŒ ํ•˜๋Š” ์—ด์ฒ˜๋ฆฌ ๊ธฐ์ˆ ์ด๋‹ค. ๋ณธ ์—ฐ๊ตฌ์—์„œ ์‚ฐํ™” ํ™˜์› ๋ฐ˜์‘์—์„œ์˜ ์—ด์—ญํ•™๊ณ„์‚ฐ์„ ํ†ตํ•ด ์„ ํƒ์  ์‚ฐํ™” ์—ด์ฒ˜๋ฆฌ ๊ณต์ •์„ ์„ค๊ณ„ํ•˜์˜€๋‹ค. ๊ทธ๋ฆฌ๊ณ  ์ด๋ฅผ Fe-Si-Cr ์—ฐ์ž์„ฑ ๋ถ„๋ง ํ•ฉ๊ธˆ๊ณ„์™€ Co-Cr-Mo ์ƒ์ฒด ํ•ฉ๊ธˆ๊ณ„์— ์ ์šฉํ•˜์—ฌ ํ•ฉ๊ธˆ ํ‘œ๋ฉด์˜ ์‚ฐํ™”์ธต์„ ๊ฐœ์งˆํ•˜๊ณ  ์ž์„ฑ ๋ฐ ๋ถ€์‹ ํŠน์„ฑ์„ ํ–ฅ์ƒ์‹œ์ผฐ๋‹ค. ์šฐ์„  Fe-Si-Cr ๋ถ„๋ง์— ๋‹ค์–‘ํ•œ ์‚ฐํ™”ํฌํ…์…œ์„ ๊ฐ€์ง€๋Š” ๋ถ„์œ„๊ธฐ๋กœ ์—ด์ฒ˜๋ฆฌ๋ฅผ ์‹ค์‹œํ•˜์—ฌ pH2(g)/pH2O(g) =41.8 ์กฐ๊ฑด์—์„œ Si ๊ณผ Cr ์œ„์ฃผ์˜ ์‚ฐํ™”์ธต์œผ๋กœ ๊ฐœ์งˆ ๋˜๋Š” ๊ฒƒ์„ ํ™•์ธํ•˜์˜€๋‹ค. ๋ถ„๋ง์˜ ์ž์„ฑํŠน์„ฑ๊ณผ ์ ˆ์—ฐํŠน์„ฑ์„ ์ธก์ •ํ•œ ๊ฒฐ๊ณผ ์ž์„ฑํŠน์„ฑ์ด ์ดˆ๊ธฐ ๋ถ„๋ง๋ณด๋‹ค pH2(g)/pH2O(g)=41.8 ์กฐ๊ฑด์—์„œ ํ–ฅ์ƒ๋˜์—ˆ์Œ์„ ํ™•์ธํ•˜์˜€๊ณ  ๋‚ด์ „์•• ์‹œํ—˜์„ ํ†ตํ•ด ์ ˆ์—ฐํŠน์„ฑ์„ ๋ถ„์„ํ•œ ๊ฒฐ๊ณผ ์ดˆ๊ธฐ๋ถ„๋ง๊ณผ ๋น„๊ตํ–ˆ์„ ๋•Œ 2๋ฐฐ ์ด์ƒ ํ–ฅ์ƒ๋œ ๊ฐ’์„ ๊ฐ€์ง€๋Š” ๊ฒƒ์„ ํ™•์ธํ•˜์˜€๋‹ค. ๋ถ„๋ง ๋‹จ์œ„์—์„œ ์—ด์—ญํ•™ ๊ณ„์‚ฐ์„ ํ†ตํ•ด ์„ค๊ณ„ํ•œ ์„ ํƒ์  ์‚ฐํ™” ์—ด์ฒ˜๋ฆฌ ๊ณต์ •์„ ์ ์šฉํ•˜๊ฒŒ ๋˜๋ฉด ๋ถ„๋ง ํ‘œ๋ฉด์ด ์„ ํƒ์ ์œผ๋กœ Si ๊ณผ Cr ๋งŒ์„ ์‚ฐํ™”์‹œํ‚ค๋Š” ์กฐ๊ฑด์ž„์„ ํ™•์ธํ•˜์˜€์œผ๋ฏ€๋กœ ์„ ํƒ์  ์‚ฐํ™” ์—ด์ฒ˜๋ฆฌ ์‹œ๊ฐ„์„ ์ฆ๊ฐ€์‹œ์ผœ ์‚ฐํ™”์ธต ํ˜•์„ฑ ๊ฑฐ๋™์„ ํ™•์ธํ•˜๋Š” ์‹คํ—˜์„ ์ง„ํ–‰ํ•˜์˜€๋‹ค. ๊ทธ๋ฆฌ๊ณ  ์ด์— ๋”ํ•ด ์‹ค์ œ๋กœ ๋ถ„๋ง ์•ผ๊ธˆ ๊ณต์ •์„ ์ ์šฉํ•˜์—ฌ ์—ฐ์ž์„ฑ ๋ถ„๋ง ๋””์Šคํฌ ๋ฐ ํ† ๋กœ์ด๋“œ ์ฝ”์–ด๋ฅผ ์ œ์กฐํ•˜์—ฌ ์ž์„ฑ ๋ฐ ์ ˆ์—ฐ ํŠน์„ฑ์„ ๋ถ€ํ’ˆ๋‹จ์œ„ ์ˆ˜์ค€์—์„œ ์ง„ํ–‰ํ•˜์˜€๋‹ค. ์„ ํƒ์  ์‚ฐํ™” ์—ด์ฒ˜๋ฆฌ๋ฅผ ๊ฑฐ์นœ ๋ถ„๋ง๋กœ ์ œ์กฐ๋œ ์ฝ”์–ด๋Š” ๊ธฐ์กด์˜ ์Šต์‹๊ณต์ •์„ ์ ์šฉํ•ด ์ œ์กฐ๋œ ์ฝ”์–ด์™€ ๋‚ด์ „์•• ์‹œํ—˜ ๋ฐ ์ธ๋•ํ„ด์Šค ์ธก์ • ์‹œํ—˜์„ ํ†ตํ•ด ๋น„๊ต ๋ถ„์„ํ•˜์˜€๋‹ค. ์ฝ”์–ด์˜ ํ’ˆ์งˆ์„ ์ข…ํ•ฉ์ ์œผ๋กœ ํ‰๊ฐ€ํ•˜๋Š” ํ’ˆ์งˆ๊ณ„์ˆ˜ ๊ฐ’์ด ๊ธฐ์กด์˜ ์Šต์‹๊ณต์ •์œผ๋กœ ์ œ์กฐ๋œ ์ธ๋•ํ„ฐ ์ฝ”์–ด๋ณด๋‹ค ์„ ํƒ์  ์‚ฐํ™” ์—ด์ฒ˜๋ฆฌ๋ฅผ ์ ์šฉํ•œ ๋ถ„๋ง๋กœ ์ œ์กฐ๋œ ์ฝ”์–ด์—์„œ ์•ฝ 16% ํ–ฅ์ƒ๋˜์—ˆ์Œ์„ ํ™•์ธํ•  ์ˆ˜ ์žˆ์—ˆ๋‹ค. ๊ทธ๋ฆฌ๊ณ  ์‹ค์ œ ์ธ๋•ํ„ฐ์˜ ์‚ฌ์šฉ ํ™˜๊ฒฝ์„ ๊ณ ๋ คํ•˜์—ฌ ๊ณ ์˜จ ๋ถ€ํ•˜๋ฅผ 1000์‹œ๊ฐ„ ๋™์•ˆ ๋ถ€์—ฌํ•˜๋Š” ๊ณ ์˜จ ๋ถ€ํ•˜ ํŠน์„ฑ ์‹œํ—˜๊ณผ ๋ถ€์‹ ํŠน์„ฑ์„ ์•Œ์•„ ๋ณด๊ธฐ ์œ„ํ•ด ์ถ”๊ฐ€์ ์œผ๋กœ ์ „๊ธฐํ™”ํ•™ ์‹คํ—˜์„ ์ง„ํ–‰ํ•˜์˜€๋‹ค. ๊ท ์ผํ•˜๊ณ  ์น˜๋ฐ€ํ•œ ์ ˆ์—ฐ์ธต์ด ํ˜•์„ฑ๋˜์–ด์žˆ๊ธฐ ๋•Œ๋ฌธ์— ๊ณ ์˜จ ๋ถ€ํ•˜ ํŠน์„ฑ ์‹คํ—˜ ํ›„์—๋„ ํ’ˆ์งˆ ๊ณ„์ˆ˜๊ฐ€ ์„ ํƒ์  ์‚ฐํ™” ์—ด์ฒ˜๋ฆฌ๋ฅผ ์ ์šฉํ•˜์—ฌ ์ œ์กฐ๋œ ์ฝ”์–ด์—์„œ ๊ฐ์†Œํ•˜์ง€ ์•Š๋Š” ๊ฒƒ์„ ํ™•์ธํ•  ์ˆ˜ ์žˆ์—ˆ๋‹ค. ์ „๊ธฐํ™”ํ•™ ์‹คํ—˜ ๊ฒฐ๊ณผ ์„ ํƒ์  ์‚ฐํ™” ์—ด์ฒ˜๋ฆฌ๋ฅผ ํ†ตํ•ด Fe-Si-Cr ํ•ฉ๊ธˆ ํ‘œ๋ฉด์— ํ˜•์„ฑ๋œ ์ ˆ์—ฐ์ธต์ด ๋ถ€์‹ ์ €ํ•ญ์„ฑ์„ ๊ฐ€์ง€๊ฒŒ ๋˜๋Š” ๊ฒƒ์„ ํ™•์ธํ•  ์ˆ˜ ์žˆ์—ˆ๋‹ค. ์ ˆ์—ฐ์ธต ๋‚ด๋ถ€์—” SiO2 ๊ฐ€ ํ˜•์„ฑ๋˜์—ˆ๊ณ  ์ ˆ์—ฐ์ธต ์™ธ๋ถ€์—” Cr2O3 ์ ˆ์—ฐ์ธต์ด ํ˜•์„ฑ๋˜์–ด ์žˆ์—ˆ์Œ์„ XPS ๋ถ„์„๊ณผ TEM ๋ถ„์„์„ ํ†ตํ•ด ํ™•์ธํ•˜์˜€์œผ๋ฉฐ ์„ ํƒ์  ์‚ฐํ™” ์—ด์ฒ˜๋ฆฌ ์‹œ๊ฐ„์ด ์ฆ๊ฐ€ํ• ์ˆ˜๋ก ์ ˆ์—ฐ์ธต์˜ ๋‘๊ป˜๊ฐ€ ์ฆ๊ฐ€ํ•˜๋Š” ๊ฒฝํ–ฅ์„ ๋‚˜ํƒ€๋‚ด์—ˆ๋‹ค. ์„ ํƒ์  ์‚ฐํ™” ์—ด์ฒ˜๋ฆฌ์— ์˜ํ•ด ํ˜•์„ฑ๋œ ์ ˆ์—ฐ์ธต์€ ๋ถ„๊ทน ์‹คํ—˜ ๊ฒฐ๊ณผ ๋ถ€์‹์ „์œ„์˜ ํ–ฅ์ƒ์„ ์•ผ๊ธฐ์‹œํ‚ค๋Š” ๊ฒƒ์„ ํ™•์ธํ•˜์˜€์œผ๋ฉฐ ์ด๋ฅผ ํ†ตํ•ด ๋ถ€์‹ํŠน์„ฑ์ด ํ–ฅ์ƒ๋˜์—ˆ๋‹ค๊ณ  ๋ฏธ๋ฃจ์–ด ๋ณผ ์ˆ˜ ์žˆ์—ˆ๋‹ค. ์—ฌ๊ธฐ์— ๋”ํ•ด 3.5wt% NaCl ์šฉ์•ก์—์„œ์˜ EIS ์‹คํ—˜์„ ํ†ตํ•ด ์„ ํƒ์  ์‚ฐํ™” ์—ด์ฒ˜๋ฆฌ ์‹œ๊ฐ„์ด ์ฆ๊ฐ€ํ•จ์— ๋”ฐ๋ผ ์ž„ํ”ผ๋˜์Šค ๋ฐ˜์›์ด ํฌ๊ฒŒ ์ธก์ •๋˜์—ˆ๊ณ  ์ ˆ์—ฐ์ธต ํŒŒ๊ดด์‹œ๊ฐ„์ด ์ง€์—ฐ๋˜๋Š” ๊ฒƒ์„ ํ™•์ธํ•  ์ˆ˜ ์žˆ์—ˆ๋Š”๋ฐ ์ด๋ฅผ ํ†ตํ•ด ์„ ํƒ์  ์‚ฐํ™” ์—ด์ฒ˜๋ฆฌ ์‹œ๊ฐ„์ด ์ฆ๊ฐ€ํ• ์ˆ˜๋ก ๋ถ€์‹ํŠน์„ฑ์ด ํ–ฅ์ƒ๋˜๋Š” ๊ฒƒ์„ ํ™•์ธํ•˜์˜€๋‹ค. Co-Cr-Mo ์ƒ์ฒด ํ•ฉ๊ธˆ๊ณ„์—์„œ๋„ ์‹ ์ฒด ๋‚ด๋ถ€์— ์‚ฝ์ž…๋˜์—ˆ์„ ๋•Œ Co ์ด์˜จ์ด ์šฉ์ถœ๋˜๋Š” ๊ฒƒ์„ ๋ง‰๊ธฐ ์œ„ํ•ด ๋ถ€์‹ํŠน์„ฑ ํ–ฅ์ƒ์ด ํ•„์ˆ˜์ ์ธ๋ฐ ์—ด์ฒ˜๋ฆฌ ์‹œ pH2(g)/pH2O(g)=41.8 ์กฐ๊ฑด์—์„œ Co ์™€ Mo ๋Š” ์‚ฐํ™”์‹œํ‚ค์ง€ ์•Š๊ณ  ๋ถ€์‹ํŠน์„ฑ์ด ์šฐ์ˆ˜ํ•œ Cr ์›์†Œ๋งŒ์„ ์„ ํƒ์ ์œผ๋กœ ์‚ฐํ™”์‹œํ‚ค๋Š” ์กฐ๊ฑด์ž„์„ ํ™•์ธํ•˜์˜€๋‹ค. ๊ทธ๋ฆฌ๊ณ  ์•ž์„œ ์ˆ˜ํ–‰ํ•œ ์ „๊ธฐํ™”ํ•™ ์‹คํ—˜ ๊ฒฐ๊ณผ ๋ถ€์‹ํŠน์„ฑ์ด ํ–ฅ์ƒ๋˜๋Š” ๊ฒƒ์„ ํ™•์ธํ•  ์ˆ˜ ์žˆ์—ˆ๋‹ค. ์ด์ฒ˜๋Ÿผ ์„ ํƒ์  ์‚ฐํ™” ์—ด์ฒ˜๋ฆฌ ๊ธฐ์ˆ ์€ ๋‹ค์–‘ํ•œ ํ•ฉ๊ธˆ๊ณ„์— ์ ์šฉ ๊ฐ€๋Šฅํ•˜๋ฉฐ ๊ธฐ์ƒ๋ฐฉ์‹์œผ๋กœ ์ ˆ์—ฐ์ธต์„ ํ˜•์„ฑํ•˜๊ธฐ ๋•Œ๋ฌธ์— ํฌ๊ธฐ๊ฐ€ ์ž‘์€ ๋ถ„๋ง์—๋„ ์ ์šฉ์ด ๊ฐ€๋Šฅํ•  ๊ฒƒ์œผ๋กœ ์˜ˆ์ƒ๋˜๋Š” ์ฐจ์„ธ๋Œ€ ์ ˆ์—ฐ ๊ธฐ์ˆ ์ด๋‹ค.Fe-Si-Cr based alloy powder is an alloy system mainly used for soft magnetic composites (SMCs) cores. Since it can be manufactured in a complex shape and has the advantage of having isotropic magnetic properties, it is manufactured as an inductor core, an energy conversion device, through a powder metallurgy process. Considering the operating environment and energy storage of the core, it is essential to form a dense and uniform insulating layer between the powders. However, the method of forming the insulating layer in the conventional inductor core manufacturing process was mainly manufactured by applying a wet chemical process. Therefore, a non-uniform insulating layer is formed on the surface of the powder, and accordingly, a problem in that magnetic properties and insulating properties are continuously deteriorated is occurring. If only elements having excellent insulating properties are selectively oxidized in a vapor phase method rather than wet chemical process, it is possible to form a dense insulating layer having excellent insulating properties on the powder surface. This heat treatment technique is referred to as a selective oxidation annealing. Selective oxidation heat annealing is a heat treatment technology that makes it possible to oxidize only a specific element by controlling the oxidation potential during heat treatment by using the different oxidation driving forces of the elements constituting the alloy. In this study, a selective oxidation annealing process was designed through thermodynamic calculations in redox reactions. And, by applying this to the Fe-Si-Cr soft magnetic powder alloy system and the Co-Cr-Mo alloy system, the oxide layer on the alloy surface was modified and the properties were improved. First, heat treatment was performed on the Fe-Si-Cr powder in an atmosphere having various oxidation potentials, and it was confirmed that an oxide layer mainly of Si and Cr was selectively oxidized and formed on the powder surface under the condition of pH2(g)/pH2O(g)=41.8. As a result of measuring the magnetic properties and insulating properties of the powder, it was confirmed that the magnetic properties were improved under condition pH2(g)/pH2O(g)=41.8 compared to the initial powder. As a result of analyzing the insulation property through the withstand voltage test, it was confirmed that the withstanding voltage value was more than twice as high as that of the initial powder. When applying the selective oxidation annealing designed through thermodynamic calculation at the powder level, it was confirmed that the powder surface was selectively oxidized. Therefore, an additional experiment was conducted to confirm the oxide layer formation behavior by increasing the selective oxidation annealing time. In addition, by applying the powder metallurgy process, soft magnetic powder discs and toroid cores were manufactured and magnetic and insulating properties were evaluated at the component level. The cores manufactured from the powders subjected to the selective oxidation annealing were compared and analyzed with the cores manufactured by applying the conventional wet chemical process through the withstand voltage test and the inductance measurement test. It was confirmed that the quality factor value, which comprehensively evaluates the quality of the core, was improved by about 16% in the core manufactured from the selectively oxidized powder compared to the inductor core manufactured by the wet chemical process. And considering the operating environment of the actual inductor, a high-temperature load characteristic test in which a high-temperature load is applied for 1000 hrs and an additional electrochemical experiment were conducted to figure out the corrosion characteristics. Since a uniform and dense insulating layer was formed, it was confirmed that the quality factor did not decrease in the inductor core manufactured by applying the selective oxidation heat treatment even after the high-temperature load characteristics test. As a result of the electrochemical experiment, it was confirmed that the insulating layer formed on the surface of the Fe-Si-Cr alloy had corrosion resistance through selective oxidation heat treatment. It was analyzed through XPS analysis and TEM that SiO2 was formed inside the insulating layer and Cr2O3 insulating layer was formed outside, and the thickness of the insulating layer tended to increase as the selective oxidation annealing time increased. The insulating layer formed by the selective oxidation annealing caused an improvement in the corrosion potential as a result of the polarization test, and it could be assumed that the corrosion characteristics were improved. In addition, through the EIS experiment in 3.5wt% NaCl solution, it was confirmed that the impedance semicircle tended to increase as the selective oxidation annealing time increased, and the insulation layer deterioration time was delayed. Through this, as the selective oxidation annealing time increased, the corrosion properties improved. Even in the Co-Cr-Mo bio-alloy system, it is essential to improve the corrosion properties to prevent the elution of cobalt ions when inserted into the body. Under the condition of pH2(g)/pH2O(g)=41.8, during annealing, Co and Mo are not oxidized and only Cr elements with excellent corrosion properties are selectively oxidized. Through this, selective oxidation annealing was applied to the Co-Cr-Mo alloy system to evaluate the corrosion properties. As such, the selective oxidation annealing technology is applicable to various alloy systems and is a next-generation insulation technology that is expected to be applicable to submicron-sized powders because it forms an insulation layer in a vapor phase method.Chapter 1. Introduction 2 Chapter 2. Thermodynamics of selective oxidation 10 Chapter 3. Formation of Fe-Si-Cr powder surface insulating layer through selective oxidation heat treatment 25 Chapter 4. Improvement of magnetic & insulation properties of cores fabricated by selectively oxidized Fe-Si-Cr powders compared to wet chemical process 45 Chapter 5. Surface modification of Fe-Si-Cr alloy by selective oxidation annealing and its corrosion properties 114 Chapter 6. Enhancement of the corrosion properties of selective laser melted Co-Cr-Mo alloys by selective oxidation annealing 142 Chapter 7. Conclusions 165 Bibliography 168 Abstract in Korean 178๋ฐ•

    A Comparative Study on the Prediction Performance of Stochastic Process Model and Deep Learning Model for Energy Resource Prices

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    ํ•™์œ„๋…ผ๋ฌธ(์„์‚ฌ) -- ์„œ์šธ๋Œ€ํ•™๊ต๋Œ€ํ•™์› : ๊ณต๊ณผ๋Œ€ํ•™ ์—๋„ˆ์ง€์‹œ์Šคํ…œ๊ณตํ•™๋ถ€, 2023. 2. ํ—ˆ์€๋…•.This study analyzed the energy resource market price using an one factor stochastic process model, an stochastic volatility model, and a deep learning model, and finally compared the results between all models. The three target resources used for this study were crude oil, natural gas, and copper, and ten years of daily data, ranging from October 1st, 2012 to September 30, 2022, were utilized. Within the one factor stochastic process model, nine models were used: Merton, Vasicek, CIR-SR, Dothan, GBM, Brennan-Schwartz, CIR-VR, CEV, and CKLS. For the stochastic volatility model, the four models; mean-reverting stochastic volatility model without jumps(MRSV), mean-reverting stochastic volatility model with jumps in the spot price only(MRSVJ), mean-reverting stochastic volatility model with independent jumps(MRSVIJ), and mean-reverting stochastic volatility model with correlated jumps(MRSVCJ) were analyzed, and in the deep learning model, the three models RNN, LSTM, and GRU were used. First of all, this study analyzed data through the application of the one factor stochastic process model, stochastic volatility model, and deep learning model for the entire analysis period, and the data were further divided into in-sample data and out-of-sample data, which were then analyzed separately up to September 30, 2020. The results of the analysis indicate that crude oil and copper prices had mean-reverting properties prior to COVID-19, and volatility did not react sensitively to price levels, but considering the entire time period, it was difficult to suggest that they had mean-reverting properties and volatility was also sensitive to price levels. On the other hand, gas prices did not demonstrate a significant difference in dynamic characteristics prior or to or following COVID-19. In addition, it was confirmed that each resource was affected by long-term data. RMSE, MAPE, R2 SCORE, accuracy, and precision were used to compare predictive performance between models. In the case of crude oil, the predictive performance of RMSE, MAPE, and R2 SCORE was found to be high in descending order from the deep learning model, to the one factor stochastic process model, and to the stochastic volatility model, and in the case of gas and copper, it showed a high predictive performance in descending order from the one factor stochastic process model, to the stochastic volatility model, and to the deep learning model. Although there some differences were discovered between resources based on accuracy, it showed excellent performance in descending order from deep learning, to the one factor stochastic process model, and to the stochastic volatility model. Similarly, although there were differences by resource based on precision, the precision tends to be high in descending order from the stochastic volatility model, to the deep learning model, and to the one factor stochastic process model. The findings suggest that the model to be used for analysis differs depending on each individual resource and purpose. In addition, as there are cases in which the difference in predictive performance for each model is not significant, it was confirmed that selecting a model that is easy to calculate in consideration of efficiency can serve as one alternative method.๋ณธ ์—ฐ๊ตฌ์—์„œ๋Š” ๋‹จ์ผ์š”์ธ ํ™•๋ฅ ๊ณผ์ • ๋ชจํ˜•๊ณผ ํ™•๋ฅ ๋ณ€๋™์„ฑ ๋ชจํ˜•, ๋”ฅ๋Ÿฌ๋‹ ๋ชจํ˜•์„ ์‚ฌ์šฉํ•˜์—ฌ ์—๋„ˆ์ง€์ž์›๊ฐ€๊ฒฉ์„ ๋ถ„์„ํ•˜์˜€์œผ๋ฉฐ ๋ชจํ˜• ๊ฐ„ ์˜ˆ์ธก์„ฑ๋Šฅ ๊ฒฐ๊ณผ๋ฅผ ๋น„๊ตํ•˜์˜€๋‹ค. ๋ถ„์„ ๋Œ€์ƒ์€ ์›์œ , ์ฒœ์—ฐ๊ฐ€์Šค, ๊ตฌ๋ฆฌ ๋“ฑ 3๊ฐœ ์ž์›์ด๋‹ค. ์—๋„ˆ์ง€์ž์›๊ฐ€๊ฒฉ ์ค‘์—์„œ๋„ ๊ตญ์ œ์‹œ์žฅ๊ฐ€๊ฒฉ์„ ์„ ์ •ํ•˜์˜€์œผ๋ฉฐ ๋ถ„์„ ๊ธฐ๊ฐ„ 2012.10.01.~2022.09.30.์˜ ์ผ๋ณ„ ์ข…๊ฐ€์ž๋ฃŒ๋ฅผ ์‚ฌ์šฉํ•˜์˜€๋‹ค. ๋‹จ์ผ์š”์ธ ํ™•๋ฅ ๊ณผ์ • ๋ชจํ˜•์—์„œ๋Š” Merton, Vasicek, CIR-SR, Dothan, GBM, Brennan-Schwartz, CIR-VR, CEV, CKLS 9๊ฐ€์ง€ ๋ชจํ˜•์„ ์‚ฌ์šฉํ•˜์˜€๊ณ , ํ™•๋ฅ ๋ณ€๋™์„ฑ ๋ชจํ˜•์—์„œ๋Š” ํ‰๊ท ํšŒ๊ท€ ํ™•๋ฅ ๋ณ€๋™์„ฑ(MRSV), ๊ฐ€๊ฒฉ์˜ ์ ํ”„๋ฅผ ๊ณ ๋ คํ•œ ํ‰๊ท ํšŒ๊ท€ ํ™•๋ฅ ๋ณ€๋™์„ฑ(MRSVJ), ๋…๋ฆฝ๋œ ์ ํ”„๋ฅผ ๊ฐ–๋Š” ํ‰๊ท ํšŒ๊ท€ ํ™•๋ฅ ๋ณ€๋™์„ฑ(MRSVIJ), ์—ฐ๊ด€๋œ ์ ํ”„๋ฅผ ๊ฐ–๋Š” ํ‰๊ท ํšŒ๊ท€ ํ™•๋ฅ ๋ณ€๋™์„ฑ(MRSVCJ) 4๊ฐ€์ง€ ๋ชจํ˜•, ๋”ฅ๋Ÿฌ๋‹ ๋ชจํ˜•์—์„œ๋Š” ํฌ๊ฒŒ RNN, LSTM, GRU 3๊ฐ€์ง€ ๋ชจํ˜•์„ ์‚ฌ์šฉํ•˜์˜€๋‹ค. ์šฐ์„  ๋ถ„์„ ๊ธฐ๊ฐ„ ์ „์ฒด์— ๋Œ€ํ•ด ๋‹จ์ผ์š”์ธ ํ™•๋ฅ ๊ณผ์ • ๋ชจํ˜•, ํ™•๋ฅ ๋ณ€๋™์„ฑ ๋ชจํ˜•, ๋”ฅ๋Ÿฌ๋‹ ๋ชจํ˜•์„ ์ ์šฉํ•˜์—ฌ ๋ถ„์„ํ•˜์˜€๋‹ค. ๋ถ„์„ ๊ธฐ๊ฐ„ ์ค‘ 80% ๊ธฐ๊ฐ„์— ํ•ด๋‹นํ•˜๋Š” ์ž๋ฃŒ๋ฅผ ๋‚ดํ‘œ๋ณธ, 20% ๊ธฐ๊ฐ„์— ํ•ด๋‹นํ•˜๋Š” ์ž๋ฃŒ๋ฅผ ์™ธํ‘œ๋ณธ์œผ๋กœ ๋ถ„๋ฅ˜ํ•˜์˜€์œผ๋ฉฐ ์ด์— ๋”ฐ๋ผ 2020.09.30.์„ ๊ธฐ์ค€์œผ๋กœ ๋‚ดํ‘œ๋ณธ๊ณผ ์™ธํ‘œ๋ณธ์œผ๋กœ ๊ตฌ๋ถ„ํ•˜์—ฌ ๋ถ„์„ํ•˜์˜€๋‹ค. ๋ถ„์„ ๊ฒฐ๊ณผ ์›์œ  ์‹œ์žฅ๊ฐ€๊ฒฉ๊ณผ ๊ตฌ๋ฆฌ ์‹œ์žฅ๊ฐ€๊ฒฉ์€ COVID-19 ์ด์ „์—๋Š” ํ‰๊ท ํšŒ๊ท€ ์„ฑ์งˆ์„ ๊ฐ€์ง€๊ณ  ๋ณ€๋™์„ฑ์ด ๊ฐ€๊ฒฉ ์ˆ˜์ค€์— ๋ฏผ๊ฐํ•˜๊ฒŒ ๋ฐ˜์‘ํ•˜์ง€ ์•Š์•˜์œผ๋‚˜, ์ „์ฒด ๊ธฐ๊ฐ„์„ ๊ณ ๋ คํ•˜๋ฉด ํ‰๊ท ํšŒ๊ท€ ์„ฑ์งˆ์„ ๊ฐ–๋Š”๋‹ค๊ณ  ๋ณด๊ธฐ ์–ด๋ ค์› ์œผ๋ฉฐ ๋ณ€๋™์„ฑ๋„ ๊ฐ€๊ฒฉ ์ˆ˜์ค€์— ๋ฏผ๊ฐํ•˜๊ฒŒ ๋ฐ˜์‘ํ•˜์˜€๋‹ค. ๋ฐ˜๋ฉด ์ฒœ์—ฐ๊ฐ€์Šค ์‹œ์žฅ๊ฐ€๊ฒฉ์€ COVID-19 ์ด์ „๊ณผ ์ดํ›„ ๋™ํƒœ์  ํŠน์„ฑ์— ํฐ ์ฐจ์ด๊ฐ€ ์—†์—ˆ๋‹ค. ๋˜ํ•œ ์ž์› ๋ณ„๋กœ ์žฅ๊ธฐ์ ์ธ ์ •๋ณด์— ์˜ํ–ฅ์„ ๋ฐ›๋Š”์ง€ ์—ฌ๋ถ€๊ฐ€ ๋‹ค๋ฆ„์„ ํ™•์ธํ•˜์˜€๋‹ค. ๋ชจํ˜• ๊ฐ„ ์˜ˆ์ธก์„ฑ๋Šฅ ๋น„๊ต๋ฅผ ์œ„ํ•ด RMSE, MAPE, R2 SCORE, ์ •ํ™•๋„, ์ •๋ฐ€๋„๋ฅผ ๊ธฐ์ค€์œผ๋กœ ์‚ฌ์šฉํ•˜์˜€๋‹ค. ์›์œ ์˜ ๊ฒฝ์šฐ ๋”ฅ๋Ÿฌ๋‹ ๋ชจํ˜•, ๋‹จ์ผ์š”์ธ ํ™•๋ฅ ๊ณผ์ • ๋ชจํ˜•, ํ™•๋ฅ ๋ณ€๋™์„ฑ ๋ชจํ˜•์˜ ์ˆœ์„œ๋กœ RMSE, MAPE, R2 SCORE์˜ ์˜ˆ์ธก ์„ฑ๋Šฅ์ด ๋†’์€ ๊ฒฝํ–ฅ์„ ๋‚˜ํƒ€๋ƒˆ์œผ๋ฉฐ ์ฒœ์—ฐ๊ฐ€์Šค์™€ ๊ตฌ๋ฆฌ์˜ ๊ฒฝ์šฐ ๋‹จ์ผ์š”์ธ ํ™•๋ฅ ๊ณผ์ • ๋ชจํ˜•, ํ™•๋ฅ ๋ณ€๋™์„ฑ ๋ชจํ˜•, ๋”ฅ๋Ÿฌ๋‹ ๋ชจํ˜•์˜ ์ˆœ์„œ์˜€๋‹ค. ์ •ํ™•๋„ ๊ธฐ์ค€์œผ๋กœ ์ž์›๋งˆ๋‹ค ์ผ๋ถ€ ์ฐจ์ด๊ฐ€ ์žˆ์œผ๋‚˜ ๋”ฅ๋Ÿฌ๋‹, ๋‹จ์ผ์š”์ธ ํ™•๋ฅ ๊ณผ์ •, ํ™•๋ฅ ๋ณ€๋™์„ฑ ๋ชจํ˜• ์ˆœ์„œ๋กœ ์šฐ์ˆ˜ํ•œ ์„ฑ๋Šฅ์„ ๋‚˜ํƒ€๋ƒˆ๋‹ค. ์ •๋ฐ€๋„ ๊ธฐ์ค€์œผ๋กœ๋Š” ์ž์›๋ณ„๋กœ ์ฐจ์ด๊ฐ€ ์žˆ์œผ๋‚˜ ํ™•๋ฅ ๋ณ€๋™์„ฑ ๋ชจํ˜•, ๋”ฅ๋Ÿฌ๋‹ ๋ชจํ˜•, ๋‹จ์ผ์š”์ธ ํ™•๋ฅ ๊ณผ์ • ๋ชจํ˜•์˜ ์ˆœ์„œ๋กœ ์ •๋ฐ€๋„๊ฐ€ ๋†’์€ ๊ฒฝํ–ฅ์„ ๋‚˜ํƒ€๋ƒˆ๋‹ค. ์ด์— ๋”ฐ๋ผ ์ž์›๋ณ„๋กœ ๊ทธ๋ฆฌ๊ณ  ๋ชฉ์ ๋ณ„๋กœ ๋ถ„์„์— ์‚ฌ์šฉํ•ด์•ผ ํ•˜๋Š” ๋ชจํ˜•์ด ๋‹ค๋ฆ„์„ ํ™•์ธํ•˜์˜€๋‹ค. ๋˜ํ•œ ๋ชจํ˜•๋ณ„ ์˜ˆ์ธก์„ฑ๋Šฅ์˜ ์ฐจ์ด๊ฐ€ ํฌ์ง€ ์•Š์€ ๊ฒฝ์šฐ๊ฐ€ ์กด์žฌํ•˜๋ฏ€๋กœ, ํšจ์œจ์„ฑ์„ ๊ณ ๋ คํ•˜์—ฌ ๊ณ„์‚ฐ์ด ๊ฐ„ํŽธํ•œ ๋ชจํ˜•์„ ์„ ํƒํ•˜๋Š” ๊ฒƒ๋„ ํ•˜๋‚˜์˜ ๋ฐฉ์•ˆ์ด ๋  ์ˆ˜ ์žˆ์Œ์„ ์‹œ์‚ฌํ•˜์˜€๋‹ค.์ œ 1 ์žฅ ์„œ๋ก  1 ์ œ 1 ์ ˆ ์—ฐ๊ตฌ ๋ฐฐ๊ฒฝ ๋ฐ ๋ชฉ์  1 ์ œ 2 ์ ˆ ๋…ผ๋ฌธ์˜ ๊ตฌ์„ฑ 6 ์ œ 2 ์žฅ ์„ ํ–‰์—ฐ๊ตฌ 8 ์ œ 1 ์ ˆ ์—๋„ˆ์ง€์ž์›์‹œ์žฅ๊ฐ€๊ฒฉ์˜ ํŠน์ง• 8 1. ์›์œ  ์‹œ์žฅ๊ฐ€๊ฒฉ์˜ ํŠน์ง• 9 2. ์ฒœ์—ฐ๊ฐ€์Šค ์‹œ์žฅ๊ฐ€๊ฒฉ์˜ ํŠน์ง• 13 3. ๊ตฌ๋ฆฌ ์‹œ์žฅ๊ฐ€๊ฒฉ์˜ ํŠน์ง• 17 ์ œ 2 ์ ˆ ๋ถ„์„ ๋ชจํ˜•์˜ ๋ฐœ์ „ 21 1. ํ™•๋ฅ ๊ณผ์ • ๋ชจํ˜•์˜ ๋ฐœ์ „ 21 2. ๋”ฅ๋Ÿฌ๋‹ ๋ชจํ˜•์˜ ๋ฐœ์ „ 27 ์ œ 3 ์žฅ ๋ถ„์„๋ชจํ˜• 33 ์ œ 1 ์ ˆ ๋‹จ์ผ์š”์ธ ํ™•๋ฅ ๊ณผ์ • ๋ชจํ˜• 33 1. ๋ชจํ˜•์˜ ์ข…๋ฅ˜ ๋ฐ ํŠน์ง• 33 2. ์ถ”์ •๋ฐฉ๋ฒ•๋ก  43 ์ œ 2 ์ ˆ ํ™•๋ฅ ๋ณ€๋™์„ฑ ๋ชจํ˜• 48 1. ๋ชจํ˜•์˜ ์ข…๋ฅ˜ ๋ฐ ํŠน์ง• 48 2. ์ถ”์ •๋ฐฉ๋ฒ•๋ก  55 ์ œ 3 ์ ˆ ๋”ฅ๋Ÿฌ๋‹ ๋ชจํ˜• 58 1. ๋ชจํ˜•์˜ ์ข…๋ฅ˜ ๋ฐ ํŠน์ง• 58 2. ์ถ”์ •๋ฐฉ๋ฒ•๋ก  67 ์ œ 4 ์žฅ ์‹ค์ฆ๋ถ„์„ ๊ฒฐ๊ณผ 74 ์ œ 1 ์ ˆ ๋ถ„์„์ž๋ฃŒ 74 1. ๋ถ„์„์ž๋ฃŒ ๋ฐ ๊ธฐ์ดˆํ†ต๊ณ„๋Ÿ‰ 74 2. ๋ถ„์„๊ธฐ๊ฐ„ ์ž๋ฃŒ๋ณ€๋™ ์ถ”์ด 75 ์ œ 2 ์ ˆ ๋ถ„์„๊ฒฐ๊ณผ 81 1. ์›์œ  ์‹œ์žฅ๊ฐ€๊ฒฉ ๋ถ„์„๊ฒฐ๊ณผ 81 2. ์ฒœ์—ฐ๊ฐ€์Šค ์‹œ์žฅ๊ฐ€๊ฒฉ ๋ถ„์„๊ฒฐ๊ณผ 87 3. ๊ตฌ๋ฆฌ ์‹œ์žฅ๊ฐ€๊ฒฉ ๋ถ„์„๊ฒฐ๊ณผ 93 ์ œ 3 ์ ˆ ๊ตฌ์กฐ๋ณ€ํ™”๋ฅผ ๊ณ ๋ คํ•œ ๋ถ„์„๊ฒฐ๊ณผ 99 1. ์›์œ  ์‹œ์žฅ๊ฐ€๊ฒฉ ๋ถ„์„๊ฒฐ๊ณผ 104 2. ์ฒœ์—ฐ๊ฐ€์Šค ์‹œ์žฅ๊ฐ€๊ฒฉ ๋ถ„์„๊ฒฐ๊ณผ 121 3. ๊ตฌ๋ฆฌ ์‹œ์žฅ๊ฐ€๊ฒฉ ๋ถ„์„๊ฒฐ๊ณผ 138 ์ œ 5 ์žฅ ๊ฒฐ๋ก  155 ์ œ 1 ์ ˆ ๋ชจํ˜•์˜ ์ž์›๋ณ„ ์˜ˆ์ธก์„ฑ๋Šฅ ๋น„๊ต 155 1. ๋‹จ์ผ์š”์ธ ํ™•๋ฅ ๊ณผ์ • ๋ชจํ˜•์˜ ์ž์›๋ณ„ ์˜ˆ์ธก์„ฑ๋Šฅ ๋น„๊ต 155 2. ํ™•๋ฅ ๋ณ€๋™์„ฑ ๋ชจํ˜•์˜ ์ž์›๋ณ„ ์˜ˆ์ธก์„ฑ๋Šฅ ๋น„๊ต 161 3. ๋”ฅ๋Ÿฌ๋‹ ๋ชจํ˜•์˜ ์ž์›๋ณ„ ์˜ˆ์ธก์„ฑ๋Šฅ ๋น„๊ต 165 ์ œ 2 ์ ˆ ์ž์›์˜ ๋ชจํ˜•๋ณ„ ์˜ˆ์ธก์„ฑ๋Šฅ ๋น„๊ต 172 1. ์›์œ  ์‹œ์žฅ๊ฐ€๊ฒฉ์˜ ๋ชจํ˜•๋ณ„ ๋น„๊ต 172 2. ์ฒœ์—ฐ๊ฐ€์Šค ์‹œ์žฅ๊ฐ€๊ฒฉ์˜ ๋ชจํ˜•๋ณ„ ๋น„๊ต 181 3. ๊ตฌ๋ฆฌ ์‹œ์žฅ๊ฐ€๊ฒฉ์˜ ๋ชจํ˜•๋ณ„ ๋น„๊ต 190 ์ œ 3 ์ ˆ ๊ฒฐ๊ณผ์˜ ์˜์˜ ๋ฐ ํ•œ๊ณ„์  199์„

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    ํ•™์œ„๋…ผ๋ฌธ (์„์‚ฌ)-- ์„œ์šธ๋Œ€ํ•™๊ต ๋Œ€ํ•™์› : ์˜ํ•™๊ณผ, 2014. 8. ์ •์ง„์—ฝ.์„œ๋ก : ๊ณ ๊ด€์ ˆ ๋ถˆ์•ˆ์ •์„ฑ์€ ๋‡Œ์„ฑ๋งˆ๋น„ ํ™˜์ž์˜ ํ†ต์ฆ ๋ฐ ๊ธฐ๋Šฅ์žฅ์• ๋ฅผ ์ผ์œผํ‚ค๋Š” ๊ทผ๊ณจ๊ฒฉ๊ณ„ ํ•ฉ๋ณ‘์ฆ์ด๋‹ค. ๊ธฐ์กด์˜ ์—ฐ๊ตฌ๋“ค์€ ๊ณ ๊ด€์ ˆ ๋ถˆ์•ˆ์ •์„ฑ์ด ์ง„ํ–‰์„ฑ์ž„์„ ๊ธฐ์ˆ ํ•˜์˜€์ง€๋งŒ ์ง„ํ–‰ ์†๋„๋‚˜ ์œ„ํ—˜์ธ์ž, ๊ทธ๋ฆฌ๊ณ  ๋Œ€์šด๋™ ๊ธฐ๋Šฅ ๋ถ„๋ฅ˜ ์‹œ์Šคํ…œ(Gross Motor Function Classification System, GMFCS) ๋‹จ๊ณ„์™€ ์ง„ํ–‰ ์ •๋„์˜ ๊ด€๊ณ„์— ๋Œ€ํ•œ ์—ฐ๊ตฌ๋Š” ๋ถ€์กฑํ•œ ์‹ค์ •์ด๋‹ค. ๋ณธ ์—ฐ๊ตฌ์—์„œ๋Š” ๋‡Œ์„ฑ๋งˆ๋น„ ํ™˜์ž์˜ ๊ณ ๊ด€์ ˆ ์ถ”์ ๊ด€์ฐฐ ์ค‘ ๋Œ€์šด๋™ ๊ธฐ๋Šฅ ๋ถ„๋ฅ˜ ์‹œ์Šคํ…œ(GMFCS) ๋‹จ๊ณ„์— ๋”ฐ๋ผ ๋ถ„๋ฅ˜ํ•œ ๊ตฐ์—์„œ์˜ ์˜์ƒ์˜ํ•™์  ์†Œ๊ฒฌ ๋ณ€ํ™”๋ฅผ ํ‰๊ฐ€ํ•˜์—ฌ ๊ณ ๊ด€์ ˆ ๋ถˆ์•ˆ์ •์„ฑ์˜ ์ง„ํ–‰์†๋„ ๋ฐ ์œ„ํ—˜์ธ์ž๋ฅผ ๋ถ„์„ํ•˜์—ฌ ์˜ˆ์ธก ๊ฐ€๋Šฅ์„ฑ ์—ฌ๋ถ€๋ฅผ ์—ฐ๊ตฌํ•˜์˜€๋‹ค. ๋ฐฉ๋ฒ•: 2003๋…„ 7์›”๋ถ€ํ„ฐ 2013๋…„ 4์›”๊นŒ์ง€ ๋ณธ์›์„ ๋ฐฉ๋ฌธํ•ด 2ํšŒ ์ด์ƒ ์—ฐ์†๋œ ๊ณ ๊ด€์ ˆ ๋ฐฉ์‚ฌ์„ ์ดฌ์˜ ๊ธฐ๋ก์„ ๊ฐ€์ง„ ๋‡Œ์„ฑ๋งˆ๋น„ ํ™˜์ž๋“ค์˜ ์˜๋ฌด๊ธฐ๋ก๊ณผ ๋ฐฉ์‚ฌ์„  ์˜์ƒ์„ ๋ถ„์„ํ•˜์˜€๋‹ค. ๊ณผ๊ฑฐ ๊ฑด์ ˆ๋‹จ์ˆ˜์ˆ  ๋ฐ ์—ฐ์žฅ์ˆ˜์ˆ  ๋“ฑ์˜ ์—ฐ๋ถ€์กฐ์ง ์ˆ˜์ˆ , ๋Œ€ํ‡ด๊ณจ ๋ฐ ๊ณจ๋ฐ˜๊ณจ ์ ˆ๊ณจ์ˆ˜์ˆ  ๋“ฑ ๊ณ ๊ด€์ ˆ ์ˆ˜์ˆ ๋ณ‘๋ ฅ์ด ์žˆ๊ฑฐ๋‚˜ ์™ธ์ƒ, ๊ฐ์—ผ, ์ข…์–‘์— ์˜ํ•œ ๊ณ ๊ด€์ ˆ ๋ณ€ํ˜•์ด ์žˆ๋Š” ๊ฒฝ์šฐ, ๋ฐฉ์‚ฌ์„  ์˜์ƒ์ด ๋ถ€์ ํ•ฉํ•œ ๊ฒฝ์šฐ, ๋‡Œ์„ฑ๋งˆ๋น„ ์ด์™ธ์˜ ์‹ ๊ฒฝ, ๊ทผ์œก ์ด์ƒ์ด ์žˆ๋Š” ํ™˜์ž๋Š” ์ œ์™ธํ•˜๊ณ  ์„ ์ •๋œ ํ™˜์ž์˜ ๋ฐฉ์‚ฌ์„  ์‚ฌ์ง„์—์„œ 5๊ฐ€์ง€์˜ ๋ฐฉ์‚ฌ์„  ์ง€ํ‘œ๋ฅผ ๋‡Œ์„ฑ๋งˆ๋น„ ํ™˜์ž์˜ ๊ณ ๊ด€์ ˆ ๋ถˆ์•ˆ์ •์„ฑ ๋ฐœ์ƒ ์œ„ํ—˜์„ ํŒ์ •ํ•˜๋Š”๋ฐ ์ ํ•ฉํ•œ ์ธ์ž๋กœ ์„ ์ •ํ•˜์˜€๋‹ค. ์„ ์ •๋œ ๋ฐฉ์‚ฌ์„  ์ง€ํ‘œ๋Š” ์ „์ด๋ฐฑ๋ถ„์œจ (migration percentage, MP), ๋Œ€ํ‡ด๊ฒฝ๊ฐ„๊ฐ (neck-shaft angle, NSA), ๋Œ€ํ‡ด๊ณจ๋‘-๊ฐ„๋ถ€๊ฐ (head-shaft angle, HSA), ๋น„๊ตฌ ์ง€์ˆ˜ (acetabular index, AI), ๊ทธ๋ฆฌ๊ณ  ๊ณจ๋ฐ˜ ๊ฒฝ์‚ฌ (pelvic obliquity, PO)์ด๋ฉฐ ์‹ ๋ขฐ๋„ ์‹œํ—˜ ํ›„ ๋ฐฉ์‚ฌ์„  ์‚ฌ์ง„์—์„œ ์ธก์ •ํ•˜์˜€๋‹ค. ๊ณ ๊ด€์ ˆ ์ถ”์ ๊ด€์ฐฐ ๋™์•ˆ ๋ฐฉ์‚ฌ์„ ์ง€ํ‘œ์˜ ์—ฐ๋ณ„ ๋ณ€ํ™”๋ฅผ ๋ถ„์„ํ•˜๊ธฐ ์œ„ํ•ด ์„ ํ˜• ๋ณตํ•ฉ๋ชจ๋ธ(linear mixed model, LMM)์„ ์ ์šฉํ•˜์—ฌ GMFCS๋‹จ๊ณ„์— ๋”ฐ๋ฅธ ์œ„ํ—˜์ธ์ž ๋ณด์ •์„ ๊ฑฐ์ณ ๊ฐ๊ฐ์˜ ์ธก์ •๊ฐ’์„ ๊ธฐ๋กํ•˜์˜€๋‹ค. ๊ฒฐ๊ณผ: ์ด 157๋ช…์˜ ํ™˜์ž์˜ ๋ฐฉ์‚ฌ์„  ์‚ฌ์ง„ 614์žฅ์„ ํ‰๊ฐ€ํ–ˆ๋‹ค. GMFCS ๋ถ„๋ฅ˜์ƒ 95๋ช…์€ Iโ€“III๋‹จ๊ณ„, 32๋ช…์€ IV๋‹จ๊ณ„, ๊ทธ๋ฆฌ๊ณ  30๋ช…์€ V๋‹จ๊ณ„์— ์†ํ–ˆ๋‹ค. V๋‹จ๊ณ„์— ์†ํ•œ ํ™˜์ž๊ตฐ์˜ MP๋Š”7.1%/๋…„ (p=0.018)์˜ ์†๋„๋กœ ํ†ต๊ณ„์ ์œผ๋กœ ์˜๋ฏธ ์žˆ๊ฒŒ ์ฆ๊ฐ€ํ–ˆ๋‹ค. NSA๋Š” GMFCS ๋‹จ๊ณ„ Iโ€“III, IV, V๊ตฐ์—์„œ ๊ฐ๊ฐ 3.2ยฐ/๋…„ (p<0.001), 4.7ยฐ/๋…„ (p<0.001), 5.3ยฐ/๋…„ (p<0.001)์”ฉ ์œ ์˜ํ•˜๊ฒŒ ์ฆ๊ฐ€ํ•˜์˜€์œผ๋ฉฐ HSA๋Š” GMFCS V ๋‹จ๊ณ„ ํ™˜์ž๊ตฐ์—์„œ 3.8ยฐ/๋…„ (p=0.003)๋กœ ์œ ์˜ํ•˜๊ฒŒ ์ฆ๊ฐ€ํ•œ ๋ฐ ๋ฐ˜ํ•ด AI์™€ PO๋Š” ํ†ต๊ณ„์ ์œผ๋กœ ์˜๋ฏธ ์žˆ๋Š” ๋ณ€ํ™”๋Š” ์—†์—ˆ๋‹ค. ๊ฒฐ๋ก : ๋ณธ ์—ฐ๊ตฌ๋Š” ๋‡Œ์„ฑ๋งˆ๋น„ ํ™˜์ž์—์„œ์˜ ๊ณ ๊ด€์ ˆ ๋ถˆ์•ˆ์ •์„ฑ ์ง„ํ–‰ ์†๋„๋ฅผ ์—ฐ๊ตฌํ•˜๊ณ  ๋ถˆ์•ˆ์ •์„ฑ ์ง„ํ–‰์— ์˜ํ–ฅ์„ ๋ฏธ์น˜๋Š” ์ธ์ž๋ฅผ ์‚ดํŽด๋ณด๋ฉฐ GMFCS์™€ ์ง„ํ–‰ ์ •๋„์˜ ์ƒ๊ด€๊ด€๊ณ„๋ฅผ ํ‰๊ฐ€ํ•˜์˜€๋‹ค. ๊ณ ๊ด€์ ˆ ๋ถˆ์•ˆ์ •์— ๋Œ€ํ•ด ์ˆ˜์ˆ ํ•˜๊ธฐ ์ „ ํ™˜์ž๊ฐ€ ์„ฑ์žฅํ•จ์— ๋”ฐ๋ผ ์œ„ํ—˜์ธ์ž๋กœ ์„ ์ •๋œ ๋ฐฉ์‚ฌ์„  ์ง€ํ‘œ ์ค‘ ์ „์ด๋ฐฑ๋ถ„์œจ (migration percentage, MP), ๋Œ€ํ‡ด๊ฒฝ๊ฐ„๊ฐ (neck-shaft angle, NSA), ๋Œ€ํ‡ด๊ณจ๋‘-๊ฐ„๋ถ€๊ฐ(head-shaft angle, HSA)์ด ์ฆ๊ฐ€๋˜์—ˆ๊ณ  ๊ทธ ์†๋„๋Š” GMFCS๋‹จ๊ณ„์— ๋”ฐ๋ผ ์œ ์˜ํ•˜๊ฒŒ ๋‹ค๋ฅด๋‹ค๋Š” ์‚ฌ์‹ค์„ ๋ฐœ๊ฒฌํ–ˆ๋‹ค. GMFCS V๋‹จ๊ณ„์—์„œ ๊ณ ๊ด€์ ˆ ๋ถˆ์•ˆ์ • ์ง„ํ–‰์˜ ์œ„ํ—˜์ธ์ž๋กœ์„œ ์œ„ 3๊ฐ€์ง€ ๋ฐฉ์‚ฌ์„  ์ง€ํ‘œ๊ฐ€ ํ†ต๊ณ„์ ์œผ๋กœ ์œ ์˜ํ•˜์˜€์œผ๋ฉฐ ์ด๋ฅผ ํ†ตํ•ด ๋ณดํ–‰์ด ๋ถˆ๊ฐ€๋Šฅํ•œ GMFCS V๋‹จ๊ณ„ํ™˜์ž์—์„œ ์ •๊ธฐ์ ์ธ ๋ฐฉ์‚ฌ์„ ํ•™์  ๊ณ ๊ด€์ ˆ ์ถ”์ ๊ด€์ฐฐ์˜ ํ•„์š”์„ฑ์„ ์ž…์ฆํ•˜์˜€๋‹ค.Introduction: Hip instability is problematic in patients with cerebral palsy (CP). Some reports described the progression of hip instability, however, there are few reports about rate of progression, affecting factors, and relationship between Gross Motor Function Classification System (GMFCS) level and degree of progression of hip instability. In the present study, we aimed to investigate affecting factors and rate of progression of hip instability in patients with CP by assessing changes in the radiographic indices according to GMFCS level during hip surveillance. Methods: We analyzed medical records of consecutive patients with CP who had visited our hospital between July 2003 and April 2013, and had more than two serial hip radiographs obtained during duration of hip surveillance were included in this study, excluding those with (1) history of hip surgery(2) presence of hip deformities caused by trauma, infection, tumor, etc.(3) inadequate taken or scanty number of hip radiographsand (4) presence of neuromuscular diseases other than CP. Through panel consensus, five indices of radiographic measurements were selected including migration percentage (MP), neck-shaft angle (NSA), head-shaft angle (HSA), acetabular index (AI) and pelvic obliquity (PO) on the serial hip radiograph. A linear mixed model (LMM) application was used to analyze annual changes in radiographic indices of hip instability during duration hip surveillance. Measurements were adjusted for risk factors according to GMFCS levels. Results: A total of 157patients were included in this study, and 614 radiographs were evaluated. GMFCS classifications were as followed: level Iโ€“III in 95 patients, level IV in 32, and level V in 30. In patient with GMFCS level V, MP significantly increased by 7.1%/year (p=0.018). NSA significantly increased over the duration of hip surveillance in patients with GMFCS levels Iโ€“III, IV, and V by 3.2ยฐ/year (p<0.001), 4.7ยฐ/year (p<0.001), 5.3ยฐ/year (p<0.001), respectively. HSA significantly increased by 3.8ยฐ/year (p=0.003) in patient with GMFCS level V, whereas AI and PO did not change significantly. Conclusions: This study investigated the rate of progression of hip instability in patients with CP, the factors influencing this progression, and relation between GMFCS level and degree of the progression. Of the 5 indices investigated in the study, we found that MP, NSA, and HSA significantly escalated with age, and tended to increase in higher GMFCS levels. In patients with GMFCS V, the above three indices were statistically significant in predicting hip instability, thus warranting periodic radiographic hip surveillance in this group.์ดˆ๋ก i ๋ชฉ์ฐจ iv ํ‘œ ๋ฐ ๊ทธ๋ฆผ ๋ชฉ๋ก v ์„œ๋ก  1 ์—ฐ๊ตฌ์žฌ๋ฃŒ ๋ฐ ๋ฐฉ๋ฒ• 4 ๊ฒฐ๊ณผ 14 ๊ณ ์ฐฐ 15 ์ฐธ๊ณ ๋ฌธํ—Œ 26 ์ดˆ๋ก (์˜๋ฌธ)... 32Maste

    (An) analysis of factors for gastric cancer screening

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    ๋ณด๊ฑดํ•™๊ณผ/์„์‚ฌ[ํ•œ๊ธ€] ๋ฐฐ๊ฒฝ: ์„ธ๊ณ„์ ์œผ๋กœ ๋งค๋…„ 1,000๋งŒ ๋ช…์˜ ์•” ํ™˜์ž๊ฐ€ ๋ฐœ์ƒํ•˜๊ณ  ์žˆ์œผ๋ฉฐ, 2020๋…„์ด ๋˜๋ฉด ์•ฝ 1,500๋งŒ ๋ช…์˜ ์•” ํ™˜์ž๊ฐ€ ๋งค๋…„ ๋ฐœ์ƒํ•  ๊ฒƒ์œผ๋กœ ์ถ”์ •ํ•˜๊ณ  ์žˆ๋‹ค. ์šฐ๋ฆฌ๋‚˜๋ผ๋„ ๋งค๋…„ ์•ฝ 10๋งŒ ๋ช…์˜ ์•” ํ™˜์ž๊ฐ€ ์ƒˆ๋กญ๊ฒŒ ๋ฐœ์ƒํ•˜๊ณ  ์žˆ์œผ๋ฉฐ, ์•ฝ 6๋งŒ ๋ช…์ด ์•”์œผ๋กœ ์‚ฌ๋งํ•˜๊ณ  ์žˆ๋‹ค. WHO์—์„œ๋Š” ์•” ํ™˜์ž์™€ ๊ทธ ๊ฐ€์กฑ๋“ค์˜ ์‚ถ์˜ ์งˆ์„ ํ–ฅ์ƒ์‹œํ‚ค๊ธฐ ์œ„ํ•œ ๊ฐ€์žฅ ํšจ๊ณผ์ ์ธ ๊ตญ๊ฐ€ ๋‹จ์œ„์˜ ๋…ธ๋ ฅ์œผ๋กœ ๊ตญ๊ฐ€์•”๊ด€๋ฆฌ์‚ฌ์—… ์ˆ˜ํ–‰์„ ๊ถŒ์žฅํ•˜๊ณ  ์žˆ๋‹ค. ์šฐ๋ฆฌ๋‚˜๋ผ๋„ ์ด๋Ÿฌํ•œ ๊ตญ๊ฐ€์  ๋…ธ๋ ฅ์œผ๋กœ 1996๋…„๋ถ€ํ„ฐ โ€œ์•”์ •๋ณต 10๊ฐœ๋…„ ๊ณ„ํšโ€์„ ์ˆ˜๋ฆฝํ•˜์—ฌ ์ถ”์ง„ํ•˜๊ณ  ์žˆ๋‹ค. 2007๋…„ ๊ตญ๋ฏผ์˜ 5๋Œ€ ์•”๊ฒ€์ง„ ์ˆ˜๊ฒ€๋ฅ ์€ 47.5%์ด๋ฉฐ, ์œ„์•”์˜ ์ˆ˜๊ฒ€๋ฅ ์€ 45.6%๋กœ ์„ ์ง„ ์™ธ๊ตญ์˜ 70~80%์— ๋น„ํ•˜๋ฉด ์—ฌ์ „ํžˆ ๋‚ฎ์€ ์ˆ˜์ค€์ด๋‹ค.๋ชฉ์ : ์ธ๊ตฌ์‚ฌํšŒํ•™์  ํŠน์„ฑ์ด ์œ„์•” ์กฐ๊ธฐ๊ฒ€์ง„ ์ˆ˜๊ฒ€์˜๋„์— ์–ด๋– ํ•œ ์˜ํ–ฅ์„ ๋ฏธ์น˜๋Š”์ง€๋ฅผ Andersen ๋ชจํ˜•์„ ์ด์šฉํ•˜์—ฌ ์•Œ์•„๋ณด๊ณ ์ž ํ•œ๋‹ค.๋ฐฉ๋ฒ•: ๊ตญ๋ฆฝ์•”์„ผํ„ฐ์—์„œ 2005๋…„๋ถ€ํ„ฐ ์‹œํ–‰ํ•˜๊ณ  ์žˆ๋Š” 5๋Œ€ ์•”๊ฒ€์ง„ ์ˆ˜๊ฒ€๋ฅ  ๋ฐ ์•”์ •๋ณด ํ˜„ํ™ฉ์— ๋Œ€ํ•œ ์กฐ์‚ฌ ์ž๋ฃŒ๋ฅผ ์ด์šฉํ•˜์˜€๊ณ , ๊ฒฝ๊ธฐ๋„ 2๊ฐœ ์‹œ ์ง€์—ญ๊ณผ 1๊ฐœ ๊ตฐ ์ง€์—ญ์— ๊ฑฐ์ฃผํ•˜๋Š” ์ด 226๋ช…์„ ๋Œ€์ƒ์œผ๋กœ ์†Œ์ธ์„ฑ, ๊ฐ€๋Šฅ์„ฑ, ํ•„์š” ์š”์ธ์˜ ํŠน์„ฑ์„ ์•Œ์•„๋ณด์•˜์œผ๋ฉฐ, ์ˆ˜๊ฒ€์˜๋„์™€์˜ ๊ด€๊ณ„๋ฅผ ์ด๋ณ€๋Ÿ‰ ๋ถ„์„๊ณผ ๋‹ค๋ณ€๋Ÿ‰ ๋ถ„์„์„ ํ†ตํ•ด ์•Œ์•„๋ณด์•˜๋‹ค.๊ฒฐ๊ณผ: ์ด๋ณ€๋Ÿ‰ ๋ถ„์„ ๊ฒฐ๊ณผ ์ˆ˜๊ฒ€์˜๋„๊ฐ€ ์žˆ๋Š” ์‚ฌ๋žŒ ์ค‘ ์ž๊ฐ ๊ฑด๊ฐ•์ƒํƒœ๊ฐ€ ์ข‹์€ ์‚ฌ๋žŒ์€ 95.5%, ํ‰์†Œ ์šด๋™์„ ํ•œ๋‹ค๋Š” ์‚ฌ๋žŒ์ด 61.1%๋กœ ๋งŽ์•˜์œผ๋ฉฐ, ํ†ต๊ณ„์ ์œผ๋กœ ์œ ์˜ํ•˜์˜€๋‹ค. ๋‹ค๋ณ€๋Ÿ‰ ๋ถ„์„๊ฒฐ๊ณผ ์ž๊ฐ ๊ฑด๊ฐ•์ƒํƒœ๊ฐ€ ์ข‹์€ ์‚ฌ๋žŒ์˜ ๊ต์ฐจ๋น„๋Š” 3.72์˜€์œผ๋ฉฐ, ํ‰์†Œ ์šด๋™์„ ํ•˜๋Š” ์‚ฌ๋žŒ์˜ ๊ต์ฐจ๋น„๋Š” 1.90์œผ๋กœ ํ†ต๊ณ„์ ์œผ๋กœ ์œ ์˜ํ•˜์˜€๋‹ค.๊ฒฐ๋ก : ๊ฑด๊ฐ•ํ•œ ์‚ฌ๋žŒ์ด ์กฐ๊ธฐ๊ฒ€์ง„ ์ˆ˜๊ฒ€์˜๋„๊ฐ€ ๋†’์€ ๊ฒƒ์œผ๋กœ ์กฐ์‚ฌ๋˜์—ˆ๋‹ค. ๋”ฐ๋ผ์„œ ํ‰์†Œ ๊ฑด๊ฐ•ํ–‰ํƒœ๋ฅผ ์‹ค์ฒœํ•˜์ง€ ์•Š๋Š” ์‚ฌ๋žŒ๋“ค์˜ ์ˆ˜๊ฒ€์˜๋„๋ฅผ ๋†’์ด๊ธฐ ์œ„ํ•œ ๊ต์œก์  ์ ‘๊ทผ์ด ํ•„์š”ํ•  ๊ฒƒ์ด๋‹ค. ์œ„์•” ์˜ˆ๋ฐฉ์— ๋Œ€ํ•œ ์ง€์‹์„ ๋†’์ผ ์ˆ˜ ์žˆ๋Š” ์ ๊ทน์ ์ธ ํ™๋ณด์™€ ๋ณด๊ฑด๊ต์œก์ด ์ด๋ฃจ์–ด์ ธ์•ผ ํ•  ๊ฒƒ์ด๋‹ค. [์˜๋ฌธ] Background: There are 10 million cancer patients worldwide, and it is estimated that there will be 15 million cancer patients in 2020. There are approximately 100 thousand cancer patients yearly in Korea and about 60 thousand patients die of cancer. The WTO recommends the implementation of a National Cancer Screening Program to enhance the quality of life of cancer patients and their families as an efficient national resource. The Korean government also has been promoting a 10?year plan for cancer control as a national effort since 1996. The cancer?screening rate for five major cancers was 47.5% and the gastric cancer screening rate was 45.6% in 2007; these rates that are lower than that of other developed countries.Object: To examine how socio?demographic factors affect the gastric cancer screening rate determined by the Anderson model.Methods: We used factors for the screening of five major cancers that have been implemented by the National Cancer Program. We targeted 226 people who resided in urban areas and rural areas for 2 weeks from 16 August 2005. We examined characteristics of predisposition , enabling and need factors, and the relationship with the intention for cancer screening by the use of bivariate analysis and multivariate analysis.Results: According to bivariate analysis, among subjects with an intention for cancer screening, 95% of the subjects had a good self?conscious health status, and 61.6% of the subjects exercised regularly; these findings were significant statistically. According to multivariate analysis, the odds ratio of subjects with a good self?conscious health status was 3.72, and the odds ratio of subjects who exercised regularly was 1.90.Conclusions: It was determined that a healthy subject had a higher intention to participate in gastric cancer screening. Therefore, we need to provide education to subjects in poorer health so that they will also participate in cancer screening.. Active promotion and health education should be performed to elevate knowledge about the prevention of gastric cancer.ope

    LiCl-KCl ์šฉ์œต์—ผ ๊ธฐ๋ฐ˜ ์‚ฌ์šฉํ›„ํ•ต์—ฐ๋ฃŒ ๋ฐฉ์‚ฌํ™” ์ง€๋ฅด์นผ๋กœ์ด-4 ํ”ผ๋ณต๊ด€ ์ „ํ•ด์ •๋ จ

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    ํ•™์œ„๋…ผ๋ฌธ (๋ฐ•์‚ฌ)-- ์„œ์šธ๋Œ€ํ•™๊ต ๋Œ€ํ•™์› : ์—๋„ˆ์ง€์‹œ์Šคํ…œ๊ณตํ•™๋ถ€, 2014. 8. ํ™ฉ์ผ์ˆœ.์ง€๋ฅด์ฝ”๋Š„ ํ•ฉ๊ธˆ์€ ๋‚ฎ์€ ์—ด์ค‘์„ฑ์ž ํก์ˆ˜๋‹จ๋ฉด์ ๊ณผ ์šฐ์ˆ˜ํ•œ ๋‚ด๋ถ€์‹์„ฑ ๋ฐ ๊ธฐ๊ณ„์  ์„ฑ์งˆ์„ ๊ฐ€์ง€๊ณ  ์žˆ์–ด, ์›์ž๋กœ์˜ ๊ณ ์˜จโ€ข๊ณ ์••โ€ข๊ณ ๋ฐฉ์‚ฌ์„ ๊ณผ ๊ฐ™์€ ๊ฐ€ํ˜นํ•œ ํ™˜๊ฒฝ์— ์ ํ•ฉํ•ด ์›์ž๋ ฅ ๋ฐœ์ „์†Œ์˜ ์ฃผ์š” ๊ตฌ์กฐ์žฌ๋กœ ํ™œ์šฉ๋˜์–ด ์™”๋‹ค. ์šฐ๋ฆฌ๋‚˜๋ผ๋Š” ๊ฐ€์••๊ฒฝ์ˆ˜๋กœ์™€ ์ค‘์ˆ˜๋กœ์—์„œ ํ•ต์—ฐ๋ฃŒํ”ผ๋ณต๊ด€, ์••๋ ฅ๊ด€, ์นผ๋ž€๋“œ๋ฆฌ์•„๊ด€ ๋“ฑ์˜ ์šฉ๋„๋กœ ์ง€๋ฅด์ฝ”๋Š„ ํ•ฉ๊ธˆ์„ ์‚ฌ์šฉํ•ด์˜ค๊ณ  ์žˆ๋‹ค. ๋”ฐ๋ผ์„œ ์›์ „์˜ ์šด์˜ ์ค‘, ์šด์˜ ํ›„์— ๋งŽ์€ ์–‘์˜ ๋ฐฉ์‚ฌ์„ฑ ์ง€๋ฅด์ฝ”๋Š„ ํ๊ธฐ๋ฌผ์˜ ๋ฐœ์ƒ์€ ํ•„์—ฐ์ ์ด๋‹ค. ๋ฐฉ์‚ฌ์„ฑ ์ง€๋ฅด์ฝ”๋Š„ ํ•ฉ๊ธˆ ํ๊ธฐ๋ฌผ ์ค‘ ์‚ฌ์šฉํ›„ํ•ต์—ฐ๋ฃŒ ํ”ผ๋ณต๊ด€์€ ์‚ฌ์šฉํ›„ํ•ต์—ฐ๋ฃŒ ์ง‘ํ•ฉ์ฒด ์งˆ๋Ÿ‰์˜ ์•ฝ 16%๋ฅผ ์ฐจ์ง€ํ•˜์—ฌ ๋ฐœ์ƒ๋Ÿ‰์ด ๊ฐ€์žฅ ๋งŽ๋‹ค. ๋˜ํ•œ ํ•ต์—ฐ๋ฃŒ์™€ ์ง์ ‘ ๋งž๋‹ฟ์•„ ์žˆ์–ด ์›์ „ ์šด์˜ ์ค‘ ์•…ํ‹ฐ๋‚˜์ด๋“œ ์›์†Œ์™€ ํ•ต๋ถ„์—ด์ƒ์„ฑ๋ฌผ์ด ์นจํˆฌํ•˜์—ฌ IAEA ๋ฐฉ์‚ฌ์„ฑํ๊ธฐ๋ฌผ ์‹ ๋ถ„๋ฅ˜ ์ฒด๊ณ„์˜ ์ค‘์ค€์œ„ํ๊ธฐ๋ฌผ๋กœ ๋ถ„๋ฅ˜๋œ๋‹ค. ๊ทธ๋Ÿฌ๋‚˜ ํ”ผ๋ณต๊ด€์˜ ๋Œ€๋ถ€๋ถ„์€ ๋ฐฉ์‚ฌํ™”๋˜์ง€ ์•Š์€ ์ง€๋ฅด์ฝ”๋Š„์œผ๋กœ ์ด๋ฃจ์–ด์ ธ ์žˆ๋‹ค. ๋”ฐ๋ผ์„œ ์‚ฌ์šฉํ›„ํ•ต์—ฐ๋ฃŒ ํ”ผ๋ณต๊ด€ ๋‚ด ์ง€๋ฅด์ฝ”๋Š„์„ ๋ฐฉ์‚ฌ์„ฑ ์›์†Œ ๋ฐ ๊ธฐํƒ€ ๋ถˆ์ˆœ๋ฌผ๋กœ๋ถ€ํ„ฐ ๋ถ„๋ฆฌํ•ด๋‚ผ ์ˆ˜ ์žˆ๋‹ค๋ฉด, ์‚ฌ์šฉํ›„ํ•ต์—ฐ๋ฃŒ ์ง‘ํ•ฉ์ฒด๋กœ๋ถ€ํ„ฐ ๋ฐœ์ƒํ•˜๋Š” ๋ฐฉ์‚ฌ์„ฑํ๊ธฐ๋ฌผ ์ฒ˜๋ถ„๋Ÿ‰์„ ํฌ๊ฒŒ ๊ฐ์†Œ์‹œํ‚ฌ ์ˆ˜ ์žˆ์„ ๊ฒƒ์œผ๋กœ ์˜ˆ์ƒ๋˜๋ฉฐ, ํšŒ์ˆ˜๋œ ์ง€๋ฅด์ฝ”๋Š„์„ ์›์ž๋ ฅ ์‚ฐ์—…์—์„œ ๋‹ค์‹œ ์žฌํ™œ์šฉ๋  ์ˆ˜ ์žˆ์„ ๊ฒƒ์œผ๋กœ ๊ธฐ๋Œ€๋œ๋‹ค. ์ด๋Ÿฌํ•œ ์ด์œ ๋กœ ์‚ฌ์šฉํ›„ํ•ต์—ฐ๋ฃŒ ํ”ผ๋ณต๊ด€์„ ์ œ์—ผํ•˜๊ธฐ ์œ„ํ•œ ๋‹ค์–‘ํ•œ ๊ณต์ •์ด ์—ฐ๊ตฌ๋˜์–ด์™”๋‹ค. 2009๋…„ ๋ฐœํ‘œ๋œ ๋…ผ๋ฌธ์—์„œ๋Š” HF๋ฅผ ์‚ฌ์šฉํ•œ ์‚ฌ์šฉํ›„ํ•ต์—ฐ๋ฃŒ ํ”ผ๋ณต๊ด€ ํ‘œ๋ฉด์ œ์—ผ์„ ํ†ตํ•ด ์•…ํ‹ฐ๋‚˜์ด๋“œ ์›์†Œ ๋ฐ ํ•ต๋ถ„์—ด์ƒ์„ฑ๋ฌผ์„ ์ œ๊ฑฐํ•˜๊ณ ์ž ํ•˜์˜€๋‹ค. ๊ทธ๋Ÿฌ๋‚˜ ์ด๋“ค ์›์†Œ์˜ ์นจํˆฌ๊นŠ์ด๊ฐ€ ๊นŠ์–ด 180ฮผm ์ด์ƒ ์ œ์—ผ์ดํ›„์—๋„ ๋ฐฉ์‚ฌ์„  ์ค€์œ„๊ฐ€ GTCC (Greater Than Class C) ํ๊ธฐ๋ฌผ ๋ถ„๋ฅ˜๊ธฐ์ค€์„ ์ƒํšŒํ•˜์˜€๋‹ค. ๋”ฐ๋ผ์„œ ํ‘œ๋ฉด์ œ์—ผ๋งŒ์œผ๋กœ๋Š” ์‚ฌ์šฉํ›„ํ•ต์—ฐ๋ฃŒ ํ”ผ๋ณต๊ด€์˜ ๋ฐฉ์‚ฌ์„  ์ค€์œ„๋ฅผ ๋‚ฎ์ถ”๊ธฐ์—๋Š” ๋ถ€์กฑํ•˜๋‹ค. ์‚ฌ์šฉํ›„ํ•ต์—ฐ๋ฃŒ ํ”ผ๋ณต๊ด€์˜ ์ถฉ๋ถ„ํ•œ ์ œ์—ผ์„ ์œ„ํ•ด์„œ๋Š” ์ฒด์ ์ œ์—ผ์ด ์ด๋ฃจ์–ด์ ธ์•ผ ํ•˜๋ฉฐ ์ฒด์ ์ œ์—ผ ๋ฐฉ๋ฒ•์—๋Š” ์—ผ์†Œ๋‚˜ ์•„์ด์˜ค๋”˜ ๊ธฐ์ฒด์™€ ํ”ผ๋ณต๊ด€์„ ๋ฐ˜์‘์‹œํ‚ค๋Š” ๊ธฐ์ฒด๋ฐ˜์‘๋ฒ•๊ณผ ์ „ํ•ด์ •๋ จ ๋ฐฉ๋ฒ• ๋“ฑ์ด ์žˆ๋‹ค. ๊ธฐ์ฒด๋ฐ˜์‘๋ฒ•์€ ๋†’์€ ์ˆœ๋„์˜ ์ง€๋ฅด์ฝ”๋Š„์„ ๋ถ„๋ฆฌํ•  ์ˆ˜ ์žˆ๋‹ค๋Š” ์žฅ์ ์ด ์žˆ์œผ๋‚˜, ์•„์ด์˜ค๋‹ค์ธ ๊ธฐ์ฒด๋ฐ˜์‘๋ฒ•์€ ZrI4์˜ ํก์Šต์„ฑ์ด ๋†’๊ณ , ZrI4์—์„œ Zr์„ ๋ถ„๋ฆฌํ•˜๋Š” ๊ณต์ •์˜ ์†๋„๊ฐ€ ๋Š๋ฆฌ๋‹ค๋Š” ๋‹จ์ ์ด ์žˆ์œผ๋ฉฐ, ์—ผ์†Œ ๊ธฐ์ฒด๋ฐ˜์‘๋ฒ•์€ ZrCl4์—์„œ Zr์„ Kroll ๊ณต์ •์œผ๋กœ ๋ถ„๋ฆฌํ•˜๋Š” ๊ณผ์ •์—์„œ ๋งŽ์€ ์–‘์˜ Mg ํ๊ธฐ๋ฌผ์ด ๋ฐœ์ƒํ•  ์ˆ˜ ์žˆ๋‹ค. ์ „ํ•ด์ •๋ จ์„ ํ†ตํ•œ ์‚ฌ์šฉํ›„ํ•ต์—ฐ๋ฃŒ ํ”ผ๋ณต๊ด€์˜ ์ œ์—ผ์€ ์—ผํ™”๋ฌผ์ด๋‚˜ ๋ถˆํ™”๋ฌผ๊ณผ ๊ฐ™์€ ์šฉ์œต์—ผ์„ ์ „ํ•ด์งˆ๋กœ ์‚ฌ์šฉํ•˜๋Š” ๊ณต์ •์ด ์—ฐ๊ตฌ๋˜์–ด ์™”๋‹ค. ๋ถˆํ™”๋ฌผ LiF-KF๋ฅผ ์ „ํ•ด์งˆ๋กœ ์‚ฌ์šฉํ•˜๋Š” ์ „ํ•ด์ •๋ จ ๊ณต์ •์€ ๋†’์€ ์ˆœ๋„์˜ ์ง€๋ฅด์ฝ”๋Š„์„ ํฐ ์ž…์žํ˜•ํƒœ๋กœ ํšŒ์ˆ˜ํ•  ์ˆ˜ ์žˆ๋‹ค๋Š” ์žฅ์ ์ด ์žˆ์œผ๋‚˜ ๋ถˆํ™”๋ฌผ์˜ ๋…น๋Š”์ ์ด ๋†’์•„ ์ „ํ•ด์ •๋ จ ์šด์ „์˜จ๋„๊ฐ€ ๋†’์œผ๋ฉฐ ๋ถˆํ™”๋ฌผ๋กœ ์ธํ•œ ๊ตฌ์กฐ์žฌ ๋ถ€์‹์˜ ์šฐ๋ ค๊ฐ€ ์žˆ๋‹ค. ์—ผํ™”๋ฌผ๊ณผ ๋ถˆํ™”๋ฌผ์„ ํ•จ๊ป˜ ์‚ฌ์šฉํ•˜๋Š” ๊ณต์ •์˜ ๊ฒฝ์šฐ์—๋Š” ์šด์ „์˜จ๋„๋ฅผ ๋‚ฎ์ถœ ์ˆ˜๋Š” ์žˆ์œผ๋‚˜ ์—ผํ™”๋ฌผ์„ ์‚ฌ์šฉํ•˜๋Š” ๊ฒฝ์šฐ๋ณด๋‹ค๋Š” ๋†’๊ณ , ๋ถˆํ™”๋ฌผ๋กœ ์ธํ•œ ๋ถ€์‹์˜ ๊ฐ€๋Šฅ์„ฑ์ด ์—ฌ์ „ํžˆ ์กด์žฌํ•œ๋‹ค. ์—ผํ™”๋ฌผ์„ ์ „ํ•ด์งˆ๋กœ ์‚ฌ์šฉํ•˜๋Š” ์ „ํ•ด์ •๋ จ์€ ๋น„๊ต์  ๋‚ฎ์€ ์˜จ๋„์—์„œ ์ž‘์—…์ด ๊ฐ€๋Šฅํ•˜๋ฉฐ ์ƒ๋Œ€์ ์œผ๋กœ ๋ถ€์‹๋ฌธ์ œ๋„ ์ ์–ด ์ƒ์šฉ ๊ณต์ •์— ์ ํ•ฉํ•œ ํŠน์„ฑ์„ ์ง€๋‹ˆ๊ณ  ์žˆ๋‹ค. ๊ทธ๋Ÿฌ๋‚˜ ์—ผํ™”์—ผ ๋‚ด ์ง€๋ฅด์ฝ”๋Š„์˜ ์‚ฐํ™”ํ™˜์› ๊ฑฐ๋™์ด ๋ณต์žกํ•˜์—ฌ ZrCl๊ฐ€ ์ง€๋ฅด์ฝ”๋Š„ ๊ธˆ์†๊ณผ ํ•จ๊ป˜ ์Œ๊ทน์— ์ „์ฐฉ๋  ๊ฐ€๋Šฅ์„ฑ์ด ์žˆ์œผ๋ฉฐ, ์Œ๊ทน์—์„œ ์ง€๋ฅด์ฝ”๋Š„ ์ด์˜จ์˜ ํ™˜์› ๋ฐ˜์‘ ์ด์™ธ์— Zr(IV) ์ด์˜จ์ด ์ง€๋ฅด์ฝ”๋Š„ ๊ธˆ์†๊ณผ ๋ฐ˜์‘ํ•˜์—ฌ Zr(II)์„ ํ˜•์„ฑํ•˜๋Š” ๋ถˆ๊ท ๋“ฑํ™” ๋ฐ˜์‘์ด ํ•จ๊ป˜ ์ผ์–ด๋‚  ์ˆ˜ ์žˆ๋‹ค. ์—ผํ™”๋ฌผ ๋‚ด ์ง€๋ฅด์ฝ”๋Š„์˜ ์‚ฐํ™”ํ™˜์› ๊ฑฐ๋™ ๋Œ€ํ•œ ์—ฐ๊ตฌ๋ฅผ ๋ฐ”ํƒ•์œผ๋กœ ZrCl ํ˜•์„ฑ ๋ฐ ๋ถˆ๊ท ๋“ฑํ™” ๋ฐ˜์‘์„ ์–ต์ œํ•  ์ˆ˜ ์žˆ๋‹ค๋ฉด, ์—ผํ™”์—ผ ๊ธฐ๋ฐ˜ ์ „ํ•ด์ •๋ จ์„ ์‚ฌ์šฉํ›„ํ•ต์—ฐ๋ฃŒ ํ”ผ๋ณต๊ด€ ์ œ์—ผ์„ ์œ„ํ•œ ์ฃผ์š” ๊ณต์ •์œผ๋กœ ํ™œ์šฉํ•  ์ˆ˜ ์žˆ์„ ๊ฒƒ์œผ๋กœ ๊ธฐ๋Œ€๋œ๋‹ค. ๋ณธ ๋…ผ๋ฌธ์—์„œ๋Š” ์—ผํ™”์—ผ์„ ๊ธฐ๋ฐ˜์œผ๋กœํ•œ ์ „ํ•ด์ •๋ จ ๊ณต์ •์„ ๊ฐœ๋ฐœํ•˜๋Š” ๊ฒƒ์„ ๋ชฉํ‘œ๋กœ ํ•œ๋‹ค. ๋ฐฉ์‚ฌํ™” ํ”ผ๋ณต๊ด€ ๋‚ด๋ถ€์—๋Š” Cs-137, Sr-90๊ณผ ๊ฐ™์€ ๊ณ ๋ฐฉ์‚ฌ์„ฑ ๋™์œ„์›์†Œ๊ฐ€ ์กด์žฌํ•˜์—ฌ ์—ผํ™”์—ผ CsCl ๋ฐ SrCl2๋ฅผ ๊ธฐ๋ฐ˜์œผ๋กœ ํ•˜๋Š” ์šฉ์œต์—ผ์€ ์ด๋“ค ๋™์œ„์›์†Œ๋ฅผ ํฌ์„์‹œ์ผœ ์ž์นซ ์ตœ์ข… ์ฒ˜๋ถ„๋˜๋Š” ํ๊ธฐ๋ฌผ์˜ ์–‘์„ ์ฆ๊ฐ€์‹œํ‚ฌ ์šฐ๋ ค๊ฐ€ ์žˆ์–ด ๋ณธ ๋…ผ๋ฌธ์—์„œ๋Š” ์—ผํ™”์—ผ ์ค‘ LiCl-KCl์„ ์ „ํ•ด์งˆ๋กœ ์ฑ„ํƒํ•˜์˜€๋‹ค. ๋˜ํ•œ ์ œ์—ผ๋Œ€์ƒ ํ”ผ๋ณต๊ด€์€ ๊ตญ๋‚ด์—์„œ ๊ฐ€์žฅ ๋จผ์ € ์‚ฌ์šฉ๋˜์–ด ์‚ฌ์šฉํ›„ํ•ต์—ฐ๋ฃŒ ์žฌํ™œ์šฉ ๊ณต์ • ์ ์šฉ ์‹œ ๊ฐ€์žฅ ๋จผ์ € ํ๊ธฐ๋ฌผ๋กœ ๋ฐœ์ƒํ•  ๊ฐ€๋Šฅ์„ฑ์ด ๋†’์€ Zircaloy-4 ํ”ผ๋ณต๊ด€์œผ๋กœ ํ•œ์ •ํ•˜์˜€๋‹ค. ๋ณธ ๋…ผ๋ฌธ์—์„œ๋Š” ์‹คํ—˜์‹ค ๊ทœ๋ชจ ์‹คํ—˜์„ ๋ฐ”ํƒ•์œผ๋กœ ํ•œ ์šฉ์œต์—ผ ๋‚ด ์ง€๋ฅด์ฝ”๋Š„ ๋ฐ ๊ธฐํƒ€ ์ฃผ์š” ์›์†Œ ์‚ฐํ™”โ€ขํ™˜์› ๊ฑฐ๋™ ์—ฐ๊ตฌ ์ˆ˜ํ–‰๊ณผ ํ•จ๊ป˜ ์‹คํ—˜์‹ค์—์„œ ๋‹ค๋ฃจ๊ธฐ ์–ด๋ ค์šด ์•…ํ‹ฐ๋‚˜์ด๋“œ ์›์†Œ์— ๋Œ€ํ•œ ์˜ํ–ฅ์„ ํ‰๊ฐ€ํ•˜๊ณ  ์‹คํ—˜์„ ํ†ตํ•ด์„œ๋Š” ํŒŒ์•…ํ•˜๊ธฐ ์–ด๋ ค์šด ์ „ํ•ด์ •๋ จ๋กœ ๋‚ด ๊ตญ๋ถ€์  ์ด์˜จ ๊ฑฐ๋™์„ ํ™•์ธํ•˜๊ธฐ ์œ„ํ•œ 3์ฐจ์› ์ „๊ธฐํ™”ํ•™ ๋ฐ˜์‘ ์ „์‚ฐ ๋ชจ๋ธ์„ ๊ฐœ๋ฐœโ€ข๊ฒ€์ฆํ•˜๊ณ  ์ด๋ฅผ ํ™œ์šฉํ•˜์—ฌ ํŒŒ์ผ๋Ÿฟ ๊ทœ๋ชจ์˜ ์ „ํ•ด์ •๋ จ๋กœ๋ฅผ ์„ค๊ณ„ํ•˜๋Š” ๊ฒƒ์„ ์ตœ์ข…๋ชฉํ‘œ๋กœ ํ•˜์˜€๋‹ค. ์šฉ์œต์—ผ ๋‚ด ์ง€๋ฅด์ฝ”๋Š„์˜ ์‚ฐํ™”ํ™˜์› ๊ฑฐ๋™์— ๋Œ€ํ•œ ์—ฐ๊ตฌ๋Š” LiCl-KCl-ZrCl4 ์šฉ์œต์—ผ์—์„œ ์ˆœํ™˜์ „์œ„๋ฒ•์„ ํ†ตํ•ด ์ด๋ฃจ์–ด์กŒ๋‹ค. ์ˆœํ™˜์ „์œ„๋ฒ•์„ ํ†ตํ•ด LiCl-KCl-ZrCl4 ์šฉ์œต์—ผ์—์„œ 4๊ฐœ์˜ ์‚ฐํ™” ํ”ผํฌ์™€ 3๊ฐœ์˜ ํ™˜์› ํ”ผํฌ๊ฐ€ ๋‚˜ํƒ€๋‚˜๋Š” ๊ฒƒ์„ ํ™•์ธํ•˜์˜€์œผ๋ฉฐ ๊ฐ ํ”ผํฌ์— ํ•ด๋‹นํ•˜๋Š” ์‚ฐํ™”ํ™˜์› ๋ฐ˜์‘์€ ์ „๊ธฐ๋ถ„ํ•ด ๋ฐ˜์‘ ํ›„ ์Œ๊ทน์ „์ฐฉ๋ฌผ์˜ ํ™”ํ•™์  ํ˜•ํƒœ ๋ถ„์„๊ณผ ์ฃผ์‚ฌ์†๋„ ๋ฐ ์ฃผ์‚ฌ๋ฒ”์œ„์— ๋”ฐ๋ฅธ ํ”ผํฌ ๋†’์ด์˜ ๋ณ€ํ™”๋ฅผ ํ†ตํ•ด ์ •์˜๋˜์—ˆ๋‹ค. ์ด๋ฅผ ๋ฐ”ํƒ•์œผ๋กœ Zr(IV) ์ด์˜จ์€ โ€“1.5 V (vs. Ag/AgCl) ๋ณด๋‹ค ๋†’์€ ์ „์•• ์˜์—ญ์—์„œ๋Š” ZrCl๋ฅผ ๊ฑฐ์ณ Zr ๊ธˆ์†์œผ๋กœ ํ™˜์›๋˜๋Š” ๊ฒƒ์ด ํ™•์ธ๋˜์—ˆ์œผ๋ฉฐ, ์ด๋ณด๋‹ค ์ถฉ๋ถ„ํžˆ ๋‚ฎ์€ ์ „์••์˜์—ญ์—์„œ๋Š” Zr(IV)์—์„œ Zr ๊ธˆ์†์œผ๋กœ ๋ฐ”๋กœ ํ™˜์›๋  ๊ฐ€๋Šฅ์„ฑ์ด ์žˆ์Œ์ด ํ™•์ธ๋˜์—ˆ๋‹ค. -1.0 V (vs. Ag/AgCl) ๊ทผ์ฒ˜์—์„œ๋Š” Zr(IV)๊ฐ€ Zr(II)๋กœ ํ™˜์›๋  ์ˆ˜ ์žˆ์œผ๋‚˜ ZrCl4์˜ ๋†๋„๊ฐ€ ๋‚ฎ์€ ๊ฒฝ์šฐ์—๋Š” ๋ฐ˜์‘์†๋„๊ฐ€ ๋Š๋ ค Zr(II)์˜ ์–‘์ด ๋งค์šฐ ์ ์„ ๊ฒƒ์œผ๋กœ ์˜ˆ์ƒ๋œ๋‹ค. Zr ๊ธˆ์†์˜ ์‚ฐํ™” ๊ณผ์ •์€ ํ™˜์›๊ณผ์ •๊ณผ๋Š” ๋‹ฌ๋ฆฌ ZrCl๋ฅผ ๊ฑฐ์น˜์ง€ ์•Š๊ณ  Zr(IV) ๋˜๋Š” Zr(II) ์ด์˜จ์œผ๋กœ ๋ฐ”๋กœ ์‚ฐํ™”๋˜๋Š” ๊ฒƒ์œผ๋กœ ์กฐ์‚ฌ๋˜์—ˆ์œผ๋ฉฐ, ZrCl4์˜ ๋†๋„๊ฐ€ ๋‚ฎ์€ ๊ฒฝ์šฐ์—๋Š” ํ™˜์›๋ฐ˜์‘๊ณผ ๋งˆ์ฐฌ๊ฐ€์ง€๋กœ Zr(II)๋Š” ๊ฑฐ์˜ ํ˜•์„ฑ๋˜์ง€ ์•Š๊ณ  ๋Œ€๋ถ€๋ถ„ Zr(IV)๋กœ ๋ฐ”๋กœ ํ™˜์›๋˜๋Š” ๊ฒƒ์œผ๋กœ ๋‚˜ํƒ€๋‚ฌ๋‹ค. ํ”ผ๋ณต๊ด€ ์ „ํ•ด์ •๋ จ ๊ณผ์ •์—์„œ ์ค‘์š”ํ•œ ๋ฌธ์ œ ์ค‘ ํ•˜๋‚˜์ธ ZrCl์˜ ์ „์ฐฉ์€ Zr(IV)๊ฐ€ ZrCl์„ ๊ฑฐ์ณ Zr ๊ธˆ์†์œผ๋กœ ํ™˜์›๋˜๋ฏ€๋กœ ๋‚ฎ์€ ๋†๋„์˜ ZrCl4์„ ์‚ฌ์šฉํ•˜๋Š” ๊ฒฝ์šฐ, Zr(IV)๋กœ๋ถ€ํ„ฐ ZrCl๊ฐ€ ํ˜•์„ฑ๋˜๋Š” ์†๋„๊ฐ€ ZrCl์ด Zr ๊ธˆ์†์œผ๋กœ ๋ณ€ํ•˜๋Š” ์†๋„๋ณด๋‹ค ๋Š๋ ค์ ธ ์Œ๊ทน์—์„œ ZrCl์ด ํ•จ๊ป˜ ํšŒ์ˆ˜๋˜๋Š” ๊ฒƒ์„ ๋ฐฉ์ง€ํ•  ์ˆ˜ ์žˆ์Œ์„ ํ™•์ธํ•˜์˜€๋‹ค. ์‚ฌ์šฉํ›„ํ•ต์—ฐ๋ฃŒ Zircaloy-4 ํ”ผ๋ณต๊ด€ ๋‚ด ์ฃผ์š” ์›์†Œ์ธ Sn, Cr, Fe๊ณผ ํ•จ๊ป˜ ์ฃผ์š” ๋ฐฉ์‚ฌ์„ฑ ๋™์œ„์›์†Œ์ธ Co์— ๋Œ€ํ•ด์„œ๋„ ์ˆœํ™˜์ „์œ„๋ฒ•์„ ํ†ตํ•ด LiCl-KCl ์šฉ์œต์—ผ ๋‚ด ์‚ฐํ™”ํ™˜์› ๊ฑฐ๋™์„ ํŒŒ์•…ํ•˜์˜€๋‹ค. ์ด๋“ค ์›์†Œ๋Š” ์ง€๋ฅด์ฝ”๋Š„๊ณผ๋Š” ๋‹ฌ๋ฆฌ ๋ถ€์ฐจ์ ์ธ ๋‹จ๊ณ„ ์—†์ด ๊ธˆ์†์œผ๋กœ ๋ฐ”๋กœ ํ™˜์›๋˜์—ˆ์œผ๋ฉฐ, ์ง€๋ฅด์ฝ”๋Š„๋ณด๋‹ค ํ™˜์›๊ฒฝํ–ฅ์„ฑ์ด ํฐ ๊ฒƒ์œผ๋กœ ํ™•์ธ๋˜์—ˆ๋‹ค. ์‚ฌ์šฉํ›„ํ•ต์—ฐ๋ฃŒ Zircaloy-4 ํ”ผ๋ณต๊ด€ ๋‚ด ์ฃผ์š” ์›์†Œ๋“ค์˜ ์‚ฐํ™”ํ™˜์› ๊ฑฐ๋™์— ๋Œ€ํ•œ ์ •๋ณด๋ฅผ ๋ฐ”ํƒ•์œผ๋กœ ์—ฐ๊ตฌ์‹ค ๊ทœ๋ชจ์˜ ๋น„๋ฐฉ์‚ฌํ™” Zircaloy-4 ์‹œํŽธ์— ๋Œ€ํ•œ ์ „ํ•ด์ •๋ จ์„ ์ˆ˜ํ–‰ํ•˜์˜€๋‹ค. Zr์„ ์ œ์™ธํ•œ Zircaloy-4 ๋‚ด ์ฃผ์š”์›์†Œ๋“ค์ด Zr๋ณด๋‹ค ํ™˜์›๊ฒฝํ–ฅ์„ฑ์ด ํฌ๋ฏ€๋กœ ์–‘๊ทน์—์„œ ์šฉํ•ด๋  ์‹œ ์Œ๊ทน์— ์ง€๋ฅด์ฝ”๋Š„๋ณด๋‹ค ์šฐ์„  ์ „์ฐฉ๋œ๋‹ค. ๋”ฐ๋ผ์„œ ์–‘๊ทน์˜ ์ „์œ„๋ฅผ โ€“0.9 V (vs. Ag/AgCl) ์ดํ•˜๋กœ ์œ ์ง€ํ•˜๋ฉฐ ์ „ํ•ด์ •๋ จ์„ ์ง„ํ–‰ํ•˜์—ฌ ์–‘๊ทน์—์„œ ์ง€๋ฅด์ฝ”๋Š„๋งŒ ์šฉํ•ด๋˜๋„๋ก ํ•˜์˜€๋‹ค. 5๊ฐ€์ง€์˜ ZrCl4 ๋†๋„ (0.1, 0.5, 1.0, 2.0, 4.0 wt. %)์—์„œ ์ „ํ•ด์ •๋ จ์„ ์ˆ˜ํ–‰ํ•˜๊ณ  XRD๋กœ ์ „์ฐฉ๋ฌผ์˜ ํ™”ํ•™์  ํ˜•ํƒœ๋ฅผ ๋ถ„์„ํ•จ์œผ๋กœ์จ ZrCl4 ๋†๋„๊ฐ€ ์ง€๋ฅด์ฝ”๋Š„ ์ „์ฐฉ๋ฌผ ํ˜•ํƒœ์— ๋ฏธ์น˜๋Š” ์˜ํ–ฅ์„ ํŒŒ์•…ํ•˜์˜€์œผ๋ฉฐ ์ „์ฐฉ๋ฌผ์˜ ์กฐ์„ฑ์€ ICP-MS๋กœ ๋ถ„์„ํ•˜์˜€๋‹ค. ๋ชจ๋“  ์ „ํ•ด์ •๋ จ ๊ฒฝ์šฐ์— ๋Œ€ํ•ด์„œ ์ง€๋ฅด์ฝ”๋Š„์„ ์ œ์™ธํ•œ ์›์†Œ๊ฐ€ ๊ฒ€์ถœ๋˜์ง€ ์•Š์•˜์œผ๋ฉฐ ์ˆœํ™˜์ „์œ„๋ฒ•์„ ํ†ตํ•ด ์˜ˆ์ธกํ•œ ๋ฐ”์™€ ๊ฐ™์ด ์ƒ๋Œ€์ ์œผ๋กœ ZrCl4์˜ ๋†๋„๊ฐ€ ๋‚ฎ์€ ๊ฒฝ์šฐ (0.1, 0.5 wt. %)์—๋Š” ์Œ๊ทน์— ZrCl ์—†์ด Zr ๊ธˆ์†๋งŒ ์ „์ฐฉ๋˜์—ˆ์œผ๋ฉฐ, ๋†๋„๊ฐ€ ๋†’์€ ๊ฒฝ์šฐ (2.0, 4.0 wt. %)์—๋Š” ์Œ๊ทน์— ZrCl๋งŒ ์ „์ฐฉ๋˜์—ˆ๋‹ค. ZrCl4์˜ ๋†๋„๊ฐ€ 1.0 wt. %์ธ ๊ฒฝ์šฐ์—๋Š” ZrCl์™€ Zr ๊ธˆ์†์ด ํ•จ๊ป˜ ๊ฒ€์ถœ๋˜์—ˆ๋‹ค. ์ผ๋ฐ˜์ ์œผ๋กœ ์šฉ์œต์—ผ ๋‚ด์— ํšŒ์ˆ˜ํ•˜๊ณ ์ž ํ•˜๋Š” ์›์†Œ์˜ ๋†๋„๊ฐ€ ๋†’์„ ๋•Œ, ๋†’์€ ์ƒ์‚ฐ๋Ÿ‰์„ ํ™•๋ณดํ•˜๋Š” ๊ฒƒ์ด ๊ฐ€๋Šฅํ•˜๋ฏ€๋กœ ZrCl์˜ ์ „์ฐฉ ์—†์ด Zr ๊ธˆ์† ํšŒ์ˆ˜๊ฐ€ ๊ฐ€๋Šฅํ•œ ZrCl4 ๋†๋„ ์ค‘ ๊ฐ€์žฅ ํฐ 0.5 wt. %๊ฐ€ ํ”ผ๋ณต๊ด€ ์ „ํ•ด์ •๋ จ์„ ์œ„ํ•ด ๊ฐ€์žฅ ์ ํ•ฉํ•˜๋‹ค. 3์ฐจ์› ์ „๊ธฐํ™”ํ•™ ๋ฐ˜์‘ ์ „์‚ฐ ๋ชจ๋ธ์€ ์ƒ์šฉ ์ „์‚ฐ์œ ์ฒด ์ฝ”๋“œ์ธ ANSYS-CFX๋ฅผ ๋ฐ”ํƒ•์œผ๋กœ ์ „ํ•ด์งˆ์˜ ์œ ์ฒด์—ญํ•™์  ๊ฑฐ๋™๊ณผ ์ „๊ธฐ์žฅ ํ•ด์„ ๋ฐ ์ „๊ธฐํ™”ํ•™ ๋ฐ˜์‘ ํ•ด์„์„ ๊ฒฐํ•ฉํ•˜์—ฌ ๊ฐœ๋ฐœ๋˜์—ˆ๋‹ค. ๊ฐœ๋ฐœ๋œ ๋ชจ๋ธ ์ค‘ ์Œ๊ทน์ „์ฐฉ ๋ชจ๋ธ์€ rotating cylindrical Hull cell์—์„œ ๊ตฌ๋ฆฌ์ „์ฐฉ ๋ฐ˜์‘ ์‹œ ์Œ๊ทน ์œ„์น˜์— ๋”ฐ๋ฅธ ๊ณผ์ „์•• ๋ถ„ํฌ๋ฅผ ๋ฒค์น˜๋งˆํฌํ•จ์œผ๋กœ์จ ๊ฒ€์ฆํ•˜์˜€๋‹ค. ์–‘๊ทน ์šฉํ•ด ๋ฐ ํŒŒ์ผ๋Ÿฟ ์Šค์ผ€์ผ ์ „ํ•ด์ •๋ จ๋กœ์— ๋Œ€ํ•œ ์ „์‚ฐ ๋ชจ๋ธ ๊ฒ€์ฆ์€ ๋ฏธ๊ตญ ์•„์ด๋‹คํ˜ธ ๊ตญ๋ฆฝ์—ฐ๊ตฌ์†Œ์—์„œ EBR-II ์›์ž๋กœ์˜ ์‚ฌ์šฉํ›„ํ•ต์—ฐ๋ฃŒ์˜ ์ฒ˜๋ฆฌ๋ฅผ ์œ„ํ•ด ์šด์šฉํ•˜๊ณ  ์žˆ๋Š” Mark-IV ์ „ํ•ด์ •๋ จ๋กœ์˜ ์ธ๊ฐ€ ์ „๋ฅ˜์— ๋”ฐ๋ฅธ ์…€ ์ „์œ„๋ฅผ ๋ฒค์น˜๋งˆํฌํ•จ์œผ๋กœ์จ ์ˆ˜ํ–‰ํ•˜์˜€๋‹ค. ์–‘๊ทน ๋ฉด์ ์˜ ๋ณ€ํ™”๊ฐ€ ์ ์€ ์ „ํ•ด์ •๋ จ ์ดˆ๊ธฐ์— ๋Œ€ํ•ด์„œ๋Š” ์‹คํ—˜์ ์œผ๋กœ ์ธก์ •๋œ ์…€์ „์œ„์™€ ์ „์‚ฐ ๋ชจ๋ธ๋ง์„ ํ†ตํ•ด ์–ป์€ ๊ฐ’์ด ์ž˜ ์ผ์น˜ํ•˜์˜€์œผ๋‚˜, ์ „ํ•ด์ •๋ จ์ด ์ง„ํ–‰๋จ์— ๋”ฐ๋ผ ์–‘๊ทน ๋ฉด์ ์ด ๋ณต์žกํ•˜๊ฒŒ ๋ณ€ํ™”ํ•˜์—ฌ ๊ฐ€์ •ํ•œ ์–‘๊ทน๋ฉด์  ๋ณ€ํ™” ๊ณก์„ ์— ๋”ฐ๋ผ ๊ณ„์‚ฐ๋œ ์…€์ „์œ„์˜ ์ฐจ์ด๊ฐ€ ๋น„๊ต์  ํฌ๊ฒŒ ๋‚˜ํƒ€๋‚ฌ๋‹ค. ๋”ฐ๋ผ์„œ ๊ฐœ๋ฐœ๋œ ์ „์‚ฐ๋ชจ๋ธ์€ ์Œ๊ทน ์ „์ฐฉ ๊ฑฐ๋™์„ ๋ชจ์‚ฌํ•˜๋Š”๋ฐ ์‚ฌ์šฉํ•˜๊ฑฐ๋‚˜ ์ „ํ•ด์ •๋ จ ์ดˆ๊ธฐ๋‹จ๊ณ„ ๋ชจ๋ธ๋ง์— ํ™œ์šฉํ•˜๋Š” ๊ฒƒ์ด ์ข‹์„ ๊ฒƒ์œผ๋กœ ํŒ๋‹จ๋œ๋‹ค. ์ง€๋ฅด์ฝ”๋Š„ ํ™˜์› ๋ฐ˜์‘์€ ์•ž์„œ ๋ฒค์น˜๋งˆํฌํ•œ ์ˆ˜์šฉ์•ก ์‹œ์Šคํ…œ์—์„œ์˜ ๊ตฌ๋ฆฌ ์ „์ฐฉ์ด๋‚˜ ์šฉ์œต์—ผ ์‹œ์Šคํ…œ์—์„œ ์•…ํ‹ฐ๋‚˜์ด๋“œ ์›์†Œ์˜ ์ „์ฐฉ๊ฑฐ๋™๊ณผ๋Š” ๋‹ฌ๋ฆฌ, Zr(IV) ์ด์˜จ์ด ZrCl์„ ๊ฑฐ์ณ Zr ๊ธˆ์†์œผ๋กœ ์ „์ฐฉ๋˜๋Š” ๋‹ค๋‹จ๊ณ„ ํ™˜์›๊ณผ์ •์„ ๊ฑฐ์นœ๋‹ค. ๋”ฐ๋ผ์„œ Zircaloy-4 ํ”ผ๋ณต๊ด€ ์ „ํ•ด์ •๋ จ์— ๋Œ€ํ•œ ๋ชจ๋ธ๋ง์„ ์œ„ํ•ด์„œ๋Š” ์ „์‚ฐ๋ชจ๋ธ์˜ ๋‹ค๋‹จ๊ณ„ ํ™˜์›๋ฐ˜์‘์— ๋Œ€ํ•œ ๊ฒ€์ฆ์ด ํ•„์š”ํ•˜๋‹ค. ์ด๋ฅผ ์œ„ํ•ด ์•ž์„œ ๋‹ค์–‘ํ•œ ๋†๋„์—์„œ ์ˆ˜ํ–‰๋œ ๋น„๋ฐฉ์‚ฌํ™” Zircaloy-4 ์ „ํ•ด์ •๋ จ ๋ฐ์ดํ„ฐ๋ฅผ ํ™œ์šฉํ•˜์˜€๋‹ค. ์ „์‚ฐ๋ชจ๋ธ์„ ํ†ตํ•ด ์‹คํ—˜ ๊ฒฐ๊ณผ์™€ ๋™์ผํ•˜๊ฒŒ ์šฉ์œต์—ผ ๋‚ด ZrCl4์˜ ๋†๋„๊ฐ€ 0.1, 0.5 wt. %์ธ ๊ฒฝ์šฐ์—๋Š” ์Œ๊ทน์— ZrCl ์ „์ฐฉ ์—†์ด Zr ๊ธˆ์†๋งŒ ํšŒ์ˆ˜๋˜๋Š” ๊ฒƒ์„ ํ™•์ธํ•˜์˜€์œผ๋ฉฐ, 1 wt. %์ธ ๊ฒฝ์šฐ์—๋Š” ZrCl์™€ Zr ๊ธˆ์†์ด ํ•จ๊ป˜ ํšŒ์ˆ˜๋จ์„, ๊ทธ ์ด์ƒ์˜ ๋†๋„์—์„œ๋Š” ZrCl๋งŒ ์ „์ฐฉ๋˜๋Š” ๊ฒƒ์„ ํ™•์ธํ•˜์˜€๋‹ค. ์šฉ์œต์—ผ ์‹คํ—˜์„ ํ†ตํ•ด ํŒŒ์•…ํ•œ ์ง€๋ฅด์ฝ”๋Š„์˜ ์‚ฐํ™”โ€ขํ™˜์› ๊ฑฐ๋™ ํŠน์„ฑ๊ณผ ๊ฐœ๋ฐœ๋œ 3์ฐจ์› ์ „์‚ฐ๋ชจ๋ธ์„ ๋ฐ”ํƒ•์œผ๋กœ ํŒŒ์ผ๋Ÿฟ ๊ทœ๋ชจ์˜ ์‚ฌ์šฉํ›„ํ•ต์—ฐ๋ฃŒ Zircaloy-4 ํ”ผ๋ณต๊ด€ ์ „ํ•ด์ •๋ จ๋กœ๋ฅผ ์„ค๊ณ„ํ•˜์˜€๋‹ค. 3์ฐจ์› ๋ชจ๋ธ๋ง์„ ํ†ตํ•œ ์„ค๊ณ„์— ์•ž์„œ 1์ฐจ์› ์‹œ๊ฐ„์ข…์† ์ „๊ธฐํ™”ํ•™ ๋ฐ˜์‘ ์ „์‚ฐ ๋ชจ๋ธ ์ฝ”๋“œ์ธ REFIN์„ ์‚ฌ์šฉํ•˜์—ฌ ๋ฐฉ์‚ฌํ™” ํ”ผ๋ณต๊ด€ ์ „ํ•ด์ •๋ จ์— ๋Œ€ํ•œ ์˜ˆ๋น„ํ•ด์„์„ ์ˆ˜ํ–‰ํ•˜์˜€๋‹ค. ์ด๋ฅผ ํ†ตํ•ด ์–‘๊ทน ์ „์œ„ ์กฐ์ ˆ์„ ํ†ตํ•ด Sn, Cr, Fe, Co์™€ ๊ฐ™์€ ํ™˜์›๊ฒฝํ–ฅ์„ฑ์ด ํฐ ์›์†Œ์˜ ์šฉํ•ด๋ฅผ ๋ง‰์•„ ์Œ๊ทน ์˜ค์—ผ์„ ์ตœ์†Œํ™” ํ•  ์ˆ˜ ์žˆ์Œ์„ ์žฌ์ฐจ ํ™•์ธํ•˜์˜€๋‹ค. ์šฐ๋ผ๋Š„์„ ํฌํ•จํ•œ ์•…ํ‹ฐ๋‚˜์ด๋“œ ์›์†Œ์˜ ๊ฒฝ์šฐ ์ง€๋ฅด์ฝ”๋Š„ ๋ณด๋‹ค ์‚ฐํ™”๊ฒฝํ–ฅ์„ฑ์ด ์ปค ์ „ํ•ด์ •๋ จ์ด ์ง„ํ–‰๋˜๋Š” ๋™์•ˆ ์šฉ์œต์—ผ ๋‚ด๋กœ ์šฉํ•ด๋˜๋‚˜ ์Œ๊ทน์—๋Š” ์ „์ฐฉ๋˜์ง€ ์•Š์Œ์„ ํ™•์ธํ•˜์˜€๋‹ค. ํŒŒ์ผ๋Ÿฟ ๊ทœ๋ชจ์˜ ์‚ฌ์šฉํ›„ํ•ต์—ฐ๋ฃŒ Zircaloy-4 ํ”ผ๋ณต๊ด€ ์ „ํ•ด์ •๋ จ๋กœ ์„ค๊ณ„๋Š” ์—ฐ๊ฐ„ 0.1~0.2ํ†ค์˜ ํ”ผ๋ณต๊ด€์„ ์ฒ˜๋ฆฌํ•  ์ˆ˜ ์žˆ๋Š” ์ „ํ•ด์ •๋ จ๋กœ๋ฅผ ์„ค๊ณ„ํ•˜๋Š” ๊ฒƒ์„ ๋ชฉํ‘œ๋กœ ์ง„ํ–‰ํ•˜์˜€๋‹ค. ํ”ผ๋ณต๊ด€ ๋‚ด์— ์กด์žฌํ•˜๋Š” ์šฐ๋ผ๋Š„ ๋ฐ ์•…ํ‹ฐ๋‚˜์ด๋“œ ์›์†Œ๋Š” ์ง€๋ฅด์ฝ”๋Š„๋ณด๋‹ค ์‚ฐํ™”๊ฒฝํ–ฅ์„ฑ์ด ํฌ๊ธฐ ๋•Œ๋ฌธ์— ์–‘๊ทน ๋ฐ”์Šค์ผ“์— ํ•œ ๋ฒˆ์— ํˆฌ์ž…๋˜๋Š” ํ”ผ๋ณต๊ด€์˜ ์–‘์ด ๋งŽ์œผ๋ฉด ์šฉ์œต์—ผ ๋‚ด ์•…ํ‹ฐ๋‚˜์ด๋“œ์˜ ๋†๋„๊ฐ€ ์ฆ๊ฐ€ํ•˜์—ฌ ์•…ํ‹ฐ๋‚˜์ด๋“œ ์›์†Œ๊ฐ€ ์Œ๊ทน์— ๊ฐ€๋Šฅ์„ฑ์ด ์ฆ๊ฐ€ํ•œ๋‹ค. ์ด๋Ÿฌํ•œ ์ด์œ ๋กœ ์ „ํ•ด์ •๋ จ๋กœ์— ํˆฌ์ž…๋˜๋Š” ํ”ผ๋ณต๊ด€์˜ ์–‘์€ 10 kg์œผ๋กœ ์ œํ•œํ•˜์˜€์œผ๋ฉฐ, ์ „์ฒด ์…€์˜ ํฌ๊ธฐ๋Š” ํ”ผ๋ณต๊ด€ ๋‚ด์˜ ์•…ํ‹ฐ๋‚˜์ด๋“œ๊ฐ€ ๋ชจ๋‘ ์šฉํ•ด๋˜์–ด๋„ ์šฉ์œต์—ผ ๋‚ด ์•…ํ‹ฐ๋‚˜์ด๋“œ ๋†๋„๊ฐ€ ์ถฉ๋ถ„ํžˆ ๋‚ฎ๊ฒŒ ์œ ์ง€๋˜์–ด ์•…ํ‹ฐ๋‚˜์ด๋“œ ์ „์ฐฉ ์—†์ด ๋†’์€ ์ˆœ๋„์˜ ์ง€๋ฅด์ฝ”๋Š„์„ ํšŒ์ˆ˜ํ•  ์ˆ˜ ์žˆ๋„๋ก ์ถฉ๋ถ„ํžˆ ํฌ๊ฒŒ ์„ค๊ณ„ํ•˜์˜€๋‹ค. ์Œ๊ทน ์ฃผ๋ณ€ ํ™•์‚ฐ๊ฒฝ๊ณ„์ธต์ด ๋„ˆ๋ฌด ์ž‘์€ ๊ฒฝ์šฐ, ์Œ๊ทน ํ‘œ๋ฉด์œผ๋กœ Zr(IV) ์ด์˜จ์˜ ์Œ๊ทน์œผ๋กœ์˜ ๊ณต๊ธ‰์ด ๋นจ๋ผ์ ธ, ZrCl์˜ ํ˜•์„ฑ ์†๋„๊ฐ€ ์ฆ๊ฐ€ํ•˜์—ฌ ZrCl์ด Zr ๊ธˆ์†๊ณผ ํ•จ๊ป˜ ์Œ๊ทน์—์„œ ํšŒ์ˆ˜๋  ์ˆ˜ ์žˆ์–ด ์–‘๊ทน๋ฐ”์Šค์ผ“์€ ๊ณ ์ •์‹œํ‚ค๊ณ  ์Œ๊ทน๋งŒ์„ ํšŒ์ „์‹œ์ผœ ์ ๋‹นํ•œ ์ˆ˜์ค€์˜ ํ™•์‚ฐ๊ฒฝ๊ณ„์ธต์„ ์œ ์ง€ํ•  ์ˆ˜ ์žˆ๋„๋ก ํ•˜์˜€๋‹ค. ์–‘๊ทน ๋ฐ”์Šค์ผ“์€ ์ „ํ•ด์ •๋ จ๋กœ ๊ฐ€์šด๋ฐ ์žˆ๋Š” ์Œ๊ทน์„ ์ค‘์‹ฌ์œผ๋กœ ๋“ฑ๊ฐ„๊ฒฉ์œผ๋กœ ๋ฐฐ์น˜ํ•˜์—ฌ ๊ตญ๋ถ€์  ์ „๋ฅ˜์˜ ์ง‘์ค‘์„ ์ตœ์†Œํ™” ํ•˜์˜€๋‹ค. ๋ณธ ๋…ผ๋ฌธ์„ ํ†ตํ•ด ๊ฐœ๋ฐœ๋œ 3์ฐจ์› ์ „์‚ฐ ๋ชจ๋ธ์„ ํ†ตํ•ด ์„ค๊ณ„๋œ ์ „ํ•ด์ •๋ จ๋กœ์˜ ๋‹ค์–‘ํ•œ ์šด์ „์กฐ๊ฑด์— ๋Œ€ํ•ด ๋ชจ๋ธ๋ง์„ ์ง„ํ–‰ํ•จ์œผ๋กœ์จ ์„ฑ๋Šฅ์„ ๊ฒ€์ฆํ•˜์˜€๋‹ค. ์–‘๊ทน ๋ฐ”์Šค์ผ“์„ 3๊ฐœ ์ด์ƒ ์‚ฌ์šฉํ•˜๋Š” ๊ฒฝ์šฐ, ์›์ฃผ๋ฐฉํ–ฅ์˜ ์ „์œ„ ํŽธ์ฐจ๊ฐ€ ์ถฉ๋ถ„ํžˆ ๊ฐ์†Œํ•จ์„ ํ™•์ธํ•˜์˜€๋‹ค. ๋˜ํ•œ ์„ค๊ณ„๋œ ์ „ํ•ด์ •๋ จ๋กœ์—์„œ ์šฐ๋ผ๋Š„์— ์˜ํ•œ ์˜ค์—ผ๊ณผ ZrCl์˜ ๊ณต์ „์ฐฉ ์—†์ด Zr ๊ธˆ์†์„ ํšŒ์ˆ˜ํ•˜๋Š” ๊ฒƒ์ด ๊ฐ€๋Šฅํ•จ์„ ํ™•์ธํ•˜์˜€์œผ๋ฉฐ ๋ชฉํ‘œ๋กœ ํ•˜๋Š” 0.1~0.2 ํ†ค ๊ทœ๋ชจ์˜ ์—ฐ๊ฐ„์ฒ˜๋ฆฌ๋Ÿ‰์˜ ๋‹ฌ์„ฑ์ด ๊ฐ€๋Šฅํ•จ์„ ํ™•์ธํ•˜์˜€๋‹ค.Zirconium alloys have low thermal neutron absorption cross section, high corrosion resistance and superior mechanical characteristics. These alloys have been used for structure materials in nuclear reactor systems that must maintain integrity over long period of time in harsh environment such as high temperature, high pressure and strong radiation. Nuclear power plants in the Republic of Korea utilize zirconium alloys for fuel cladding, pressure tube and calandria tube in both Pressurized Water Reactors (PWR) and CANada Deuterium Uranium reactors (CANDU). Therefore, a large amount of radioactive zirconium alloy waste is inevitably generated as results of nuclear power plant operation. Claddings of spent nuclear fuels constitute the largest portion of radioactive zirconium alloy wastes as about 16 wt. % of spent nuclear fuel assembly. In addition, the cladding separated from spent nuclear fuels is classified as an intermediate level waste in the latest radioactive waste classification of International Atomic Energy Agency (IAEA) since non-negligible amount of long-living actinide elements and fission products could penetrate into fuel claddings during irradiation in nuclear reactor and long-living niobium-94 is produced by neutron activation (IAEA, 2009). If zirconium can be chemically separated from irradiated claddings, the final volume of radioactive waste in geological repositories can be greatly reduced and recovered zirconium can be recycled for reutilization in nuclear industry. For this reason, limited but active investigation have been conducted in recent years to decontaminate spent nuclear fuel zirconium alloy cladding. Rudisill attempted to remove actinide elements and fission products by surface removal using hydrogen fluoride acid (Rudisill, 2009). However, since penetration depths of these elements at the concentration limit of the U.S. Class C level waste was as deep as 180 ฮผm, the surface removal was ineffective. It is concluded that volumetric decontamination processes such as gaseous reaction methods or molten salt electrorefining techniques are required. Iodination and chlorination methods have been developed as a gaseous reaction method. While gaseous methods can separate zirconium with high purity there are some drawbacks. In iodination methods, concentration of moisture in the reaction chamber should be maintained very low since ZrI4 is very hydroscopic. In addition, reduction of ZrI4 into Zr metal would be very slow. In chlorination or Kroll process, large amount of Mg waste could be generated from the process to reduce ZrCl4 into Zr metal. Electrorefining in molten salts such as fluoride or chloride salt have been also developed as a volumetric decontamination process for zirconium cladding from spent nuclear fuels. Electrorefining using fluoride electrolytes such as LiF-KF has an advantage over chloride salts that dense zirconium metal with high purity could be recovered on cathode. However, the fluoride salts have high corrosivity to structural materials of electrorefiner at high (~700oC) operating temperature. Chloride-fluoride mixed molten salts can lower operating temperature to about 650oC but the corrosivity remains to be an issue. Since chloride-based molten salts has lower melting point and corrosivity, chloride based electrorefining would be preferred for commercial decontamination process with low operating temperature about 500oC. However, since redox behavior of zirconium in chloride salt is very complicated, cathode product would contain ZrCl with Zr metal in certain conditions and a disproportionate reaction producing Zr(II) from Zr(IV) and Zr metal can occur. If both ZrCl formation and disproportionate reaction of zirconium could be suppressed, chloride based electrorefining would be an attractive option for commercial spent nuclear fuel cladding decontamination processes. It has been suggested that ZrCl formation can be retarded by introducing more stable salts such as CsCl and SrCl2. Irradiated cladding contains Cs-137 and Sr-90 whose radioactivities are very high. If molten salts based on CsCl or SrCl2 are used, theses radioisotopes could be diluted and this could result in volume increase of final disposed radioactive waste. Therefore, in this study, LiCl-KCl salt is selected as an electrolyte. In addition, target cladding material is selected as Zircaloy-4 cladding since Zircaloy-4 cladding is the first generation cladding used in the Republic of Korea from 1978 to 2001. This study has been carried out in three stages. First, redox behavior of zirconium in LiCl-KCl salts has been investigated by lab-scale experiments. Second, three-dimensional computational electrochemo-hydrodynamic model has been developed to simulate actinide behavior in chloride salts and design a pilot-scale electrorefiner. Finally, based on lab-scale experiment and developed computational model, pilot-scale irradiated Zircaloy-4 eletrorefiner has been designed and performance of the electrorefiner has been verified. In this dissertation, Zr redox behaviors in LiCl-KCl salts have been studied by cyclic voltammetries. It is identified that four oxidation peaks and three reduction peaks would appear in cyclic voltammograms. Reduction or oxidation reactions for each peak were determined based on chemical form of cathode deposits after electrolysis and peak height changes according to scan rates and scan ranges. From cyclic voltammograms, it is shown that if cathode potential is more negative than -1.2 V (vs. Ag/AgCl), Zr(IV) ion could be reduced into ZrCl and ZrCl could be reduced again into Zr metal. If cathode potential is more negative than -1.5 V (vs. Ag/AgCl), Zr(IV) ion could be directly reduced into Zr metal. Zr(II) ion could be formed from Zr(IV) ion at near -1.0 V (vs. Ag/AgCl) but the reaction rate might be slow when the concentration of Zr(IV) ion is low. For oxidation reactions of Zr metal and ZrCl, it is identified that most of Zr metal and ZrCl would be directly oxidized into Zr(IV) without an intermediate step but if the concentration of Zr(IV) is high, Zr(II) could be produced from Zr metal and ZrCl. Since the reaction rate of ZrCl formation from Zr(IV) is dependent on Zr(IV) concentration while ZrCl reduction into Zr metal is not, net ZrCl formation rate could be reduced by lowering Zr(IV) concentration. In lab-scale experiment, redox behaviors of significant elements in irradiated Zicaloy-4 cladding (Sn, Cr, Fe and Co) were investigated in the same way of Zr and it is confirmed that these elements are much reductive than Zr and redox mechanisms are much simpler than Zr. Lab-scale electrorefining has been conducted for unirradiated Zircaloy-4 specimen on the basis of investigated redox behaviors of Zr and other elements. Since all elements in Zircaloy-4 except Zr are more reductive than Zr, these elements could be deposited with Zr if they are dissolved from anode. To dissolve only zirconium from anode, anode potential was maintained more negative than -0.9 V (vs. Ag/AgCl). In addition, electrorefining was conducted in five different ZrCl4 concentration (0.1, 0.5, 1.0, 2.0, 4.0 wt. %) and chemical form and composition of cathode deposit was investigated by X-ray diffraction (XRD) and inductively coupled plasma mass spectrometry (ICP-MS) respectively. For all cases of electrorefining, only zirconium was detected in cathode deposits. As identified in cyclic voltammetry at low ZrCl4 concentrations, 0.1 wt. % and 0.5 wt. %, respectively, Zr metal was recovered on cathode without ZrCl while ZrCl was recovered at high ZrCl4 concentration, 2.0 wt. % and 4.0 wt. %, respectively.At the concentration of 1.0 wt. %, both Zr metal and ZrCl were recovered. In general, high ZrCl4 concentration is preferred to secure high throughput of electrorefiner. Therefore, to recover Zr metal with high throughput, ZrCl4 concentration of 0.5 wt. % would be recommendable. A three-dimensional computational electrochemo-hydrodynamic model has been developed by combining fluid dynamic, electrostatic and electrochemical analysis based on a commercial fluid dynamic code, ANSYS-CFXยฉ. Cathode deposition model in the developed computational model was verified by benchmarking overpotential distribution for copper deposition in rotating cylindrical Hull cell with cupric sulfate solution. Usefulness of anode dissolution model was investigated by benchmarking potential versus current data of Mark-IV electrorefiner which has been utilized for reprocessing spent fuels of Experimental Breeder Reactor-II. At the initial stage of electrorefining, computational modeling results accorded with experimental results but, as electrorefining progressed, calculated potential became very dependent on assumed effective anode surface area profiles. Therefore, the developed computational model could be utilized for modeling of cathode deposition or early stage of electrorefining. To simulate zirconium redox behavior in chloride salts, it is required to secure material constants used for Butler-Volmer equation such as reaction rate constant and transfer coefficient because these material properties could greatly influence calculated currents and potentials. To determine proper material constants, several values were tested in conditions that are equivalent to lab-scale electrorefining experiments. In addition, multi-step electrochemical reaction model for zirconium in LiCl-KCl molten salt was also introduced and verified by benchmarking on chemical forms of cathode deposits from lab-scale electroreifning experiments. By applying the developed computational model benchmarked by using lab-scale experiments, a pilot-scale electrorefiner for recovery of zirconium from Zircaloy-4 cladding has been designed. In addition to three-dimensional computational modeling, one-dimensional preliminary modeling was conducted by using a one-dimensional time-dependent electrochemical reaction code, REFIN. It is identified again that the dissolution of Sn, Cr, Fe and Co from fuel cladding can be prevented by controlling an anode potential. After electrorefining under the anodic potential, most of these elements would be remaining in the anode basket as unoxidized metals. On the other hand, actinides elements from fuel cladding will remain dissolved in the molten salts after electrorefining and they would not be deposited on the cathode and remained in the molten salts because actinide elements are more active than zirconium and other alloying elements. The throughput of a pilot-scale electrorefiner for spent nuclear fuel Zircaloy-4 cladding designed by applying computer models is predicted to be about 0.1~0.2 ton/year at the ZrCl4 concentration of 0.5 wt. %. It is expected that the throughput can be further increased by optimizing design parameters.Chapter 1 Introduction 1 1.1 Background 1 1.2 Radiological characteristics of irradiated cladding 4 1.3 Objective 13 Chapter 2 Literature Review 14 2.1 Surface decontamination process 14 2.2 Volumetric decontamination processes 18 2.2.1 Halogenation method 18 2.2.2 Electrorefining 24 Chapter 3 Research Design 42 3.1 Research questions and approaches 42 3.2 Molten salt electrochemical experiment 46 3.3 Computational electrorefining model development 48 3.4 Pilot-scale electrorefiner design 49 Chapter 4 Molten Salt Electrochemical Experiment 50 4.1 Redox behavior of Zr in LiCl-KCl 50 4.1.1 Experimental setup 50 4.1.2 Cyclic voltammetry results 58 4.1.3 Discussion 80 4.2 Redox behavior of Sn, Cr, Fe and Co in LiCl-KCl 92 4.2.1 Experimental setup 92 4.2.2 Cyclic voltammetry results 94 4.2.3 Discussion 114 4.3 Lab-scale electrorefining of unirradiated Zircaloy-4 specimen 121 4.3.1 Experimental setup 121 4.3.2 Electrorefining Results 126 4.3.3 Discussion 139 4.4 Suggestions on Zircaloy-4 electrorefining based on lab-scale experiment 144 Chapter 5 Computational Electrorefining Model Development 146 5.1 Hydrodynamic-electrochemical computational model 146 5.2 Surrogate aqueous electrodeposition system benchmark 149 5.2.1 Rotating Cylindrical Hull cell description 149 5.2.2 Mathematical model 152 5.2.3 RCH cell experiment 157 5.2.4 Results 159 5.2.5 Discussion 165 5.3 Molten salt electrorefining system benchmark 166 5.3.1 Selected experiment for simulation 166 5.3.2 Modeling strategy 171 5.3.3 Mathematical model 178 5.3.4 Results 186 5.3.5 Discussion 194 5.4 Zircaloy-4 electrorefining benchmark 199 5.4.1 Modeling strategy 200 5.4.2 Mathematical model 204 5.4.3 Results 211 5.4.4 Discussion 217 Chapter 6 Pilot-scale Electrorefiner Design 219 6.1 Preliminary Zircaloy-4 electrorefining modeling 219 6.1.1 Mathematical model 219 6.1.2 Modeling conditions and electrorefiner geometry 223 6.1.3 Results 232 6.1.4 Discussion 246 6.2 3-D Zircaloy-4 cladding electrorefiner design 251 6.2.1 Design concept and assumptions 253 6.2.2 Potential window for obtaining high purity Zr metal 255 6.2.3 Weights of molten salts 259 6.2.4 The number of anode basket 262 6.3 Verification of Zircaloy-4 cladding electrorefiner capability 266 6.3.1 Effect of applied current and cathode rotating speed 266 6.3.2 Verified capabilities of electrorefiner 274 Chapter 7 Conclusions and Future Work 277 7.1 Conclusions 277 7.2 Future Work 279 Bibliography 282 ์ดˆ ๋ก 294Docto

    ์ง„์‹ค์˜ ๊ฐ€์†Œ์„ฑ์„ ํ†ตํ•œ ์ž‘ํ’ˆ์—ฐ๊ตฌ

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    ํ•™์œ„๋…ผ๋ฌธ (์„์‚ฌ)-- ์„œ์šธ๋Œ€ํ•™๊ต ๋Œ€ํ•™์› : ์กฐ์†Œ๊ณผ(์กฐ์†Œ์ „๊ณต), 2013. 2. ๋ฌธ์ฃผ.๊ตญ๋ฌธ์ดˆ๋ก ํ˜„์žฌ, ์šฐ๋ฆฌ๋Š” ๋ณต์žกํ•œ ์‚ฌํšŒ ๊ตฌ์กฐ์™€ ์ •๋ณด์˜ ํ™์ˆ˜ ์†์— ์‚ด์•„๊ฐ€๊ณ  ์žˆ๋‹ค. ์ˆ˜๋งŽ์€ ์ •๋ณด๋“ค์€ ์šฐ๋ฆฌ๋“ค์—๊ฒŒ ๋ฌดํ•œ์ • ์ œ๊ณต๋˜๊ณ  ๊ทธ ์ •๋ณด๋“ค์€ ์ธ์‹์˜ ํ•œ๊ณ„๋‚˜ ์ „๋‹ฌ๊ณผ์ •์˜ ์˜ค๋ฅ˜ ๋“ฑ์œผ๋กœ ์ธํ•ด ๋ณ€์งˆ๋˜๊ฑฐ๋‚˜, ๋ณ€ํ˜•๋  ์ˆ˜ ์žˆ๋‹ค. ๋ณธ ์—ฐ๊ตฌ๊ณผ์ •์€ ์ผ์ • ์‚ฌ์•ˆ์„ ์ง„์‹ค์ด๋ผ ๊ฒ€์ฆํ•˜๋Š” ๊ณผ์ • ์ค‘ ๋ฐœ์ƒํ•  ์ˆ˜ ์žˆ๋Š” ์ง„์‹ค์˜ ๋ณ€ํ˜•, ๋ณ€์งˆ์— ๊ด€ํ•œ ์˜๋ฌธ์—์„œ๋ถ€ํ„ฐ ์‹œ์ž‘๋˜์—ˆ๋‹ค. ์ฒ˜์Œ ๋ณธ์ธ์€ ์ง„์‹ค์˜ ํ—ˆ์œ„์„ฑ์„ ๊ณ ๋ฐœํ•˜๊ณ  ๊ทธ ์ง„์œ„์—ฌ๋ถ€๋ฅผ ๊ตฌ๋ถ„ํ•˜๊ณ ์ž ํ•˜์˜€์œผ๋‚˜ ์ž‘์—…์„ ๊ฑฐ๋“ญํ•˜๋ฉด์„œ ์ง„์งœ์™€ ๊ฐ€์งœ, ํ—ˆ๊ตฌ์™€ ์‹ค์žฌ ์˜ ๊ฒฝ๊ณ„๋ฅผ ํ™•์—ฐํžˆ ๊ตฌ๋ถ„ํ•  ์ˆ˜ ์—†๋‹ค๋Š” ๊ฒƒ์„ ๊นจ๋‹ฌ์•˜๋‹ค. ๋‹ค๋งŒ, ์ง„์‹ค์€ ์ ˆ๋Œ€์ ์ด์ง€ ์•Š์œผ๋ฉฐ, ๋‚˜์•„๊ฐ€ ํ™๊ณผ ๊ฐ™์ด ๋ณ€ํ˜• ๊ฐ€๋Šฅํ•œ ๊ฐ€์†Œ์„ฑ์„ ๋ˆ๋‹ค๋Š” ๊ฒƒ์„ ๋ฐœ๊ฒฌํ•  ์ˆ˜ ์žˆ์—ˆ๋‹ค. ์ด๋Ÿฌํ•œ ์ง„์‹ค์˜ ๊ฐ€์†Œ์„ฑ์€ ์ง„์‹ค์„ ๋ณ€ํ™” ์‹œํ‚ค๊ฑฐ๋‚˜ ์ฐฝ์กฐํ•  ์ˆ˜ ์žˆ๋‹ค๋Š” ์ ์—์„œ ์˜ˆ์ˆ ์  ๊ฐ€๋Šฅ์„ฑ์„ ์ œ์‹œํ–ˆ๋‹ค. ๋ณธ์ธ์€ ๋‰ด์Šค์— ๋‚˜์˜ค๋Š” ์‚ฌ๊ธฐ๊พผ๋“ค์˜ ์ˆ˜๋ฒ•์„ ํ•™์Šตํ•˜๊ฑฐ๋‚˜ ์œ„์กฐ๋œ ์ค‘๊ตญ์‚ฐ ์ œํ’ˆ์„ ๊ด€์ฐฐํ•˜๋Š” ๋“ฑ์˜ ๋ฐฉ์‹์„ ํ†ตํ•ด ์ง„์‹ค์„ ๊ฐ€์†Œํ•˜๋Š” ๋ฐฉ๋ฒ•๋ก ์„ ๊ตฌ์ƒํ•˜์˜€๋‹ค, ๊ทธ๋ฆฌ๊ณ  ๊ทธ ๋ฐฉ๋ฒ•๋ก ์„ ๊ณต๊ฐ„์—ฐ์ถœ์— ์ ์šฉํ•˜์—ฌ ์‚ฌ๋žŒ๋“ค์˜ ๋ฐ˜์‘์„ ๊ด€์ฐฐํ•˜์˜€๋‹ค. ๋‚˜์•„๊ฐ€ ๋ณธ์ธ์€ ์ง„์‹ค์„ ๊ฐ€์†Œํ•˜๋Š” ๋ฐฉ๋ฒ•๋ก ๊ณผ ๋‚ด๋Ÿฌํ‹ฐ๋ธŒ๋ฅผ ๊ฒฐํ•ฉํ•˜์—ฌ ๋ฏธ์ˆ ์ „์‹œ ํ–‰์œ„๋‚˜ ์ด์•ผ๊ธฐ ๊ตฌ์กฐ๊ฐ€ ๊ทธ ๊ฒฝ๊ณ„๋ฅผ ๋ฒ—์–ด๋‚˜ ์‹ค์ œ ํ˜„์‹ค์˜ ํ™•์žฅ์— ์˜ํ–ฅ์„ ๋ผ์น˜๋Š” ๊ฒƒ์„ ์‹œ๋„ํ•˜์˜€๋‹ค. ํ•˜์ง€๋งŒ, ์ด์™€ ๊ฐ™์€ ์‹œ๋„๋Š” ๊ด€๊ฐ์˜ ๋ฐ˜์‘์— ์˜ํ•ด ๊ฒฐ๋ก ์— ์ด๋ฅด๋ฉฐ, ์„ฑ๊ณต์—ฌ๋ถ€๋ฅผ ํ™•์ธํ•˜๋Š”๋ฐ ๋‹ค์†Œ ์‹œ๊ฐ„์ด ๊ฑธ๋ฆฌ๊ธฐ์— ์ด๋ฅผ ์ „๊ฐœํ•˜๋Š” ๋‹ค์–‘ํ•˜๊ณ  ์žฅ๊ธฐ์ ์ธ ์‹œ๋„์™€ ๊ด€์ฐฐ์ด ์š”๊ตฌ๋œ๋‹ค. ์ฃผ์š”์–ด : ์ง„์‹ค, ์ง„์‹ค์˜ ๊ฐ€์†Œ์„ฑ, ํ˜„์‹ค์˜ ํ™•์žฅ์„œ ๋ก  .................................................................................... 1 ์ง„์‹ค์„ ๊ฒ€์ฆํ•˜๋Š” ์ฒด๊ณ„์˜ ์˜ค๋ฅ˜์™€ ์ง„์‹ค์˜ ๊ฐ€์†Œ์„ฑ(ๅฏๅก‘ๆ€ง) ............ 2 ์ง„์‹ค์˜ ๊ฐ€์†Œ๋ฐฉ๋ฒ• 1) ์‹ ๋ขฐ๋ฅผ ์ž๊ทนํ•˜๋Š” ์กฐ๊ฑด์˜ ๊ฒฐํ•ฉ .............................................................. 3 2) ๊ฐ€์ƒ์˜ ๊ฐ๊ฐ ๊ตฌ์ถ• .................................................................................. 5 ์ง„์‹ค์˜ ๊ฐ€์†Œ์„ฑ๊ณผ ๋‚ด๋Ÿฌํ‹ฐ๋ธŒ์˜ ๊ฒฐํ•ฉ ............................................................. 7 1) ์ง„์‹ค์˜ ๊ฐ€์†Œ ๋ฐฉ๋ฒ•๋ก - ์ด์•ผ๊ธฐ ์ „๋‹ฌ์˜ ํšจ๊ณผ์  ์งˆ๋ฃŒ............................ 7 2) ๋‚ด๋Ÿฌํ‹ฐ๋ธŒ์˜ ํ•ฉ์„ฑ, ํ˜„์‹ค์˜ ํ™•์žฅ ............................................................. 8 ๊ฒฐ ๋ก  .................................................................................. 10 ์ž‘ํ’ˆ์„ค๋ช… .................................................................................. 11 ์ž‘ํ’ˆ์‚ฌ์ง„ .................................................................................. 15 Abstract ................................................................................. 22Maste

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    ํ•™์œ„๋…ผ๋ฌธ (์„์‚ฌ)-- ์„œ์šธ๋Œ€ํ•™๊ต ๋Œ€ํ•™์› : ์‚ฌํšŒํ•™๊ณผ, 2016. 8. ์ด์žฌ์—ด.์ •์น˜์ฐธ์—ฌ์˜ ์˜ํ–ฅ์š”์ธ์€ ๋‹ค์–‘ํ•˜๋ฉฐ ๋งค์šฐ ๋ณตํ•ฉ์ ์ด๋‹ค. ๊ทธ ์ค‘ ์ผ๋ฐ˜์‹ ๋ขฐ์™€ ์ •๋ถ€์‹ ๋ขฐ๋Š” ๊ฐ๊ฐ ์ƒ์ดํ•œ ๋งฅ๋ฝ์—์„œ ์‹œ๋ฏผ์‚ฌํšŒ์™€ ๋ฐ€์ ‘ํ•œ ๊ด€๊ณ„๋ฅผ ๋งบ๊ณ  ์žˆ๋‹ค. ์ •๋ถ€์‹ ๋ขฐ๋Š” ์™ธ์  ์ •์น˜ํšจ๋Šฅ๊ฐ์„ ๋Œ€๋ณ€ํ•˜๋Š” ๊ฐ€์น˜๋กœ ๋‚˜ํƒ€๋‚˜๋Š” ๋ฐ˜๋ฉด, ์ผ๋ฐ˜ ์‹ ๋ขฐ๋Š” ์‚ฌํšŒ์  ํ–‰์œ„์ž๋“ค ๊ฐ„์˜ ๊ฑฐ๋ž˜๋น„์šฉ์„ ๊ฐ์†Œ์‹œํ‚ค๋Š” ์‚ฌํšŒ์  ์ž๋ณธ์˜ ํ•˜๋‚˜๋กœ์„œ ์‹œ๋ฏผ์‚ฌํšŒ์™€ ๋ฏผ์ฃผ์ฃผ์˜ ๋ฐœ์ „์— ๊ธฐ์—ฌํ•˜๋Š” ๊ธ์ •์ ์ธ ๊ฐ€์น˜๋กœ ๊ฐ„์ฃผ๋œ๋‹ค. ์ผ๋ฐ˜์‹ ๋ขฐ์™€ ์ •๋ถ€์‹ ๋ขฐ๊ฐ€ ์ •์น˜์ฐธ์—ฌ์— ๋ฏธ์น˜๋Š” ์˜ํ–ฅ์€ ๋‹ค์ˆ˜์˜ ์—ฐ๊ตฌ๋ฅผ ํ†ตํ•ด ํ™•์ธ๋œ ๋ฐ” ์žˆ์ง€๋งŒ ๊ทธ ์˜ํ–ฅ๋ ฅ์ด ์‚ฌํšŒ์  ์ง‘๋‹จ์˜ ์†์„ฑ์— ๋”ฐ๋ผ ๋‹ฌ๋ผ์ง€๋Š”์ง€ ์—ฌ๋ถ€๋Š” ์ƒ๋Œ€์ ์œผ๋กœ ์•Œ๋ ค์ง€์ง€ ์•Š์•˜๋‹ค. ํ•œ๊ตญ์—์„œ๋Š” ํŠนํžˆ ์„ธ๋Œ€์  ํŠน์„ฑ๊ณผ ์‹ ๋ขฐ๊ฐ€ ์ƒํ˜ธ์ž‘์šฉํ•  ๋•Œ ์ •์น˜์ฐธ์—ฌ์— ์–ด๋– ํ•œ ์˜ํ–ฅ์„ ๋ฏธ์น˜๋Š”์ง€ ํ™•์ธํ•  ํ•„์š”๊ฐ€ ์žˆ๋‹ค. ํ•œ๊ตญ์‚ฌํšŒ๋Š” ํ•ด๋ฐฉ ์ดํ›„ ์•ฝ 40๋…„ ๋™์•ˆ ํ•œ๊ตญ์ „์Ÿ์—์„œ๋ถ€ํ„ฐ ์••์ถ•์„ฑ์žฅ, ๋ฏผ์ฃผํ™”, ์ •๋ณดํ™”์— ์ด๋ฅด๋Š” ๊ธ‰๊ฒฉํ•œ ์‚ฌํšŒ๋ณ€๋™์„ ๊ฑฐ์ณ์™”๊ธฐ ๋•Œ๋ฌธ์— ์„ธ๋Œ€๋ณ„ ํŠน์„ฑ์ด ๋šœ๋ ทํ•˜๊ฒŒ ๋ถ€๊ฐ๋˜๊ธฐ ๋•Œ๋ฌธ์ด๋‹ค. ๋ณธ ์—ฐ๊ตฌ๋Š” ์ธ๊ตฌํ•™์  ํŠน์„ฑ๊ณผ ์‚ฌํšŒ์—ญ์‚ฌ์  ๊ฒฝํ—˜์— ๊ทผ๊ฑฐํ•˜์—ฌ 1945๋…„๋ถ€ํ„ฐ 1994๋…„๊นŒ์ง€์˜ ์ถœ์ƒ์ž๋ฅผ ๋‹ค์„ฏ ๊ฐœ ์ฝ”ํ˜ธํŠธ๋กœ ๋ถ„๋ฅ˜ํ•ด ํ•ด๋ฐฉ๋‘ฅ์ด, ๋ฒ ์ด๋น„๋ถ, X, ๋””์ง€ํ„ธ 1.0, ๋””์ง€ํ„ธ 2.0์„ธ๋Œ€๋กœ ์นญํ•˜์˜€๋‹ค. ๊ทธ๋ฆฌ๊ณ  2014๋…„ ํ•œ๊ตญ์ข…ํ•ฉ์‚ฌํšŒ์กฐ์‚ฌ ์ž๋ฃŒ๋ฅผ ํ™œ์šฉํ•˜์—ฌ ๋‹ค์„ฏ ์„ธ๋Œ€๊ฐ€ ๋‹ค์–‘ํ•œ ์ •์น˜ํ™œ๋™์— ์ฐธ์—ฌํ•  ํ™•๋ฅ ๊ณผ ๊ทธ ๊ด€๊ณ„์—์„œ ์‹ ๋ขฐ์˜ ์กฐ์ ˆํšจ๊ณผ๋ฅผ ๊ฒฝํ—˜์ ์œผ๋กœ ์—ฐ๊ตฌํ•˜์˜€๋‹ค. ๋ถ„์„๊ฒฐ๊ณผ ์ฒซ์งธ, ๋Œ€์ฒด์ ์œผ๋กœ ๋น„์ œ๋„์  ์ •์น˜ํ™œ๋™์—์„œ X์„ธ๋Œ€, ๋””์ง€ํ„ธ 1.0์„ธ๋Œ€์™€ 2.0์„ธ๋Œ€์˜ ์ฐธ์—ฌํ™•๋ฅ ์ด ํ•ด๋ฐฉ๋‘ฅ์ด ์„ธ๋Œ€๋ณด๋‹ค ๋†’์€ ๋ฐ˜๋ฉด ํˆฌํ‘œ ์ฐธ์—ฌํ™•๋ฅ ์€ ํ•ด๋ฐฉ๋‘ฅ์ด ์„ธ๋Œ€๊ฐ€ ์ด๋“ค ์„ธ๋Œ€๋ณด๋‹ค ๋†’๊ฒŒ ๋‚˜ํƒ€๋‚ฌ๋‹ค. ๋‘˜์งธ, ๋ฒ ์ด๋น„๋ถ ์„ธ๋Œ€๋Š” ๋น„์ œ๋„์  ์ •์น˜ ํ™œ๋™์—์„œ ์ •๋ถ€์‹ ๋ขฐ์˜ ์กฐ์ ˆํšจ๊ณผ๊ฐ€ ํ•ด๋ฐฉ๋‘ฅ์ด ์„ธ๋Œ€์™€ ๋น„๊ตํ•˜์—ฌ ์ตœ์†Œ 10% ์œ ์˜์ˆ˜์ค€์—์„œ ์œ ์˜๋ฏธํ•œ ์ฐจ์ด๋ฅผ ๋ณด์˜€๋‹ค. ์…‹์งธ, ํ•ด๋ฐฉ๋‘ฅ์ด ์„ธ๋Œ€์™€ ๋””์ง€ํ„ธ 1.0์„ธ๋Œ€๋Š” ์ •๋ถ€์‹ ๋ขฐ๊ฐ€ ๋†’์„ ๊ฒฝ์šฐ ์ฒญ์›์„œ ์„œ๋ช… ํ™œ๋™์— ๊ธ์ •์ ์ธ ์ฐธ์—ฌ์˜์‚ฌ๋ฅผ ๊ฐ€์งˆ ํ™•๋ฅ ์ด ํฐ ํญ์œผ๋กœ ๊ฐ์†Œํ•˜๋Š” ๊ฒฝํ–ฅ์„ ๋ณด์˜€์œผ๋‚˜, ์ผ๋ฐ˜์‹ ๋ขฐ๊ฐ€ ๋†’์„ ๊ฒฝ์šฐ์—๋Š” ํ•ด๋ฐฉ๋‘ฅ์ด ์„ธ๋Œ€์—์„œ ์ฐธ์—ฌ๊ฐ€ ๊ฐ์†Œํ•˜๋Š” ๋ฐ˜๋ฉด ๋””์ง€ํ„ธ 1.0์„ธ๋Œ€์—์„œ๋Š” ์ฐธ์—ฌ๊ฐ€ ์ด‰์ง„๋˜์–ด ์‹ ๋ขฐ ์œ ํ˜•์— ๋”ฐ๋ฅธ ์„ธ๋Œ€๋ณ„ ์ฐธ์—ฌ ์–‘์ƒ์˜ ์ฐจ์ด๊ฐ€ ๋„๋“œ๋ผ์กŒ๋‹ค. ๋„ท์งธ, ์ •๋ถ€๊ธฐ๊ด€์ธ์‚ฌ ์ ‘์ด‰ ํ™œ๋™์—์„œ ํ•ด๋ฐฉ๋‘ฅ์ด ์„ธ๋Œ€๋Š” ์ •๋ถ€์‹ ๋ขฐ๊ฐ€ ๋†’์„์ˆ˜๋ก ์‹ค์งˆ์  ์ฐธ์—ฌ ํ™•๋ฅ ์ด ๊ฐ์†Œํ•œ ๋ฐ˜๋ฉด ๋‚˜๋จธ์ง€ ์„ธ๋Œ€์—์„œ๋Š” ์ฐธ์—ฌ ํ™•๋ฅ ์ด ๋ณ€ํ™”ํ•˜์ง€ ์•Š๊ฑฐ๋‚˜ ์ƒ์Šนํ•˜์˜€๋‹ค. ์ข…ํ•ฉํ•ด๋ณด๋ฉด ์ฃผ๋กœ ํˆฌํ‘œ, ์„œ๋ช…, ์ •๋ถ€๊ธฐ๊ด€์ธ์‚ฌ ์ ‘์ด‰๊ณผ ๊ฐ™์ด ๊ธฐ๋Œ€ํšจ๊ณผ์— ๋น„ํ•ด ์ƒ๋Œ€์ ์œผ๋กœ ์ฐธ์—ฌ๋น„์šฉ์ด ์ ์€ ์ฐธ์—ฌ์—์„œ ์ผ๋ฐ˜์‹ ๋ขฐ์™€ ์ •๋ถ€์‹ ๋ขฐ์˜ ์กฐ์ ˆํšจ๊ณผ๊ฐ€ ์„ธ๋Œ€๋ณ„๋กœ ์ฐจ์ด๋ฅผ ๋ณด์˜€๋‹ค. ๋ณธ ์—ฐ๊ตฌ๋Š” ์ •์น˜์‚ฌํšŒ์  ์ง‘๋‹จ์œผ๋กœ์„œ ์„ธ๋Œ€์˜ ์ค‘์š”์„ฑ์„ ๊ฐ•์กฐํ•œ๋‹ค. ๋˜ํ•œ ์—ฐ๊ตฌ๊ฒฐ๊ณผ์— ๊ทผ๊ฑฐํ•ด ์„ธ๋Œ€๋ณ„ ์ •์น˜์ฐธ์—ฌ๋ฅผ ์ฆ์ง„์‹œํ‚ค๊ธฐ ์œ„ํ•ด์„œ๋Š” ์‹œ๋ฏผ๊ณผ ์ •์ฑ…๊ฒฐ์ •๊ธฐ๊ด€ ๊ฐ„์— ๋†’์€ ์‹ ๋ขฐ๋ฅผ ์Œ“๊ธฐ ์œ„ํ•œ ๋…ธ๋ ฅ์ด ํ•„์š”ํ•˜๋‹ค๊ณ  ๊ฒฐ๋ก  ๋งบ๋Š”๋‹ค.I. ์„œ๋ก  1 II. ๋ฌธํ—Œ๊ณ ์ฐฐ 3 1. ๊ฐœ๋…์ •๋ฆฌ 3 ๊ฐ€. ์„ธ๋Œ€ ๊ฐœ๋… 3 ๋‚˜. ์ •์น˜์ฐธ์—ฌ์˜ ์ •์˜ 3 2. ์ •์น˜ํ–‰์œ„์ž๋กœ์„œ์˜ ์„ธ๋Œ€ 4 ๊ฐ€. ์ •์น˜์„ธ๋Œ€ ์ด๋ก  4 ๋‚˜. ์„ธ๋Œ€์˜ ๊ตฌ๋ถ„ 6 ๋‹ค. ์‚ฌํšŒ๋ณ€๋™๊ณผ ์„ธ๋Œ€๊ฒฝํ—˜ 9 3. ์ •์น˜์ฐธ์—ฌ 16 ๊ฐ€. ์ •์น˜์ฐธ์—ฌ์˜ ๊ตฌ๋ถ„ 16 ๋‚˜. ์ •์น˜์ฐธ์—ฌ์˜ ์˜ํ–ฅ์š”์ธ 18 ๋‹ค. ์„ธ๋Œ€๋ณ„ ์ •์น˜์ฐธ์—ฌ ์˜ํ–ฅ์š”์ธ์œผ๋กœ์„œ์˜ ์‹ ๋ขฐ 20 4. ๋ฌธํ—Œ๊ณ ์ฐฐ ๊ฒฐ๋ก  23 III. ์ž๋ฃŒ ๋ฐ ์—ฐ๊ตฌ๋ฐฉ๋ฒ•๋ก  25 1. ์—ฐ๊ตฌ๋ชจํ˜• 25 2. ์ž๋ฃŒ 26 3. ๋ณ€์ˆ˜๊ตฌ์„ฑ 26 4. ์—ฐ๊ตฌ๋ฐฉ๋ฒ• 29 IV. ๋ถ„์„๊ฒฐ๊ณผ 31 1. ๋น„์ œ๋„์  ์ •์น˜ํ™œ๋™ ์ฐธ์—ฌ 31 ๊ฐ€. ์ธํ„ฐ๋„ท ํ† ๋ก  ์ฐธ์—ฌ 33 ๋‚˜. ์„œ๋ช… ํ™œ๋™ 38 2. ์ œ๋„์  ์ •์น˜ํ™œ๋™ ์ฐธ์—ฌ 44 3. ๋ถ„์„๊ฒฐ๊ณผ ์†Œ๊ฒฐ 48 V. ๊ฒฐ๋ก  ๋ฐ ํ•จ์˜ 53 ์ฐธ๊ณ  ๋ฌธํ—Œ 56 Abstract 64 ๋ถ€๋ก 65Maste

    ํ•œ๊ตญ์‚ฐ ์†Œ๋‚˜๋ฌด ์žŽ ์ฐฉ์ƒ๊ท ์˜ ์ƒํƒœํ•™ ๋ฐ ๊ณ„ํ†ตํ•™์  ์—ฐ๊ตฌ

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    ํ•™์œ„๋…ผ๋ฌธ(๋ฐ•์‚ฌ)--์„œ์šธ๋Œ€ํ•™๊ต ๋Œ€ํ•™์› :์ƒ๋ช…๊ณผํ•™๋ถ€,2007.Docto

    ์„ฑ๊ณผ์ฃผ์˜์˜ˆ์‚ฐ์ œ๋„ ๋„์ž…์ดํ›„ ๊ตญํšŒ ๊ฒฐ์‚ฐ์‹ฌ์‚ฌ์˜ ๋ณ€ํ™”์— ๊ด€ํ•œ ์—ฐ๊ตฌ

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    ํ•™์œ„๋…ผ๋ฌธ(์„์‚ฌ)--์„œ์šธ๋Œ€ํ•™๊ต ํ–‰์ •๋Œ€ํ•™์› :ํ–‰์ •ํ•™๊ณผ ํ–‰์ •ํ•™์ „๊ณต,2002.Maste

    Prediction model of knee joint line orientation after medial open wedge high tibial osteotomy

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    ํ•™์œ„๋…ผ๋ฌธ (์„์‚ฌ)-- ์„œ์šธ๋Œ€ํ•™๊ต ๋Œ€ํ•™์› ์˜๊ณผ๋Œ€ํ•™ ์˜ํ•™๊ณผ, 2017. 8. ์žฅ์ข…๋ฒ”.Background: A joint line parallel to the floor is an important objective after medial open wedge high tibial osteotomy(MOWHTO). One of the methods to assess the coronal alignment of the knee after MOWHTO is knee joint line orientation relative to the ground (G-KJLO). There are no tools, however, for surgeons that could predict the value of post-operative G-KJLO before the surgery. Methods: Fourteen radiographic parameters were measured in pre-operative and post-operative full-limb standing anteroposterior radiographs on 50 patients who underwent MOWHTO. The parameters were analyzed using multivariate linear regression to predict the G-KJLO after MOWHTO. Results: After MOWHTO, G-KJLO increased from a mean value of -0.8ยฐ to 2.9ยฐ(P < 0.001). G-AJLO decreased after MOWHTO from a mean value of 8.3ยฐ to 1.5ยฐ(P < 0.001). Based on the multiple regression analysis by backward elimination of parameters influencing post-operative G-KJLO, we have derived an equation that can estimate post-operative G-KJLO after MOWHTOpost-operative G-KJLO (ยฐ) = 8.300 + 0.419 โ…น pre-operative G-KJLO (ยฐ) + 0.923 โ…น pre-operative medial proximal tibial angle(MPTA) (ยฐ) ยญ 0.095 โ…น pre-operative tibial width (mm) ยญ 0.655 โ…น pre-operative hip-knee-ankle(HKA) angle (ยฐ) + 0.444 โ…น lateral distal femoral angle(LDFA) (ยฐ) + 0.662 โ…น pre-operative joint space tilt angle(JSTA) (ยฐ) + 0.421 โ…น aimed correction angle (ยฐ). Conclusion: This study analyzed the effects of pre-operative anatomical alignment parameters to the post-operative G-KJLO. We established an equation which predicts post-operative G-KJLO with pre-operative anatomical alignment factors. This equation might help selecting optimal patients and operative plan for MOWHTO.Introduction 1 Material and Methods 5 Results 10 Discussion 17 References 24 Abstract in Korean 30Maste
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