한국건축시공학회지 (Journal of the Korea Institute of Building Construction)

  • 제21권3호
  • /
  • Pages.189-194
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  • 2021
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  • 1598-2033(pISSN)
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  • 2233-5706(eISSN)
한국건축시공학회 (The Korean Institute of Building Construction)
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LIBS를 활용한 수용액과 모르타르 내 염화물량 분석

Analysis of Chloride Content in Aqueous Solution and Mortar using Laser Induced Breakdown Spectroscopy

  • Ryu, Hwa-Sung (Hanyang Experiment and Consulting, Hanyang University ERICA) ;
  • Park, Won-Jun (Department of Architectural Engineering, Kangwon National University)
  • 투고 : 2021.04.01
  • 심사 : 2021.04.19
  • 발행 : 2021.06.20
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초록

본 연구에서는 Lab. 스케일 LIBS 장치를 제작하여 모르타르 내 염화물 분석에서의 LIBS 적용성과 재현성 검토를 수행하였다. 염화물 함량을 조절한 모르타르를 대상으로 기존의 분석방법(XRF, 전위차 적정법)과 LIBS 분석을 동시에 진행하였다. LIBS 분석 결과, 염소이온은 837.59nm 파장에서 검출되었고, 다양한 농도 구간에서의 정밀도를 향상시키기 위하여 전기장 강화를 통한 약 50배의 LIBS 신호증폭을 구현하였다. 수용액 기반의 재현성을 검증을 통하여 LIBS 신호 강도와 Cl농도 사이의 높은 상관관계를 확인할수 있었으며, 콘크리트 염해 내구성 진단에 LIBS적용 가능성을 확인하였다.

LIBS has been attracting attention as an analytical method capable of real-time measurement without sample preparation. In this study, a Lab. scale LIBS device was fabricated to examine the applicability and reproducibility of LIBS in the analysis of chloride contents in mortar. The existing analysis method and LIBS analysis were performed simultaneously on the mortar test specimen with the chloride content adjusted. Compared to the chloride content condition of the mortar, the XRF and Potentiometric Titration results also showed a similar trend. As a result of LIBS analysis, chlorine ions were detected at a wavelength of 837.59 nm according to the chloride content condition. In order to improve the precision in various concentration ranges, the LIBS signal amplification of about 50 times through the electric field enhancement was implemented. Through the verification of the aqueous solution-based reproducibility, a high correlation between the LIBS signal strength and the Cl concentration was confirmed, and the possibility of applying LIBS to the durability diagnosis of concrete damage by chloride was confirmed.

키워드

과제정보

Special thanks to Wan-ki Min, CTO of 'SPECLIPSE', for helping to curate data using LIBS.

참고문헌

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