메뉴 건너뛰기
.. 내서재 .. 알림
소속 기관/학교 인증
인증하면 논문, 학술자료 등을  무료로 열람할 수 있어요.
한국대학교, 누리자동차, 시립도서관 등 나의 기관을 확인해보세요
(국내 대학 90% 이상 구독 중)
로그인 회원가입 고객센터 ENG
주제분류

추천
검색

논문 기본 정보

자료유형
학술저널
저자정보
Choi, Sung-Min (PCAM Korea) Song, Jin-Kun (Chemolee Lab Corporation) Kim, Sang-Jin (Chemolee Lab Corporation)
저널정보
한국유화학회 한국유화학회지 한국응용과학기술학회지 제33권 제1호
발행연도
2016.1
수록면
195 - 203 (9page)

이용수

표지
📌
연구주제
📖
연구배경
🔬
연구방법
🏆
연구결과
AI에게 요청하기
추천
검색

초록· 키워드

오류제보하기
Heavy metals have been analyzed on the non-woven from the 24 kinds of wet wipes and 8 kinds of mask packs. The following materials used in the non-woven according to each product are: rayon+polyester for the 12 wet wipe products, rayon+PET for the 5 wet wipe products, and rayon, cotton, rayon+polyester+cotton, pulp+polypropylene for the rest of the wet wipe products. No further information on the materials was found on the 3 wet wipes and 8 mask packs. However, polyester may be applied for the non-woven in wet wipes, because PET is part of the polyester group. The heavy metals analysis in the 24 kinds of wet wipes and 8 kinds of mask packs revealed the following: arsenic was found from $47.14{\pm}1.13$ to $71.75{\pm}1.64{\mu}g/L$ on the 3 products, the amount of nickel in the 2 products were $261.26{\pm}5.14$ and $1,242.63{\pm}43.71{\mu}g/L$, $53.69{\pm}1.45$ and $103.52{\pm}2.02mg/L$ on the 2 mask packs. It was also revealed that lead was detected from $7.23{\pm}0.32$ to $55.67{\pm}1.46{\mu}g/L$ on the 6 wet wipes, antimony was ranged from $187.86{\pm}5.24$ to $19,558.35{\pm}3,537.30{\mu}g/L$ on the 12 wet wipes, and $5.25{\pm}0.25$ and $8,936{\pm}55.22{\mu}g/L$ on the 2 mask packs. No cadmium, mercury, or thallium were detected from all the products. A high concentration of antimony might come from antimony trioxide, which was used as a catalyst when manufacturing the polyester. Therefore, it is strongly recommended that a non-woven used for cosmetic purposes should not use heavy metals as a catalyst when manufacturing, and it's important to clarify which materials are used in non-woven.

목차

등록된 정보가 없습니다.

참고문헌 (0)

참고문헌 신청

함께 읽어보면 좋을 논문

논문 유사도에 따라 DBpia 가 추천하는 논문입니다. 함께 보면 좋을 연관 논문을 확인해보세요!

이 논문의 저자 정보

최근 본 자료

전체보기

댓글(0)

0