인문학
사회과학
자연과학
공학
의약학
농수해양학
예술체육학
복합학
DBpia AI
AI 에이전트
AI 아이디어
AI 리더
AI 뷰어
Citeasy
크롬 서지관리 다운로드
지원사업
학술연구/단체지원/교육 등 연구자 활동을 지속하도록 DBpia가 지원하고 있어요.
커뮤니티
연구자들이 자신의 연구와 전문성을 널리 알리고, 새로운 협력의 기회를 만들 수 있는 네트워킹 공간이에요.
초록·키워드
Abstract Hydrochar from waste biomass is a promising material for removing emerging contaminants (e.g., antibiotics) in water/soil environment. Abundant small-sized hydrochar particles (HPs) with a high content of reactive functional groups and high mobility are easily released into ecosystems through hydrochar applications. However, the photodegradation ability and corresponding structures of HPs are largely unknown, which hinder accurate estimation of the remediation effect of hydrochar in ecosystems. Herein, photodegradation performance of HP towards targeted norfloxacin (NOR, a typical antibiotic) under light irradiation (visible and UV light) were investigated after adsorption processes upon release into soil/water, and its reactive species and photoactive structures were clarified and compared with those of residual bulk hydrochar (BH) comprehensively. The results showed that: (1) photodegradation percentages of HPs were 4.02 and 4.48 times higher than those of BHs under UV and visible light, in which reactive species of both HPs and BHs were ·OH and ·O 2 − ; (2) density functional theory (DFT) results identified that the main photoactive structure of graphitic-N decreased the energy gap (Eg) of HPs, and C=O, COOH groups improved electron donating ability of BHs; (3) well-developed graphitization structure of HP resulted from higher polymerization reaction was an significant photoactive structure involving its superior photodegradation ability relative to that of BH. The distinct heterogeneities of photodegradation ability in HP and BH and underlying photoactive structures provide an in-depth understanding of hydrochar application for removing emerging contaminants in soil/water environment. Identifying photoactive structures is helpful to predict photodegradation ability of hydrochar according to their abundance. Graphical Abstract
인공지능 문자 인식 모델을 통해 추출된 텍스트로, 일부 오타나 오류가 포함될 수 있으나 지속적으로 개선 중입니다.
오류를 발견하셨다면 해당 부분을 드래그한 후 ' 를 통해 신고해주세요.
오류를 발견하셨다면 해당 부분을 드래그한 후 ' 를 통해 신고해주세요.
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