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Dynamic Flow Approaches for Automated Radiochemical Analysis in Environmental, Nuclear and Medical Applications

Automated sample processing techniques are desirable in radiochemical analysis for environmental radioactivity monitoring, nuclear emergency preparedness, nuclear waste characterization and management during operation and decommissioning of nuclear facilities, as well as medical isotope production,...

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Detalles Bibliográficos
Autor principal: Qiao, Jixin
Formato: Online Artículo Texto
Lenguaje:English
Publicado: MDPI 2020
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7144463/
https://www.ncbi.nlm.nih.gov/pubmed/32213999
http://dx.doi.org/10.3390/molecules25061462
Descripción
Sumario:Automated sample processing techniques are desirable in radiochemical analysis for environmental radioactivity monitoring, nuclear emergency preparedness, nuclear waste characterization and management during operation and decommissioning of nuclear facilities, as well as medical isotope production, to achieve fast and cost-effective analysis. Dynamic flow based approaches including flow injection (FI), sequential injection (SI), multi-commuted flow injection (MCFI), multi-syringe flow injection (MSFI), multi-pumping flow system (MPFS), lab-on-valve (LOV) and lab-in-syringe (LIS) techniques have been developed and applied to meet the analytical criteria under different situations. Herein an overall review and discussion on these techniques and methodologies developed for radiochemical separation and measurement of various radionuclides is presented. Different designs of flow systems with combinations of radiochemical separation techniques, such as liquid–liquid extraction (LLE), liquid–liquid microextraction (LLME), solid phase extraction chromatography (SPEC), ion exchange chromatography (IEC), electrochemically modulated separations (EMS), capillary electrophoresis (CE), molecularly imprinted polymer (MIP) separation and online sensing and detection systems, are summarized and reviewed systematically.