Preparing for the Next Pandemic: Predicting UV Inactivation of Coronaviruses with Machine Learning-Reference-Cited by-同舟云学术

Preparing for the Next Pandemic: Predicting UV Inactivation of Coronaviruses with Machine Learning

Published:2023-09-03 Issue:37 Volume:57 Page:13767-13777
ISSN:0013-936X
Container-title:Environmental Science & Technology
language:en
Short-container-title:Environ. Sci. Technol.

Author:

Huang Ruixing¹²,Ma Chengxue¹²,Huangfu Xiaoliu²^ORCID,Ma Jun¹^ORCID

Affiliation:

1. State Key Laboratory of Urban Water Resource and Environment, School of Environment, Harbin Institute of Technology, Harbin 150090, China

2. Key Laboratory of Eco-environments in the Three Gorges Reservoir Region, Ministry of Education, College of Environmental and Ecology, Chongqing University, Chongqing 400044, China

Funder

National Key Research and Development Program of China

National Natural Science Foundation of China

Chongqing Talents: Exceptional Young Talents Project

Publisher

American Chemical Society (ACS)

Subject

Environmental Chemistry,General Chemistry

Link

https://pubs.acs.org/doi/pdf/10.1021/acs.est.3c03707

Reference45 articles.

1. A critical review on the inactivation of surface and airborne SARS-CoV-2 virus by ozone gas

2. WHO. WHO Coronavirus (COVID-19) Dashboard. https://covid19.who.int/ (accessed 2023-05-14).

3. COVID-19 pandemic lesson learned- critical parameters and research needs for UVC inactivation of viral aerosols

4. UV-Based Technologies for SARS-CoV2 Inactivation: Status and Perspectives

5. Decontamination of respirators amid shortages due to SARS-CoV-2

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