Tracing Microplastic Aging Processes Using Multimodal Deep Learning: A Predictive Model for Enhanced Traceability-Reference-Cited by-同舟云学术

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Tracing Microplastic Aging Processes Using Multimodal Deep Learning: A Predictive Model for Enhanced Traceability

Published:2024-09-09 Issue: Volume: Page:
ISSN:0013-936X
Container-title:Environmental Science & Technology
language:en
Short-container-title:Environ. Sci. Technol.

Author:

Li Yunlong¹,Wang Xue¹^ORCID,Zhang Han²,Wang Qing²,Cao Xun³,Gong Rongyi¹,Guo Jianli⁴,Shan Jiajia¹^ORCID

Affiliation:

1. School of Chemical Engineering, Ocean and Life Sciences, Dalian University of Technology, Panjin 124221, Liaoning, China

2. School of Environmental Science and Technology, Dalian University of Technology, Dalian 116081, Liaoning, China

3. China Unicom Online Information Technology Co., Ltd., Beijing 100032, China

4. Panjin Institute of Industrial Technology, Dalian University of Technology, Panjin, Liaoning, China 124000

Funder

National Natural Science Foundation of China

Publisher

American Chemical Society (ACS)

Link

https://pubs.acs.org/doi/pdf/10.1021/acs.est.4c05022

Reference51 articles.

1. Weathering and fragmentation of plastic debris in the ocean environment

2. Comprehensive understanding of the aging and biodegradation of polystyrene-based plastics

3. Abiotic Long-Term Simulation of Microplastic Weathering Pathways under Different Aqueous Conditions

4. Investigation of microplastics release behavior from ozone-exposed plastic pipe materials

5. Biofilm facilitates metal accumulation onto microplastics in estuarine waters

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