Compatibility and Interaction Mechanism between the C4F7N/CO2/O2 Gas Mixture and FKM and NBR-Reference-Cited by-同舟云学术

Compatibility and Interaction Mechanism between the C₄F₇N/CO₂/O₂ Gas Mixture and FKM and NBR

Published:2023-03-15 Issue:12 Volume:8 Page:11414-11424
ISSN:2470-1343
Container-title:ACS Omega
language:en
Short-container-title:ACS Omega

Author:

Zhuo Ran¹²³,Chen Junyi⁴^ORCID,Xiao Song⁴,Fu Mingli¹²³,Wang Dibo¹²³^ORCID,Tan Xiangyu⁵,Li Yi⁴,Wu Peng⁴^ORCID,Tang Ju⁴,Zhang Xiaoxing⁶^ORCID

Affiliation:

1. Electric Power Research Institute, China Southern Power Grid, Guangzhou 510623, China

2. National Engineering Research Center of UHV Technology and New Electrical Equipment Fundamentals, Guangzhou 510623, China

3. United Laboratory of Advanced Electrical Materials and Equipment Support Technology, China Southern Power Grid, Guangzhou 510623, China

4. School of Electrical Engineering and Automation, Wuhan University, Wuhan 430072, China

5. Power Science Research Institute of Yunnan Power Grid Co., Ltd, Kunming 650217, China

6. Key Laboratory for High-efficiency Utilization of Solar Energy and Operation Control of Energy Storage System, School of Electrical and Electronic Engineering, Hubei University of Technology, Wuhan 430068, China

Funder

China Southern Power Grid

Publisher

American Chemical Society (ACS)

Subject

General Chemical Engineering,General Chemistry

Link

https://pubs.acs.org/doi/pdf/10.1021/acsomega.3c00195

Reference38 articles.

1. Assessment of Eco-friendly Gases for Electrical Insulation to Replace the Most Potent Industrial Greenhouse Gas SF6

2. Experimental Sensing and Density Functional Theory Study of H2S and SOF2Adsorption on Au-Modified Graphene

3. Nanomaterials‐based gas sensors of SF 6 decomposed species for evaluating the operation status of high‐voltage insulation devices

4. Green Gas to Replace SF6 in Electrical Grids

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1. Molecular dynamics simulation of thermal decomposition characteristics of C₄F₇N/CO₂/O₂ gas mixture;2024 IEEE International Conference on Plasma Science (ICOPS);2024-06-16

2. Comparison of machine learning algorithms based on machine learning for the prediction of thermal plasma physical parameters of C4F7N and CO2 environmentally friendly gas mixtures;AIP Advances;2024-03-01

3. Partial Discharge and Decomposition Characteristics of C₄F₇N/CO₂/O₂ Under Metallic Protrusion Defects;2023 2nd Asia Power and Electrical Technology Conference (APET);2023-12-28