Assessing Water Solubility of Ester‐Based Oils and Unravelling Their Mechanisms by a Quantitative Model

ABSTRACT Moisture is a sensitive issue for transformer oils, as it adversely affects the stability of insulation papers and dielectric strength of the oils. However, the lack of a quantitative model makes it challenging to evaluate the water solubility of ester‐based oils, which is an undesirable restriction for developing novel ester‐based oils. Herein, a quantitative model, which requires only the molecular structure as input, was developed to assess the water solubility. Experimental data revealed that both the molecular structure and temperature are the primary factors influencing the water saturation. Our model successfully reproduced the results with a deviation of < 10.0%. Next, we explored the mechanisms that govern the water saturation, focusing on the contribution of each group within molecular structures. It was found that the ester groups play a key role in determining the water saturation, and their contribution value varies from 180 mg/(kg·atom) (FR3) to 820 mg/(kg·atom) (palm fatty acid ester). This variation arises from the differences in the electrostatic potential (ESP), and a linear relationship between the maximum absolute ESP value and the group contribution value was revealed. Finally, we analysed the vapour–liquid equilibrium, revealing the change of water content in the oils when the operating conditions of transformers vary.

Authors

Institutions

Publication Details

Journal
High Voltage
Published
2026-05-22
DOI
https://doi.org/10.1049/hve2.70192
Primary Topic
Power Transformer Diagnostics and Insulation
Type
article
Field-Weighted Citation Impact
0.00
Controls
|||
ALL TIME
JAN
FEB
MAR
APR
MAY
JUN
JUL
AUG
SEP
OCT
article

Assessing Water Solubility of Ester‐Based Oils and Unravelling Their Mechanisms by a Quantitative Model

Jinlu Sheng, Linyang Dan, Feng Tang, Hao Wen et al.
High Voltage
Power Transformer Diagnostics and Insulation
article

Assessing Water Solubility of Ester‐Based Oils and Unravelling Their Mechanisms by a Quantitative Model

Jinlu Sheng, Linyang Dan, Feng Tang, Hao Wen, Nan Liu, Xin Chen
article en

Abstract

ABSTRACT Moisture is a sensitive issue for transformer oils, as it adversely affects the stability of insulation papers and dielectric strength of the oils. However, the lack of a quantitative model makes it challenging to evaluate the water solubility of ester‐based oils, which is an undesirable restriction for developing novel ester‐based oils. Herein, a quantitative model, which requires only the molecular structure as input, was developed to assess the water solubility. Experimental data revealed that both the molecular structure and temperature are the primary factors influencing the water saturation. Our model successfully reproduced the results with a deviation of < 10.0%. Next, we explored the mechanisms that govern the water saturation, focusing on the contribution of each group within molecular structures. It was found that the ester groups play a key role in determining the water saturation, and their contribution value varies from 180 mg/(kg·atom) (FR3) to 820 mg/(kg·atom) (palm fatty acid ester). This variation arises from the differences in the electrostatic potential (ESP), and a linear relationship between the maximum absolute ESP value and the group contribution value was revealed. Finally, we analysed the vapour–liquid equilibrium, revealing the change of water content in the oils when the operating conditions of transformers vary.

High Voltage
Chongqing University (CN), Chongqing Jiaotong University (CN)
Clean water and sanitation
Openalex Percentile: Top 8%
Power Transformer Diagnostics and Insulation
AI Navigator

Ask Laika to Summarize, Analyze, and Connect papers live on the map.

Summarize Papers & Methodologies

Extract key findings, datasets, and comparative methods across publications.

Benchmark Rankings & Visual Analytics

Rank top research institutions, authors, funders, topics, and journals by Field-Weighted Citation Impact (FWCI) and paper volume with instant charts.

Connect Distant Disciplines

Bridge topological clusters on the map to find hidden collaborative intersections.