Abstract
This study uses bibliometric methods, machine learning, and data analysis to examine Salinity Gradient Energy (SGE), a renewable energy source derived from saline water sources of different concentrations such as seawater, waste brines and mining industries. SGE's use of advanced membrane processes efficiently extracts energy from the difference in salinity between different waters. Based on the dataset collected up to January 22, 2024 that contains 1270 articles, the following in-depth analysis sheds light on the SGE scientific progress, trending topics, strong collaborations, current trends, dominant authors, influential articles, important affiliations, basic statistics, common words, sentiments, and emotions to reveal the quality, quantity, and impact of the domain. Since the first SGE paper published in 1976, SGE research has attracted considerable attention from researchers over the last 20 years. Reverse Electrodialysis (RED) and Pressure Retarded Osmosis (PRO) are identified as the leading energy harvesting technologies. However, in recent years, the number of research studies on RED has increased. Institutions from China and the USA contributed more to the SGE progress. “Ion current rectification” is the trending topic of 2023. Sentiment and emotion scores revealed researchers' optimistic and neutral views on SGE technologies.
| Original language | English |
|---|---|
| Article number | 115812 |
| Journal | Renewable and Sustainable Energy Reviews |
| Volume | 219 |
| DOIs | |
| State | Published - Sep 2025 |
| Externally published | Yes |
Bibliographical note
Publisher Copyright:© 2025 The Authors
UN SDGs
This output contributes to the following UN Sustainable Development Goals (SDGs)
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SDG 7 Affordable and Clean Energy
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SDG 9 Industry, Innovation, and Infrastructure
Keywords
- Bibliometric analysis
- Blue energy
- Emotion analysis
- Machine learning
- Salinity gradient power
- Sentiment analysis
- Zero-shot classification
ASJC Scopus subject areas
- Renewable Energy, Sustainability and the Environment
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