RT Journal Article
T1 Faradaic deionization technology: Insights from bibliometric, data mining and machine learning approaches
A1 Aytaç, Ersin
A1 Fombona-Pascual, Alba
A1 Lado, Julio J.
A1 García Quismondo, Enrique
A1 Palma, Jesús
A1 Khayet Souhaimi, Mohamed
AB Faradaic deionization (FDI) is an emerging water treatment technology based on electrodes able to remove ionic species from water by charge transfer reactions. It is a young and promising technology that has attracted much attention due to its large capacity to store ions and the high selectivity of the faradaic electrode materials. This study reviews published papers on FDI from different angles: data mining, bibliometric and machine learning. Metrics such as annual growth rate, most important journals, relevant authors, collaborations maps, sentiment and subjectivity analysis, similarity and clustering analysis were performed. The results indicated that the strong interest in FDI really started in 2016, China is the most active country in FDI, and Desalination is the most important journal publishing FDI articles. The word cloud method showed that the most preferred adopted words are deionization, capacitive, electrode, material. Sentiment analysis results indicated that most of the researchers are optimistic about FDI technology. The title similarity method revealed that FDI researchers were successful in proposing unique and appropriate titles. The clustering approach stressed that FDI literature is concentrated on electrode material production, desalination application, lithium recovery and comparison with CDI.
PB Elsevier
SN 0011-9164
YR 2023
FD 2023-10-01
LK https://hdl.handle.net/20.500.14352/102965
UL https://hdl.handle.net/20.500.14352/102965
LA eng
NO 2023 Acuerdos transformativos CRUE
NO Scientific and Technological Research Council of Turkey (TUBITAK)
NO Comunidad de Madrid
NO Universidad Complutense de Madrid
DS Docta Complutense
RD 9 abr 2025