[Development of a machine learning-based ionization efficiency prediction model for per- and polyfluoroalkyl substances and its application in semi-quantitative analysis].
- DOI
- 10.3724/sp.j.1123.2025.02012
- Published
- 2026 Apr
- Container
- Se pu = Chinese journal of chromatography
- Publisher
- Not recorded
- Open access
- yes
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Cite this work
BibTeX
@article{allodium:10.3724/sp.j.1123.2025.02012,
title = {[Development of a machine learning-based ionization efficiency prediction model for per- and polyfluoroalkyl substances and its application in semi-quantitative analysis].},
author = {Sun SZ and Li YY and Gao Y and Li KC and Chen Z and Li XQ and Zhang QH},
year = {2026},
journal = {Se pu = Chinese journal of chromatography},
doi = {10.3724/sp.j.1123.2025.02012},
url = {https://doi.org/10.3724/sp.j.1123.2025.02012}
}RIS
TY - JOUR TI - [Development of a machine learning-based ionization efficiency prediction model for per- and polyfluoroalkyl substances and its application in semi-quantitative analysis]. AU - Sun SZ AU - Li YY AU - Gao Y AU - Li KC AU - Chen Z AU - Li XQ AU - Zhang QH PY - 2026 JO - Se pu = Chinese journal of chromatography DO - 10.3724/sp.j.1123.2025.02012 UR - https://doi.org/10.3724/sp.j.1123.2025.02012 ER -
APA
SZ, S., YY, L., Y, G., KC, L., Z, C., XQ, L., & QH, Z. (2026). [Development of a machine learning-based ionization efficiency prediction model for per- and polyfluoroalkyl substances and its application in semi-quantitative analysis].. Se pu = Chinese journal of chromatography. https://doi.org/10.3724/sp.j.1123.2025.02012
Source records
- pubmed · retrieved 2026-09-26T22:58:40.657Z