X-ray fluorescence spectroscopy analysis
US12345667B2 · kind B2 · utility
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4References
19Claims
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Key dates
| Filing date | Oct 5, 2022 |
| Grant date | Jul 1, 2025 |
| Priority date | — |
| Expiry date | Dec 29, 2043 |
Classification
- Technology area (CPC G)Physics
- CPC primaryG01N2223/507
- WIPO fieldMeasurement
- WIPO sectorInstruments
Abstract
Multivariate machine learning (ML) techniques can be applied to an XRF spectra and mitigate matrix effects and enable simultaneous quantification of composition, even when markers elements or ions of interest are imperceptible in the XRF spectra. Physical (e.g., density) and chemical (e.g., total dissolved solids and hardness) properties of the material can be also quantified using ML techniques.
Source: USPTO / EPO open patent data. Objective bibliographic and citation counts.