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ZENODO
Dataset . 2025
License: CC BY
Data sources: ZENODO
ZENODO
Dataset . 2025
License: CC BY
Data sources: Datacite
ZENODO
Dataset . 2025
License: CC BY
Data sources: Datacite
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Multiparametric Optical Pressure Sensing in YAG:Ce3+ Enabled by Multiple Linear Regression: A New Paradigm for Superior Sensor Performance

Authors: Woźny, Przemysław; Hernández-Rodríguez, Miguel; Kamada, Kei; Yoshikawa, Akira; Majewska, Natalia; Mahlik, Sebastian; Runowski, Marcin; +2 Authors

Multiparametric Optical Pressure Sensing in YAG:Ce3+ Enabled by Multiple Linear Regression: A New Paradigm for Superior Sensor Performance

Abstract

Existing luminescent pressure sensors, including multi-modal ones, rely on a single spectroscopic parameter at a time for optical readout, which limits their sensing accuracy and precision. This work presents the first example of a truly multiparametric luminescent manometer, simultaneously utilizing several parameters for optical readout - based on the photophysical analysis of Ce³⁺ in a single-crystal yttrium aluminum garnet (YAG) host. The band energies, intensities, bandwidths and excited-state lifetime of the Ce³⁺-doped YAG were studied under extreme conditions (>14 GPa), to assess its potential as a new-generation optical pressure gauge. Both conventional single-parameter and the proposed multiparametric approaches were applied to the same dataset to evaluate its sensing performance. This new, multiparametric approach, based on multiple linear regression (MLR), led to a 50-fold increase in relative sensitivity and a 4-fold reduction in pressure uncertainty compared to the best single-parameter analysis. These results demonstrate that multiparametric analysis provides significantly enhanced accuracy and reliability in pressure sensing, without requiring changes to the material or experimental setup. This methodology is readily transferable and could be applied to a wide range of luminescent materials, laying the foundation for a new generation of high-performance optical manometers for use in high-pressure physics, materials science, and beyond.

Country
Poland
Keywords

multiple linear regression, sensor performance, optical pressure

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selected citations
These citations are derived from selected sources.
This is an alternative to the "Influence" indicator, which also reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
BIP!Citations provided by BIP!
popularity
This indicator reflects the "current" impact/attention (the "hype") of an article in the research community at large, based on the underlying citation network.
BIP!Popularity provided by BIP!
influence
This indicator reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
BIP!Influence provided by BIP!
impulse
This indicator reflects the initial momentum of an article directly after its publication, based on the underlying citation network.
BIP!Impulse provided by BIP!
0
Average
Average
Average
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