Uni- and multivariate calibration of temperature from the neodymium fluorescence spectra in nanocrystals of yttrium-gadolinium oxide and yttrium-gadolinium garnet
Abstract
The use of neodymium-doped nanocrystalline powders of yttrium-gadolinium oxide and yttrium gadolinium garnet to increase the sensitivity of local fluorescent optical temperature sensors is considered. Based on the temperature dependences of the neodymium fluorescence spectra in this powders, univariate (using fluorescence intensity ratio from thermally coupled energy levels of the activator) and multivariate (using the partial least squares method) calibration models are developed. When using the spectral range 860 – 950 nm falling into the first biological transparency window (700 – 980 nm), both calibration models have a standard deviation of about 10 % and are comparable in accuracy. The spectral variables selection by searching combination moving window in the multivariate model made it possible to reduce the root mean square error for yttrium-gadolinium oxide by more than 12 times (from 9.8 to 0.8 °C), and for yttrium-gadolinium garnet by more than 2 times(from 8.7 to 4.0 °С). The result obtained indicatesthe proposed neodymium-doped nanocrystalline powders and multivariate methods of calibration can be used to localise areas with febrile temperatures for biological and medical purposes.
References
- Hao Chen, Gongxun Bai, Qinghua Yang, Youjie Hua, Shiqing Xu, Liang Chen. Non-contact fluorescence intensity ratio optical thermometer based on Yb3+/Nd3+ codoped Bi4Ti3O12 microcrystals. Journal of Luminescence. 2020;221:117095. DOI: 10.1016/j.jlumin.2020.117095.
- Carbonati T, Ciontiac C, Cosaert E, Nimmegeers B, Meroniac D, Poelman D. NIR emitting GdVO4 : Nd nanoparticles for bioimaging: the role of the synthetic pathway. Journal of Alloys and Compounds. 2021;862:158413. DOI: 10.1016/j.jallcom.2020.158413.
- Manzoor O, Soleja N, Khan P, Hassan MI, Mohsin M. Visualization of thiamine in living cells using genetically encoded fluorescent nanosensor. Biochemical Engineering Journal. 2019;146:170–178. DOI: 10.1016/j.bej.2019.03.018.
- del Rosal B, Rocha U, Ximendes EC, Rodríguez EM, Jaque D, García Solé J. Nd3+ ions in nanomedicine: perspectives and applications. Optical Materials. 2017;63:185–196. DOI: 10.1016/j.optmat.2016.06.004.
- Balabhadra S, Debasu ML, Brites CDS, Nunes LAO, Malta OL, Rocha J, et al. Boosting the sensitivity of Nd3+-based luminescent nanothermometers. Nanoscale. 2015;7(41):17261–17267. DOI: 10.1039/C5NR05631D.
- Wade SA, Collins SF, Baxter GW. Fluorescence intensity ratio technique for optical fiber point temperature sensing. Journal of Applied Physics. 2003;94(8):4743–4756. DOI: 10.1063/1.1606526.
- Miniscalco WJ. Optical and electronic properties of rare earth ions in glasses. In: Digonnet MJF, editor. Rare-earth-doped fiber lasers and amplifiers. 2nd edition. Boca Raton: CRC Press; 2001. p. 17–112 (Optical science and engineering; volume 71). DOI: 10.1201/9780203904657.ch2.
- Svelto O. Principles of lasers. 3rd edition. New York: Plenum; 1989. 494 p. DOI: 10.1007/978-1-4615-7670-9.
- Yuan Zhou, Feng Qin, Yangdong Zheng, Zhiguo Zhang, Wenwu Cao. Fluorescence intensity ratio method for temperature sensing. Optics Letters. 2015;40(19):4544–4547. DOI: 10.1364/OL.40.004544.
- Rai VK. Temperature sensors and optical sensors. Applied Physics B. 2007;88(2):297–303. DOI: 10.1007/s00340-007-2717-4.
- Khodasevich МА, Аseev VА, Varaksa YuА, Kolobkova ЕV, Sinitsyn GV. Erbium-doped lead fluoride nano-glass-ceramics: application of principal component analysis to upconversion fluorescence spectra for temperature measurement. Materials Physics and Mechanics. 2015;24(1):18–23. Russian.
- Geladi P, Kowalski BR. Partial least-squares regression: a tutorial. Analytica Chimica Acta. 1986;185:1–17. DOI: 10.1016/0003-2670(86)80028-9.
- Zornoza R, Guerrero C, Mataix-Solera J, Scow KM, Arcenegui V, Mataix-Beneyto J. Near infrared spectroscopy for determination of various physical, chemical and biochemical properties in Mediterranean soils. Soil Biology & Biochemistry. 2008;40(7):1923–1930. DOI: 10.1016/j.soilbio.2008.04.003.
- Bro R, Smilde AK. Principal component analysis. Analytical Methods. 2014;6:2812–2831. DOI: 10.1039/C3AY41907J.
- Kennard RW, Stone LA. Computer aided design of experiments. Technometrics. 1969;11(1):137–148. DOI: 10.2307/1266770.
- Khodasevich МА, Aseev VА. [Spectral variables selection and increasing the accuracy of temperature calibration using the projection to latent structures from Yb3+ : CaF2 fluorescence spectra]. Optika i spektroskopiya. 2018;124(5):713–717. Russian. DOI: 10.21883/OS.2018.05.45958.22-18.
- Du YP, Liang YZ, Jiang JH, Berry RJ, Ozaki Y. Spectral regions selection to improve prediction ability of PLS models by changeable size moving window partial least squares and searching combination moving window partial least squares. Analytica Chimica Acta. 2004;501(2):183–191. DOI: 10.1016/j.aca.2003.09.041.
Copyright (c) 2022 Journal of the Belarusian State University. Physics

This work is licensed under a Creative Commons Attribution-NonCommercial 4.0 International License.
The authors who are published in this journal agree to the following:
- The authors retain copyright on the work and provide the journal with the right of first publication of the work on condition of license Creative Commons Attribution-NonCommercial. 4.0 International (CC BY-NC 4.0).
- The authors retain the right to enter into certain contractual agreements relating to the non-exclusive distribution of the published version of the work (e.g. post it on the institutional repository, publication in the book), with the reference to its original publication in this journal.
- The authors have the right to post their work on the Internet (e.g. on the institutional store or personal website) prior to and during the review process, conducted by the journal, as this may lead to a productive discussion and a large number of references to this work. (See The Effect of Open Access.)