☆ 4.6 Article

Time resolved study of temperature sensing using Gd2O3:Er,Yb: deep learning approach

PHYSICA SCRIPTA (2023)

相关参考文献

注意：仅列出部分参考文献，下载原文获取全部文献信息。

Article Engineering, Aerospace

Time resolved study of laser triggered electric discharge spark in atmosphere: Machine learning approach

Maja S. Rabasovic et al.

Summary: In this paper, the possibilities of using machine learning algorithms for analyzing optical spectra of electric discharge spark in atmosphere are analyzed. The study demonstrates the potential of using machine learning methods to classify optical spectra of plasmas with different electron temperatures obtained from different excitation energies. The results show that training computer software to recognize spectra corresponding to different electron temperatures is an effective alternative to the conventional method of identifying spectral peaks and calculating their intensity ratios.

ADVANCES IN SPACE RESEARCH (2023)

添加到收藏夹

Article Optics

Quantum yield and energy transfer in up-conversion SrGd2O4:Yb, Er nanoparticles obtained via sol-gel assisted combustion

Tijana Stamenkovic et al.

Summary: Nanopowders of up-conversion SrGd2O4 orthorhombic (Pnma) phase co-doped with different Yb3+ (1, 2.5 and 5 at%) and constant Er3+ (0.5 at%) ions were prepared via sol-gel assisted combustion. The obtained powders are composed of agglomerated nanoparticles with a uniform distribution of all elements. Increasing Yb3+ content enhances the up-conversion emission in the visible spectrum, leading to a significant change in the green to red ratio. Two-photon up-conversion processes are established through Er3+ f-f electronic transitions, resulting in green emission at 523 and 551 nm and red emission at 661 nm. The nanoparticles doped with 0.5 at% Er3+ and co-doped with 5 at% Yb3+ exhibit the highest absolute quantum yield of 0.055% under specific excitation conditions.

JOURNAL OF LUMINESCENCE (2023)

添加到收藏夹

Article Optics

Convolutional neural networks open up horizons for luminescence thermometry

Junqi Cui et al.

Summary: A novel strategy using convolutional neural network for luminescence thermometry is proposed, which can autonomously select and extract multiple temperature-dependent features for regression temperature calculation, fully utilizing the temperature-dependent spectral data. Compared with traditional ratiometric technology and multiple linear regression method, the proposed method exhibits significantly higher accuracy, indicating the potential of deep learning in the field of luminescence thermometry.

JOURNAL OF LUMINESCENCE (2023)

添加到收藏夹

Article Engineering, Chemical

The low-temperature sonochemical synthesis of up-converting β NaYF4: Yb,Er mesocrystals

Marina Vukovic et al.

Summary: This paper reports the successful synthesis of hexagonal NaYF4:Yb,Er mesocrystals using mild sonochemical methods at low temperature. The formation process of crystal structures is investigated and it is found that the pure beta phase can be obtained after 2 hours of pulsed sonication. The transition from the alpha phase to the beta phase is concluded to be a result of dissolution-recrystallization process based on the analysis of nanoparticle morphology.

ADVANCED POWDER TECHNOLOGY (2022)

添加到收藏夹

Article Chemistry, Physical

Luminescence properties of Yb3+and Er3+co-doped into Gd2O3:Bi3+phosphor powder

Mogahid H. M. Abdelrehman et al.

Summary: The structural and optical properties of Yb3+ and Er3+ co-doped Gd2O3:Bi3+ phosphor were studied. The addition of Yb3+ ions increased the optical bandgap of Gd2O3 and enhanced the near-infrared emission. The emission intensities of Yb3+ and Er3+ ions were significantly enhanced after Bi3+ doping. The results suggest that these phosphors have the potential to improve photovoltaic conversion efficiency through spectral modification and utilizing the down-conversion and upconversion processes.

JOURNAL OF ALLOYS AND COMPOUNDS (2022)

添加到收藏夹

Article Computer Science, Information Systems

Two-step learning for crowdsourcing data classification

Hao Yu et al.

Summary: Crowdsourcing learning plays an increasingly important role in the era of big data, but the uneven knowledge level of workers often leads to low accuracy of the labels. To solve this problem, this paper proposes a two-step learning crowdsourced data classification algorithm that optimizes the label data by considering worker abilities and sample similarity.

MULTIMEDIA TOOLS AND APPLICATIONS (2022)

添加到收藏夹

Article Optics

Less is more: dimensionality reduction as a general strategy for more precise luminescence thermometry

Erving Ximendes et al.

Summary: This study improves the thermal resolution of luminescent thermometers by using dimensionality reduction techniques on calibration datasets, enabling precise monitoring of temperature changes smaller than 0.1 degrees C.

LIGHT-SCIENCE & APPLICATIONS (2022)

添加到收藏夹

Review Chemistry, Multidisciplinary

Luminescence Thermometry for Brain Activity Monitoring: A Perspective

Paloma Rodriguez-Sevilla et al.

Summary: Monitoring brain activity is crucial for understanding its working principles and diagnosing diseases. We discuss the potential of brain thermometry as an alternative to conventional methods and highlight its advantages, drawbacks, and future challenges. Promoting the development of near infrared luminescence for brain activity monitoring is of great importance for various research areas.

FRONTIERS IN CHEMISTRY (2022)

添加到收藏夹

Review Instruments & Instrumentation

A brief review of new data analysis methods of laser-induced breakdown spectroscopy: machine learning

Dianxin Zhang et al.

Summary: Laser-induced breakdown spectroscopy (LIBS) is a technology used for content and composition analysis based on the atomic excitation and emission spectrum of materials. It has advantages such as fast detection speed, no environmental limitation, and no sample pretreatment. The low accuracy of LIBS is a major problem, and machine learning algorithms have significantly improved its accuracy compared to traditional analysis methods. Researchers have begun to focus on the application of machine learning algorithms in LIBS data analysis.

APPLIED SPECTROSCOPY REVIEWS (2022)

添加到收藏夹

Review Computer Science, Interdisciplinary Applications

Spectral Classification and Particular Spectra Identification Based on Data Mining

Peng Yang et al.

Summary: This paper reviews the importance of spectral classification and identification in astronomy and the application of data mining methods in automatic spectral analysis. The advantages and disadvantages of these methods are analyzed, and experimental results of representative methods are discussed. Existing problems and potential research trends are also pointed out.

ARCHIVES OF COMPUTATIONAL METHODS IN ENGINEERING (2021)

添加到收藏夹

Article Optics

Temperature sensing using YAG:Dy single-crystal phosphor

Dragutin Sevic et al.

Summary: In this paper, remote temperature sensing of YAG:Dy3+ single crystal was analyzed using fluorescence intensity ratio method, and the temperature calibration curve was calculated based on the ratio of intensities of spectral lines. The synthesized material was found to be efficiently used for thermographic purposes, up to 1273 K, and results were compared with other studies using principal component analysis.

EUROPEAN PHYSICAL JOURNAL D (2021)

添加到收藏夹

Article Nanoscience & Nanotechnology

Synthesis and characterization of Gd2O3: Er3+, Yb3+ doped with Mg2+, Li+ ions-effect on the photoluminescence and biological applications

Izabela Kaminska et al.

Summary: Nanoparticles with efficient upconverting luminescence were synthesized, with a notable increase in red luminescence intensity for 2.5% Mg2+ doping. X-ray analysis showed that the largest crystallite size at 2.5% Mg concentration contributed to the enhancement of luminescence intensity, while the addition of Li+ ions decreased the crystallite size.

NANOTECHNOLOGY (2021)

添加到收藏夹

Review Computer Science, Artificial Intelligence

A review and experimental analysis of active learning over crowdsourced data

Burcu Sayin et al.

Summary: This paper reviews existing active learning approaches and tests them on crowdsourced datasets for hybrid human-machine classification. The study identifies three categories of state-of-the-art active learning methods based on predefined queries for data sampling. Empirical evidence shows that the performance of active learning approaches is influenced by various factors in hybrid classification contexts, such as data noise level, label fusion technique, and task characteristics. Challenges and potential directions for designing active learning strategies for hybrid classification problems are also discussed.

ARTIFICIAL INTELLIGENCE REVIEW (2021)

添加到收藏夹

Article Materials Science, Ceramics

The gadolinium effect on crystallization behavior and luminescence of β-NaYF4:Yb,Er phase

Marina Vukovic et al.

INTERNATIONAL JOURNAL OF APPLIED CERAMIC TECHNOLOGY (2020)

添加到收藏夹

Article Physics, Applied

YVO4:Eu3+ nanopowders: multi-mode temperature sensing technique

D. Sevic et al.

JOURNAL OF PHYSICS D-APPLIED PHYSICS (2020)

添加到收藏夹

Article Spectroscopy

Laser-induced breakdown spectroscopy assisted by machine learning for olive oils classification: The effect of the experimental parameters

Elli Bellou et al.

SPECTROCHIMICA ACTA PART B-ATOMIC SPECTROSCOPY (2020)

添加到收藏夹

Article Engineering, Electrical & Electronic

Effects of temperature on luminescent properties of Gd2O3:Er, Yb nanophosphor

D. Sevic et al.

OPTICAL AND QUANTUM ELECTRONICS (2020)

添加到收藏夹

Article Nanoscience & Nanotechnology

Use of Machine Learning with Temporal Photoluminescence Signals from CdTe Quantum Dots for Temperature Measurement in Microfluidic Devices

Charles Lewis et al.

ACS APPLIED NANO MATERIALS (2020)

添加到收藏夹

Article Chemistry, Analytical

Deep learning networks for the recognition and quantitation of surface-enhanced Raman spectroscopy

Shizhuang Weng et al.

ANALYST (2020)

添加到收藏夹

Article Multidisciplinary Sciences

Towards calibration-invariant spectroscopy using deep learning

M. Chatzidakis et al.

SCIENTIFIC REPORTS (2019)

添加到收藏夹

Article Biochemical Research Methods

The Parallel Factor Analysis of Beer Fluorescence

Tatjana Dramicanin et al.

JOURNAL OF FLUORESCENCE (2019)

添加到收藏夹

Article Instruments & Instrumentation

Computer vision system and near-infrared spectroscopy for identification and classification of chicken with wooden breast, and physicochemical and technological characterization

Bruna Caroline Geronimo et al.

INFRARED PHYSICS & TECHNOLOGY (2019)

添加到收藏夹

Article Optics

Effects of temperature and pressure on luminescent properties of Sr2CeO4:Eu3+ nanophosphor

A. Vlasic et al.

JOURNAL OF LUMINESCENCE (2018)

添加到收藏夹

Article Instruments & Instrumentation

Classification of Chicken Parts Using a Portable Near-Infrared (NIR) Spectrophotometer and Machine Learning

Irene Marivel Nolasco Perez et al.

APPLIED SPECTROSCOPY (2018)

添加到收藏夹

Article Biochemical Research Methods

Machine Learning Applied to Near-Infrared Spectra for Chicken Meat Classification

Sylvio Barbon Jr et al.

JOURNAL OF SPECTROSCOPY (2018)

添加到收藏夹

Article Chemistry, Applied

Fluorescence spectroscopy and principal component analysis of soy protein hydrolysate fractions and the potential to assess their antioxidant capacity characteristics

Sahan A. Ranamukhaarachchi et al.

FOOD CHEMISTRY (2017)

添加到收藏夹

Article Physics, Applied

Luminescence thermometry via the two-dopant intensity ratio of Y2O3: Er3+, Eu3+

Mihailo D. Rabasovic et al.

JOURNAL OF PHYSICS D-APPLIED PHYSICS (2016)

添加到收藏夹

Article Optics

A hybrid calibration-free/artificial neural networks approach to the quantitative analysis of LIBS spectra

Eleonora D'Andrea et al.

APPLIED PHYSICS B-LASERS AND OPTICS (2015)

添加到收藏夹

Article Instruments & Instrumentation

Time resolved laser induced fluorescence measurements: Considerations when using Nd:YAG based system

Maja S. Rabasovic et al.

NUCLEAR INSTRUMENTS & METHODS IN PHYSICS RESEARCH SECTION B-BEAM INTERACTIONS WITH MATERIALS AND ATOMS (2012)

添加到收藏夹

© Peeref 2019-2024. All rights reserved.