CdSe(ZnS) nanocomposite luminescent high temperature sensor

Pugh-Thomas, Devin; Walsh, Brian M.; Gupta, Mool C.

doi:10.1088/0957-4484/22/18/185503

Cited by 59 publications

(45 citation statements)

References 28 publications

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“…29 By making use of non-linear functions such as hyperbolic tangent sigmoids, neural network approaches are particularly efficient in dealing with non-linear aspects of the inverse problem. 30,31 This is an improvement over a simple, standard least squares fit by a sigmoidal function of the spectral feature 32 required to create the non-linear temperature relationship.…”

Section: Introductionmentioning

confidence: 99%

CdSe/ZnS quantum dot fluorescence spectra shape-based thermometry via neural network reconstruction

Munro

Liu

Glorieux

et al. 2016

Journal of Applied Physics

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Articles you may be interested in Fluorescence resonance energy transfer measured by spatial photon migration in CdSe-ZnS quantum dots colloidal systems as a function of concentration Appl. Phys. Lett. 105, 203108 (2014) As a system of interest gets small, due to the influence of the sensor mass and heat leaks through the sensor contacts, thermal characterization by means of contact temperature measurements becomes cumbersome. Non-contact temperature measurement offers a suitable alternative, provided a reliable relationship between the temperature and the detected signal is available. In this work, exploiting the temperature dependence of their fluorescence spectrum, the use of quantum dots as thermomarkers on the surface of a fiber of interest is demonstrated. The performance is assessed of a series of neural networks that use different spectral shape characteristics as inputs (peak-based-peak intensity, peak wavelength; shape-based-integrated intensity, their ratio, full-width half maximum, peak normalized intensity at certain wavelengths, and summation of intensity over several spectral bands) and that yield at their output the fiber temperature in the optically probed area on a spider silk fiber. Starting from neural networks trained on fluorescence spectra acquired in steady state temperature conditions, numerical simulations are performed to assess the quality of the reconstruction of dynamical temperature changes that are photothermally induced by illuminating the fiber with periodically intensitymodulated light. Comparison of the five neural networks investigated to multiple types of curve fits showed that using neural networks trained on a combination of the spectral characteristics improves the accuracy over use of a single independent input, with the greatest accuracy observed for inputs that included both intensity-based measurements (peak intensity) and shape-based measurements (normalized intensity at multiple wavelengths), with an ultimate accuracy of 0.29 K via numerical simulation based on experimental observations. The implications are that quantum dots can be used as a more stable and accurate fluorescence thermometer for solid materials and that use of neural networks for temperature reconstruction improves the accuracy of the measurement. Published by AIP Publishing.

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Section: Introductionmentioning

confidence: 99%

CdSe/ZnS quantum dot fluorescence spectra shape-based thermometry via neural network reconstruction

Munro

Liu

Glorieux

et al. 2016

Journal of Applied Physics

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“…In contrast, above 4 V, the PL intensity decreases monotonically with increasing bias, tracking the decrease in EQE of the QD-LED. The correspondence between the decreasing PL intensities and EQE with applied bias identifies the change in the QD luminescence efficiency to be sufficient to explain the QD-LED roll-off behavior.Reduction of PL efficiency in QD thin films has been previously measured when QDs are heated [8], charged (Auger recombination) [9], or placed under a strong electric field [10,11]. We eliminate temperature effects on the QD PL efficiency, as measurement of the operating temperature of our QD-LEDs with an infrared camera shows a change of no more than a few degrees, which is not sufficient to affect the PL efficiency and explain the roll-off.…”

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confidence: 99%

Origin of Efficiency Roll-Off in Colloidal Quantum-Dot Light-Emitting Diodes

et al. 2013

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We study the origin of efficiency roll-off (also called ''efficiency droop'') in colloidal quantum-dot light-emitting diodes through the comparison of quantum-dot (QD) electroluminescence and photoluminescence. We find that an electric-field-induced decrease in QD luminescence efficiency-and not charge leakage or QD charging (Auger recombination)-is responsible for the roll-off behavior, and use the quantum confined Stark effect to accurately predict the external quantum efficiency roll-off of QD light-emitting diodes. DOI: 10.1103/PhysRevLett.110.217403 PACS numbers: 85.60.Jb, 85.35.Be, 85.60.Bt Quantum-dot light-emitting diodes (QD-LEDs), which capitalize on the excellent color saturation and high photoluminescence efficiency of colloidal QDs, offer the prospect of a new generation of display technologies [1]. However, these devices suffer from decreasing efficiency [measured as the ratio of the number of photons emitted out of the QD-LED to the number of electrons injected into the device, per unit time, known as external quantum efficiency (EQE)] at high current densities. This behavior, termed efficiency roll-off or efficiency droop, is a problem that affects most types of LEDs [2][3][4]. The origin of the efficiency roll-off continues to be a topic of debate and understanding its cause is essential to developing highbrightness, high current density QD-LEDs. In this Letter, we investigate the origins of the roll-off behavior in QD-LEDs by performing simultaneous measurements of electroluminescence (EL) and photoluminescence (PL) intensities of a QD-LED, which pinpoint the cause to be a decrease in QD luminescence efficiency. Comparison of EL and PL spectra reveals that strong electric fields are responsible for the reduced QD luminescence, and the quantum confined Stark effect (QCSE) and transient PL measurements consistently explain the observed phenomena.The device structure investigated was a QD-LED with organic-inorganic hybrid charge transport layers that has recently attracted attention owing to its record high EQE and brightness [2]. The device was fabricated on a glass substrate coated with indium tin oxide and has the structure: ITO ð150nmÞ=ZnO ð50 nmÞ=QDs ð30 nmÞ=4, 4-bis(carbazole-9-yl) biphenyl (CBP) ð100 nmÞ=MoO 3 ð10 nmÞ=Al (100 nm). ZnO was radio-frequency sputtered, QDs were spin-cast out of chloroform, and CBP, MoO 3 , and Al were thermally evaporated. We used CdSe-ZnCdS core-shell QDs with a peak PL wavelength of 610 nm, provided by QD Vision, Inc. Current density and normalized EQE for a typical device are shown in Fig. 1(a). The EQE peaks at 2% for 4 V applied bias and rolls-off by 50% by 8 V. The energy band diagram of the device is shown in the inset and is based on literature values [4][5][6][7].The decrease in EQE at high biases may be a result of either charge carriers leaking out of the QD layer or a reduction in QD luminescence efficiency. To identify which of these two mechanisms dominates, we perform a simultaneous EL-PL experiment and monitor the relative PL efficiency of t...

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“…And the sensitivity shown by the sensor is around 0.14 nm/°C. The wavelength shift can be explained by the fact that heat expands the crystalline of the quantum dots material and causes a change in the band gap [13], which is only decided by the properties of the quantum dots.…”

Section: Nonmagnetic and Magnetic Quantum Dots 80mentioning

confidence: 99%

“…These semiconductor nanoparticles offer several advantages including narrow fluorescence emission, tunable wavelength, relatively high quantum yield, outstanding photo stability as well as flexible photo excitation. It also has been reported that the behavior of the luminescent properties of quantum dots with temperature has suitable characteristics for application as temperature probes [10][11][12][13][14][15]. The luminescence properties, such as the excited state lifetime, emission intensity, and peak wavelength, have been proven to be good indicators of temperature.…”

Section: Introductionmentioning

confidence: 99%

CdTe Quantum Dot Fluorescence Thermometry of Rolling Bearing

Yan¹,

Bai²

2018

Nonmagnetic and Magnetic Quantum Dots

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Temperature is one of the most important parameters affecting the service life and performance of a rolling element bearing component. In this paper, a nonintrusive method is developed to monitor the temperature variation of the inner raceway during bearing operation utilizing CdTe quantum dots as the temperature sensors. The CdTe quantum dots were synthesized and were used in constructing a sensor film by means of layer-bylayer electrostatic self-assembly method on an ultrathin glass slice. The peak wavelength shift of the fluorescence spectrum of the sensor film shows a linear and reversible relationship with temperature, and it is used to sense the temperature of the inner raceway. The resolution of the CdTe optothermal sensor is determined to be 0.14 nm/°C. The temperature measurement of rolling element bearing was conducted on a bearing test rig incorporated with an optical fiber fluorescence spectrum detecting system. To verify the accuracy of the temperature obtained by quantum dots sensor film, a thermocouple was used to test the temperature of the inner raceway right before and after the operation. Results show that the temperature obtained by the CdTe quantum dots film sensor is consistent with that by the thermocouple, with an error typically below 10% or smaller.

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CdSe(ZnS) nanocomposite luminescent high temperature sensor

Cited by 59 publications

References 28 publications

CdSe/ZnS quantum dot fluorescence spectra shape-based thermometry via neural network reconstruction

CdSe/ZnS quantum dot fluorescence spectra shape-based thermometry via neural network reconstruction

Origin of Efficiency Roll-Off in Colloidal Quantum-Dot Light-Emitting Diodes

CdTe Quantum Dot Fluorescence Thermometry of Rolling Bearing

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