Dual luminescent arrays sensor fabricated by inkjet-printing of pressure- and temperature-sensitive paints

Kameya, Tomohiro; Matsuda, Yu; Egami, Yasuhiro; Yamaguchi, Hiroki; Niimi, Tomohide

doi:10.1016/j.snb.2013.08.011

Cited by 51 publications

(14 citation statements)

References 22 publications

(39 reference statements)

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“…416 Dual luminescent arrays sensors were also fabricated by inkjet-printing of pressure-sensitive and temperature-sensitive paints. 562 This dual sensor consists of discrete dot arrays of a PSP and a TSP and has been developed for a precise measurement of barometric pressure on the solid surface of aircraft models. The PSP and TSP luminophores are spatially isolated from each other so that there is no interaction between the two luminophores.…”

Section: Multiple Sensingmentioning

confidence: 99%

Optical methods for sensing and imaging oxygen: materials, spectroscopies and applications

2014

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We review the current state of optical methods for sensing oxygen. These have become powerful alternatives to electrochemical detection and in the process of replacing the Clark electrode in many fields. The article (with 694 references) is divided into main sections on direct spectroscopic sensing of oxygen, on absorptiometric and luminescent probes, on polymeric matrices and supports, on additives and related materials, on spectroscopic schemes for read-out and imaging, and on sensing formats (such as waveguide sensing, sensor arrays, multiple sensors and nanosensors). We finally discuss future trends and applications and summarize the properties of the most often used indicator probes and polymers. The ESI† (with 385 references) gives a selection of specific applications of such sensors in medicine, biology, marine and geosciences, intracellular sensing, aerodynamics, industry and biotechnology, among others.

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Section: Multiple Sensingmentioning

confidence: 99%

Optical methods for sensing and imaging oxygen: materials, spectroscopies and applications

2014

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“…The typical approaches to multiple sensing are based on either the use of a single luminescence indicator (luminophore), in which the luminescence is sensitive to more than one physical quantity, or the use of several luminophores, one for each quantity, embedded in a substrate and placed in close physical proximity [ 1 , 2 , 3 , 4 , 5 , 6 , 7 , 8 , 9 ]. To be able to determine each quantity separately, it may be necessary to determine more than one optical property (e.g., absorption spectrum, emission spectrum, luminescence intensity, decay time).…”

Section: Introductionmentioning

confidence: 99%

Dual Oxygen and Temperature Luminescence Learning Sensor with Parallel Inference

Venturini

Michelucci

Baumgärtner

2020

Sensors

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A well-known approach to the optical measure of oxygen is based on the quenching of luminescence by molecular oxygen. The main challenge for this measuring method is the determination of an accurate mathematical model for the sensor response. The reason is the dependence of the sensor signal from multiple parameters (like oxygen concentration and temperature), which are cross interfering in a sensor-specific way. The common solution is to measure the different parameters separately, for example, with different sensors. Then, an approximate model is developed where these effects are parametrized ad hoc. In this work, we describe a new approach for the development of a learning sensor with parallel inference that overcomes all these difficulties. With this approach we show how to generate automatically and autonomously a very large dataset of measurements and how to use it for the training of the proposed neural-network-based signal processing. Furthermore, we demonstrate how the sensor exploits the cross-sensitivity of multiple parameters to extract them from a single set of optical measurements without any a priori mathematical model with unprecedented accuracy. Finally, we propose a completely new metric to characterize the performance of neural-network-based sensors, the Error Limited Accuracy. In general, the methods described here are not limited to oxygen and temperature sensing. They can be similarly applied for the sensing with multiple luminophores, whenever the underlying mathematical model is not known or too complex.

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“…The protype built by the authors in [14] is a luminescence based sensor, that was used to measure at the same time oxygen concentration and temperature. The simultaneous determination of multiple physical quantities (multiple sensing) is known to be a hard problem, and is normally solved by complex measuring processes or by the combination of different sensors in one single device [1,[15][16][17][18][19][20][21][22][23][24][25][26].…”

Section: Ais Prototype For Oxygen Sensingmentioning

confidence: 99%

New Autonomous Intelligent Sensor Design Approach for Multiple Parameter Inference

Michelucci

Venturini

2021

7th International Electronic Conference on Sensors and Applications

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The determination of multiple parameters via luminescence sensing is of great interest for many applications in different fields, like biosensing and biological imaging, medicine, and diagnostics. The typical approach consists in measuring multiple quantities and in applying complex and frequently just approximated mathematical models to characterize the sensor response. The use of machine learning to extract information from measurements in sensors have been tried in several forms before. But one of the problems with the approaches so far, is the difficulty in getting a training dataset that is representative of the measurements done by the sensor. Additionally, extracting multiple parameters from a single measurement has been so far an impossible problem to solve efficiently in luminescence. In this work a new approach is described for building an autonomous intelligent sensor, which is able to produce the training dataset self-sufficiently, use it for training a neural network, and then use the trained model to do inference on measurements done on the same hardware. For the first time the use of machine learning additionally allows to extract two parameters from one single measurement using multitask learning neural network architectures. This is demonstrated here by a dual oxygen concentration and temperature sensor.

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Dual luminescent arrays sensor fabricated by inkjet-printing of pressure- and temperature-sensitive paints

Cited by 51 publications

References 22 publications

Optical methods for sensing and imaging oxygen: materials, spectroscopies and applications

Optical methods for sensing and imaging oxygen: materials, spectroscopies and applications

Dual Oxygen and Temperature Luminescence Learning Sensor with Parallel Inference

New Autonomous Intelligent Sensor Design Approach for Multiple Parameter Inference

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