Wavelength-Selective Photothermal Infrared Sensors

The book covers the sensing and monitoring of poisonous carbon monoxide pollution in the environment. The sensors covered include semiconducting metal oxides, carbon nanotubes, conducting polymeric thin films, sensors based on colorimetric detection, non-dispersive infrared sensors, electrochemical sensors and photoacoustic detectors.

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A Computational Study on the Role of Parameters for Identification of Thyroid Nodules by Infrared Images (and Comparison with Real Data)

Sensors ◽

10.3390/s21134459 ◽

2021 ◽

Vol 21 (13) ◽

pp. 4459

Author(s):

José R. González ◽

Charbel Damião ◽

Maira Moran ◽

Cristina A. Pantaleão ◽

Rubens A. Cruz ◽

...

Keyword(s):

Heat Transfer ◽

Thyroid Nodules ◽

Numerical Study ◽

Computational Study ◽

Internal Heat ◽

Heat Transfer Process ◽

The Body ◽

Physical Parameters ◽

Infrared Sensors ◽

Wide Range

According to experts and medical literature, healthy thyroids and thyroids containing benign nodules tend to be less inflamed and less active than those with malignant nodules. It seems to be a consensus that malignant nodules have more blood veins and more blood circulation. This may be related to the maintenance of the nodule’s heat at a higher level compared with neighboring tissues. If the internal heat modifies the skin radiation, then it could be detected by infrared sensors. The goal of this work is the investigation of the factors that allow this detection, and the possible relation with any pattern referent to nodule malignancy. We aim to consider a wide range of factors, so a great number of numerical simulations of the heat transfer in the region under analysis, based on the Finite Element method, are performed to study the influence of each nodule and patient characteristics on the infrared sensor acquisition. To do so, the protocol for infrared thyroid examination used in our university’s hospital is simulated in the numerical study. This protocol presents two phases. In the first one, the body under observation is in steady state. In the second one, it is submitted to thermal stress (transient state). Both are simulated in order to verify if it is possible (by infrared sensors) to identify different behavior referent to malignant nodules. Moreover, when the simulation indicates possible important aspects, patients with and without similar characteristics are examined to confirm such influences. The results show that the tissues between skin and thyroid, as well as the nodule size, have an influence on superficial temperatures. Other thermal parameters of thyroid nodules show little influence on surface infrared emissions, for instance, those related to the vascularization of the nodule. All details of the physical parameters used in the simulations, characteristics of the real nodules and thermal examinations are publicly available, allowing these simulations to be compared with other types of heat transfer solutions and infrared examination protocols. Among the main contributions of this work, we highlight the simulation of the possible range of parameters, and definition of the simulation approach for mapping the used infrared protocol, promoting the investigation of a possible relation between the heat transfer process and the data obtained by infrared acquisitions.

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Indirect light absorption model for highly strained silicon infrared sensors

Journal of Applied Physics ◽

10.1063/5.0057350 ◽

2021 ◽

Vol 130 (5) ◽

pp. 055105

Author(s):

Nicolas Roisin ◽

Guillaume Brunin ◽

Gian-Marco Rignanese ◽

Denis Flandre ◽

Jean-Pierre Raskin

Keyword(s):

Light Absorption ◽

Strained Silicon ◽

Absorption Model ◽

Infrared Sensors ◽

Highly Strained

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Dual functionality metamaterial enables ultra-compact, highly sensitive uncooled infrared sensor

Nanophotonics ◽

10.1515/nanoph-2020-0607 ◽

2021 ◽

Vol 10 (4) ◽

pp. 1337-1346

Author(s):

Jin Tao ◽

Zhongzhu Liang ◽

Guang Zeng ◽

Dejia Meng ◽

David R. Smith ◽

...

Keyword(s):

High Sensitivity ◽

Metamaterial Absorber ◽

Bulk Acoustic Wave ◽

Infrared Sensors ◽

Bulk Acoustic Wave Resonator ◽

Wave Resonator ◽

Highly Sensitive ◽

Film Bulk ◽

Perfect Metamaterial Absorber ◽

High Absorption

Abstract Cointegration and coupling a perfect metamaterial absorber (PMA) together with a film bulk acoustic wave resonator (FBAR) in a monolithic fashion is introduced for the purpose of producing ultracompact uncooled infrared sensors of high sensitivity. An optimized ultrathin multilayer stack was implemented to realize the proposed device. It is experimentally demonstrated that the resonance frequency of the FBAR can be used efficiently as a sensor output as it downshifts linearly with the intensity of the incident infrared irradiation. The resulting sensor also achieves a high absorption of 88% for an infrared spectrum centered at a wavelength of 8.2 μm. The structure is compact and can be easily integrated on a CMOS-compatible chip since both the FBAR and PMA utilize and share the same stack of metal and dielectric layers.

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Hafnium Zirconium Oxide Thin Films for CMOS Compatible Pyroelectric Infrared Sensors

Engineering Proceedings ◽

10.3390/i3s2021dresden-10138 ◽

2021 ◽

Vol 6 (1) ◽

pp. 27

Author(s):

Clemens Mart ◽

Malte Czernohorsky ◽

Kati Kühnel ◽

Wenke Weinreich

Keyword(s):

Thin Films ◽

Lead Zirconate Titanate ◽

Cost Effective ◽

Atomic Layer ◽

Lead Zirconate ◽

Temperature Oscillation ◽

Current Profile ◽

Infrared Sensors ◽

Integrated Sensor ◽

Ferroelectric Hysteresis

Pyroelectric infrared sensors are often based on lead-containing materials, which are harmful to the environment and subject to governmental restrictions. Ferroelectric Hf1−xZrxO2 thin films offer an environmentally friendly alternative. Additionally, CMOS integration allows for integrated sensor circuits, enabling scalable and cost-effective applications. In this work, we demonstrate the deposition of pyroelectric thin films on area-enhanced structured substrates via thermal atomic layer deposition. Scanning electron microscopy indicates a conformal deposition of the pyroelectric film in the holes with a diameter of 500 nm and a depth of 8 μm. By using TiN electrodes and photolithography, capacitor structures are formed, which are contacted via the electrically conductive substrate. Ferroelectric hysteresis measurements indicate a sizable remanent polarization of up to 331 μC cm−2, which corresponds to an area increase of up to 15 by the nanostructured substrate. For pyroelectric analysis, a sinusoidal temperature oscillation is applied to the sample. Simultaneously, the pyroelectric current is monitored. By assessing the phase of the measured current profile, the pyroelectric origin of the signal is confirmed. The devices show sizable pyroelectric coefficients of −475 μC m−2 K−1, which is larger than that of lead zirconate titanate (PZT). Based on the experimental evidence, we propose Hf1−xZrxO2 as a promising material for future pyroelectric applications.

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Heterogeneous fairness algorithm based on federated learning in intelligent transportation system

Journal of Computational Methods in Sciences and Engineering ◽

10.3233/jcm-214991 ◽

2021 ◽

pp. 1-9

Author(s):

Yue Jiang ◽

Gaochao Xu ◽

Zhiyi Fang ◽

Shinan Song ◽

Bingbing Li

Keyword(s):

Intelligent Transportation System ◽

Influence Factor ◽

Learning Algorithm ◽

Intelligent Transportation ◽

Transportation System ◽

Massive Data ◽

Infrared Sensors ◽

Distributed Sensors ◽

Average Accuracy ◽

Global Fairness

With the development of the Intelligent Transportation System, various distributed sensors (including GPS, radar, infrared sensors) process massive data and make decisions for emergencies. Federated learning is a new distributed machine learning paradigm, in which system heterogeneity is the difficulty of fairness design. This paper designs a system heterogeneous fair federated learning algorithm (SHFF). SHFF introduces the equipment influence factor I into the optimization target and dynamically adjusts the equipment proportion with other performance. By changing the global fairness parameter θ, the algorithm can control fairness according to the actual needs. Experimental results show that, compared with the popular q-FedAvg algorithm, the SHFF algorithm proposed in this paper improves the average accuracy of the Worst 10% by 26% and reduces the variance by 61%.

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Night-Time Vehicle Sensing in Far Infrared Image with Deep Learning

Journal of Sensors ◽

10.1155/2016/3403451 ◽

2016 ◽

Vol 2016 ◽

pp. 1-8 ◽

Cited By ~ 11

Author(s):

Hai Wang ◽

Yingfeng Cai ◽

Xiaobo Chen ◽

Long Chen

Keyword(s):

Detection Rate ◽

False Positive Rate ◽

Infrared Image ◽

Far Infrared ◽

Night Vision ◽

Infrared Sensors ◽

Night Time ◽

Detection Rates ◽

Positive Rate ◽

And Performance

The use of night vision systems in vehicles is becoming increasingly common. Several approaches using infrared sensors have been proposed in the literature to detect vehicles in far infrared (FIR) images. However, these systems still have low vehicle detection rates and performance could be improved. This paper presents a novel method to detect vehicles using a far infrared automotive sensor. Firstly, vehicle candidates are generated using a constant threshold from the infrared frame. Contours are then generated by using a local adaptive threshold based on maximum distance, which decreases the number of processing regions for classification and reduces the false positive rate. Finally, vehicle candidates are verified using a deep belief network (DBN) based classifier. The detection rate is 93.9% which is achieved on a database of 5000 images and video streams. This result is approximately a 2.5% improvement on previously reported methods and the false detection rate is also the lowest among them.

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