hyperspectral imaging electrical materials
214765035
Near infrared hyperspectral imaging based approach for end of life flat monitors recycling
Abstract The technological innovation and the relentless marketing of new electronic products with improved performance generate increasing quantities of Waste from Electrical and Electronic Equipment (WEEE) In this scenario, End Of Life (EOL) flat monitors and screens represent a category generating, as a consequence of the rapid change in technology, an important amount of waste. Considering future estimations, the implementation of an adequate recycling infrastructure is necessary. An efficient, reliable and low cost analytical tool is thus needed to perform detection/control actions in order to assess: i) waste composition and ii) physical chemical attributes of the resulting materials. The knowledge of these information is a requirement to set up and to implement correct recycling actions. In this study, a cascade identification approach, based on Near InfraRed (NIR) HyperSpectral Imaging (HSI) was carried out. More in detail, a four steps classification was designed, implemented and set up in order to recognize different materials occurring in a specific WEEE stream: EOL milled monitors and flat screens. Adopting the proposed approach, different material categories are correctly recognized and classified. Obtained results can be useful not only to set up a quality control system, but also to improve sorting actions in this specific recycling sector.
Autom.
Giuseppe Bonifazi Riccardo Gasbarrone Roberta Palmieri Silvia Serranti
234987217
DEVELOPMENT OF A SELECTION SYSTEM BASED ON HYPERSPECTRAL IMAGING FOR PLASTIC WASTE WITH BROMINATED FLAME RETARDANTS
Brominated flame retardants (BFRs) are used in different types of products such as plastic, textiles and electronic circuits with the aim to increase fire resistance and to avoid or to delay the propagation of accidental combustion. However, high concentrations of bromine in waste from electrical and electronic equipment (WEEE) hinder the possibility of their use as secondary raw materials. Furthermore, the possibility that BFRs can be released during mechanical recycling processes, imposes the need for ad hoc separation processes through an appropriate selection system. In order to adopt solutions based on the circular economy, it is necessary to develop an efficient strategy for selecting plastic waste containing BFRs from waste flow addressed to recycling. In this perspective, the use of a rapid and non destructive technique, such as hyperspectral imaging (HSI) represents a powerful solution for the identification and to perform quality control of plastics waste. The study aims to develop a new methodology based on HSI in the short wave infrared range (SWIR: 1000 2500 nm) coupled with chemometrics and X ray fluorescence analysis in order to discriminate plastic waste with BFRs into two classes (low Br <2000 mg/kg and high Br> 2000 mg/kg) in agreement with the limits recommended by technical specification for WEEE. The promising results achieved suggest that this methodology may be applicable for the separation of plastics containing BFRs in recycling plants.
Ludovica Fiore Giuseppe Bonifazi Pierre Hennebert Silvia Serranti
221745524
Visualizing Polymer Damage Using Hyperspectral Imaging
Silicone rubbers (SIRs) are common industrial materials which are often used for electrical insulation including weather sheds on non ceramic insulators (NCIs) While SIRs are typically resilient to outside environments, aging can damage SIRs' favorable properties such as hydrophobicity and electrical resistance. Detecting SIR aging and damage, however, can be difficult, especially in service. In this study we used hyperspectral imaging (HSI) and previously investigated aging methods as a proof of concept to show how HSI may be used to detect various types of aging damage in different SIR materials. The spectral signature changes in four different SIRs subjected to four different in service aging environments all occurred between 400 650 nm. Therefore, remote sensing of NCIs using HSI could concentrate on bands below 700 nm to successfully detect in service SIR damage.
Polymers
Monika Bleszynski Shaun Mann Maciej Kumosa
215829578
An Efficient Strategy Based on Hyperspectral Imaging for Brominated Plastic Waste Sorting in a Circular Economy Perspective
Plastic is one of the materials mostly used in many industrial sectors, as those of packaging, construction, agriculture, etc. Furthermore, polymers are also extensively used in electrical and electronic equipment (EEE) manufacturing.
Giuseppe Bonifazi Ludovica Fiore Pierre Hennebert Silvia Serranti
235786691
Large Scale Mapping of Moire Superlattices by Hyperspectral Raman Imaging.
Moire superlattices can induce correlated electronic phases in twisted van der Waals materials: strongly correlated quantum phenomena emerge, such as superconductivity and the Mott insulating state. However, moire superlattices produced through artificial stacking can be quite inhomogeneous, which hampers the development of a clear correlation between the moire period and the emerging electrical and optical properties. Here, it is demonstrated in twisted bilayer transition metal dichalcogenides that low frequency Raman scattering can be utilized not only to detect atomic reconstruction, but also to map out the inhomogeneity of the moire lattice over large areas. The method is established based on the finding that both the interlayer breathing mode and moire phonons are highly susceptible to the moire period and provide characteristic fingerprints. Hyperspectral Raman imaging visualizes microscopic domains of a 5deg twisted bilayer sample with an effective twist angle resolution of about 0.1deg. This ambient methodology can be conveniently implemented to characterize and preselect high quality areas of samples for subsequent device fabrication, and for transport and optical experiments.
Advanced materials
Johannes Holler Jonas M Bauer Philipp Parzefall Marten Scheuck Bo Peng Tobias Korn Sebastian Bange John M Lupton Christian Schuller
208040789
Hyperspectral Unmixing Using L2,1 Norm and Total Variation for Material Detection on Earth's Surface
Hyperspectral imaging is often used to determine what components present in a scene of the earth's surface. Each pixel in a hyperspectral image may contain of a pure material or a mixture of multiple materials due to the limitation of spatial resolution. To determine the abundance of each component in a pixel, a process called hyperspectral unmixing was introduced. In hyperspectral unmixing, each pixel in an image is compared to a spectral library to determine material types and their proportion in the pixel. In this study, we construct an algorithm to optimize the hyperspectral unmixing problem using L2,1 norm and Total Variation regularization to reduce reconstruction error. Specifically, our research aims to improve the unmixing results by applying L2,1 norm to impose collaborative sparsity on all pixels in the image and adding Total Variation regularization to improve the smoothness of resulting image. Our experimental results with both synthetic and real hyperspectral data show improvements in terms of lower RMSE and higher SSIM than those of other methods.
2019 16th International Conference on Quality in Research (QIR) International Symposium on Electrical and Computer Engineering
Danan Arya Pradana Icha Fatwasauri Mia Rizkinia
201712032
Application Note 152 Performing Hyperspectral Mapping with AFM DataCube Nanoelectrical Modes
in fields ranging from semiconductors to piezoelectric materials, energy research, and biology. Modes are available to characterize the local conductivity, resistivity, charge, carrier concentration, carrier type, or piezoelectric properties with nanometer scale spatial resolution, and usually require a direct contact between the AFM tip and sample. The data produced have traditionally been in the form of a two dimensional (2D) map, generated in contact mode, with a single electrical data point per XY location. At few, carefully selected locations in this map, electrical ramps or spectra are generated to get a deeper insight in the local electrical properties. This application note introduces a new approach to nanoelectrical imaging that goes beyond a 2D map, creating an entire electrical data cube and correlated nanomechanical data cube while operating at normal imaging speeds. This approach has the added benefit that it avoids contact mode imaging, thus extending electrical measurements to soft and fragile samples and improving measurement consistency through increased tip lifetime. Moreover, this is a general approach that is applicable to most nanoelectrical modes and applications. The more complete data set contains new information and enables functional imaging on complex samples as shown in examples of barrier height mapping in heterogeneous metal oxides, semiconductor carrier profiling, piezoelectric domain switching dynamics, and Li ion cathode characterization. Application Note #152 Performing Hyperspectral Mapping with AFM DataCube Nanoelectrical Modes
174804813
Study on Detection Method of Composite Insulator Ageing Based on Hyperspectral Technology
Thanks to excellent hydrophobic and low cost, silicone rubber composite insulators have been widely used in power systems in recent years. The silicone rubber composite insulator is a high molecular polymer, the main chain is a Si O bond. With the increase of working years, The properties of silicone rubber materials will also change, resulting in powdering, Hydrophobic loss, material embrittlement and so on. At present, the detection methods of composite insulator ageing are mainly divided into direct and indirect measurement methods. The direct methods include voltage measurement, electric field measurement, leakage current method and so on. The indirect methods include Fourier transform infrared spectroscopy, ultraviolet imaging, X ray imaging and so on. However, there are many defects in the above methods. The direct method requires the operation by boarding pole, the indirect method is complicated, and the efficiency is low. Therefore, finding a non contact, fast and non damaging ageing detection method is of great value for maintaining stable operation of the power system and ensuring national economic security. Under the action of long term corona discharge, the internal organic polymer's chemical bonds will be destroyed and then generate a large amount of free radicals, causing the material properties of the material to change. The change of the material will absorb and generate electromagnetic waves of different wavelength bands. Therefore, the ageing state of the composite insulator detected by hyperspectral have become a possibility. In order to study a new method for ageing detection of composite insulators based on hyperspectral technology, get the ageing silicone rubber composite insulation by conducting corona ageing experiments in the laboratory. The experiment uses the multi needle plate electrode system recommended by the CIGRED1.14 working group of the International Large Power Grid Conference. The silicone rubber composite insulator's size is set to $80\times 80\times 3\mathbf{mm} and the ageing time was set to 50h, 100h, 150h, 200h, 250h, 300h, respectively. Taken out and then place the simple in a dry and clean environment for 24 hours, finally imaging sample with a hyperspectral imaging system to obtain a surface spectral reflectance intensity of a total of 256 bands of the silicone rubber insulator in the range of 400nm to 900nm. Black and white correction of the acquired spectral data to obtain a relative spectral reflectance with a relative value in the range of 0 1. The collected spectral line information is analyzed to establish a response mechanism between the spectral line and different ageing times. After obtaining the spectral data of the sample, extract the band number which can best reflect the ageing state of composite insulator. Using the hyperspectral image processing software to enhance the single band grayscale image at the extracted band number, and an enhancement process is performed to obtain a visualization of the highlight distribution of the surface change of the insulator. According to the final result, the hyperspectral image of the sample at different ageing time has obvious difference. As the ageing time increases, the spectral curve of the silicone rubber insulating material shows a decrease in reflectance in the near infrared band. The hyperspectral line has a peak at 750 nm, and the peak height increases with the ageing time, the reflectivity decreases. The band that can highly reflect the surface change of the composite insulator is concentrated in the range of 600 nm 900 nm bands. By analyzing the spectral information of the insulator collected by hyperspectral technology, the researcher can obtain the ageing state of the composite insulator.
2019 2nd International Conference on Electrical Materials and Power Equipment (ICEMPE)
Runming Gao Xueqin Zhang Yujun Guo Chao Fan Yan Qiu Yuansheng Li Guangning Wu
210879788
Applications for compressed ultrafast photography to biological imaging and sensing
Compressed ultrafast photography (CUP) is a new imaging technique which incorporates the high speed imaging capabilities of a streak camera with principles from compressed sensing to allow for single shot, ultrafast imaging of optical phenomena at up to 100 billion frames per second1. While this technique has primarily been utilized to observe physical phenomena, it has broad ranging application to biological imaging including fluorescence lifetime microscopy, and single shot hyperspectral imaging2. Additionally, similar optical systems can be used to for streak camera microscopy (SCM) enabling the resolution of sub microsecond changes in cellular membrane potential in response to electrical stimulation3. Here, we present several applications for CUP based imaging and spectroscopy as a novel tool to enable more rapid biological imaging and sensing.
Micro Nano Materials, Devices, and Applications
Joel N Bixler Allen Keister Zachary N Coker Bennett L Ibey
210993398
Thermal analysis of semiconductor devices and materials Why should I not trust a thermal simulation
Semiconductor device temperature is challenging to measure; often IR thermography or electrical measurements are used which do not have a high enough spatial resolution for most of the current semiconductor technology to detect sub micron size hot spots. Thermal simulation is often therefore used to predict peak device temperature. Limitations of thermal simulations are highlighted. Latest developments in the actual measurement of semiconductor device temperature with sub micron spatial resolution including Raman Thermography, High Spatial Resolution Hyperspectral Quantum Rod Thermal Imaging, Thermal Atomic Force Microscopy, and thermoreflectance are detailed, which enable validation of thermal simulations.
2019 IEEE BiCMOS and Compound semiconductor Integrated Circuits and Technology Symposium (BCICTS)
Martin Kuball James W Pomeroy Filip Gucmann Bahar Oner