Reference-Free Material Characterisation of Objects Based on Terahertz Ellipsometry

Friederich, B.; Damyanov, D.; Balzer, Jan C.; Schultze, Thorsten

doi:10.1109/access.2020.3029355

Cited by 5 publications

(2 citation statements)

References 35 publications

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“…This will reduce the resolution gap between conventional imaging based on focusing optics and terahertz near-field microscopy. Furthermore, the method can be combined with terahertz ellipsometry to determine reference-free material parameters from the images [27]. Additionally, the use of neural networks could enable a classification of the measured material [28].…”

Section: Discussionmentioning

confidence: 99%

3D THz-TDS SAR Imaging by an Inverse Synthetic Cylindrical Aperture

et al. 2023

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Terahertz time-domain spectroscopy (THz-TDS) is a promising tool for high-resolution 3D imaging of objects due to the high center frequency and bandwidth compared to microwave systems. In addition, terahertz waves have a higher penetration depth than visible or near-infrared radiation. Typically, optics are used to focus the terahertz radiation onto an object under test. This limits the imaging capability in the axial dimension to the depth of field and limits simple imaging of complex surfaces. In this work, we adapt a backpropagation algorithm from synthetic aperture radar (SAR) imaging to reconstruct highresolution 3D images from time-domain traces acquired with a lensless THz-TDS system. For this purpose, an inverse cylindrical aperture is used and an equation that describes the maximum achievable resolution as a function of the beam pattern, the bandwidth, and the length of the synthetic aperture is derived. The calculated resolution is 960 µm for the linear dimension of the aperture and 75 µm for the rotationally symmetric dimension of the cylindrical aperture for a bandwidth of 2 THz. The resolving power is verified by measurements on metallic and dielectric objects. In the future, this method can be used for non-destructive testing of objects with complex shaped surfaces and internal structures.INDEX TERMS Synthetic aperture radar, terahertz time-domain spectroscopy, lensless terahertz imaging, radar migration algorithms.

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Section: Discussionmentioning

confidence: 99%

3D THz-TDS SAR Imaging by an Inverse Synthetic Cylindrical Aperture

et al. 2023

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“…Reflections from the backside of the sample can be filtered in the time-domain. Also, a reference free material characterization can be carried out using an ellipsometry measurement setup [29]. As the presented approach is capable of a classification in a certain thickness range, a training with more thicknesses leads possibly to a well-trained network capable of classifying all materials within the trained range.…”

Section: Discussionmentioning

confidence: 99%

Material Classification for Terahertz Images Based on Neural Networks

Kubiczek

Balzer

2022

IEEE Access

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Terahertz time-domain spectroscopy enables the extraction of electrical properties from materials. An extraction of the complex permittivity can be carried out with measurements in transmission or reflection geometry enabling the identification of materials. To perform an exact identification, the sample thickness and the angle of incidence of the terahertz radiation must be known. However, when those parameters are unknown and additionally the materials show strong absorbances, a precise differentiation between materials is challenging. A promising approach is the use of a neural network for automated material classification of terahertz images from different materials. Here, we show that a trained neural network can differentiate between 16 3D printed dielectric materials with a high accuracy of 98 % from measurements taken in transmission mode. As the constitution of the dataset has a big impact on the accuracy, various data preparations were investigated as well as the number of traces needed for achieving a well-trained network was determined. Finally, the trained neural network was evaluated with different sample thicknesses, revealing the huge impact of the materials absorbance on the extrapolation ability. This approach can be used in security application to classify harmful substances as well as for the automated generation of material maps.

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Refractive Index Resolved Imaging Enabled by Terahertz Time-Domain Spectroscopy Ellipsometry

Alibeigloo,

Kubiczek,

Aqlan

et al. 2024

J Infrared Milli Terahz Waves

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Material characterization in the terahertz range is an interesting topic of research due to its great applications in material science, health monitoring, and security applications. Advances in terahertz generation, detection, and data acquisition have contributed to improved bandwidth, signal power, and signal-to-noise ratio. This enables advanced material characterization methods such as ellipsometry, which has been little explored in the terahertz frequency range, yet. Here, we introduce a comparison between material characterization with terahertz time-domain spectroscopy in transmission geometry and ellipsometry reflection geometry. Terahertz ellipsometry images were taken, showing spatially resolved refractive index estimation in the far field and higher image quality compared to single-polarization imaging.

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Reference-Free Material Characterisation of Objects Based on Terahertz Ellipsometry

Cited by 5 publications

References 35 publications

3D THz-TDS SAR Imaging by an Inverse Synthetic Cylindrical Aperture

3D THz-TDS SAR Imaging by an Inverse Synthetic Cylindrical Aperture

Material Classification for Terahertz Images Based on Neural Networks

Refractive Index Resolved Imaging Enabled by Terahertz Time-Domain Spectroscopy Ellipsometry

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