Principal Investigator: Prof. Dr. Jan C. Balzer, UDE

Achieved results and methods

In the 2^nd phase of MARIE, M05 was divided into three work packages. The first working package of M05 picked up the results from the 1^st phase and extended it towards central questions and scenarios related to fire detection and fire damage assessment. In the frame of WP1 methods for the material characterization and imaging were investigated for the implementation in WP2. The goals of WP1 were (i) to image arbitrary dielectric objects as precisely as possible and (ii) to estimate material parameters, in particular the relative dielectric permittivity, especially for material classification. Regarding imaging, methods for THz-based 3D imaging were investigated that allow shape determination with a precision of up to 50 µm. Various scanning methods based on linear [1], cylindrical [2] and spherical aperture were studied. Fig. 1 shows the fine resolution reconstruction of a 20-sided dice by an inverse spherical aperture. The imaging methods were applied to data from different measuring devices from M05 and the project partners M01, C07, including THz-TDS systems, Frequency Modulated Continuous Wave (FMCW) radar systems and Vector Network Analyzers (VNA) [3], [4].

The advantages and disadvantages of focused and unfocused measurements were investigated. In co-operation with M01, the imaging of hidden objects without a-priori information was investigated using high-power THz-TDS systems [5]. In order not to limit the investigations to the fire protection engineering application envisaged in M05, and thus also to make it available to the MARIE project partner, the geometries investigated were kept as general as possible. The use of canonical geometries also has the advantage that the actual geometry can be determined with maximum precision.

Initially, ellipsometric methods were investigated for material characterization, but new promising ANN-based methods were also explored [6]. According to our results, these have the advantage of being able to distinguish even small material differences that are difficult to distinguish with classical THz-based ellipsometry. The ANN-method was investigated using 3D printed materials, as these are very well specified and are much less subject to natural variations than, for example, wood. A total of 16 different polymers were examined. For each polymer, 4800 measurements were carried out, of which 4000 were used for training and the remaining 800 measurements were used for validation. This resulted in a classification accuracy of over 98%. The resulting material map can be seen in Fig. 2. To further improve the method and extend it to natural materials such as wood, this fundamental research will be continued in the 3^rd.

WP2 focuses on the characterization of internal structures of e.g. partially burnt or one-sided wet objects. This research question is also based on the vision of using THz-supported methods in fire protection engineering for the in-situ and non-destructive assessment of charred beams, e.g. a roof truss after a fire. THz-based approaches for measuring the layer thickness of foils have been known for many years. However, natural materials and in particular the layer thickness measurement on composites without

sharp material separation (e.g. partially burnt objects) place high demands on the measuring principle, as (i) the layer transitions can be geometrically very complex (i.e. nonuniform surface) and (ii) the contrast between the materials is small or in the worst case a continuous transition.

The thickness measurement of the charred layer of a wooden beam is the final estimate of a series of previously necessary parameter estimates, including the precise determination of the surface structure and the estimation of the dielectric properties of the objects. Therefore, within the 2^nd phase of MARIE, focused and unfocused THz-based imaging techniques were investigated, which are addressed in the previous section WP1. These methods were iteratively adapted to the needs in WP2. The inverse synthetic aperture method, in which the scattering information of a divergent THz beam is processed into an image, is promising for the task in WP2. The results with a defined burnt wooden beam are shown in Fig. 3. It can be seen that THz-TDS SAR measurements are feasible to estimate the burning depth in wood as indicated by the red circle in Fig 3a.

Since only smaller fires in their initial phase (approx. 150 kW on average) can be carried out in the fire detection laboratory at the University of Duisburg-Essen, wood samples from a large fire in an old forge (16.11.2022, Mülheim an der Ruhr, Germany) are now being examined.

The vision behind WP3 is the detection of hidden hot spots, with the subsequent aim of detecting fires, e.g. the thermal runaway of Li-ion batteries in freight. This vision was driven by the need to detect battery fires as early as possible, particularly for the aircraft industry and large cargo ships. It is aimed to implement the hardware developed in C08 - highly sensitive passive THz detectors. The hardware prototypes from C08 are currently being implemented in the M05 setup as shown in Fig. 4. To advance the work in M05 in parallel with the hardware development work of C08, a measurement setup with a THz power meter has been realized. The setup provides a hot surface with defined temperature and shape and the possibility of imaging the surface with a THz system and a thermal imaging camera for reference measurements.

The results are promising and show that it is possible to detect hidden hot spots, e.g. through packaging material. The task places great demands on the sensitivity of the THz sensors. Depending on the cardboard packaging, even the carrier structures in the cardboard can cause considerable resonances, which in turn lead to frequency- and polarization-dependent attenuation. One challenge in the scientific evaluation of the results of WP3 to date is the separation between the information obtained from IR radiation and the information from the THz component. It is expected that this challenge will be overcome by using the THz sensors developed in C08. In later use as a fire detection system, this separation will be no longer necessary, and the hardware requirements will therefore be lower.

Most of the current work within the framework of the 2^nd phase is strongly focused on applications in the field of fire detection & engineering. To work on the questions arising in this context, co-operations must be entered into with application-related co-operation partners that cannot be founded within the framework of MARIE. These include logistics companies and fire brigades, for example. As a result, a DFG knowledge transfer project will be applied by the former PI Dr. Schultze by mid-2025, which will take up the results from the 2^nd phase of M05. The 3^rd phase of the M05 project will therefore be led by Prof. Balzer and refocus on fundamental issues as described in the work program. Dr. Schultze works in the group of Prof. Balzer and both have of a long-term track record of scientific cooperation.

Prof. Balzer is an associated member of the SFB since 2018. Since January 2022 his DFG project GZ: BA 6049/5-1 was integrated into the SFB and knowledge gained by this project will be integrated into M05 3^rd phase. The project will end together with the 2^nd phase of MARIE. An important point is here the development of a compact UHRR-THz-TDS system based on Mode-Locked Laser Diodes (MLLD) which will replace the immobile conventional THz-TDS systems which was used throughout the 1^st and 2^nd phase. Besides being more compact, it was also demonstrated that these systems have a higher peak dynamic range than the commercial systems for the same number of averages as shown in Fig. 5a. Further, a record high peak dynamic range for photonic systems of 133 dB with a single shot peak dynamic range of 90 dB was demonstrated [7]. With these systems, a range resolution of less than 10 µm was proven in cooperation with S01 [8]. Additionally, a compact demonstrator was developed in close cooperation with Dr. Kolpatzeck (new PI within C06) which combines the advantage of a mobile system and an increased SNR at the low frequency part of the spectrum.

 Selected project-related publications

1. D. Damyanov, B. Friederich, M. Yahyapour, N. Vieweg, A. Deninger, K. Kolpatzeck, X. Liu, A. Czylwik, T. Schultze, I. Willms, and J. C. Balzer, “High Resolution Lensless Terahertz Imaging and Ranging,” IEEE Access, vol. 7, pp. 147704–147712, 2019, doi: 10.1109/ACCESS.2019.2934582.
2. D. Damyanov, T. Kubiczek, K. Kolpatzeck, A. Czylwik, T. Schultze, and J. C. Balzer, “3D THz-TDS SAR Imaging by an Inverse Synthetic Cylindrical Aperture,” IEEE Access, vol. PP, pp. 1–1, 2023, doi: 10.1109/ACCESS.2023.3240101.
3. D. Damyanov, A. Batra, B. Friederich, T. Kaiser, T. Schultze, and J. C. Balzer, “High-Resolution Long-Range THz Imaging for Tunable Continuous-Wave Systems,” IEEE Access, vol. 8, pp. 151997–152007, 2020, doi: 10.1109/ACCESS.2020.3017821.
4. A. Batra, J. Barowski, D. Damyanov, M. Wiemeler, I. Rolfes, T. Schultze, J. C. Balzer, D. Göhringer, and T. Kaiser, “Short-Range SAR Imaging From GHz to THz Waves,” IEEE Journal of Microwaves, vol. 1, no. 2, pp. 1–12, 2021, doi: 10.1109/JMW.2021.3063343.
5. S. Mansourzadeh, D. Damyanov, T. Vogel, F. Wulf, R. B. Kohlhaas, B. Globisch, T. Schultze, M. Hoffmann, J. C. Balzer, and C. J. Saraceno, “High-Power Lensless THz Imaging of Hidden Objects,” IEEE Access, vol. 9, pp. 6268–6276, 2021, doi: 10.1109/ACCESS.2020.3048781.
6. T. Kubiczek and J. C. Balzer, “Material Classification for Terahertz Images Based on Neural Networks,” IEEE Access, vol. 10, no. July, pp. 88667–88677, 2022, doi: 10.1109/ACCESS.2022.3200473.
7. V. Cherniak, T. Kubiczek, K. Kolpatzeck, and J. C. Balzer, “Laser diode based THz-TDS system with 133 dB peak signal-to-noise ratio at 100 GHz,” Sci Rep, vol. 13, no. 1, p. 13476, Aug. 2023, doi: 10.1038/s41598-023-40634-3.
8. K. Kolpatzeck, X. Liu, L. Häring, J. C. Balzer, and A. Czylwik, “Ultra-high repetition rate terahertz time-domain spectroscopy for micrometer layer thickness measurement,” Sensors, vol. 21, no. 16, 2021, doi: 10.3390/s21165389.
9. J. C. Balzer, C. J. Saraceno, M. Koch, P. Kaurav, U. R. Pfeiffer, W. Withayachumnankul, T. Kürner, A. Stöhr, M. El-Absi, A. Al-Haj Abbas, T. Kaiser, and A. Czylwik, “THz Systems Exploiting Photonics and Communications Technologies,” IEEE Journal of Microwaves, vol. 3, no. 1, pp. 268–288, Jan. 2023, doi: 10.1109/JMW.2022.3228118.
10. X. Liu, L. Schmitt, B. Sievert, J. Lipka, C. Geng, K. Kolpatzeck, D. Erni, A. Rennings, J. C. Balzer, M. Hoffmann, and A. Czylwik, “Terahertz Beam Steering Using a MEMS-Based Reflectarray Configured by a Genetic Algorithm,” IEEE Access, vol. 10, no. June, 2022, doi: 10.1109/ACCESS.2022.3197202