@inproceedings{BaranowskiZychlaKrysztofetal., author = {Baranowski, Kamil and Zychla, Michał and Krysztof, Michał and Ż{\´o}łtowski, Michał and Hausladen, Matthias and Schreiner, Rupert and Kn{\´a}pek, Aleksandr}, title = {Experimenal method for studying electron beams in gaseous environments using a CMOS image sensor}, series = {38th International Vacuum Nanoelectronics Conference (IVNC)}, booktitle = {38th International Vacuum Nanoelectronics Conference (IVNC)}, publisher = {IEEE}, isbn = {979-8-3315-3705-0}, doi = {10.1109/IVNC65669.2025.11120851}, pages = {2}, abstract = {Detecting and analyzing electron beams in atmospheric conditions remains a significant challenge due to scattering and absorption of electrons by gas molecules. In this work, a novel approach using a CMOS image sensor for real-time electron beam detection after its transmission through air is presented. The setup enables visualization of beam divergence, emission profiles, and dynamic behavior under atmospheric pressure. Presented results demonstrate the potential of CMOS image sensor for electron beam analysis in gaseous environment.}, language = {en} } @inproceedings{AllahamBurdaKnapeketal., author = {Allaham, Mohammad M. and Burda, Daniel and Kn{\´a}pek, Alexandr and Krysztof, Michał and Baranowski, Kamil and Hausladen, Matthias and Schreiner, Rupert}, title = {Testing the performance of tungsten-graphite cathodes as MEMS Electron microscope electron source}, series = {38th International Vacuum Nanoelectronics Conference (IVNC)}, booktitle = {38th International Vacuum Nanoelectronics Conference (IVNC)}, publisher = {IEEE}, doi = {10.1109/IVNC65669.2025.11121041}, pages = {2}, abstract = {This work presents preliminary results of the performance testing of exfoliated graphene layers deposited on the nanotip of a tungsten field emission cathode. The obtained tungsten-graphite cathodes were then operated in a 3D-printed MEMS electron microscope testing model for later applications. The results were promising, where a maximum emission current of 50.2 μA was obtained with an extraction voltage of 1 kV and anode voltage of 3 kV.}, language = {en} } @inproceedings{AsgharzadeBartlHausladenetal., author = {Asgharzade, Ali and Bartl, Mathias and Hausladen, Matthias and Chen, Yang and Buchner, Philipp and Edler, Simon and Bachmann, Michael and She, Juncong and Schreiner, Rupert}, title = {Investigation on the influence of internal voltage drops on the emission behavior of silicon field emission arrays using CMOS image sensor}, series = {38th International Vacuum Nanoelectronics Conference (IVNC)}, booktitle = {38th International Vacuum Nanoelectronics Conference (IVNC)}, publisher = {IEEE}, doi = {10.1109/IVNC65669.2025.11120937}, pages = {2}, abstract = {In this paper we report on an improved measurement and analysis method for determining the emission current distribution of field emitter arrays with CMOS sensors. It can also be used for field emission arrays where not all surfaces of the emitters are at the same electrical potential (e.g. for p-doped Si tips, where a strong current saturation occurs). To demonstrate the functionality of this method, a n-doped field emission array was measured using a variable external series resistance. Brightness variations in emission spots were analyzed to re-calculate the known series resistances for comparison. The re-calculated value is in good agreement with the actual value of the resistance. This method offers a quantitative approach to assess internal voltage drop effects on field emission using optical readout}, language = {en} } @article{BuchnerHausladenBartletal., author = {Buchner, Philipp and Hausladen, Matthias and Bartl, Mathias and Bachmann, Michael and Schreiner, Rupert}, title = {High current field emission from Si nanowires on pillar structures}, series = {Journal of Vacuum Science and Technology B: Nanotechnology and Microelectronics}, volume = {42}, journal = {Journal of Vacuum Science and Technology B: Nanotechnology and Microelectronics}, number = {2}, publisher = {AIP}, issn = {2166-2754}, doi = {10.1116/6.0003384}, abstract = {We investigate the influence of the geometry and doping level on the performance of n-type silicon nanowire field emitters on silicon pillar structures. Therefore, multiple cathodes with 50 by 50 pillar arrays (diameter: 5 μm, height: 30 μm, spacing: 50 μm) were fabricated and measured in diode configuration. In the first experiment, we compared two geometry types using the same material. Geometry 1 is black silicon, which is a highly dense surface covering a forest of tightly spaced silicon needles resulting from self-masking during a plasma etching process of single crystal silicon. Geometry 2 are silicon nanowires, which are individual spaced-out nanowires in a crownlike shape resulting from a plasma etching process of single crystal silicon. In the second experiment, we compared two different silicon doping levels [n-type (P), 1-10 and <0.005 Ω cm] for the same geometry. The best performance was achieved with lower doped silicon nanowire samples, emitting 2 mA at an extraction voltage of 1 kV. The geometry/material combination with the best performance was used to assemble an integrated electron source. These electron sources were measured in a triode configuration and reached onset voltages of about 125 V and emission currents of 2.5 mA at extraction voltages of 400 V, while achieving electron transmission rates as high as 85.0\%.}, language = {en} } @inproceedings{SchreinerMulotGauggeletal., author = {Schreiner, Rupert and Mulot, M. and Gauggel, H. P. and Schweizer, H. and Laue, C. K. and Wallenstein, R.}, title = {Dynamic and spectral properties of red DFB lasers}, series = {Technical Digest. Summaries of papers presented at the Conference on Lasers and Electro-Optics. Postconference Technical Digest (IEEE Cat. No.01CH37170) ; Baltimore, May 6 - 11, 2001 (Trends in optics and photonics series ; 56)}, booktitle = {Technical Digest. Summaries of papers presented at the Conference on Lasers and Electro-Optics. Postconference Technical Digest (IEEE Cat. No.01CH37170) ; Baltimore, May 6 - 11, 2001 (Trends in optics and photonics series ; 56)}, publisher = {IEEE}, isbn = {1-55752-662-1}, doi = {10.1109/CLEO.2001.947498}, pages = {81 -- 82}, abstract = {Summary form only given. Narrow linewidth GaInP/AlGaInP DFB lasers are promising light sources for spectroscopy, for optical data storage systems and for plastic optical fiber WDM applications. However, little is known about the dynamic behavior of red DFB lasers. In this paper, we report on the dynamic and spectral properties of those devices. The lasers were first characterized under cw operation at 25/spl deg/C. Threshold currents are /spl sim/14 mA (475 /spl mu/m length) and /spl sim/18 mA (900 /spl mu/m length). The lasers show stable single mode emission at 680 nm with a SMSR better than -25 dB. The spectral linewidth of the 900 /spl mu/m long devices was measured by using a scanning-Fabry-Perot interferometer.}, language = {en} } @article{TanSchreinerHausladenetal., author = {Tan, Jing Jie and Schreiner, Rupert and Hausladen, Matthias and Asgharzade, Ali and Edler, Simon and Bartsch, Julian and Bachmann, Michael and Schels, Andreas and Kwan, Ban-Hoe and Ng, Danny Wee-Kiat and Hum, Yan-Chai}, title = {SiMiC: Context-aware silicon microstructure characterization using attention-based convolutional neural networks for field-emission tip analysis}, series = {Journal of Vacuum Science \& Technology B}, volume = {43}, journal = {Journal of Vacuum Science \& Technology B}, number = {6}, publisher = {AVS}, doi = {10.1116/6.0005068}, abstract = {Accurate characterization of silicon microstructures is essential for advancing microscale fabrication, quality control, and device performance. Traditional analysis using scanning electron microscopy (SEM) often requires labor-intensive, manual evaluation of feature geometry, limiting throughput and reproducibility. In this study, we propose SiMiC: Context-aware Silicon Microstructure Characterization Using Attention-based Convolutional Neural Networks for Field-Emission Tip Analysis. By leveraging deep learning, our approach efficiently extracts morphological features—such as size, shape, and apex curvature—from SEM images, significantly reducing human intervention while improving measurement consistency. A specialized dataset of silicon-based field-emitter tips was developed, and a customized convolutional neural network architecture incorporating attention mechanisms was trained for multiclass microstructure classification and dimensional prediction. Comparative analysis with classical image processing techniques demonstrates that SiMiC achieves high accuracy while maintaining interpretability. The proposed framework establishes a foundation for data-driven microstructure analysis directly linked to field-emission performance, opening avenues for correlating emitter geometry with emission behavior and guiding the design of optimized cold-cathode and SEM electron sources. The related dataset and algorithm repository that could serve as a baseline in this area can be found at https://research.jingjietan.com/?q=SIMIC.}, language = {en} }