@inproceedings{SchmidHermannLiuetal.2022, author = {Schmid, Maximilian and Hermann, Joseph and Liu, E and Elger, Gordon}, title = {Correlation of Scanning Acoustic Microscopy and Transient Thermal Analysis to Identify Crack Growth in Solder Joints}, booktitle = {Proceedings of the Twenty First InterSociety Conference on Thermal and Thermomechanical Phenomena in Electronic Systems: ITherm 2022}, publisher = {IEEE}, address = {Piscataway}, isbn = {978-1-6654-8503-6}, doi = {https://doi.org/10.1109/iTherm54085.2022.9899664}, year = {2022}, language = {en} } @inproceedings{ZippeliusStroblSchmidetal.2022, author = {Zippelius, Andreas and Strobl, Tobias and Schmid, Maximilian and Hermann, Joseph and Hoffmann, Alwin and Elger, Gordon}, title = {Predicting thermal resistance of solder joints based on Scanning Acoustic Microscopy using Artificial Neural Networks}, booktitle = {2022 IEEE 9th Electronics System-Integration Technology Conference (ESTC)}, publisher = {IEEE}, address = {Piscataway}, isbn = {978-1-6654-8947-8}, doi = {https://doi.org/10.1109/ESTC55720.2022.9939465}, pages = {566 -- 575}, year = {2022}, language = {en} } @inproceedings{SchmidHermannBhogarajuetal.2022, author = {Schmid, Maximilian and Hermann, Joseph and Bhogaraju, Sri Krishna and Elger, Gordon}, title = {Reliability of SAC Solders under Low and High Stress Conditions}, booktitle = {2022 IEEE 9th Electronics System-Integration Technology Conference (ESTC)}, publisher = {IEEE}, address = {Piscataway}, isbn = {978-1-6654-8947-8}, doi = {https://doi.org/10.1109/ESTC55720.2022.9939394}, pages = {553 -- 559}, year = {2022}, language = {en} } @inproceedings{LiuBhogarajuLuxetal.2022, author = {Liu, E and Bhogaraju, Sri Krishna and Lux, Kerstin and Elger, Gordon and Mou, Rokeya Mumtahana}, title = {Investigation Of Stress Generated By Interconnection Processes With Micro-Raman Spectroscopy (μRS)}, booktitle = {Proceedings IEEE 72nd Electronic Components and Technology Conference: ECTC 2022}, publisher = {IEEE}, address = {Piscataway}, isbn = {978-1-6654-7943-1}, doi = {https://doi.org/10.1109/ECTC51906.2022.00123}, pages = {739 -- 745}, year = {2022}, language = {en} } @inproceedings{SacconBeninBhogarajuetal.2022, author = {Saccon, Rodolfo and Benin, Alice and Bhogaraju, Sri Krishna and Elger, Gordon}, title = {Effect of binders on the performance of copper sintering pastes}, booktitle = {2022 International Conference on Electronics Packaging (ICEP 2022)}, publisher = {IEEE}, address = {Piscataway (NJ)}, isbn = {978-4-9911911-3-8}, doi = {https://doi.org/10.23919/ICEP55381.2022.9795555}, pages = {71 -- 72}, year = {2022}, language = {en} } @inproceedings{KleinerHeiderKomsiyskaetal.2021, author = {Kleiner, Jan and Heider, Alexander and Komsiyska, Lidiya and Elger, Gordon and Endisch, Christian}, title = {Experimental Study on the Thermal Interactions in Novel Intelligent Lithium-Ion Modules for Electric Vehicles}, booktitle = {Proceedings of the Twentieth InterSociety Conference on Thermal and Thermomechanical Phenomena in Electronic Systems: ITherm 2021}, publisher = {IEEE}, address = {Piscataway}, isbn = {978-1-7281-8539-2}, issn = {2694-2135}, doi = {https://doi.org/10.1109/ITherm51669.2021.9503299}, pages = {556 -- 562}, year = {2021}, language = {en} } @inproceedings{SenelElgerFestag2020, author = {Senel, Numan and Elger, Gordon and Festag, Andreas}, title = {Sensor Time Synchronization in Smart Road Infrastructure}, booktitle = {FISITA Web Congress 2020}, publisher = {FISITA}, address = {Bishops Stortford}, url = {https://www.fisita.com/library/f2020-acm-083}, year = {2020}, language = {en} } @article{ZippeliusHanssSchmidetal.2022, author = {Zippelius, Andreas and Hanss, Alexander and Schmid, Maximilian and P{\´e}rez-Vel{\´a}zquez, Judith and Elger, Gordon}, title = {Reliability analysis and condition monitoring of SAC+ solder joints under high thermomechanical stress conditions using neuronal networks}, volume = {2022}, pages = {114461}, journal = {Microelectronics Reliability}, number = {129}, publisher = {Elsevier}, address = {Amsterdam}, issn = {0026-2714}, doi = {https://doi.org/10.1016/j.microrel.2021.114461}, year = {2022}, abstract = {The thermo-mechanical fatigue of different SAC+ solders is investigated using transient thermal analysis (TTA) and predicted using artificial neural networks (ANN). TTA measures the thermal impedance and allows detection of solder cracks and delamination of material interfaces. LEDs soldered to printed circuit boards using seven different solders were aged within passive air-to-air temperature shock tests with TTA measurements every 50 cycles with the increase of the thermal resistance as failure criterium. A SnAgCuSb solder showed the best performance improvement over the SAC305 reference under the test conditions. In addition to standard evaluation by the cumulative failure-curve and Weibull plot, new approaches for reliability assessment are investigated to assess the reliability of the solder joint of the individual LEDs. A hybrid approach to predict failures in the solder joints of the individual LEDs during accelerated stress testing is set-up which processes the TTA data using artificial neural networks with memory, specifically LSTM, where the memory allows full use of the measurement history. Two ANN approaches, regression and classification, are used. Both approaches are shown to be quite accurate. The greater information gained from the regression approach requires more processing using external knowledge of the problem requirements, whereas the categorical approach can be more directly implemented. The results demonstrate the advantages of integrated approaches for assessment of the remaining useful life of solder joints.}, language = {en} } @inproceedings{HanssSchmidBhogarajuetal.2018, author = {Hanss, Alexander and Schmid, Maximilian and Bhogaraju, Sri Krishna and Conti, Fosca and Elger, Gordon}, title = {Reliability of sintered and soldered high power chip size packages and flip chip LEDs}, booktitle = {ECTC - The 2018 IEEE 68th Electronic Components and Technology Conference: Proceedings}, publisher = {IEEE}, address = {Piscataway}, isbn = {978-1-5386-5000-4}, doi = {https://doi.org/10.1109/ECTC.2018.00312}, pages = {2080 -- 2088}, year = {2018}, language = {en} } @inproceedings{BhogarajuMokhtariPascuccietal.2020, author = {Bhogaraju, Sri Krishna and Mokhtari, Omid and Pascucci, Jacopo and Hanss, Alexander and Schmid, Maximilian and Conti, Fosca and Elger, Gordon}, title = {Hybrid Cu particle paste with surface-modified particles for high temperature electronics packaging}, booktitle = {Proceedings 22nd European Microelectronics and Packaging Conference, EMPC}, publisher = {IEEE}, address = {Piscataway}, isbn = {978-1-7281-6291-1}, doi = {https://doi.org/10.23919/EMPC44848.2019.8951887}, year = {2020}, language = {en} } @article{HanssSchmidLiuetal.2015, author = {Hanss, Alexander and Schmid, Maximilian and Liu, E and Elger, Gordon}, title = {Transient thermal analysis as measurement method for IC package structural integrity}, volume = {24}, pages = {068105}, journal = {Chinese Physics B}, number = {6}, publisher = {IOP Publishing}, address = {Bristol}, issn = {2058-3834}, doi = {https://doi.org/10.1088/1674-1056/24/6/068105}, year = {2015}, language = {en} } @article{HanssElger2018, author = {Hanss, Alexander and Elger, Gordon}, title = {Residual free solder process for fluxless solder pastes}, volume = {30}, journal = {Soldering \& Surface Mount Technology}, number = {2}, publisher = {Emerald}, address = {Bingley}, issn = {0954-0911}, doi = {https://doi.org/10.1108/SSMT-10-2017-0030}, pages = {118 -- 128}, year = {2018}, language = {en} } @inproceedings{HanssSchmidBhogarajuetal.2018, author = {Hanss, Alexander and Schmid, Maximilian and Bhogaraju, Sri Krishna and Conti, Fosca and Elger, Gordon}, title = {Process development and reliability of sintered high power chip size packages and flip chip LEDs}, booktitle = {2018 International Conference on Electronics Packaging and iMAPS All Asia Conference (ICEP-IAAC)}, publisher = {IEEE}, address = {Piscataway}, isbn = {978-4-9902-1885-0}, doi = {https://doi.org/10.23919/ICEP.2018.8374351}, pages = {479 -- 484}, year = {2018}, language = {en} } @inproceedings{BhogarajuHanssSchmidetal.2018, author = {Bhogaraju, Sri Krishna and Hanss, Alexander and Schmid, Maximilian and Elger, Gordon and Conti, Fosca}, title = {Evaluation of silver and copper sintering of first level interconnects for high power LEDs}, booktitle = {2018 7th Electronic System-Integration Technology Conference (ESTC)}, publisher = {IEEE}, address = {Piscataway}, isbn = {978-1-5386-6814-6}, doi = {https://doi.org/10.1109/ESTC.2018.8546499}, year = {2018}, language = {en} } @inproceedings{SchmidElger2018, author = {Schmid, Maximilian and Elger, Gordon}, title = {Measurement of the transient thermal impedance of MOSFETs over the sensitivity of the threshold voltage}, booktitle = {EPE'18 ECCE Europe}, publisher = {IEEE}, address = {Piscataway}, isbn = {978-9-0758-1528-3}, url = {https://ieeexplore.ieee.org/document/8515480}, year = {2018}, language = {en} } @inproceedings{ElgerHanssSchmid2018, author = {Elger, Gordon and Hanss, Alexander and Schmid, Maximilian}, title = {Transient Thermal Analysis as In-Situ Method in Accelerated Stress Tests to Access Package Integrity of LEDs}, booktitle = {2018 24rd International Workshop on Thermal Investigations of ICs and Systems (THERMINIC)}, publisher = {IEEE}, address = {Piscataway}, isbn = {978-1-5386-6759-0}, doi = {https://doi.org/10.1109/THERMINIC.2018.8593278}, year = {2018}, language = {en} } @article{ContiHanssMokhtarietal.2018, author = {Conti, Fosca and Hanss, Alexander and Mokhtari, Omid and Bhogaraju, Sri Krishna and Elger, Gordon}, title = {Formation of tin-based crystals from a SnAgCu alloy under formic acid vapor}, volume = {42}, journal = {New Journal of Chemistry}, number = {23}, publisher = {RSC}, address = {London}, issn = {1369-9261}, doi = {https://doi.org/10.1039/C8NJ04173C}, pages = {19232 -- 19236}, year = {2018}, language = {en} } @inproceedings{HanssSchmidElger2019, author = {Hanss, Alexander and Schmid, Maximilian and Elger, Gordon}, title = {Combined Accelerated Stress Test with In-Situ Thermal Impedance Monitoring to Access LED Reliability}, booktitle = {Proceedings 2018 20th International Conference on Electronic Materials and Packaging (EMAP)}, publisher = {IEEE}, address = {Piscataway}, isbn = {978-1-5386-5642-6}, doi = {https://doi.org/10.1109/EMAP.2018.8660833}, year = {2019}, language = {en} } @inproceedings{ElgerBibergerMeieretal.2018, author = {Elger, Gordon and Biberger, M. and Meier, M. and Schweigart, Helmut and Schneider, Klaus and Erdogan, H{\"u}seyin}, title = {Technische Sauberkeit von Radarbaugruppen}, booktitle = {Elektronische Baugruppen und Leiterplatten EBL 2018: Multifunktionale Aufbau- und Verbindungstechnik - Beherrschung der Vielfalt}, publisher = {DVS Media GmbH}, address = {D{\"u}sseldorf}, isbn = {978-3-96144-026-9}, url = {https://www.dvs-media.eu/de/buecher/dvs-berichte/3644/elektronische-baugruppen-und-leiterplatten-ebl-2018}, pages = {339 -- 349}, year = {2018}, language = {de} } @inproceedings{BhogarajuSchmidLiuetal.2022, author = {Bhogaraju, Sri Krishna and Schmid, Maximilian and Liu, E and Saccon, Rodolfo and Elger, Gordon and Klassen, Holger and M{\"u}ller, Klaus and Pirzer, Georg}, title = {Low cost copper based sintered interconnect material for optoelectronics packaging}, booktitle = {2022 IEEE 72nd Electronic Components and Technology Conference (ECTC)}, publisher = {IEEE}, address = {Piscataway}, isbn = {978-1-6654-7943-1}, doi = {https://doi.org/10.1109/ECTC51906.2022.00270}, pages = {1720 -- 1725}, year = {2022}, language = {en} } @inproceedings{SignoriniPedronContietal.2018, author = {Signorini, Raffaella and Pedron, Danilo and Conti, Fosca and Hanss, Alexander and Bhogaraju, Sri Krishna and Elger, Gordon}, title = {Thermomechanical Stress in GaN LED Soldered on Copper Substrate Evaluated by Raman Measurements and Computer Modelling}, booktitle = {2018 24rd International Workshop on Thermal Investigations of ICs and Systems (THERMINIC)}, publisher = {IEEE}, address = {Piscataway}, isbn = {978-1-5386-6759-0}, doi = {https://doi.org/10.1109/THERMINIC.2018.8593304}, year = {2018}, language = {en} } @article{LiuBhogarajuWunderleetal.2022, author = {Liu, E and Bhogaraju, Sri Krishna and Wunderle, Bernhard and Elger, Gordon}, title = {Investigation of stress relaxation in SAC305 with micro-Raman spectroscopy}, volume = {2022}, pages = {114664}, journal = {Microelectronics Reliability}, number = {138}, publisher = {Elsevier}, address = {Amsterdam}, issn = {0026-2714}, doi = {https://doi.org/10.1016/j.microrel.2022.114664}, year = {2022}, language = {en} } @inproceedings{MohanBhogarajuLysienetal.2021, author = {Mohan, Nihesh and Bhogaraju, Sri Krishna and Lysien, Mateusz and Schneider, Ludovic and Granek, Filip and Lux, Kerstin and Elger, Gordon}, title = {Drop feature optimization for fine trace inkjet printing}, booktitle = {2021 23rd European Microelectronics and Packaging Conference \& Exhibition (EMPC): Technical Papers}, publisher = {IEEE}, address = {Piscataway}, isbn = {978-0-9568086-7-7}, doi = {https://doi.org/10.23919/EMPC53418.2021.9585004}, year = {2021}, language = {en} } @article{KettelgerdesElger2023, author = {Kettelgerdes, Marcel and Elger, Gordon}, title = {In-Field Measurement and Methodology for Modeling and Validation of Precipitation Effects on Solid-State LiDAR Sensors}, volume = {7}, journal = {IEEE Journal of Radio Frequency Identification}, publisher = {Institute of Electrical and Electronics Engineers (IEEE)}, address = {New York}, issn = {2469-7281}, doi = {https://doi.org/10.1109/JRFID.2023.3234999}, pages = {192 -- 202}, year = {2023}, language = {en} } @inproceedings{BhogarajuSchmidKotadiaetal.2021, author = {Bhogaraju, Sri Krishna and Schmid, Maximilian and Kotadia, Hiren R. and Conti, Fosca and Elger, Gordon}, title = {Highly reliable die-attach bonding with etched brass flakes}, booktitle = {2021 23rd European Microelectronics and Packaging Conference \& Exhibition (EMPC): Technical Papers}, publisher = {IEEE}, address = {Piscataway}, isbn = {978-0-9568086-7-7}, doi = {https://doi.org/10.23919/EMPC53418.2021.9584967}, year = {2021}, language = {en} } @inproceedings{SteinbergerBhogarajuElger2023, author = {Steinberger, Fabian and Bhogaraju, Sri Krishna and Elger, Gordon}, title = {Correlation between the characteristics of printed sinter paste and the quality of sintered interconnects through non-destructive analysis techniques}, booktitle = {NordPac 2023 Annual Microelectronics and Packaging Conference and Exhibition: Reviewed Papers}, publisher = {IEEE}, address = {Piscataway}, isbn = {978-91-89821-06-4}, doi = {https://doi.org/10.23919/NordPac58023.2023.10186250}, year = {2023}, language = {en} } @inproceedings{KettelgerdesElger2022, author = {Kettelgerdes, Marcel and Elger, Gordon}, title = {Modeling Methodology and In-field Measurement Setup to Develop Empiric Weather Models for Solid-State LiDAR Sensors}, booktitle = {2022 IEEE 2nd International Conference on Digital Twins and Parallel Intelligence (DTPI)}, publisher = {IEEE}, address = {Piscataway}, isbn = {978-1-6654-9227-0}, doi = {https://doi.org/10.1109/DTPI55838.2022.9998918}, year = {2022}, language = {en} } @inproceedings{TavakolibastiMeszmerKettelgerdesetal.2022, author = {Tavakolibasti, M. and Meszmer, P. and Kettelgerdes, Marcel and B{\"o}ttger, Gunnar and Elger, Gordon and Erdogan, H{\"u}seyin and Seshaditya, A. and Wunderle, Bernhard}, title = {Structural-thermal-optical-performance (STOP) analysis of a lens stack for realization of a digital twin of an automotive LiDAR}, booktitle = {2022 23rd International Conference on Thermal, Mechanical and Multi-Physics Simulation and Experiments in Microelectronics and Microsystems (EuroSimE)}, publisher = {IEEE}, address = {Piscataway, NJ}, isbn = {978-1-6654-5836-8}, doi = {https://doi.org/10.1109/EuroSimE54907.2022.9758897}, year = {2022}, language = {en} } @article{SenelKefferpuetzDoychevaetal.2023, author = {Senel, Numan and Kefferp{\"u}tz, Klaus and Doycheva, Kristina and Elger, Gordon}, title = {Multi-Sensor Data Fusion for Real-Time Multi-Object Tracking}, volume = {11}, pages = {501}, journal = {Processes}, number = {2}, publisher = {MDPI}, address = {Basel}, issn = {2227-9717}, doi = {https://doi.org/10.3390/pr11020501}, year = {2023}, abstract = {Sensor data fusion is essential for environmental perception within smart traffic applications. By using multiple sensors cooperatively, the accuracy and probability of the perception are increased, which is crucial for critical traffic scenarios or under bad weather conditions. In this paper, a modular real-time capable multi-sensor fusion framework is presented and tested to fuse data on the object list level from distributed automotive sensors (cameras, radar, and LiDAR). The modular multi-sensor fusion architecture receives an object list (untracked objects) from each sensor. The fusion framework combines classical data fusion algorithms, as it contains a coordinate transformation module, an object association module (Hungarian algorithm), an object tracking module (unscented Kalman filter), and a movement compensation module. Due to the modular design, the fusion framework is adaptable and does not rely on the number of sensors or their types. Moreover, the method continues to operate because of this adaptable design in case of an individual sensor failure. This is an essential feature for safety-critical applications. The architecture targets environmental perception in challenging time-critical applications. The developed fusion framework is tested using simulation and public domain experimental data. Using the developed framework, sensor fusion is obtained well below 10 milliseconds of computing time using an AMD Ryzen 7 5800H mobile processor and the Python programming language. Furthermore, the object-level multi-sensor approach enables the detection of changes in the extrinsic calibration of the sensors and potential sensor failures. A concept was developed to use the multi-sensor framework to identify sensor malfunctions. This feature will become extremely important in ensuring the functional safety of the sensors for autonomous driving.}, language = {en} } @inproceedings{HermannSchmidElger2022, author = {Hermann, Joseph and Schmid, Maximilian and Elger, Gordon}, title = {Crack Growth Prediction in High-Power LEDs from TTA, SAM and Simulated Data}, booktitle = {THERMINIC 2022: Proceedings 2022}, publisher = {IEEE}, address = {Piscataway}, isbn = {978-1-6654-9229-4}, doi = {https://doi.org/10.1109/THERMINIC57263.2022.9950673}, year = {2022}, language = {en} } @article{AgrawalBhanderiDoychevaetal.2023, author = {Agrawal, Shiva and Bhanderi, Savankumar and Doycheva, Kristina and Elger, Gordon}, title = {Static multi-target-based auto-calibration of RGB cameras, 3D Radar, and 3D Lidar sensors}, volume = {23}, journal = {IEEE Sensors Journal}, number = {18}, publisher = {IEEE}, address = {Piscataway}, issn = {1530-437X}, doi = {https://doi.org/10.1109/JSEN.2023.3300957}, pages = {21493 -- 21505}, year = {2023}, language = {en} } @article{KettelgerdesSarmientoErdoganetal.2024, author = {Kettelgerdes, Marcel and Sarmiento, Nicolas and Erdogan, H{\"u}seyin and Wunderle, Bernhard and Elger, Gordon}, title = {Precise Adverse Weather Characterization by Deep-Learning-Based Noise Processing in Automotive LiDAR Sensors}, volume = {16}, pages = {2407}, journal = {Remote Sensing}, number = {13}, publisher = {MDPI}, address = {Basel}, issn = {2072-4292}, doi = {https://doi.org/10.3390/rs16132407}, year = {2024}, abstract = {With current advances in automated driving, optical sensors like cameras and LiDARs are playing an increasingly important role in modern driver assistance systems. However, these sensors face challenges from adverse weather effects like fog and precipitation, which significantly degrade the sensor performance due to scattering effects in its optical path. Consequently, major efforts are being made to understand, model, and mitigate these effects. In this work, the reverse research question is investigated, demonstrating that these measurement effects can be exploited to predict occurring weather conditions by using state-of-the-art deep learning mechanisms. In order to do so, a variety of models have been developed and trained on a recorded multiseason dataset and benchmarked with respect to performance, model size, and required computational resources, showing that especially modern vision transformers achieve remarkable results in distinguishing up to 15 precipitation classes with an accuracy of 84.41\% and predicting the corresponding precipitation rate with a mean absolute error of less than 0.47 mm/h, solely based on measurement noise. Therefore, this research may contribute to a cost-effective solution for characterizing precipitation with a commercial Flash LiDAR sensor, which can be implemented as a lightweight vehicle software feature to issue advanced driver warnings, adapt driving dynamics, or serve as a data quality measure for adaptive data preprocessing and fusion.}, language = {en} } @article{MohanAhuirTorresBhogarajuetal.2024, author = {Mohan, Nihesh and Ahuir-Torres, Juan Ignacio and Bhogaraju, Sri Krishna and Webler, Ralf and Kotadia, Hiren R. and Erdogan, H{\"u}seyin and Elger, Gordon}, title = {Decomposition mechanism and morphological evolution of in situ realized Cu nanoparticles in Cu complex inks}, volume = {48}, journal = {New Journal of Chemistry}, number = {15}, publisher = {RSC}, address = {London}, issn = {1369-9261}, doi = {https://doi.org/10.1039/D3NJ05185D}, pages = {6796 -- 6808}, year = {2024}, language = {en} } @inproceedings{MohanAhuirTorresBhogarajuetal.2024, author = {Mohan, Nihesh and Ahuir-Torres, Juan Ignacio and Bhogaraju, Sri Krishna and Kotadia, Hiren R. and Elger, Gordon}, title = {Rapid Sintering of Inkjet Printed Cu Complex Inks Using Laser in Air}, booktitle = {2023 24th European Microelectronics and Packaging Conference \& Exhibition (EMPC)}, publisher = {IEEE}, address = {Piscataway}, isbn = {978-0-9568086-9-1}, doi = {https://doi.org/10.23919/EMPC55870.2023.10418323}, year = {2024}, language = {en} } @inproceedings{BhogarajuUgoliniBelponeretal.2024, author = {Bhogaraju, Sri Krishna and Ugolini, Francesco and Belponer, Federico and Greci, Alessio and Elger, Gordon}, title = {Reliability of Copper Sintered Interconnects Under Extreme Thermal Shock Conditions}, booktitle = {2023 24th European Microelectronics and Packaging Conference \& Exhibition (EMPC)}, publisher = {IEEE}, address = {Piscataway}, isbn = {978-0-9568086-9-1}, doi = {https://doi.org/10.23919/EMPC55870.2023.10418348}, year = {2024}, language = {en} } @inproceedings{BhogarajuMohanSteinbergeretal.2024, author = {Bhogaraju, Sri Krishna and Mohan, Nihesh and Steinberger, Fabian and Erdogan, H{\"u}seyin and Hadrava, Philipp and Elger, Gordon}, title = {Novel Low Temperature and Low Pressure Sintering of ADAS Radar Sensor Antenna Stack}, booktitle = {2023 24th European Microelectronics and Packaging Conference \& Exhibition (EMPC)}, publisher = {IEEE}, address = {Piscataway}, isbn = {978-0-9568086-9-1}, doi = {https://doi.org/10.23919/EMPC55870.2023.10418277}, year = {2024}, language = {en} } @inproceedings{AhuirTorresBhogarajuWestetal.2024, author = {Ahuir-Torres, Juan Ignacio and Bhogaraju, Sri Krishna and West, Geoff and Elger, Gordon and Kotadia, Hiren R.}, title = {Understanding Cu Sintering and Its Role on Corrosion Behaviour for High-Temperature Microelectronic Application}, booktitle = {2023 24th European Microelectronics and Packaging Conference \& Exhibition (EMPC)}, publisher = {IEEE}, address = {Piscataway}, isbn = {978-0-9568086-9-1}, doi = {https://doi.org/10.23919/EMPC55870.2023.10418365}, year = {2024}, language = {en} } @article{ElgerBhogarajuSchneiderRamelow2024, author = {Elger, Gordon and Bhogaraju, Sri Krishna and Schneider-Ramelow, Martin}, title = {Hybrid Cu sinter paste for low temperature bonding of bare semiconductors}, volume = {2024}, pages = {136973}, journal = {Materials Letters}, number = {372}, publisher = {Elsevier}, address = {New York}, issn = {1873-4979}, doi = {https://doi.org/10.1016/j.matlet.2024.136973}, year = {2024}, abstract = {A novel hybrid copper paste was developed for low temperature sintering of bare semiconductors. Cu(II) formate (Cu(for)) is complexed in amino-2-propanol (A2P) and added to a paste of etched brass micro flakes. A two-step sintering process is applied: The paste is printed and dried at 120 °C under formic acid (FA) enriched N2 atmosphere (FAN2) for 5 min. Afterwards, bare semiconductors are placed and sintered at 250 °C for 5 min applying a bonding pressure of 20 MPa/10 MPa. By the thermal decomposition of the Cu(for) atomic Cu is released and forms in-situ Cu-nanoparticles. An interconnect is realized with shear strength >100 MPa.}, language = {en} } @inproceedings{HanKefferpuetzElgeretal.2024, author = {Han, Longfei and Kefferp{\"u}tz, Klaus and Elger, Gordon and Beyerer, J{\"u}rgen}, title = {FlexSense: Flexible Infrastructure Sensors for Traffic Perception}, booktitle = {2023 IEEE 26th International Conference on Intelligent Transportation Systems (ITSC)}, publisher = {IEEE}, address = {Piscataway}, isbn = {979-8-3503-9946-2}, doi = {https://doi.org/10.1109/ITSC57777.2023.10422616}, pages = {3810 -- 3816}, year = {2024}, language = {en} } @inproceedings{HanXuKefferpuetzetal.2024, author = {Han, Longfei and Xu, Qiuyu and Kefferp{\"u}tz, Klaus and Lu, Ying and Elger, Gordon and Beyerer, J{\"u}rgen}, title = {Scalable Radar-based Roadside Perception: Self-localization and Occupancy Heat Map for Traffic Analysis}, booktitle = {2024 IEEE Intelligent Vehicles Symposium (IV)}, publisher = {IEEE}, address = {Piscataway}, isbn = {979-8-3503-4881-1}, doi = {https://doi.org/10.1109/iv55156.2024.10588397}, pages = {1651 -- 1657}, year = {2024}, language = {en} } @inproceedings{OlcayMeessElger2024, author = {Olcay, Ertug and Meeß, Henri and Elger, Gordon}, title = {Dynamic Obstacle Avoidance for UAVs using MPC and GP-Based Motion Forecast}, booktitle = {2024 European Control Conference (ECC)}, publisher = {IEEE}, address = {Piscataway}, isbn = {978-3-9071-4410-7}, doi = {https://doi.org/10.23919/ECC64448.2024.10591083}, pages = {1024 -- 1031}, year = {2024}, language = {en} } @inproceedings{ParetBhogarajuBusseetal.2024, author = {Paret, Paul and Bhogaraju, Sri Krishna and Busse, Dirk and Dahlb{\"u}dding, Alexander and Elger, Gordon and Narumanchi, Sreekant}, title = {Thermomechanical Degradation of Sintered Copper under High-Temperature Thermal Shock}, booktitle = {Proceedings: IEEE 74th Electronic Components and Technology Conference, ECTC 2024}, publisher = {IEEE}, address = {Piscataway}, isbn = {979-8-3503-7598-5}, doi = {https://doi.org/10.1109/ECTC51529.2024.00196}, pages = {1219 -- 1224}, year = {2024}, language = {en} } @inproceedings{SteinbergerMohanRaemeretal.2024, author = {Steinberger, Fabian and Mohan, Nihesh and R{\"a}mer, Olaf and Elger, Gordon}, title = {Low temperature die-attach bonding using copper particle free inks}, booktitle = {2024 IEEE 10th Electronics System-Integration Technology Conference (ESTC), Proceedings}, publisher = {IEEE}, address = {Piscataway}, isbn = {979-8-3503-9036-0}, doi = {https://doi.org/10.1109/ESTC60143.2024.10712150}, year = {2024}, language = {en} } @inproceedings{AgrawalSongKohlietal.2022, author = {Agrawal, Shiva and Song, Rui and Kohli, Akhil and Korb, Andreas and Andre, Maximilian and Holzinger, Erik and Elger, Gordon}, title = {Concept of Smart Infrastructure for Connected Vehicle Assist and Traffic Flow Optimization}, booktitle = {Proceedings of the 8th International Conference on Vehicle Technology and Intelligent Transport Systems}, editor = {Ploeg, Jeroen and Helfert, Markus and Berns, Karsten and Gusikhin, Oleg}, publisher = {SciTePress}, address = {Set{\´u}bal}, isbn = {978-989-758-573-9}, issn = {2184-495X}, doi = {https://doi.org/10.5220/0011068800003191}, pages = {360 -- 367}, year = {2022}, abstract = {The smart infrastructure units can play a vital role to develop smart cities of the future and in assisting automated vehicles on the road by providing extended perception and timely warnings to avoid accidents. This paper focuses on the development of such an infrastructure unit, that is specifically designed for a pedestrian crossing junction. It can control traffic lights at the junction by real-time environment perception through its sensors and can optimize the flow of vehicles and passing vulnerable road users (VRUs). Moreover, it can assist on-road vehicles by providing real-time information and critical warnings via a v2x module. This paper further describes different use-cases of the work, all major hardware components involved in the development of smart infrastructure unit, referred to as an edge, different sensor fusion approaches using the camera, radar, and lidar mounted on the edge for environment perception, various modes of communication including v2x, system design}, language = {en} } @inproceedings{StreckHerschelWallrathetal.2022, author = {Streck, Egor and Herschel, Reinhold and Wallrath, Patrick and Sunderam, M. and Elger, Gordon}, title = {Comparison of Two Different Radar Concepts for Pedestrian Protection on Bus Stops}, booktitle = {Proceedings of the 11th International Conference on Sensor Networks}, editor = {Prasad, Venkatesha and Pesch, Dirk and Ansari, Nirwan and Benavente-Peces, C{\´e}sar}, publisher = {SciTePress}, address = {Set{\´u}bal}, isbn = {978-989-758-551-7}, issn = {2184-4380}, doi = {https://doi.org/10.5220/0010777100003118}, pages = {89 -- 96}, year = {2022}, abstract = {This paper presents the joint work from the "HORIS" project, with a focus on pedestrian detection at bus-stops by radar sensors mounted in the infrastructure to support future autonomous driving and protecting pedestrians in critical situations. Two sensor systems are investigated and evaluated. The first based on single radar sensor phase-sensitive raw data analysis and the second based on sensor data fusion of cluster data with two radar sensors using neural networks to predict the position of pedestrians.}, language = {en} } @inproceedings{ContiLuxBhogarajuetal.2021, author = {Conti, Fosca and Lux, Kerstin and Bhogaraju, Sri Krishna and Liu, E and Lenz, Christoph and Seitz, Roland and Elger, Gordon}, title = {Raman spectroscopy to investigate gallium nitride light emitting diodes after assembling onto copper substrates}, booktitle = {Optical Sensors 2021}, editor = {Baldini, Francesco and Homola, Jiri and Lieberman, Robert A.}, publisher = {SPIE}, address = {Bellingham}, isbn = {978-1-5106-4379-6}, doi = {https://doi.org/10.1117/12.2591947}, year = {2021}, language = {en} } @article{BhanderiAgrawalElger2025, author = {Bhanderi, Savankumar and Agrawal, Shiva and Elger, Gordon}, title = {Deep segmentation of 3+1D radar point cloud for real-time roadside traffic user detection}, volume = {15}, pages = {38489}, journal = {Scientific Reports}, publisher = {Springer Nature}, address = {London}, issn = {2045-2322}, doi = {https://doi.org/10.1038/s41598-025-23019-6}, year = {2025}, abstract = {Smart cities rely on intelligent infrastructure to enhance road safety, optimize traffic flow, and enable vehicle-to-infrastructure (V2I) communication. A key component of such infrastructure is an efficient and real-time perception system that accurately detects diverse traffic participants. Among various sensing modalities, automotive radar is one of the best choices due to its robust performance in adverse weather and low-light conditions. However, due to low spatial resolution, traditional clustering-based approaches for radar object detection often struggle with vulnerable road user detection and nearby object separation. Hence, this paper proposes a deep learning-based D radar point cloud clustering methodology tailored for smart infrastructure-based perception applications. This approach first performs semantic segmentation of the radar point cloud, followed by instance segmentation to generate well-formed clusters with class labels using a deep neural network. It also detects single-point objects that conventional methods often miss. The described approach is developed and experimented using a smart infrastructure-based sensor setup and it performs segmentation of the point cloud in real-time. Experimental results demonstrate 95.35\% F1-macro score for semantic segmentation and 91.03\% mean average precision (mAP) at an intersection over union (IoU) threshold of 0.5 for instance segmentation. Further, the complete pipeline operates at 43.61 frames per second with a memory requirement of less than 0.7 MB on the edge device (Nvidia Jetson AGX Orin).}, language = {en} } @unpublished{BhanderiAgrawalElger2025, author = {Bhanderi, Savankumar and Agrawal, Shiva and Elger, Gordon}, title = {Deep Segmentation of 3+1D Radar Point Cloud for Real-Time Roadside Traffic User Detection}, titleParent = {Research Square}, publisher = {Research Square}, address = {Durham}, doi = {https://doi.org/10.21203/rs.3.rs-7222130/v1}, year = {2025}, abstract = {Smart cities rely on intelligent infrastructure to enhance road safety, optimize traffic flow, and enable vehicle-to-infrastructure (V2I) communication. A key component of such infrastructure is an efficient and real-time perception system that accurately detects diverse traffic participants. Among various sensing modalities, automotive radar is one of the best choices due to its robust performance in adverse weather and low-light conditions. However, due to low spatial resolution, traditional clustering-based approaches for radar object detection often struggle with vulnerable road user detection and nearby object separation. Hence, this paper proposes a deep learning-based 3+1D radar point cloud clustering methodology tailored for smart infrastructure-based perception applications. This approach first performs semantic segmentation of the radar point cloud, followed by instance segmentation to generate well-formed clusters with class labels using a deep neural network. It also detects single-point objects that conventional methods often miss. The described approach is developed and experimented using a smart infrastructure-based sensor setup and it performs segmentation of the point cloud in real-time. Experimental results demonstrate 95.35\% F1-macro score for semantic segmentation and 91.03\% mean average precision (mAP) at an intersection over union (IoU) threshold of 0.5 for instance segmentation. Further, the complete pipeline operates at 43.61 frames per second with a memory requirement of less than 0.7 MB on the edge device (Nvidia Jetson AGX Orin).}, language = {en} } @article{KleinerHeiderKomsiyskaetal.2021, author = {Kleiner, Jan and Heider, Alexander and Komsiyska, Lidiya and Elger, Gordon and Endisch, Christian}, title = {Thermal behavior of intelligent automotive lithium-ion batteries: Experimental study with switchable cells and reconfigurable modules}, volume = {2021}, pages = {103274}, journal = {Journal of Energy Storage}, number = {44, Part A}, publisher = {Elsevier}, address = {Amsterdam}, issn = {2352-1538}, doi = {https://doi.org/10.1016/j.est.2021.103274}, year = {2021}, language = {en} } @article{KleinerLechermannKomsiyskaetal.2021, author = {Kleiner, Jan and Lechermann, Lorenz and Komsiyska, Lidiya and Elger, Gordon and Endisch, Christian}, title = {Thermal behavior of intelligent automotive lithium-ion batteries}, volume = {2021}, pages = {102686}, journal = {Journal of energy storage}, subtitle = {operating strategies for adaptive thermal balancing by reconfiguration}, number = {40}, publisher = {Elsevier}, address = {Amsterdam}, issn = {2352-1538}, doi = {https://doi.org/10.1016/j.est.2021.102686}, year = {2021}, language = {en} }