@inproceedings{ContiLiuBhogarajuetal.2021, author = {Conti, Fosca and Liu, E and Bhogaraju, Sri Krishna and Lenz, Christoph and Seitz, Roland and Elger, Gordon}, title = {Stress evaluations of silicon nitride chips bonded onto copper substrates via SAC soldering, AuSn soldering, and copper sintering}, booktitle = {2020 26th International Workshop on Thermal Investigations of ICs and Systems (THERMINIC)}, publisher = {IEEE}, address = {Piscataway}, isbn = {978-1-7281-7643-7}, doi = {https://doi.org/10.1109/THERMINIC49743.2020.9420523}, pages = {204 -- 208}, year = {2021}, language = {en} } @inproceedings{KeimTetzlaffElger2020, author = {Keim, Simon and Tetzlaff, Ulrich and Elger, Gordon}, title = {The influence of different-sized Ni micro- and nanopowders on the processing and microstructural properties of Sn-Ag-Cu-solder with low Ag content}, booktitle = {Proceedings: IEEE 70th Electronic Components and Technology Conference, ECTC 2020}, publisher = {IEEE}, address = {Piscataway}, isbn = {978-1-7281-6180-8}, issn = {2377-5726}, doi = {https://doi.org/10.1109/ECTC32862.2020.00312}, pages = {2005 -- 2012}, year = {2020}, language = {en} } @inproceedings{BhogarajuContiElger2020, author = {Bhogaraju, Sri Krishna and Conti, Fosca and Elger, Gordon}, title = {Copper die bonding using copper formate based pastes with α-terpineol, amino-2-propanol and hexylamine as binders}, booktitle = {2020 IEEE 8th Electronics System-Integration Technology Conference (ESTC)}, publisher = {IEEE}, address = {Piscataway}, isbn = {978-1-7281-6293-5}, doi = {https://doi.org/10.1109/ESTC48849.2020.9229801}, year = {2020}, language = {en} } @inproceedings{ContiLiuBhogarajuetal.2020, author = {Conti, Fosca and Liu, E and Bhogaraju, Sri Krishna and Wunderle, Bernhard and Elger, Gordon}, title = {Finite Element simulations and Raman measurements to investigate thermomechanical stress in GaN-LEDs}, booktitle = {2020 IEEE 8th Electronics System-Integration Technology Conference (ESTC)}, publisher = {IEEE}, address = {Piscataway}, isbn = {978-1-7281-6293-5}, doi = {https://doi.org/10.1109/ESTC48849.2020.9229843}, year = {2020}, language = {en} } @inproceedings{KuehnPandeyZippeliusetal.2020, author = {K{\"u}hn, Stephan and Pandey, Amit and Zippelius, Andreas and Schneider, Klaus and Erdogan, H{\"u}seyin and Elger, Gordon}, title = {Analysis of package design of optic modules for automotive cameras to realize reliable image sharpness}, booktitle = {2020 IEEE 8th Electronics System-Integration Technology Conference (ESTC)}, publisher = {IEEE}, address = {Piscataway}, isbn = {978-1-7281-6293-5}, doi = {https://doi.org/10.1109/ESTC48849.2020.9229786}, year = {2020}, language = {en} } @inproceedings{KleinerHeiderHanzletal.2020, author = {Kleiner, Jan and Heider, Alexander and Hanzl, Christian and Komsiyska, Lidiya and Elger, Gordon and Endisch, Christian}, title = {Thermal behavior of an intelligent li-ion cell under vehicle conditions}, booktitle = {Proceedings: IECON 2020 The 46th Annual Conference of the IEEE Industrial Electronics Society}, publisher = {IEEE}, address = {Piscataway}, isbn = {978-1-7281-5414-5}, issn = {2577-1647}, doi = {https://doi.org/10.1109/IECON43393.2020.9254336}, pages = {2081 -- 2086}, year = {2020}, language = {en} } @inproceedings{SchmidBhogarajuElger2021, author = {Schmid, Maximilian and Bhogaraju, Sri Krishna and Elger, Gordon}, title = {Characterization of copper sintered interconnects by transient thermal analysis}, booktitle = {2021 International Conference on Electronics Packaging (ICEP 2021)}, publisher = {IEEE}, address = {Piscataway}, isbn = {978-4-9911-9111-4}, doi = {https://doi.org/10.23919/ICEP51988.2021.9451966}, pages = {71 -- 72}, year = {2021}, language = {en} } @inproceedings{BhogarajuSchmidHufnageletal.2021, author = {Bhogaraju, Sri Krishna and Schmid, Maximilian and Hufnagel, Elias and Conti, Fosca and Kotadia, Hiren R. and Elger, Gordon}, title = {Low temperature and low pressure die-attach bonding of high power light emitting diodes with self reducing copper complex paste}, booktitle = {IEEE 71st Electronic Components and Technology Conference ECTC 2021, Proceedings}, publisher = {IEEE}, address = {Piscataway}, isbn = {978-1-6654-4097-4}, doi = {https://doi.org/10.1109/ECTC32696.2021.00094}, pages = {526 -- 531}, year = {2021}, language = {en} } @inproceedings{PascucciContiBhogarajuetal.2021, author = {Pascucci, Jacopo and Conti, Fosca and Bhogaraju, Sri Krishna and Signorini, Raffaella and Liu, E and Pedron, Danilo and Elger, Gordon}, title = {Micro-Raman to detect stress phenomena in Si-chips bonded onto Cu substrates}, booktitle = {Integrated Optics: Design, Devices, Systems and Applications VI}, editor = {Cheben, Pavel and Čtyrok{\´y}, Jiř{\´i} and Molina-Fern{\´a}ndez, I{\~n}igo}, publisher = {SPIE}, address = {Bellingham}, isbn = {978-1-5106-4385-7}, doi = {https://doi.org/10.1117/12.2576414}, year = {2021}, 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} } @inproceedings{TavakolibastiMeszmerBoettgeretal.2021, author = {Tavakolibasti, M. and Meszmer, P. and B{\"o}ttger, Gunnar and Kettelgerdes, Marcel and Elger, Gordon and Erdogan, H{\"u}seyin and Seshaditya, A. and Wunderle, Bernhard}, title = {Thermo-mechanical-optical coupling within a digital twin development for automotive LiDAR}, booktitle = {2021 22nd International Conference on Thermal, Mechanical and Multi-Physics Simulation and Experiments in Microelectronics and Microsystems (EuroSimE)}, publisher = {IEEE}, address = {Piscataway}, isbn = {978-1-6654-1373-2}, doi = {https://doi.org/10.1109/EuroSimE52062.2021.9410831}, year = {2021}, language = {en} } @inproceedings{LiuContiBhogarajuetal.2021, author = {Liu, E and Conti, Fosca and Bhogaraju, Sri Krishna and Elger, Gordon}, title = {Simulations and experiments to analyze stress phenomena in soldered and sintered interconnections between silicon nitride chips and copper substrates}, booktitle = {2021 22nd International Conference on Thermal, Mechanical and Multi-Physics Simulation and Experiments in Microelectronics and Microsystems (EuroSimE)}, publisher = {IEEE}, address = {Piscataway}, isbn = {978-1-6654-1373-2}, doi = {https://doi.org/10.1109/EuroSimE52062.2021.9410869}, year = {2021}, language = {en} } @inproceedings{AgrawalElger2021, author = {Agrawal, Shiva and Elger, Gordon}, title = {Concept of infrastructure based environment perception for IN2Lab test field for automated driving}, booktitle = {2021 IEEE International Smart Cities Conference (ISC2)}, publisher = {IEEE}, address = {Piscataway}, isbn = {978-1-6654-4919-9}, issn = {2687-8860}, doi = {https://doi.org/10.1109/ISC253183.2021.9562894}, year = {2021}, language = {en} } @article{MokhtariContiBhogarajuetal.2019, author = {Mokhtari, Omid and Conti, Fosca and Bhogaraju, Sri Krishna and Meier, Markus and Schweigart, Helmut and Tetzlaff, Ulrich and Elger, Gordon}, title = {Characterization of tin-oxides and tin-formate crystals obtained from SnAgCu solder alloy under formic acid vapor}, volume = {43}, journal = {New Journal of Chemistry}, number = {26}, publisher = {RSC}, address = {London}, issn = {1369-9261}, doi = {https://doi.org/10.1039/C9NJ02135C}, pages = {10227 -- 10231}, year = {2019}, language = {en} } @article{BhogarajuContiKotadiaetal.2020, author = {Bhogaraju, Sri Krishna and Conti, Fosca and Kotadia, Hiren R. and Keim, Simon and Tetzlaff, Ulrich and Elger, Gordon}, title = {Novel approach to copper sintering using surface enhanced brass micro flakes for microelectronics packaging}, volume = {2020}, pages = {156043}, journal = {Journal of Alloys and Compounds}, number = {844}, publisher = {Elsevier}, address = {Amsterdam}, issn = {1873-4669}, doi = {https://doi.org/10.1016/j.jallcom.2020.156043}, year = {2020}, language = {en} } @article{SchmidBhogarajuLiuetal.2020, author = {Schmid, Maximilian and Bhogaraju, Sri Krishna and Liu, E and Elger, Gordon}, title = {Comparison of Nondestructive Testing Methods for Solder, Sinter, and Adhesive Interconnects in Power and Opto-Electronics}, volume = {10}, pages = {8516}, journal = {Applied Sciences}, number = {23}, publisher = {MDPI}, address = {Basel}, issn = {2076-3417}, doi = {https://doi.org/10.3390/app10238516}, year = {2020}, abstract = {Reliability is one of the major requirements for power and opto-electronic devices across all segments. High operation temperature and/or high thermomechanical stress cause defects and degradation of materials and interconnects, which may lead to malfunctions with costly or even life-threatening consequences. To avoid or at least reduce failures, nondestructive testing (NDT) methods are common within development and production of power and opto-electronics. Currently, the dominating NDT methods are X-ray, scanning acoustic microscopy (SAM), and transient thermal analysis (TTA). However, they have different strengths and weaknesses with respect to materials and mechanical designs. This paper compares these NDT methods for different interconnect technologies, i.e., reflow soldering, adhesive, and sintered interconnection. While X-ray provided adequate results for soldered interfaces, inspection of adhesives and sintered interconnects was not possible. With SAM, evaluation of adhesives and sintered interconnects was also feasible, but quality depended strongly on the sample under test. TTA enabled sufficiently detailed results for all the interconnect applications. Automated TTA equipment, as the in-house developed tester used within this investigation, enabled measurement times compatible with SAM and X-ray. In the investigations, all methods revealed their pros and cons, and their selection has to depend on the sample under tests and the required analysis depth and data details. In the paper, guidelines are formulated for an appropriate decision on the NDT method depending on sample and requirements.}, language = {en} } @article{BhogarajuMokhtariContietal.2020, author = {Bhogaraju, Sri Krishna and Mokhtari, Omid and Conti, Fosca and Elger, Gordon}, title = {Die-attach bonding for high temperature applications using thermal decomposition of copper(II) formate with polyethylene glycol}, volume = {2020}, journal = {Scripta Materialia}, number = {182}, publisher = {Elsevier}, address = {Amsterdam}, issn = {1359-6462}, doi = {https://doi.org/10.1016/j.scriptamat.2020.02.045}, pages = {74 -- 80}, year = {2020}, language = {en} } @article{SchmidBhogarajuHanssetal.2021, author = {Schmid, Maximilian and Bhogaraju, Sri Krishna and Hanss, Alexander and Elger, Gordon}, title = {A new noise-suppression algorithm for transient thermal analysis in semiconductors over pulse superposition}, volume = {70}, pages = {6500409}, journal = {IEEE Transactions on Instrumentation and Measurement}, publisher = {IEEE}, address = {New York}, issn = {0018-9456}, doi = {https://doi.org/10.1109/TIM.2020.3011818}, year = {2021}, language = {en} } @article{KleinerSinghSchmidetal.2020, author = {Kleiner, Jan and Singh, Randeep and Schmid, Michael and Komsiyska, Lidiya and Elger, Gordon and Endisch, Christian}, title = {Influence of heat pipe assisted terminal cooling on the thermal behavior of a large prismatic lithium-ion cell during fast charging in electric vehicles}, volume = {2021}, pages = {116328}, journal = {Applied Thermal Engineering}, number = {188}, publisher = {Elsevier}, address = {Amsterdam}, issn = {1359-4311}, doi = {https://doi.org/10.1016/j.applthermaleng.2020.116328}, year = {2020}, language = {en} } @article{BhogarajuKotadiaContietal.2021, author = {Bhogaraju, Sri Krishna and Kotadia, Hiren R. and Conti, Fosca and Mauser, Armin and Rubenbauer, Thomas and Bruetting, Robert and Schneider-Ramelow, Martin and Elger, Gordon}, title = {Die-attach bonding with etched micro brass metal pigment flakes for high-power electronics packaging}, volume = {3}, journal = {ACS Applied Electronic Materials}, number = {10}, publisher = {ACS Publications}, address = {Washington}, issn = {2637-6113}, doi = {https://doi.org/10.1021/acsaelm.1c00721}, pages = {4587 -- 4603}, year = {2021}, language = {en} } @article{MokhtariContiSacconetal.2021, author = {Mokhtari, Omid and Conti, Fosca and Saccon, Rodolfo and Bhogaraju, Sri Krishna and Elger, Gordon}, title = {Formic acid and formate salts for chemical vapor deposition of copper on glass substrates at atmospheric pressure}, volume = {45}, journal = {New Journal of Chemistry}, number = {43}, publisher = {RSC}, address = {London}, issn = {1369-9261}, doi = {https://doi.org/10.1039/D1NJ02476K}, pages = {20133 -- 20139}, 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} } @article{TheisslerPerezVelazquezKettelgerdesetal.2021, author = {Theissler, Andreas and P{\´e}rez-Vel{\´a}zquez, Judith and Kettelgerdes, Marcel and Elger, Gordon}, title = {Predictive maintenance enabled by machine learning: Use cases and challenges in the automotive industry}, volume = {2021}, pages = {107864}, journal = {Reliability Engineering \& System Safety}, number = {215}, publisher = {Elsevier}, address = {Amsterdam}, issn = {0951-8320}, doi = {https://doi.org/10.1016/j.ress.2021.107864}, year = {2021}, abstract = {Recent developments in maintenance modelling fuelled by data-based approaches such as machine learning (ML), have enabled a broad range of applications. In the automotive industry, ensuring the functional safety over the product life cycle while limiting maintenance costs has become a major challenge. One crucial approach to achieve this, is predictive maintenance (PdM). Since modern vehicles come with an enormous amount of operating data, ML is an ideal candidate for PdM. While PdM and ML for automotive systems have both been covered in numerous review papers, there is no current survey on ML-based PdM for automotive systems. The number of publications in this field is increasing — underlining the need for such a survey. Consequently, we survey and categorize papers and analyse them from an application and ML perspective. Following that, we identify open challenges and discuss possible research directions. We conclude that (a) publicly available data would lead to a boost in research activities, (b) the majority of papers rely on supervised methods requiring labelled data, (c) combining multiple data sources can improve accuracies, (d) the use of deep learning methods will further increase but requires efficient and interpretable methods and the availability of large amounts of (labelled) data.}, language = {en} } @article{DaRosaZanattaCarvalhoLustosadaCostaAntreichetal.2020, author = {Da Rosa Zanatta, Mateus and Carvalho Lustosa da Costa, Joao Paulo and Antreich, Felix and Haardt, Martin and Elger, Gordon and Lopes de Mendon{\c{c}}a, F{\´a}bio L{\´u}cio and de Sousa Junior, Rafael Tim{\´o}teo}, title = {Tensor-based framework with model order selection and high accuracy factor decomposition for time-delay estimation in dynamic multipath scenarios}, volume = {8}, journal = {IEEE Access}, publisher = {IEEE}, address = {New York}, issn = {2169-3536}, doi = {https://doi.org/10.1109/ACCESS.2020.3024597}, pages = {174931 -- 174942}, year = {2020}, abstract = {Global Navigation Satellite Systems (GNSS) are crucial for applications that demand very accurate positioning. Tensor-based time-delay estimation methods, such as CPD-GEVD, DoA/KRF, and SECSI, combined with the GPS3 L1C signal, are capable of, significantly, mitigating the positioning degradation caused by multipath components. However, even though these schemes require an estimated model order, they assume that the number of multipath components is constant. In GNSS applications, the number of multipath components is time-varying in dynamic scenarios. Thus, in this paper, we propose a tensor-based framework with model order selection and high accuracy factor decomposition for time-delay estimation in dynamic multipath scenarios. Our proposed approach exploits the estimates of the model order for each slice by grouping the data tensor slices into sub-tensors to provide high accuracy factor decomposition. We further enhance the proposed approach by incorporating the tensor-based Multiple Denoising (MuDe).}, language = {en} } @article{LiuContiBhogarajuetal.2020, author = {Liu, E and Conti, Fosca and Bhogaraju, Sri Krishna and Signorini, Raffaella and Pedron, Danilo and Wunderle, Bernhard and Elger, Gordon}, title = {Thermomechanical stress in GaN-LEDs soldered onto Cu substrates studied using finite element method and Raman spectroscopy}, volume = {51}, journal = {Journal of Raman Spectroscopy}, number = {10}, publisher = {Wiley}, address = {Chichester}, issn = {1097-4555}, doi = {https://doi.org/10.1002/jrs.5947}, pages = {2083 -- 2094}, year = {2020}, abstract = {Local thermomechanical stress can cause failures in semiconductor packages during long-time operation under harsh environmental conditions. This study helps to explain the packaging-induced stress in blue GaN-LEDs soldered onto copper substrates using AuSn alloy as lead-free interconnect material. Based on the finite element method, a virtual prototype is developed to simulate the thermomechanical behavior and stress in the LED and in the complete LED/AuSn/Cu assembly considering plastic and viscoplastic strain. The investigations were performed by varying the temperature between -50°C and 180°C. To validate the model, the simulation results are compared to experimental data collected with Raman spectroscopy. Studies of the urn:x-wiley:03770486:media:jrs5947:jrs5947-math-0003 phonon mode of GaN semiconductor are elaborated to understand the induced thermomechanical stress. The model enables evaluation of the stress in the interfaces of the assembly, which otherwise cannot be accessed by measurements. It serves to predict how assemblies would perform, before committing resources to build a physical prototype.}, language = {en} } @article{KleinerKomsiyskaElgeretal.2019, author = {Kleiner, Jan and Komsiyska, Lidiya and Elger, Gordon and Endisch, Christian}, title = {Thermal modelling of a prismatic lithium-ion cell in a battery electric vehicle environment}, volume = {13}, pages = {62}, journal = {Energies}, subtitle = {influences of the experimental validation setup}, number = {1}, publisher = {MDPI}, address = {Basel}, issn = {1996-1073}, doi = {https://doi.org/10.3390/en13010062}, year = {2019}, abstract = {In electric vehicles with lithium-ion battery systems, the temperature of the battery cells has a great impact on performance, safety, and lifetime. Therefore, developing thermal models of lithium-ion batteries to predict and investigate the temperature development and its impact is crucial. Commonly, models are validated with experimental data to ensure correct model behaviour. However, influences of experimental setups or comprehensive validation concepts are often not considered, especially for the use case of prismatic cells in a battery electric vehicle. In this work, a 3D electro-thermal model is developed and experimentally validated to predict the cell's temperature behaviour for a single prismatic cell under battery electric vehicle (BEV) boundary conditions. One focus is on the development of a single cell's experimental setup and the investigation of the commonly neglected influences of an experimental setup on the cell's thermal behaviour. Furthermore, a detailed validation is performed for the laboratory BEV scenario for spatially resolved temperatures and heat generation. For validation, static and dynamic loads are considered as well as the detected experimental influences. The validated model is used to predict the temperature within the cell in the BEV application for constant current and Worldwide harmonized Light vehicles Test Procedure (WLTP) load profile.}, language = {en} }