TY - JOUR A1 - Schmid, Maximilian A1 - Bhogaraju, Sri Krishna A1 - Liu, E A1 - Elger, Gordon T1 - Comparison of Nondestructive Testing Methods for Solder, Sinter, and Adhesive Interconnects in Power and Opto-Electronics JF - Applied Sciences N2 - 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. UR - https://doi.org/10.3390/app10238516 KW - reliability KW - nondestructive testing KW - power electronics KW - X-ray KW - scanning acoustic microscopy KW - transient thermal analysis KW - TTA KW - sintering KW - LED KW - MOSFET Y1 - 2020 UR - https://doi.org/10.3390/app10238516 UR - http://nbn-resolving.de/urn/resolver.pl?urn:nbn:de:bvb:573-12518 SN - 2076-3417 VL - 10 IS - 23 PB - MDPI CY - Basel ER - TY - CHAP A1 - Stenzel, Gerhard A1 - Schmid, Kyrill A1 - Kölle, Michael A1 - Altmann, Philipp A1 - Lingsch-Rosenfeld, Marian A1 - Zorn, Maximilian A1 - Bücher, Tim A1 - Gabor, Thomas A1 - Wirsing, Martin A1 - Belzner, Lenz ED - Steffen, Bernhard T1 - SEGym: Optimizing Large Language Model Assisted Software Engineering Agents with Reinforcement Learning T2 - Bridging the Gap Between AI and Reality, Second International Conference, AISoLA 2024, Crete, Greece, October 30 – November 3, 2024, Proceedings UR - https://doi.org/10.1007/978-3-031-75434-0_8 Y1 - 2024 UR - https://doi.org/10.1007/978-3-031-75434-0_8 SN - 978-3-031-75434-0 SP - 107 EP - 124 PB - Springer CY - Cham ER - TY - CHAP A1 - Bhogaraju, Sri Krishna A1 - Schmid, Maximilian A1 - Hufnagel, Elias A1 - Conti, Fosca A1 - Kotadia, Hiren R. A1 - Elger, Gordon T1 - Low temperature and low pressure die-attach bonding of high power light emitting diodes with self reducing copper complex paste T2 - IEEE 71st Electronic Components and Technology Conference ECTC 2021, Proceedings UR - https://doi.org/10.1109/ECTC32696.2021.00094 KW - low temperature sintering KW - rapid sintering KW - Cu(II) formate KW - reducing binder KW - low pressure sintering KW - high bond strength Y1 - 2021 UR - https://doi.org/10.1109/ECTC32696.2021.00094 SN - 978-1-6654-4097-4 SP - 526 EP - 531 PB - IEEE CY - Piscataway ER - TY - CHAP A1 - Schmid, Maximilian A1 - Bhogaraju, Sri Krishna A1 - Elger, Gordon T1 - Characterization of copper sintered interconnects by transient thermal analysis T2 - 2021 International Conference on Electronics Packaging (ICEP 2021) UR - https://doi.org/10.23919/ICEP51988.2021.9451966 KW - copper sintering KW - transient thermal analysis (TTA) KW - thermal impedance (Zth) KW - non-destructive testing (NDT) KW - scanning acoustic microscopy (SAM) Y1 - 2021 UR - https://doi.org/10.23919/ICEP51988.2021.9451966 SN - 978-4-9911-9111-4 SP - 71 EP - 72 PB - IEEE CY - Piscataway ER - TY - CHAP A1 - Schmid, Maximilian A1 - Bhogaraju, Sri Krishna A1 - Riedel, Andreas A1 - Elger, Gordon T1 - Development of an in-line capable transient thermal analysis equipment for a power module with five half bridges T2 - 2020 26th International Workshop on Thermal Investigations of ICs and Systems (THERMINIC) UR - https://doi.org/10.1109/THERMINIC49743.2020.9420493 KW - MOSFET KW - Power measurement KW - Pulse measurements KW - Current measurement KW - Multichip modules KW - Time measurement KW - Thermal analysis Y1 - 2021 UR - https://doi.org/10.1109/THERMINIC49743.2020.9420493 SN - 978-1-7281-7643-7 SP - 268 EP - 273 PB - IEEE CY - Piscataway ER - TY - CHAP A1 - Liu, E A1 - Schmid, Maximilian A1 - Bhogaraju, Sri Krishna A1 - Elger, Gordon T1 - Advanced location resolved transient thermal analysis T2 - 2020 26th International Workshop on Thermal Investigations of ICs and Systems (THERMINIC) UR - https://doi.org/10.1109/THERMINIC49743.2020.9420538 KW - Temperature measurement KW - Semiconductor device measurement KW - Thermal resistance KW - Thermal conductivity KW - Dielectric measurement KW - Thermal analysis KW - Dielectrics Y1 - 2021 UR - https://doi.org/10.1109/THERMINIC49743.2020.9420538 SN - 978-1-7281-7643-7 SP - 191 EP - 196 PB - IEEE CY - Piscataway ER - TY - JOUR A1 - Schmid, Maximilian A1 - Bhogaraju, Sri Krishna A1 - Hanss, Alexander A1 - Elger, Gordon T1 - A new noise-suppression algorithm for transient thermal analysis in semiconductors over pulse superposition JF - IEEE Transactions on Instrumentation and Measurement UR - https://doi.org/10.1109/TIM.2020.3011818 KW - LED KW - linear time-invariant (LTI) system KW - MOSFET KW - noise suppression KW - reliability KW - semiconductor KW - signal processing KW - thermal impedance (Zth) KW - transient thermal analysis (TTA) Y1 - 2021 UR - https://doi.org/10.1109/TIM.2020.3011818 SN - 0018-9456 VL - 70 PB - IEEE CY - New York ER - TY - CHAP A1 - Zippelius, Andreas A1 - Hanss, Alexander A1 - Liu, E A1 - Schmid, Maximilian A1 - Pérez-Velázquez, Judith A1 - Elger, Gordon T1 - Comparing prediction methods for LED failure measured with Transient Thermal Analysis T2 - 2020 21st International Conference on Thermal, Mechanical and Multi-Physics Simulation and Experiments in Microelectronics and Microsystems (EuroSimE) UR - https://doi.org/10.1109/EuroSimE48426.2020.9152657 KW - Temperature measurement KW - Artificial neural networks KW - Light emitting diodes KW - Aging KW - Current measurement KW - Training KW - Heating systems Y1 - 2020 UR - https://doi.org/10.1109/EuroSimE48426.2020.9152657 SN - 978-1-7281-6049-8 PB - IEEE CY - Piscataway ER - TY - CHAP A1 - Bhogaraju, Sri Krishna A1 - Conti, Fosca A1 - Schmid, Maximilian A1 - Meier, Markus A1 - Schweigart, Helmut A1 - Elger, Gordon T1 - Development of sinter paste with surface modified copper alloy particles for die-attach bonding T2 - ETG-Fachbericht 161, CIPS 2020, 11th International Conference on Integrated Power Electronics Systems Y1 - 2020 UR - https://www.vde-verlag.de/proceedings-de/455225100.html SN - 978-3-8007-5226-3 SN - 978-3-8007-5225-6 N1 - Auch veröffentlicht auf IEEE: https://ieeexplore.ieee.org/document/9097746 SP - 582 EP - 587 PB - VDE Verlag CY - Berlin ER - TY - CHAP A1 - Schmid, Maximilian A1 - Hermann, Joseph A1 - Liu, E A1 - Elger, Gordon T1 - Correlation of Scanning Acoustic Microscopy and Transient Thermal Analysis to Identify Crack Growth in Solder Joints T2 - Proceedings of the Twenty First InterSociety Conference on Thermal and Thermomechanical Phenomena in Electronic Systems: ITherm 2022 UR - https://doi.org/10.1109/iTherm54085.2022.9899664 KW - reliability KW - transient thermal analysis (TTA) KW - scanning acoustic microscopy (SAM) KW - finite element simulation KW - finite element optimization KW - LED KW - solder KW - crack Y1 - 2022 UR - https://doi.org/10.1109/iTherm54085.2022.9899664 SN - 978-1-6654-8503-6 PB - IEEE CY - Piscataway ER - TY - CHAP A1 - Zippelius, Andreas A1 - Strobl, Tobias A1 - Schmid, Maximilian A1 - Hermann, Joseph A1 - Hoffmann, Alwin A1 - Elger, Gordon T1 - Predicting thermal resistance of solder joints based on Scanning Acoustic Microscopy using Artificial Neural Networks T2 - 2022 IEEE 9th Electronics System-Integration Technology Conference (ESTC) UR - https://doi.org/10.1109/ESTC55720.2022.9939465 KW - Solder Joints KW - LED KW - non-destructive testing KW - Machine Learning KW - Scanning Acoustic Microscopy (SAM) KW - Transient Thermal Analysis (TTA), Convolutional Neural Network (CNN) Y1 - 2022 UR - https://doi.org/10.1109/ESTC55720.2022.9939465 SN - 978-1-6654-8947-8 SP - 566 EP - 575 PB - IEEE CY - Piscataway ER - TY - CHAP A1 - Schmid, Maximilian A1 - Hermann, Joseph A1 - Bhogaraju, Sri Krishna A1 - Elger, Gordon T1 - Reliability of SAC Solders under Low and High Stress Conditions T2 - 2022 IEEE 9th Electronics System-Integration Technology Conference (ESTC) UR - https://doi.org/10.1109/ESTC55720.2022.9939394 KW - reliability KW - solder joint cracking KW - SAC solder KW - transient thermal analysis KW - SAM Y1 - 2022 UR - https://doi.org/10.1109/ESTC55720.2022.9939394 SN - 978-1-6654-8947-8 SP - 553 EP - 559 PB - IEEE CY - Piscataway ER - TY - JOUR A1 - Zippelius, Andreas A1 - Hanss, Alexander A1 - Schmid, Maximilian A1 - Pérez-Velázquez, Judith A1 - Elger, Gordon T1 - Reliability analysis and condition monitoring of SAC+ solder joints under high thermomechanical stress conditions using neuronal networks JF - Microelectronics Reliability N2 - 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. UR - https://doi.org/10.1016/j.microrel.2021.114461 KW - Artificial neural networks KW - LSTM KW - Prediction KW - Reliability KW - Solder joints KW - Transient thermal analysis Y1 - 2022 UR - https://doi.org/10.1016/j.microrel.2021.114461 UR - http://nbn-resolving.de/urn/resolver.pl?urn:nbn:de:bvb:573-19719 SN - 0026-2714 VL - 2022 IS - 129 PB - Elsevier CY - Amsterdam ER - TY - CHAP A1 - Bhogaraju, Sri Krishna A1 - Mokhtari, Omid A1 - Pascucci, Jacopo A1 - Hanss, Alexander A1 - Schmid, Maximilian A1 - Conti, Fosca A1 - Elger, Gordon T1 - Hybrid Cu particle paste with surface-modified particles for high temperature electronics packaging T2 - Proceedings 22nd European Microelectronics and Packaging Conference, EMPC UR - https://doi.org/10.23919/EMPC44848.2019.8951887 Y1 - 2020 UR - https://doi.org/10.23919/EMPC44848.2019.8951887 SN - 978-1-7281-6291-1 PB - IEEE CY - Piscataway ER - TY - CHAP A1 - Bhogaraju, Sri Krishna A1 - Schmid, Maximilian A1 - Liu, E A1 - Saccon, Rodolfo A1 - Elger, Gordon A1 - Klassen, Holger A1 - Müller, Klaus A1 - Pirzer, Georg T1 - Low cost copper based sintered interconnect material for optoelectronics packaging T2 - 2022 IEEE 72nd Electronic Components and Technology Conference (ECTC) UR - https://doi.org/10.1109/ECTC51906.2022.00270 KW - Cu sintering KW - flakes KW - PEG600 KW - reliability KW - encapsulation KW - oxidation KW - transient thermal analysis KW - Scanning acoustic microscopy KW - μ-Raman spectroscopy Y1 - 2022 UR - https://doi.org/10.1109/ECTC51906.2022.00270 SN - 978-1-6654-7943-1 SP - 1720 EP - 1725 PB - IEEE CY - Piscataway ER - TY - CHAP A1 - Bhogaraju, Sri Krishna A1 - Schmid, Maximilian A1 - Kotadia, Hiren R. A1 - Conti, Fosca A1 - Elger, Gordon T1 - Highly reliable die-attach bonding with etched brass flakes T2 - 2021 23rd European Microelectronics and Packaging Conference & Exhibition (EMPC): Technical Papers UR - https://doi.org/10.23919/EMPC53418.2021.9584967 KW - sintering KW - etched brass KW - flakes KW - reliability KW - LED KW - die-attach KW - in-situ copper oxide reduction KW - transient thermal analysis Y1 - 2021 UR - https://doi.org/10.23919/EMPC53418.2021.9584967 SN - 978-0-9568086-7-7 PB - IEEE CY - Piscataway ER - TY - CHAP A1 - Hermann, Joseph A1 - Schmid, Maximilian A1 - Elger, Gordon T1 - Crack Growth Prediction in High-Power LEDs from TTA, SAM and Simulated Data T2 - THERMINIC 2022: Proceedings 2022 UR - https://doi.org/10.1109/THERMINIC57263.2022.9950673 KW - reliability KW - transient thermal analysis (TTA) KW - scanning acoustic microscopy (SAM) KW - finite element simulation KW - LED KW - solder KW - crack Y1 - 2022 UR - https://doi.org/10.1109/THERMINIC57263.2022.9950673 SN - 978-1-6654-9229-4 PB - IEEE CY - Piscataway ER - TY - JOUR A1 - Schmid, Maximilian A1 - Zippelius, Andreas A1 - Hanß, Alexander A1 - Böckhorst, Stephan A1 - Elger, Gordon T1 - Investigations on High-Power LEDs and Solder Interconnects in Automotive Application: Part II - Reliability JF - IEEE Transactions on Device and Materials Reliability UR - https://doi.org/10.1109/TDMR.2023.3300355 KW - LED KW - non-destructive testing KW - reliability KW - solder KW - scanning acoustic microscopy (SAM) KW - thermal impedance (Zth) KW - thermal resistant (Rth) KW - X-ray KW - transient thermal analysis (TTA) Y1 - 2023 UR - https://doi.org/10.1109/TDMR.2023.3300355 UR - http://nbn-resolving.de/urn/resolver.pl?urn:nbn:de:bvb:573-39651 SN - 1558-2574 SN - 1530-4388 VL - 23 IS - 3 SP - 419 EP - 429 PB - IEEE CY - New York ER - TY - JOUR A1 - Schmid, Maximilian A1 - Zippelius, Andreas A1 - Hanss, Alexander A1 - Böckhorst, Stephan A1 - Elger, Gordon T1 - Investigations on High-Power LEDs and Solder Interconnects in Automotive Application: Part I - Initial Characterization JF - IEEE Transactions on Device and Materials Reliability N2 - Thermo-mechanical reliability is one major issue in solid-state lighting. Mismatches in the coefficients of thermal expansion (CTE) between high-power LED packages and substrates paired with temperature changes induce mechanical stress. This leads to a thermal degradation of LED modules by crack formation in the solder interconnect and/or delamination in the substrate, which in turn increases junction temperature and thus decreases light output and reduces lifetime. To investigate degradation and understand influence of LED package design and solder material, a reliability study with a total of 1800 samples − segmented in nine LED types and five solder pastes − is performed. First of all, in this paper a state-of-the-art review of high-power LED packages is performed by analyzing and categorizing the packaging technologies. Second, the quality inspection after assembly is realized by transient thermal analysis (TTA), scanning acoustic microscopy (SAM) and X-ray. For TTA, a new method is introduced to separate the thermal resistance of the LED package from solder interconnect and substrate by applying the transient dual interface method (TDI) on samples with different solder interconnect void ratios. Further measurement effort is not required. The datasheet values for thermal resistance are verified and the different LED package types are benchmarked. The void ratio of the solder interconnects is determined by X-ray inspection combined with an algorithm to suppress disruptive internal LED package structures. TTA and TDI revealed that initial thermal performance is independent of solder paste type and that voiding is more critical to smaller LED packages. In addition, lower silver proportion in the paste is found to increase voiding. SAM is less sensitive for initial void detection than X-ray, but it’s applied to monitor crack propagation while aging in combination with TTA. The results of the reliability study, i.e., the crack growth under temperature shock test for the different SAC solders, will be presented in a second independent paper. UR - https://doi.org/10.1109/TDMR.2022.3152590 KW - LED KW - non-destructive testing KW - reliability KW - solder KW - scanning acoustic microscopy (SAM) KW - thermal impedance (Zth) KW - thermal resistant (Rth) KW - transient thermal analysis (TTA) KW - X-ray Y1 - 2022 UR - https://doi.org/10.1109/TDMR.2022.3152590 UR - http://nbn-resolving.de/urn/resolver.pl?urn:nbn:de:bvb:573-28799 SN - 1530-4388 SN - 1558-2574 VL - 22 IS - 2 SP - 175 EP - 186 PB - IEEE CY - New York ER - TY - JOUR A1 - Mohd, Zubair Akhtar A1 - Schmid, Maximilian A1 - Zippelius, Andreas A1 - Elger, Gordon T1 - Solder joint lifetime model using AI framework operating on FEA data JF - Engineering Failure Analysis N2 - The thermo-mechanical reliability of electronic systems is often limited by the crack growth within the solder joints. Addressing this issue requires careful consideration of the design of the package and solder pads. Finite Element Analysis (FEA) is widely used to predict crack growth and to model their lifetime. Traditionally, FEA post-processing methods rely on human expertise to select appropriate regions for evaluating plastic and creep strain at critical locations and correlating these values with experimental data using the Coffin-Manson equation, which predicts fatigue lifetime based on cyclic plastic strain. This study introduces a novel method for FEA post-processing of surface-mounted devices (SMD) on printed circuit boards (PCB) using artificial intelligence. The method transforms the FEA data into a 2D grid map of creep strain values and employs a Convolutional Neural Network (CNN) for automatic feature extraction. Afterwards, a fully connected layer correlates the extracted features with the experimental measured solder joint lifetime, effectively capturing nonlinear relationships. The study focuses on the development of the concept of crack formation in the solder interconnects of ceramic based high-power LED packages used in the automotive industry for headlights. The validated FEA model is based on an extensive data set of 1800 LED packages including seven different ceramic-based LED packages and five different solders. The design of the ceramic LED package covers two-pad and three-pad footprint for soldering and thin film and thick film metallized ceramic carriers. Results show a strong agreement (R2 Score is 99.867 %) between simulations and experimental data for ceramic LED packages. This automatic feature extraction from FEA data sets a new benchmark for improving solder reliability predictions, and it has proved to be better than established methods for lifetime prediction of solder joints. UR - https://doi.org/10.1016/j.engfailanal.2024.109032 Y1 - 2024 UR - https://doi.org/10.1016/j.engfailanal.2024.109032 UR - http://nbn-resolving.de/urn/resolver.pl?urn:nbn:de:bvb:573-53803 SN - 1350-6307 VL - 2025 IS - 167, Part B PB - Elsevier CY - Oxford ER - TY - CHAP A1 - Mohd, Zubair Akhtar A1 - Kreiner, Christian A1 - Schmid, Maximilian A1 - Zippelius, Andreas A1 - Tetzlaff, Ulrich A1 - Elger, Gordon T1 - Fully Connected Neural Network (FCNN) Based Validation Framework for FEA Post Processing to Improve SAC Solder Reliability Analysis T2 - 2024 IEEE 10th Electronics System-Integration Technology Conference (ESTC), Proceedings UR - https://doi.org/10.1109/ESTC60143.2024.10712023 Y1 - 2024 UR - https://doi.org/10.1109/ESTC60143.2024.10712023 SN - 979-8-3503-9036-0 PB - IEEE CY - Piscataway ER - TY - CHAP A1 - Mohd, Zubair Akhtar A1 - Schmid, Maximilian A1 - Zippelius, Andreas A1 - Elger, Gordon T1 - LEDs Lifetime Prediction Modeling: Thermomechanical Simulation for SAC305 and SAC105 T2 - 2024 25th International Conference on Thermal, Mechanical and Multi-Physics Simulation and Experiments in Microelectronics and Microsystems (EuroSimE) UR - https://doi.org/10.1109/EuroSimE60745.2024.10491530 Y1 - 2024 UR - https://doi.org/10.1109/EuroSimE60745.2024.10491530 SN - 979-8-3503-9363-7 PB - IEEE CY - Piscataway ER - TY - JOUR A1 - Mohd, Zubair Akhtar A1 - Schmid, Maximilian A1 - Elger, Gordon T1 - AI-driven point cloud framework for predicting solder joint reliability using 3D FEA data JF - Scientific Reports N2 - Crack propagation in solder joints remains a major challenge impacting the thermo-mechanical reliability of electronic devices, underscoring the importance of optimizing package and solder pad designs. Traditional Finite Element Analysis (FEA) techniques for predicting solder joint lifespan often rely on manual post-processing to identify high-risk regions for plastic strain accumulation. However, this manual process can fail to detect complex and subtle failure mechanisms and purely based on averaging the creep strain and correlating it to lifetime values collected from experiments using Coffin Manson equation. To address these limitations, this study presents an Artificial Intelligence (AI) framework designed for automated 3D FEA post-processing of surface-mounted devices (SMDs) assembled to Printed Circuit Board (PCB). This framework integrates 3D Convolutional Neural Networks (CNNs) and PointNet architectures to automatically extract complex spatial features from 3D FEA data. These learned features are then linked to experimentally measured solder joint lifetimes through fully connected neural network layers, allowing the model to capture complex and nonlinear failure behaviours. The research specifically targets crack development in solder joints of ceramic-based high-power LED packages used in automotive lighting systems. This dataset included variations in two-pad and three-pad configurations, as well as thin and thick film metallized ceramic substrates. Results from the study demonstrate that the PointNet model outperforms the 3D CNN, achieving a high correlation with experimental data (R2 = 99.91%). This AI-driven, automated feature extraction approach significantly improves the accuracy and provide the more reliable models for solder joint lifetime predictions, offering a substantial improvement over traditional method. UR - https://doi.org/10.1038/s41598-025-06902-0 Y1 - 2025 UR - https://doi.org/10.1038/s41598-025-06902-0 UR - http://nbn-resolving.de/urn/resolver.pl?urn:nbn:de:bvb:573-60961 SN - 2045-2322 VL - 15 PB - Springer Nature CY - London ER - TY - INPR A1 - Mohd, Zubair Akhtar A1 - Schmid, Maximilian A1 - Elger, Gordon T1 - AI-Driven Point Cloud Framework for Predicting Solder Joint Reliability using 3D FEA Data T2 - Research Square N2 - Crack propagation in solder joints remains a critical challenge affecting the thermo-mechanical reliability of electronic devices, emphasizing the need for optimized package and solder pad designs. Traditional Finite Element Analysis (FEA) methods for predicting solder joint lifespan rely heavily on manual post-processing, where high-risk regions for plastic strain accumulation are identified. However, these approaches often overlook intricate failure mechanisms, as they primarily average creep strain and correlate it with experimental lifetime data using the Coffin-Manson equation, limiting their predictive accuracy. To overcome these limitations, this study introduces a novel AI-driven framework that automates 3D FEA post-processing for surface-mounted devices (SMDs) connected to printed circuit boards (PCBs). Unlike traditional methods, this framework leverages deep learning architectures—specifically, 3D Convolutional Neural Networks (CNNs) and PointNet—to extract complex spatial features directly from 3D FEA data, eliminating the need for manual interpretation. These learned features are then mapped to experimentally measured solder joint lifetimes through fully connected neural network layers, allowing the model to capture nonlinear failure behaviours that conventional methods fail to recognize. The research focuses on crack propagation in ceramic-based high-power LED packages used in automotive lighting systems, incorporating variations in two-pad and three-pad configurations, as well as thin and thick film metallized ceramic substrates with validated FEA models. Comparative analysis shows that PointNet significantly outperforms 3D CNNs, achieving an exceptionally high correlation with experimental data (R² = 99.99%). This AI-driven automated feature extraction and lifetime prediction approach marks a major advancement over traditional FEA-based methods, offering superior accuracy, reliability, and scalability for predicting solder joint reliability in microelectronics. UR - https://doi.org/10.21203/rs.3.rs-6173485/v1 Y1 - 2025 UR - https://doi.org/10.21203/rs.3.rs-6173485/v1 UR - http://nbn-resolving.de/urn/resolver.pl?urn:nbn:de:bvb:573-58308 SN - 2693-5015 PB - Research Square CY - Durham ER - TY - JOUR A1 - Zippelius, Andreas A1 - Mohd, Zubair Akhtar A1 - Schmid, Maximilian A1 - Elger, Gordon T1 - Comparison of different Input data for the prediction of LED solder joints using Artificial Neural Networks JF - IEEE Transactions on Device and Materials Reliability N2 - Scarcity of raw data is a major issue for applying data driven methods to reliability prediction, so making the best use of what is available is critical. This paper studies how different aspects of measurement data can be used best. Specifically, the reliability of the solder joint of LED packages is predicted based on Transient Thermal Analysis and Scanning Acoustic Microscopy data from a large measurement campaign. The impact of using full temporal information vs measurements at individual datapoints is investigated as well as the benefit of including the SAM data, and different ways of presenting the TTA information, either as a full curve or as expert-selected features. The impact of formatting categorical information of solder and LED package type as one-hot encoding or using embeddings is considered. Finally, the performance for Pass/Fail predictions of the best identified model with a model architecture developed on a similar dataset is compared. We identified the most relevant sources of information for predicting the behavior and the best format for the data, which helps guide the choice for future model architectures. UR - https://doi.org/10.1109/TDMR.2025.3633876 Y1 - 2025 UR - https://doi.org/10.1109/TDMR.2025.3633876 SN - 1558-2574 PB - IEEE CY - New York ER - TY - CHAP A1 - Schmid, Maximilian A1 - Momberg, Marcel A1 - Kettelgerdes, Marcel A1 - Elger, Gordon T1 - Transient thermal analysis for VCSEL Diodes T2 - 2023 29th International Workshop on Thermal Investigations of ICs and Systems (THERMINIC) UR - https://doi.org/10.1109/THERMINIC60375.2023.10325906 Y1 - 2023 UR - https://doi.org/10.1109/THERMINIC60375.2023.10325906 SN - 979-8-3503-1862-3 PB - IEEE CY - Piscataway ER - TY - CHAP A1 - Zippelius, Andreas A1 - Hufnagel, Elias A1 - Shah, Jainam A1 - Schmid, Maximilian A1 - Elger, Gordon T1 - Reliability of High-Power LEDs Under Varying Thermal Aging Conditions T2 - 2025 31st International Workshop on Thermal Investigations of ICs and Systems (THERMINIC) UR - https://doi.org/10.1109/THERMINIC65879.2025.11216869 Y1 - 2025 UR - https://doi.org/10.1109/THERMINIC65879.2025.11216869 SN - 979-8-3315-9486-2 PB - IEEE CY - Piscataway ER - TY - JOUR A1 - Schwan, Hannes A1 - Mohan, Nihesh A1 - Schmid, Maximilian A1 - Saha, Rocky Kumar A1 - Klassen, Holger A1 - Müller, Klaus A1 - Elger, Gordon T1 - Sintering for High Power Optoelectronic Devices JF - Micromachines N2 - Residual-free eutectic Au80Sn20 soldering is still the dominant assembly technology for optoelectronic devices such as high-power lasers, LEDs, and photodiodes. Due to the high cost of gold, alternatives are desirable. This paper investigates the thermal performance of copper-based sintering for optoelectronic submodules on first and second level to obtain thermally efficient thin bondlines. Sintered interconnects obtained by a new particle-free copper ink, based on complexed copper salt, are compared with copper flake and silver nanoparticle sintered interconnects and benchmarked against AuSn solder interconnects. The copper ink is dispensed and predried at 130 °C to facilitate in situ generation of Cu nanoparticles by thermal decomposition of the metal salt before sintering. Submounts are then sintered at 275 °C for 15 min under nitrogen with 30 MPa pressure, forming uniform 2–5 µm copper layers achieving shear strengths above 31 MPa. Unpackaged LEDs are bonded on first level using the copper ink but applying only 10 MPa to avoid damaging the semiconductor dies. Thermal performance is evaluated via transient thermal analysis. Results show that copper ink interfaces approach the performance of thin AuSn joints and match silver interconnects at second level. However, at first level, AuSn and sintered interconnects of commercial silver and copper pastes remained superior due to the relative inhomogeneous thickness of the thin Cu copper layer after predrying, requiring higher bonding pressure to equalize surface inhomogeneities. UR - https://doi.org/10.3390/mi16101164 Y1 - 2025 UR - https://doi.org/10.3390/mi16101164 UR - http://nbn-resolving.de/urn/resolver.pl?urn:nbn:de:bvb:573-64984 SN - 2072-666X VL - 16 IS - 10 PB - MDPI CY - Basel ER - TY - CHAP A1 - Schwan, Hannes A1 - Schmid, Maximilian A1 - Elger, Gordon T1 - Layer Resolved Thermal Impedance Measurement with Laser Stimulated Transient Thermal Analysis of Semiconductor Modules T2 - THERMINIC 2024: Proceedings of 2024, 30th International Workshop on Thermal Investigations of ICs and Systems UR - https://doi.org/10.1109/THERMINIC62015.2024.10732233 Y1 - 2024 UR - https://doi.org/10.1109/THERMINIC62015.2024.10732233 SN - 979-8-3503-8782-7 PB - IEEE CY - Piscataway ER - TY - CHAP A1 - Schwan, Hannes A1 - Schmid, Maximilian A1 - Elger, Gordon T1 - Laser Stimulated Transient Thermal Analysis of Semiconductors T2 - THERMINIC 2022: Proceedings 2022 UR - https://doi.org/10.1109/THERMINIC57263.2022.9950672 KW - transient thermal analysis KW - laser KW - thermal resistance KW - reliability KW - LED Y1 - 2022 UR - https://doi.org/10.1109/THERMINIC57263.2022.9950672 SN - 978-1-6654-9229-4 PB - IEEE CY - Piscataway ER -