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Journal Articles

Correlation Study on Voiding in Underfill of Large Quantity Ball Grid Array Chip Using Machine Learning

Calvin Ling, Muhammad Taufik Azahari, Mohamad Aizat Abas, Fei Chong Ng
Journal: Journal of Electronic Packaging
Publisher: ASME
Article Type: Research-Article
J. Electron. Packag. March 2025, 147(1): 011001.
Paper No: EP-22-1076
https://doi.org/10.1115/1.4065077
Published Online: April 5, 2024
View Article titled, Correlation Study on Voiding in Underfill of Large Quantity Ball Grid Array Chip Using Machine Learning
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Topics: Ball-Grid-Array packaging, Computer simulation, Machine learning, Pressure, Solders, Valves, Epoxy adhesives, Epoxy resins, Simulation, Temperature
Journal Articles

Machine Learning Analysis of Autonomous Vehicle Sensors Under Extreme Conditions in Alaska

Jewoo Park, Nhi V. Quach, Yonghwi Kim, Ruey-Hwa Cheng, Michal Jenco, Chenxi Yin, Alex K. Lee, Yoonjin Won
Journal: Journal of Electronic Packaging
Publisher: ASME
Article Type: Technical Briefs
J. Electron. Packag. December 2023, 145(4): 044501.
Paper No: EP-23-1039
https://doi.org/10.1115/1.4063486
Published Online: October 5, 2023
View Article titled, Machine Learning Analysis of Autonomous Vehicle Sensors Under Extreme Conditions in Alaska
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Topics: Autonomous vehicles, Drops, Machine learning, Sensors, Temperature, Vehicles
Journal Articles

Reliability of State-of-Health of the Flexible Li-Ion Batteries Under Various Flexing Conditions and Calendar Aging

Pradeep Lall, Hyesoo Jang
Journal: Journal of Electronic Packaging
Publisher: ASME
Article Type: Research-Article
J. Electron. Packag. March 2023, 145(1): 011108.
Paper No: EP-22-1030
https://doi.org/10.1115/1.4056412
Published Online: December 23, 2022
View Article titled, Reliability of State-of-Health of the Flexible Li-Ion Batteries Under Various Flexing Conditions and Calendar Aging
Open the PDF for Reliability of State-of-Health of the Flexible Li-Ion Batteries Under Various Flexing Conditions and Calendar Aging in another window
Topics: Batteries, Cycles, Lithium-ion batteries, Machine learning, Regression models, Reliability, Stress
Journal Articles

Machine Learning-Based Predictions of Benefits of High Thermal Conductivity Encapsulation Materials for Power Electronics Packaging

Palash V. Acharya, Manojkumar Lokanathan, Abdelhamid Ouroua, Robert Hebner, Shannon Strank, Vaibhav Bahadur
Journal: Journal of Electronic Packaging
Publisher: ASME
Article Type: Research-Article
J. Electron. Packag. December 2021, 143(4): 041109.
Paper No: EP-21-1087
https://doi.org/10.1115/1.4052814
Published Online: November 5, 2021
View Article titled, Machine Learning-Based Predictions of Benefits of High Thermal Conductivity Encapsulation Materials for Power Electronics Packaging
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Topics: Algorithms, Artificial neural networks, Bridges (Structures), Cooling, Heat sinks, Junctions, Machine learning, Machinery, Simulation, Steady state
Includes: Supplementary data