Reliability Assessments and Prediction Methods for Microelectronic Systems
A special issue of Applied Sciences (ISSN 2076-3417). This special issue belongs to the section "Electrical, Electronics and Communications Engineering".
Deadline for manuscript submissions: 20 January 2026 | Viewed by 21
Special Issue Editor
Interests: lead-free soldering; reliability assessment and prediction; numerical simulation; material selection and failure analysis; rheological modelling and characterizaiton
Special Issue Information
Dear Colleagues,
This Special Issue aims to bring together cutting-edge research and advancements in the field of reliability assessment and prediction for microelectronic systems. With the rapid evolution of microelectronics across diverse sectors—including automotive, aerospace, medical, and consumer electronics—ensuring long-term performance and dependability has become increasingly critical. We invite high-quality contributions that address experimental, numerical, theoretical, and review-based approaches to reliability analysis at the device, package, and system levels.
Topics of interest include, but are not limited to, the following: failure mechanisms, accelerated life testing, physics-of-failure models, and statistical reliability analysis. Contributions exploring the integration of artificial intelligence (AI) and machine learning (ML) for predictive reliability, anomaly detection, and lifetime estimation are particularly encouraged, reflecting the latest trend toward data-driven reliability engineering.
This Special Issue also welcomes interdisciplinary studies regarding emerging material reliability and robust design strategies under uncertain conditions. We encourage submissions that provide new insights, propose novel methodologies, or offer comprehensive reviews that advance understanding in this vital area. Through this Special Issue, we aim to provide a comprehensive platform for academics, researchers, and industry professionals to explore innovative solutions and emerging technologies shaping the future of reliable microelectronic systems.
I look forward to receiving your contributions.
Dr. Sabuj Mallik
Guest Editor
Manuscript Submission Information
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Keywords
- microelectronic reliability
- failure mechanisms
- predictive maintenance
- artificial intelligence in reliability
- machine learning
- physics-of-failure
- reliability modeling and simulation
- vibration and fatigue life analysis
- die-level failure mechanisms
- thin-film reliability
- electromigration
- solder joint fatigue
- die-attach and wire bond failures
- underfill delamination
- package-on-package (PoP) reliability
- warpage-induced stress
- thermal cycling reliability
- system-in-package (SiP) degradation
- fault-tolerant architecture
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