Low-temperature solders (melting point below 150°C) are being used in the portable computer industry and will continue to expand into other sectors. This webinar examines three low-temperature solders and compares them with tin-silver-copper solders. Follow the link below for more information on the next Webinar.

• 5/15/2025, 11 am US Eastern Time
  Dr. Michael Osterman
  Thermal Cycle Reliability of Low-Temperature Solder: Register Here

On June 12, Dr. Das will discuss the impact of supply chain disruptions on the reliability practices of organizations, focusing on information management for parts and systems. In this Webinar, Dr. Das will provide examples of policy changes that can impact companies, their impacts on the supply chain, and the practices one should build to protect oneself.  

Register Here

This project analyzes a cutting-edge cooling system concept from the reliability point of view. Concurrently with the project's development, it provides the necessary conceptual design alternatives to ensure practical designs that account for potential failure sites, causes, modes, and mechanisms.

CALCE faculty Dr. Diganta Das is the Principal Investigator for this project, and Prof. Michael Ohadi is leading the overall effort.

The University of Maryland Graduate School has awarded Sahithi Maddipatla the prestigious Outstanding Graduate Assistant Award for 2024–2025. Sahithi was recognized as being among the top 2% of all campus graduate assistants for her exemplary performance and contributions.

Sahithi is pursuing her Ph.D. in Mechanical Engineering under the mentorship of Professor Michael Pecht. Her work at CALCE focuses on failure analysis, testing, prognostics, and health monitoring of lithium-ion batteries.  

Lithium-ion batteries are known to present significant safety risks, particularly in terms of fire hazards and explosions. In 2023, there were approximately 2500 reported incidents involving fires and explosions, resulting in around 100 fatalities and 800 injuries. Warning labels (or marking) of these batteries are essential to ensure safe handling, operation, and disposal, thereby mitigating potential safety risks and preventing accidents. ...

Prognostic models are vital for predictive maintenance, enabling accurate prediction of remaining useful life (RUL) in complex systems. However, balancing model interpretability, accuracy, and robust uncertainty quantification remains a significant challenge. This study addresses these issues using the DS02 dataset of New Commercial Modular Aero-Propulsion System Simulation (N-CMAPSS) by developing a systematic framework that integrates interpretability, predictive accuracy, and uncertainty quantification. ...

Safety-critical, mission-critical, and infrastructure-critical systems (e.g., aerospace, transportation, defense, and power generation) are forced to source parts over exceptionally long periods of time from a supply chain that they do not control. Such systems are exposed to the dual risks of the impacts of system failure and the exposure to an unauthorized electronics marketplace over decades. Therefore, critical systems operators, manufacturers, and sustainers, must implement policies and technologies to reduce the risk of obtaining counterfeit parts. ...

Dynamic mechanical analysis (DMA) is routinely practiced in the semiconductor industry to measure the viscoelastic properties of various thermosetting polymers. Modern commercial DMA test machines are highly-advanced systems which enable users to perform automatic testing and post-processing of the experimental data. When highly filled thermosets like epoxy-based molding compound (EMC) are tested, unique challenges are encountered during measurements due to the extremely large change in modulus over the testing temperature range. ...

Fingerprint-based indoor positioning systems are being explored to aid in location-based services due to their robustness in non-line-of-sight conditions. Current systems utilize high-dimensional radio frequency (HDRF) fingerprints, such as Wi-Fi channel state information, to achieve higher positioning precision. Since data acquisition is labor-intensive, researchers proposed to enrich the dataset with generative models. ...