Technical Abstracts

In Case You Missed It

Electrochemical Migration

“Effects of Concentration of Adipic Acid on the Electrochemical Migration of Tin for Printed Circuit Board Assembly”

Author: Yi Sing Goh, et al.

Abstract: The continuous advancement in innovative electronic applications leads to closer interconnection spacing and higher electric field density, thus increasing the risk of electrochemical migration (ECM)-related failures. The ECM of tin (Sn) attracts great interest due to the wide use of Sn on the surface of the printed circuit board assembly. In this work, the authors investigated the effects of adipic acid (1ppm – saturated concentration) on the ECM of Sn using the water drop test (WDT) at 5V. In situ observation and ex situ characterization of ECM products were carried out using optical and electrochemical techniques. Results show that the electrochemical migration failure probability is higher at intermediate adipic acid concentrations (10ppm, 100ppm and 1000ppm). The major ECM reactions include anodic corrosion and the formation of dendrites, precipitates and gas bubbles. ECM failure does not occur at higher adipic acid concentrations (≥ 5000ppm), although the anodic corrosion becomes more severe. The complexation of Sn with adipic acid to form Sn adipate complex is suggested as the main factor suppressing ECM failure at higher concentrations (≥ 5000ppm) by retarding ion transport. The electrochemical parameters (Ecorr and Icorr) do not correlate with ECM failure probability. They affect the anodic dissolution stage, but not the subsequent stages in the ECM mechanism. In this study, the ion transport stage plays a more significant role in determining the ECM failure probability. (Journal of Electronic Materials, January 2023;


“Adoption of Model-Based Systems Engineering in Traditional DoD Systems”

Authors: Capt. Patrick Assef, USAF, and Lt. Col. Jeremy Geiger, USAF

Abstract: The transition to digital engineering has become a major objective within the US Department of Defense (DoD). One such method is model-based systems engineering (MBSE), or the use of models to facilitate systems engineering. Most new US DoD programs are being built from the ground up using MBSE. The question of whether MBSE should be incorporated into existing systems lingers, however. Little research currently exists on the efforts required to transition existing systems to MBSE. In this article, the authors measure the effort required to transition an existing system of systems (SoS), which primarily relied on document-centric methods, to MBSE. Time efforts were measured to develop the model for the SoS, as well as the subsystems and components it contains. Additionally, existing MBSE resources that are part of the cost of transitioning to MBSE were also compiled. The research is intended to serve as a guide for program managers throughout the DoD to roughly estimate the time and costs they will incur to transition their programs to MBSE. (Defense Acquisition Journal, March 2023;

RF Design

“How to Select the Best Power Solution for RF Signal Chain Phase Noise Performance”

Authors: Mitchell Sternberg, Erkan Acar, David Ng and Sydney Wells

Abstract: Today’s radio frequency (RF) systems are becoming more complex. This added complexity requires the best performance across all system metrics such as stringent link and noise budgets. Ensuring the proper design of the entire RF signal chain is critical. An often-overlooked section of this signal chain is DC power. It plays an important role in the system, but it can also introduce unwanted effects. One important measurement for RF systems is phase noise, a metric that can be degraded depending upon the choice of power solution. This paper investigates the effect that power designs have on the phase noise of RF amplifiers. According to the authors’ data, selecting the right power modules is essential for improving the performance of the RF signal chain and can reduce phase noise by up to 10dB. (TechOnline, March 2023;

Solder Joint Evaluation

“Development of Solder Joint Void Metrology to Monitor Solder Joint Quality in Printed Circuit Board Assemblies”

Authors: Thaer Alghoul, Ph.D., Pubudu Goonetilleke and Chris Alvarez

Abstract: Solder joint reliability is determined by multiple factors, one of which is voiding. The formation of voids in solder joints is caused by entrapped air during the reflow process and could be challenging to eliminate entirely. When voiding exceeds a certain level, it may lead to joint failure and is therefore important to quantify. X-ray inspection is a nondestructive method that can be used to measure voiding, but currently available x-ray equipment has limitations. Automated x-ray inspection tools (AXI) are fast but lack accuracy, whereas 2-D x-ray tools are accurate but slow and cannot be used in a production environment. The authors show a new method they developed using deep learning (DL) to improve the speed of void measurement with a 2-D x-ray tool while still maintaining accuracy. The DL method is a two-phase approach. The initial phase involves detection of solder ball area and then segmentation to detect the boundaries of the solder ball. The second phase involves segmentation to detect voids. The authors have achieved 99.9% solder ball detection and area segmentation, and 99.5% void segmentation. The capability of the deep learning method used is then determined using measurement capability analysis. (SMTA International 2022, Article ending bug