Speakers

​​​​​​The ongoing evolution of electronic packaging toward greater miniaturization, heterogeneous
integration, and higher power density has created growing demand for novel solder alloys that
simultaneously optimize melting behavior, electromigration resistance, and thermomechanical
reliability [1,2]. Development of such alloys increasingly relies on computational
thermodynamics and kinetics to navigate complex, multidimensional composition–temperature
space, with CALPHAD-based simulations now indispensable for predicting phase stability,
microstructure evolution, and properties ahead of experimental validation.

Traditionally, high-throughput calculations (HTCs) explore predefined compositional and
temperature ranges through forward screening: a large volume of simulations is generated, then
post-processed to identify candidates satisfying desired phase or property criteria. This brute-
force approach, while effective, is computationally intensive and increasingly impractical for
multicomponent systems, where the number of search points grows exponentially with the
number of alloy components.​

To address this limitation, we have developed a constrained target function within
the Pandat software framework. Instead of performing exhaustive forward calculations, this new
approach allows users to directly define:​

 Compositional search space​

 Temperature range​

 Target property criteria​

The constrained target function then intelligently identifies and outputs the compositions and
temperatures that satisfy the specified targets. This design strategy transforms alloy development
from passive screening to global, target-oriented optimization.​

We apply this approach to lead-free solder alloy design, efficiently mapping the
composition–temperature space to identify optimal compositions that satisfy specific design
objectives, such as the lowest liquidus temperature or a minimum or maximum phase fraction for
a given phase [1,2].​


References:

[1] Chen, S.-W., et al. “Phase transformation temperatures of Sn-Ag-Bi-Cu quaternary system,”
CALPHAD, Vol. 89 (2025): 102822.​

[2] Chen, S.-W., et al. “Phase transformation temperatures of the Sn–In–Ni–Zn quaternary
system,” CALPHAD, Vol. 90 (2025): 102854.​