Defect-Aware Semiconductor Digital Twins

We develop defect-aware predictive digital twins for semiconductor materials and advanced packaging, leveraging advanced modeling and simulation to capture defect initiation, evolution, and their effects on performance and reliability.

Reliability for Semiconductor Advanced Packaging with Defects:

We utilize computational simulations and machine learning techniques to model failure mechanisms in semiconductor advanced packaging, aiming to improve the reliability predictions and performance of microelectronic devices.

Atomistic Modeling of Interfacial Cracking in Copper-To-Copper Direct Bonding

Modeling of Microstructural Evolution within TSVs Using Atomistic Simulations

A Machine Learning Framework for Preventing Cracking in Semiconductor Materials

Simulating Defects at Materials Interfaces:

We investigate how defects—including dopants, impurities, vacancies, and dislocations—influence material properties and performance at critical interfaces such as grain boundaries and phase boundaries. Through advanced atomistic and multi-scale simulations, we aim to uncover the fundamental mechanisms governing defect nucleation, segregation, migration, and interaction at these interfaces.

First-order interfacial transformations with a critical point: breaking the symmetry at a symmetric tilt grain boundary’ mechanical properties

Role of disordered bipolar complexions on the sulfur embrittlement of nickel general grain boundaries

Effects of magnesium dopants on grain boundary migration in aluminum-magnesium alloys

Phase-field-lattice Boltzmann method for dendritic growth with melt flow and thermosolutal convection–diffusion

First-principles study of vacancy interaction with grain boundaries of tungsten under tensile strains

Concurrent Atomistic-Continuum Methods for Defect Dynamics:

We develop advanced multiscale simulation methodologies that seamlessly bridge atomistic and continuum scales. These frameworks enable efficient and accurate prediction of defect nucleation, migration, and interaction in microstructurally complex materials.

Concurrent atomistic and continuum simulation of strontium titanate

Concurrent atomistic and continuum simulation of bi-crystal strontium titanate with tilt grain boundary

Concurrent atomistic–continuum simulation of polycrystalline strontium titanate’ mechanical properties

Ballistic-diffusive phonon heat transport across grain boundaries

Modeling Defects in Advanced Energy Materials:

We use advanced computational modeling and simulation to understand and engineer defect–structure–property relationships, guiding the design of next-generation lithium-ion batteries, solid-state electrolytes, and beyond.

Lithium storage mechanisms and electrochemical behavior of a molybdenum disulfide nanoparticle anode

Lithium trapping in germanium nanopores during delithiation process

Porous microstructures for ion storage in high capacity electrodes based on surface segregation-induced separation

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