Research Areas

We develop hybrid quantum–classical computational frameworks for reliability assessment, rare-event analysis, and design under uncertainty in structural and materials systems. High-consequence engineering problems such as dynamic failure, certification of additively manufactured components, and multiscale material modeling are often limited by the computational cost of sampling high-dimensional stochastic fields using classical Monte Carlo methods.

Our research leverages quantum algorithms, including amplitude estimation and variational quantum circuits, to reformulate tail-risk metrics such as Conditional Value-at-Risk (CVaR) and rare failure probabilities into quantum-compatible inference problems. These approaches aim to reduce sampling complexity while maintaining statistical rigor and confidence guarantees.

By integrating quantum modules within finite element and topology optimization frameworks, we establish scalable approaches for quantum-accelerated uncertainty quantification and certification-grade prediction of failure in complex engineered systems.

Nanomaterials are defined as materials whose main constituents have at least one dimension below 100 nm. Examples include quantum dots, nanotubes, and nanoparticle-reinforced nanocomposites. Their novel mechanical and electronic properties enable next-generation devices with new functionalities.

Computer simulations play a central role in connecting atomic structure to macroscopic behavior. We adopt multiscale modeling to develop robust computational techniques for predicting the mechanical response of nanomaterial-containing systems. A key challenge is bridging time and length scales—from atoms to microstructures to the macroscale—using MD–continuum and quantum–continuum coupling approaches under static and dynamic loading.

Dynamic failure mechanics studies material failure under high strain rates, with examples including vehicle crashes, high-speed machining, and impact. We combine continuum and multiscale approaches to model failure under intense dynamic loading. At the macroscale, we use the extended finite element method (XFEM) to model crack initiation, growth, and branching; at the micro/atomistic scales, simulations inform cohesive forces and local mechanisms in shear bands and fracture processes. The goal is to understand micromechanisms of ductile failure and enable the design of materials with superior dynamic performance.

Using density functional theory (DFT), molecular dynamics (MD), and finite element methods, we investigate mechanical properties and failure characteristics of mono- and few-layer two-dimensional materials. Their exceptional physical, electrical, and mechanical properties make them promising for applications including supercapacitors, optoelectronics, spintronics, lithium-ion batteries, and nanocomposites. Understanding mechanical performance is essential for reliable deployment in sensitive devices. We study strength, fracture mechanisms, and the effects of defects such as grain boundaries and vacancies to support robust design and eventual industrial adoption.