To meet the growing demand for computational power, device technology continues to evolve. Our extensive expertise in novel materials and devices helps push logic and memory technologies beyond the limits of conventional scaling.

Quantum technology can tackle problems that classical technology can never solve. We are devoted to understanding and predicting materials properties relevant to the performance of solid-state qubits. In addition, we explore quantum algorithms for simulating solid-state systems on quantum computers.

We explore the interplay between electrons and phonons in disordered solids, including both semiconducting and metallic systems. By focusing on how structural disorder and vibrational excitations influence transport and localization phenomena, we apply various theoretical approaches. These include Green’s function methods with self-energy corrections as well as other analytical and numerical techniques to uncover the microscopic mechanisms of quantum transport in disordered materials.

First-principles calculations play an extensive role in understanding electronic structures, designing new materials, and explaining experimental results without relying on empirical parameters. Our modeling helps uncover microscopic mechanisms in materials and devices, offering valuable insights into experimental findings.

We apply our extensive knowledge of device theory and use numerical simulations to model and analyze novel logic and memory devices. This approach allows us to gain a comprehensive understanding of the detailed behavior of these devices and supports their further development.