This project delivers an open-source interface for Sony scientists to access a new generation of quantum materials simulator, which integrates exascalable quantum, reactive and neural-network molecular dynamics simulations with unique artificial-intelligence (AI) and quantum-computing capabilities to study a wide range of materials of Sony relevance. We develop a unified user interface for our open-source software suite named AIQ-XMaS (AI and quantum-computing enabled exascale materials simulator), not only to computationally synthesize materials and characterize their optoelectronic, thermal, mechanical and chemical properties, but also to design optimal nano-architectures and growth conditions. Specifically, we apply AIQ-XMaS to:

1. Polymer genome: Determine structure-function relationships in computationally synthesized dielectric polymers, using refractive index as a figure of merit.
2. Two-dimensional (2D) materials: Identify thermal and electronic properties of atomically thin 2D materials.

We have used the AIQ-XMAS software to compute: (1) refractive index (RI) of various amorphous polymers, including its frequency dependence; and (2) thermal and electrical conductivities of MoS2 monolayer without and with grain boundaries, which revealed highly anisotropic thermal and electrical transport across and along grain boundaries. We have successfully tested the developed software and provided access to it in virtual machine (VM) and GitHub:

1. Python scripting user interface to prepare amorphous polymer and calculate its refractive index by reactive molecular dynamics (RMD) simulation using the RXMD program in AIQ-XMAS VM image
2. Lorentz-oscillator model to predict frequency-dependent RI of polymers VM image
3. Open-source active learning software for optimal design of transition metal dichalcogenide (TMDC) heterostacks Github source