Next-Generation Materials Design Enabled by Generative AI and Quantum Computing

上午 11:40 - 下午 12:00

Generative AI is transforming materials design by enabling inverse design approaches that directly generate molecular and material candidates with target properties. At the same time, quantum computing offers a promising route to describe the quantum-mechanical nature of materials more accurately than conventional methods for selected applications.

This presentation introduces Mitsubishi Chemical’s research activities on combining generative AI, quantum computing, and GPU-accelerated computing for next-generation materials design. We will discuss how quantum-derived molecular descriptors and quantum algorithms, including the Generative Quantum Eigensolver, can be integrated with generative models such as variational autoencoders to construct physically meaningful latent spaces for molecular design. Recent progress from collaborative research activities with NVIDIA on quantum-AI approaches for molecular and materials simulation will also be introduced.

As an example relevant to semiconductor manufacturing, we will highlight applications to EUV photoresist materials, where electron dynamics, photoemission, Auger processes, and multiscale simulations are critical for improving material performance. This integrated AI–quantum approach has the potential to accelerate the discovery and optimization of advanced semiconductor materials.

 

Key Technologies Covered

  • Generative AI for inverse materials design

  • Quantum computing for materials simulation

  • Generative Quantum Eigensolver

  • Quantum-derived molecular descriptors

  • Variational autoencoder-based molecular design

  • Quantum/classical hybrid computing

  • EUV photoresist materials design

  • Electron dynamics and Auger process simulation

  • Multiscale simulation for semiconductor materials

  • AI-driven materials discovery for advanced semiconductor applications

Featured Speakers

Dr. Qi Gao

高玘博士

Distinguished Scientist, 三菱化學株式會社

Dr. Qi Gao is a Distinguished Scientist at the Science & Innovation Center of Mitsubishi Chemical Corporation. He leads research and development activities on quantum computing, generative AI, and advanced computational technologies for materials design. His current work focuses on applying quantum algorithms, high-performance computing, and machine learning to industrial materials challenges, including semiconductor materials and next-generation functional materials.

Dr. Gao has extensive experience in computational materials science, molecular simulation, and data-driven materials discovery. He has led multiple industry–academia collaborative projects with universities, national research institutes, and leading technology companies in Japan and overseas, including IBM, NVIDIA, and Fujitsu. His recent activities include the development of quantum algorithms for quantum chemistry and materials simulation, as well as the integration of generative AI with quantum computational approaches for molecular and materials design.

At SEMICON Taiwan 2026, he will discuss how the combination of generative AI and quantum computing may enable a new paradigm for next-generation materials design, particularly for advanced semiconductor applications.