# Mini Review: Synergizing Driven Quantum Dynamics, AI, and Quantum Computing for Next-Gen Materials Science

## TL;DR

This paper reviews how combining quantum dynamics, AI, and quantum computing can speed up the discovery of new quantum materials.

## Contribution

The paper highlights novel synergistic approaches integrating driven quantum dynamics, AI, and quantum computing for materials discovery.

## Key findings

- Synergistic methods enable rapid exploration of design spaces and identification of novel quantum phases.
- Recent successes include advancements in quantum batteries and rare-earth-free materials.
- AI-for-quantum computing is accelerating next-gen materials discovery.

## Abstract

The design of next-gen materials has undergone remarkable
progress
in recent years, as evidenced by the emergence of automated platforms
combining artificial intelligence (AI)-driven synthesis planning and
robotics for execution. In this Mini-Review, we analyze how synergistic
approaches that combine driven quantum dynamics, AI/machine learning,
and quantum computing accelerate the discovery and design process
of quantum materials with enhanced properties and novel functionalities.
Building on the capabilities of each of the three methods, synergistic
approaches can provide access to the materials’ response to
time-dependent fields, enable the rapid exploration of vast design
spaces, and identify novel quantum phases and materials with optimal
properties. We examine recent successes in next-gen materials science
for quantum batteries, colloidal quantum dots solar cells, quantum
phototransistors, rare-earth-free materials, and applications in quantum
information processing. We conclude with a discussion of recent research
efforts in AI-for-quantum computing and quantum machine learning for
next-gen materials discovery.