"Toward" Metal-Organic Framework Design by Quantum Computing

TL;DR

This paper explores the use of hybrid quantum-classical computing methods to design Metal-Organic Frameworks for air capture, demonstrating potential advantages of quantum computing in energy surface calculations at small scales.

Contribution

It introduces a hybrid quantum-classical approach for potential energy surface scans in MOF design, benchmarking quantum advantages in climate-related applications.

Findings

Quantum models show potential advantages at small scales.

Hybrid PISQ approach enhances computational assessment.

Benchmarking classical and quantum methods for MOF design.

Abstract

The article summarizes the study performed in the context of the Deloitte Quantum Climate Challenge in 2023. We present a hybrid quantum-classical method for calculating Potential Energy Surface scans, which are essential for designing Metal-Organic Frameworks for Direct Air Capture applications. The primary objective of this challenge was to highlight the potential advantages of employing quantum computing. To evaluate the performance of the model, we conducted total energy calculations using various computing frameworks and methods. The results demonstrate, at a small scale, the potential advantage of quantum computing-based models. We aimed to define relevant classical computing model references for method benchmarking. The most important benefits of using the PISQ approach for hybrid quantum-classical computational model development and assessment are demonstrated.