Quantum Computing & AI Partnership Accelerates New Materials Discovery

Quandela, a quantum computing company, and Alysophil, specialising in AI-assisted continuous flow chemistry, have secured renewed investment from TotalEnergies and MBDA to continue collaborative research into applying quantum computing to materials science. The project combines artificial intelligence and quantum computation to improve molecular design, addressing limitations of conventional computers in accurately simulating electronic interactions. Researchers aim to accelerate the discovery of advanced materials – including high-performance polymers – by utilising machine learning algorithms optimised for Quandela’s quantum photonic processors, with MBDA directing research towards practical applications and TotalEnergies evaluating the impact on its digital activities. The collaboration leverages Alysophil’s expertise in machine learning and quantum chemistry alongside Quandela’s quantum computing capabilities to explore a wider solution space for materials optimisation than traditional methods allow.

A collaborative effort expands the computational toolkit for materials modelling beyond conventional limitations, unlocking new possibilities in materials science. The integration of machine learning algorithms, developed by Alysophil, with Quandela’s photonic quantum processors facilitates a more comprehensive exploration of the design space and accelerates the identification of novel compounds with tailored characteristics. This focused approach translates theoretical progress into tangible benefits for specific industrial applications, validating computational predictions through real-world scenarios and establishing a robust pathway for materials discovery.

Alysophil develops bespoke machine learning algorithms specifically designed for execution on Quandela’s quantum processors, efficiently navigating the complex relationships between molecular structure and material properties. These algorithms allow researchers to explore a broader design space and identify novel compounds with tailored characteristics. The synergy between algorithmic development and quantum hardware constitutes a focused approach to overcoming computational limitations in materials modelling, enabling a more comprehensive investigation of molecular structures and properties previously inaccessible due to computational cost.

Quandela’s photonic quantum processors offer advantages in coherence and scalability, critical for complex quantum simulations. They enable accurate prediction of material properties by directly simulating the quantum mechanical interactions governing electron behaviour within molecules. TotalEnergies and MBDA direct research towards advanced materials applications, ensuring practical relevance and focusing on polymers with improved energy efficiency, strength, and reduced weight.

TotalEnergies and MBDA’s strategic direction prioritises the application of quantum computing to materials, addressing specific industrial needs. Their focus is notably on the development of high-performance polymers with enhanced characteristics. MBDA’s involvement provides crucial validation of computational predictions through real-world application scenarios, ensuring the relevance and impact of the research and accelerating the transition from theoretical advancements to tangible benefits.

The emphasis on polymers with enhanced performance characteristics underscores the practical implications of this quantum-enhanced materials design methodology, fostering innovation in materials science and engineering. This focused approach translates theoretical progress into tangible benefits for specific industrial applications, validating computational predictions through real-world scenarios and establishing a robust pathway for materials discovery.