Speaker Interview: Daniel Volz, Quantum Computing Lead, BASF

Kickstarting a Career in Quantum

Fittingly, given his current role, Daniel is a chemist by training. Upon obtaining a PhD in the field, he took his deep domain expertise and launched his career initially as a material scientist - developing speciality chemicals for display applications. “The work was a lot of fun, but also dominated by tedious, empirical lab work, based on rough hypotheses.” He learned early that while R&D could be enhanced by modelling tools that drew on classical theoretical chemistry, relying on coarse-grained models meant their results “only had limited prognostic power.” A move to McKinsey in 2017 opened his eyes to the dawning age of quantum computing and what it could mean for his sector: “the profound potential impact of quantum-based R&D workflow for the chemical industry was immediately apparent to me.” With a keen eye on the future, he made a play for buy-in. “I rallied enough support within the senior partnership to launch an effort to help clients in large corporates explore the potential of quantum computing on their business operations.” And the rest, as they say, is history.

Quantum Impact in Chemistry

For Volz, it’s too early to talk about real-world impacts. That’s not to downplay the potential, of course. Instead, he’s hopeful that value will be realised soon. “The biggest strategic differentiator I see on the horizon is improved modelling of chemical systems.” The reason it will play such an important role is twofold, according to Volz: it will help in “finding new chemicals and improving the ways to produce them” - and in so doing it will address major industry pain points.

With chemicals “moving towards a more sustainable product portfolio”, the race is on to find new products that replace known applications (think “tensides in cleaning products”) while also devising sustainable methods of creating known chemicals (think “rubber to make shoes”). On top of this, other stubborn challenges – such as deploying “catalysis to use carbon dioxide as a feedstock” and “predicting the properties of solids so as to find new better materials or magnets” – are in the crosshairs of quantum-backing chemists. With so much value waiting to be captured, Volz is confident doubling down on the tech will yield dividends: “The current investment made by chemical companies in early-stage quantum computing efforts will be recouped if only a few of these applications are actually realized.” It’s all to play for, then.

Proofs of Concept in the Pipeline

Of course, in light of the above, it stands to reason that considerable energy is being poured into chemical and material modelling today. But, Daniel explains, the POC pipeline does not end there: “It’s clear that other potential applications of quantum, like combinatorial optimisation and AI and machine learning, are also attractive.” He cautions against laying all your quantum eggs in one basket though: “It’s not really clear yet which application will achieve industrial usefulness first, so a portfolio-based approach is definitely in order.”

Is Hybrid Really All That?

Daniel takes a wary view of the ‘hybrid’ approaches that employ both classical and quantum computing. He admits that there are reasons to believe they’ll play an important role in delivering value for industry in the most early stages, but also cautions that “the jury is really still out on that, because NISQ algorithms such as VQE and QAOA seem to have scaling issues.” He boils the problem down to this: “the required classical compute seems to grow exponentially with the problem size, and this could actually get in the way of industrial usefulness.” Instead, he focuses on the positives, namely that the “quantum community has been dedicated to working on algorithms that use the small-scale quantum computers we’ll have access to in the next decade as effectively as possible.”

Tackling the Growing Skills Gap

Almost every player in the field of quantum tech is plagued by a yawning skills gap, hampering their efforts to scale up R&D and drive the next wave of innovation. For Volz, this has the potential to stall progress considerably: “It’s clear there’ll be a talent shortage for quantum experts, which might slow down the adoption of quantum computing even after it has matured enough to be of use to industry.” That’s why, he explains, capability development is at the very heart of BASF’s quantum workstream: “Fortunately, we have a strong workforce from adjacent disciplines to build upon. We can build on existing teams of theoretical chemists and mathematicians, as well as experts in data science and other modelling disciplines.” The end goal? To beef up the organization’s capabilities “to be ready to adopt quantum as it becomes useful.”

The Five Year Outlook

Volz is cautiously optimistic about the outlook for quantum in chemicals over the next five years. He doesn’t think we’ll have seen the first real-world, value-generating application of quantum computing in an industrial setting. However, Volz believes “we will have a much clearer picture” of the future by 2027. “Right now,” he explains, “there’s a vibrant, collaborative quantum ecosystem, which tests different, sometimes competing approaches. This approach “is fair as long as the path towards usefulness is not yet apparent.” While praising of this atmosphere of collaboration, he predicts that “consolidation is likely to happen” over this period.

Want to hear more? Catch Daniel Volz in person and on-stage at QuantumTech this September in London as he participates in the panel discussion: Quantum for Enterprises; providing a roadmap for early ROI and gives a keynote on Quantum Computing for the chemical industry! Register here today to ensure you don't miss your opportunity to listen to these interesting topics.