Editorial: What will it take to realize the potential of quantum computing in chemistry?

Computing hasn’t changed fundamentally since the advent of the abacus 4,500 years ago. But that could change imminently as the world ushers in the quantum computer, a radically new type of computing machine that has the potential to majorly outperform classical ones.

That powerful thought came from Nathan Baker, a quantum computing specialist at Microsoft, during C&EN’s inaugural “Future of Chemistry” panel discussion at the American Chemical Society Spring 2025 meeting. The panel also featured Jamie Garcia, a quantum applications expert at IBM; Laura Gagliardi, a computational chemist at the University of Chicago; and Todd Krauss of the University of Rochester.

Unlike conventional computers, of which the world has many billions, quantum computers number in the hundreds. They’re based on the curious properties of quantum particles, which can exist in an enormous number of states simultaneously—as opposed to the 1-or-0, on-or-off, here-or-there nature of ordinary things. That quantum character endows these emerging tools with extreme computational power that can accelerate drug development and the discovery of new materials, among other things.

The potential of this emerging field is vast. And the rate at which researchers are making important strides in developing the hardware, especially the fragile qubits at the heart of these systems, and the algorithms that drive quantum computing is “mind blowing,” in Garcia’s view.

Yet the state of play for quantum computing today is about where it was for classical computing in the 1960s, Gagliardi noted. Eventually those computers would come to be seen as primitive, and the toughest chemistry problems they tackled back then are now regarded as trivial.

Starting small may be the right and natural thing to do. And that’s where quantum computing is today. It hasn’t yet solved important problems in renewable energy or health care. It hasn’t even solved a practical chemistry problem yet.

So what’s the holdup? People—and their inability to communicate with one another.

Garcia expressed frustration at watching researchers gather in a room—experts in quantum computing, experts in classical computing, computational specialists from industry, and others—all speaking their own language.

Members of a single group may understand one another because they have experiences in common and use shared terminology to frame problems. But from one group to the next, there’s a communication breakdown. The situation is analogous to highly experienced biochemists, polymer chemists, experts in computational chemistry, and other specialties, all finding each other’s scholarly presentations and journal articles largely impenetrable.

If we want to advance beyond high-level philosophical discussions of what quantum computing may eventually be able to do, and make real progress, we need to overcome the language barrier.

We should identify highly effective communicators across a broad range of disciplines and challenge them to work together and learn from each other. Of course this group of communication champions will include a variety of computing experts, as well as theoreticians and experimentalists knowledgeable in many areas of chemistry, physics, biology, engineering, environmental and materials science. But that’s not enough.

One attendee at the panel discussion noted that 96% of manufactured products have a basis in chemistry and materials science. From there, he challenged the panelists and their colleagues to use this developing computing tool to benefit the world’s consumers. This would suggest the group of champions also needs to include economists, in addition to experts in law, health care, and environmental science, as a start.

Here is one scenario that demonstrates what is possible. And required.

Let’s figure out how to use quantum computing to do broad life-cycle assessments covering cost, environmental impact, performance, and predicted lifetime on a staggering number of products. Then rate each product with a sustainability metric—a simple number that any would-be buyer, regardless of background or education, could use to decide about purchasing or consuming that product. That means training many more people to do advanced computations and supporting them to become skilled at recognizing where quantum computers offer a real advantage. It also means coming up with a cost-effective way to put the power of quantum computing in the hands of many more people.

That goal is incredibly challenging. Meeting it would be transformative.

This editorial is the result of collective deliberation in C&EN. For this week’s editorial, the lead contributors are Mitch Jacoby and Liam Conlon.

Views expressed on this page are not necessarily those of ACS.