On a winter day in Wisconsin, you can watch chemistry at work. Road salt and moisture roughen a car’s frame. Steel structures slowly turn to rust. At the same time, we burn fuels that release carbon dioxide, and we rely on fertilizer to grow food — fertilizer that still takes a huge amount of energy to make. Corrosion, carbon capture and fertilizer sound like separate problems. In my research as a physicist, I think of them as three stops on the same road trip, because all three are controlled by the same tiny actors: electrons. Electrons decide whether metal stays strong or crumbles. They rearrange when a catalyst turns CO₂ into something useful. And they govern nitrogen chemistry, including the reactions that produce the nitrogen-containing compounds that modern agriculture depends on. In the above figure, you can see “Rusty Coast,” “Carbon Capture Crags” and “Nitrogen Valley,” with the swirling tornado of electron correlation halting our path to useful solutions. People are also reading… If we could reliably predict what electrons will do in complex materials and molecules, we could design better alloys, better catalysts and better chemical processes with far less trial and error. The catch is that electrons follow quantum mechanics. When many electrons interact strongly, the number of possibilities explodes, and even our best classical computers can struggle. Classical simulation tools are powerful and often spectacular, but some of the most important cases remain stubbornly hard. That is why I work on quantum computing for chemistry and materials. A quantum computer processes information using quantum effects. Because electrons are quantum, it’s natural to hope a quantum computer can simulate them more directly than a classical machine can. In the best cases, this could speed up calculations dramatically. But it’s not automatic. Today’s quantum devices are still at an