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In every handful of fertile soil, there are bacteria that do something no factory can: they take nitrogen straight from the air and turn it into fertilizer. The secret lies in the enzyme nitrogenase, and its working core, a cluster of iron and molybdenum atoms, looks like a tiny factory floor.

Chemists have long tried to understand how this factory works from the inside. In the new study, they calculated the energy of the lowest, most relaxed state of the cluster. To do this, they needed two powerful computational methods that usually don't work together: one is great at describing simple states, the other handles complex ones. They combined them and got a number with an accuracy that chemists consider gold standard.

It's like a part that has several equally comfortable positions and can rest in any of them. This ambiguity makes it hard to pin down which state is the real one. But it also explains why experiments give conflicting results.

The scientists tested what happens if you include additional electronic effects or slight vibrations of the protein. It turned out that the picture barely changes: several states remain almost equally favorable. This means the enzyme really works under conditions where multiple "bottom" options coexist.

Now that the energy is known precisely, we can test how well quantum computers handle such calculations. And that's a step toward one day replacing the energy-hungry industrial process of making ammonia with something cleaner and cheaper.

Original abstract

as written by the authors arXiv:2601.04621

We use classical computational methods to estimate the ground-state energy to chemical accuracy in a model of the FeMo-cofactor of nitrogenase which is widely studied as a target of quantum computing. Our result relies on the insight that the ground-state problem can be characterized as one of ranking many competing, but largely simple, states. This allows a combination of systematic high-order coupled cluster and density matrix renormalization group calculations together with an extrapolation protocol to obtain an accurate energy. Within the model we identify several spin isomer candidates for the ground-state that are degenerate to chemical accuracy. Beyond this model, we characterize the impact of additional electronic excitations and the cluster and protein geometric fluctuations on the low-lying electronic landscape. We find that many features of the landscape are retained in more detailed representations of nitrogenase, which points to the complexity of spectroscopic interpretations of the electronic structure of the FeMo-cofactor.