Sustainable Development Goals:
Fertilizers play a crucial role in feeding the world’s population and we use about 200 million metric tonnes globally every year. But the processes used to manufacture these crucial chemicals are incredibly power-hungry, accounting for approximately 1-2% of global energy use14 and use a similar fractional of global natural gas production in the reaction.
Most fertilizers today are created using the Haber-Bosch process, which involves combining nitrogen from the atmosphere with hydrogen gas at high temperatures and pressures. This method requires huge amounts of energy, which means fertilizer has to be produced in large centralized facilities that contribute significantly to climate change.
Despite the fact that the current approach is more than 100 years old we’ve yet to find a more efficient way to produce fertilizers in local small-scale facilities. Doing so could go a long way to tackling SDGs around climate change and might allow us to democratize the process of producing these vital agricultural inputs. This would have major social and economic impact for the local communities.
How quantum could help
We know that better approaches exist, because bacteria naturally fix nitrogen from the atmosphere using a fraction of the energy. But we have yet to crack the complex biochemistry that allows them to do so.
That’s partly because the interplay of different enzymes and cellular processes involved are difficult to simulate on classical computers. But quantum computers are expected to excel at simulating chemical reaction pathways and enzymatic behavior of this sort.
In principle, this should make it possible to model critical aspects of the natural nitrogen fixation pathway, which could dramatically improve our understanding of the process. This could help us design novel catalysts or even new biochemical process that could allow us to produce fertilizers using considerably less energy.
A roadmap to impact
The heart of this biochemistry problem relies on chemistry simulations that are quantum native problems for which quantum computers will provide substantial speedup and accuracy advantage. Different quantum chemistry algorithms are currently being developed by researchers. To reach the level of simulation accuracy needed to deeply understand the catalyst and biochemical processes, such as nitrogenase enzymes found in cyanobacteria, more reliable and powerful quantum computers with a very large number of qubits are necessary. Given that today’s leading processors feature just hundreds, we are unlikely to have the hardware to perform such calculations until the end of this decade, but the goal appears within reach.
