Modeling Mother Nature to feed a growing citizenry—while reducing carbon emissions

The world’s ever-growing population could reach nearly 10 billion people by 2050,¹ up from nearly 8 billion today. All those people will need to eat.

Traditional approaches to agriculture will not meet the surging demand for food, a frightening scenario that has researchers seeking more efficient and sustainable ways to meet this demand.

A big part of the solution will involve finding a better, less energy-intensive way to produce fertilizers, whose main ingredient is nitrogen—the most abundant gas in the Earth’s atmosphere. Currently, the main manufacturing technique for converting nitrogen into the nitrates needed for agriculture requires burning the equivalent of a ton of fossil fuel for every ton of fertilizer. This manufacturing method, known as the Haber-Bosch process, accounts for an estimated one percent of global carbon emissions²—hardly a sustainable and scalable production model in the era of climate change.

For as long as humans have been tilling the soil, they have relied on nitrogen-based substances to increase the yield—whether manure, compost or, in industrial agriculture, chemical fertilizers. Nitrogen, which makes up four-fifths of the air we breathe³, is a key ingredient of proteins, DNA and other molecules essential to life.

But there’s a catch: plants can use nitrogen only in “fixed” form. Certain bacteria on the roots of plants fix nitrogen naturally—nature’s clever way to make its own fertilizers to feed the plants that feed us. For more than a half-century, researchers have been trying to engineer a catalyst to improve this biological process, in a bid to address the limited supply of naturally fixed nitrogen and tackle the looming global food crisis. But they’ve been limited by their ability to observe and model the bewildering molecular complexities of this biological process.

Using the accelerated discovery cycle, researchers will sift through existing knowledge about catalysts. In a few years, a quantum computer might be able to precisely simulate different nitrogen fixation catalytic processes, further augmenting our knowledge. Then researchers would use the resulting data to construct predictive models and determine new molecules using only a small amount of energy compared to today’s industrial processes. IBM could also help validate those predictions: the candidate materials can be tested in AI-driven chemical labs via the cloud and screened to check their effectiveness.

The next goal would be to scale the process in a way that meets the world’s agricultural needs. This might be achieved using fuel cells—devices that convert a fuel’s chemical energy into electricity. It would work like a reverse battery—instead of storing energy, fuel cells could use energy from renewable sources to combine nitrogen from the atmosphere and hydrogen from water to produce ammonia. Catalytic molecules would play an important role here, by lowering the amount of energy needed to sustain the nitrogen fixation process.

Over the next five years, with AI and quantum computing in our corners, we’ll come up with an innovative solution to enable nitrogen fixation at a sustainable scale and help feed the world’s rapidly growing population.