In 2021, a group of Scholars at Oxford University published a paper that made big waves in the energy world. It argued that key clean energy technologies — wind, solar, batteries, and electrolyzers — are on learning curves which guarantee that, if they are deployed at the scale required to reach zero carbon, they will get extremely cheap.

This is, as they say, big if true. In September, I had one of the lead authors, Doyne Farmer, on Volts to discuss the paper in-depth. He made a convincing case for the paper’s thesis, but when I asked him why these technologies were on learning curves and others weren't, he could only speculate.

That's the question that's been on my mind ever since. Why are some clean-energy technologies getting rapidly cheaper while others aren't? What is it about particular technologies that make them amenable to learning curves?

I cast that question to the academic gods, and lo, they returned with a paper, and that paper is what we’re here to discuss today. It’s called “Accelerating Low-Carbon Innovation,” by Abhishek Malhotra of the School of Public Policy at the Indian Institute of Technology in New Delhi, India, and Tobias Schmidt of the Swiss Federal Institute of Technology in Zurich, Switzerland.

It sets out to chart technologies against two basic axes: design complexity and need for customization. That creates a schema that can help illuminate why some technologies developed quicker than others.

I don't want to say much more than that, since I have my Malhotra and Schmidt here with me to help explain.

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