We talk about computer modeling a lot in the context of climate science — powerful algorithms that help scientists get a better idea of how climate systems work, how they spin off into weather, and how the systems and the weather are altered by both nature and humans. But modeling plays a huge role in other sciences, as well. In fact, on the flip side of the climate change coin, modeling is an essential part of designing better solar cells to turn energy from the Sun into useable electricity. If we ever do master the art of artificial photosynthesis, we'll have the three men who just won this year's Nobel Prize for Chemistry to thank.
Back in the 1970s, Martin Karplus of Université de Strasbourg, France and Harvard University, Michael Levitt of Stanford, and Arieh Warshel of USC, were instrumental in constructing the first computer models capable of predicting the effects of chemical reactions — including ones that happen far too quickly to be observed. Today, their work touches the daily lives of chemists all over the world, doing research from solar cell design to drug development.
Karplus, Levitt, and Warshel weren't the first people to design modeling software for chemistry, but they were the first to make that software capable of thinking in terms of both classical Newtonian physics (aka, the physics you learn in junior high physics class) and quantum physics (the stuff that people win Nobel Prizes in physics for). The Nobel Committee has a nice PDF explaining why this was so important:
Previously when scientists wanted to simulate molecules on computers, they had software at their disposal that was based upon either classical Newtonian physical theories or quantum physics. Both had their strengths and weaknesses. The classical programs could calculate and process large chemical molecules. They would only display molecules in a state of rest, but gave chemists a good representation of how the atoms were positioned in the molecules. However, you could not use these programs to simulate chemical reactions. During the reaction, the molecules are filled with energy; they become excited. Classical physics simply have no understanding for such states, and that is a severe limitation.
The strength of quantum physics is that it is unbiased and the model will not include any of the scientist’s preconceptions. Therefore such simulations are more realistic. The downside is that these calculations require enormous computing power. The computer has to process every single electron and every atomic nucleus in the molecule. This can be compared to the number of pixels in a digital image. Many pixels will give you a high resolution, but also require more computer resources. Similarly, quantum physical calculations yield detailed descriptions of chemical processes, but require powerful computers. In the 1970s, this meant that scientists could only perform calculations on small molecules. When modeling, they were also forced to ignore interactions with the surrounding environment, although chemical reactions in real life most often occur in some kind of solution. However, if scientists would have wanted the computer to include the solvent in the calculation, they would have had to wait decades for the results.
Karplus, Levitt, and Warshel won the Nobel Prize today because they managed to merge those two opposing systems into a single thing, capable of modeling both large and small molecules throughout the process of a chemical reaction and accounting for how those molecules interact both with each other and with the chemistry of the environment around them. Essentially, they took a technology that made pretty pictures and turned it into one that could mimic the real world.
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Maggie Koerth-Baker is the science editor at BoingBoing.net. She writes a monthly column for The New York Times Magazine and is the author of Before the Lights Go Out, a book about electricity, infrastructure, and the future of energy. You can find Maggie on Twitter and Facebook.