As any physicist will tell you, chemistry is really all about physics. But while physical understanding of atoms and their quantum nature has progressed by leaps and bounds in the last century, not all of those insights have produced radical changes in chemistry. A mix of experience, intuition and trial-and-error still largely guides the joining of atoms to create compounds, the new materials for the next generation of drugs, batteries, auto parts and other products. Chemists have done well with this approach, but it has probed only a tiny fraction of all theoretically possible compounds. And many of those found are far from ideal. Side effects, toxicity and inefficiency hinder many otherwise useful materials. What’s needed is a way to explore the galaxy of possibilities.
Enter quantum chemistry. As Rachel Ehrenberg reports, theoretical chemists are now taking better advantage of the equation developed by physicist Erwin Schrödinger in the mid-1920s. By quantifying the quantum nature of an atom and its electrons, the equation offers seemingly magical qualities of prognostication: If you could solve it for any given molecule, you would know all about that molecule’s behavior and properties — from its melting point and how well it conducts electrons to whether it’s soluble in water or exhibits superstrength.
But solving that equation for molecules with more than a few atoms exceeds any current computer’s capability. So chemists have developed ways to calculate approximate solutions, with the help of both supercomputers and distributed computing power using desktops worldwide. Compounds can be analyzed by machine learning algorithms, which can quickly plow through libraries of candidates to find more prospects. Strong candidates can be tested in the tried-and-true, and time-consuming, way: by making them in the lab.
In this way, scientists may someday be able to swiftly find effective countermeasures to diseases like chikungunya, which, as Nathan Seppa writes, is now spreading far beyond its African origins. Success will depend on the cooperation of the physicists’ equations and the chemists’ experiments, and the clever computational strategies that connect them.