A single algorithm—throw atoms into a box and let them slide downhill on an energy landscape—can now predict the atomic structure of crystals from scratch, with no prior chemical knowledge. This matters because predicting crystal structures has been a long-standing blind spot in the physical sciences. Chemists and materials scientists often rely on intuition or trial-and-error to guess how atoms arrange themselves in solids, but that intuition fails under extreme conditions—inside giant planets, deep within Earth, or at the pressures inside a new computer chip. The researcher’s “random structure searching” method solves this by brute force: it tries thousands of random atomic arrangements, keeps the lowest-energy ones, and lets the physics teach the scientist what chemistry is happening. If the method scales, it could reshape several fields. It has already predicted the structure of hydrogen at the pressures inside gas giant planets, where it may become a room-temperature superconductor. It could help design materials with extreme properties—ultra-hard, superconducting, or highly efficient—for energy grids, electronics, or space exploration. It could also help pharmaceutical companies predict the many crystal forms (polymorphs) that drug molecules adopt, which directly affect a drug’s solubility, shelf life, and effectiveness. This is fundamental science, not applied engineering. But like quantum mechanics itself, a better way to see atoms may quietly change what we can build.
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The discovery that matter is made up of atoms ranks as one ofmankind's greatest achievements. Twenty first century science isdominated by a quest for the mastery (both in terms of control andunderstanding) of our environment at the atomic level.In biology, understanding life (preserving it, or even attempting tocreate it) revolves around large, complex, molecules -- RNA, DNA, andproteins.Global warming is dictated by the particular way atoms are arrangedto make small greenhouse gas molecules, carbon dioxide and so on.The drive for faster, more efficient, cheaper computer chips forcesnanotechnology upon us. As the transistors that make up themicroscopic circuits are packed ever closer together, electronicengineers must understand where the atoms are placed, or misplaced, inthe semiconducting and insulating materials.Astronomers are currently, daily, discovering new planets outside oursolar system, orbiting alien stars. The largest are the easiest tospot, and many are far larger than Jupiter. The more massive theplanet the higher pressures endured by the matter that makes up itsbulk. How can we hope to determine the structure of matter at theseconditions?The atomic theory of matter leads to quantum mechanics -- a mechanicsof the every small. In principle, to understand and predict thebehaviour of matter at the atomic scale simply requires the solutionof the quantum mechanical Schroedinger equations. This is a challengein itself, but in an approximate way it is now possible to quicklycompute the energies and properties of fairly large collections ofatoms. But is it possible to predict how those atoms will be arrangedin Nature - ex nihilo, from nothing but our understanding ofphysics?Some have referred to it as a scandal that the physical sciencescannot routinely predict the structure of even simple crystals -- butmost have assumed it to be a very difficult problem. A minimum energymust be found in a many dimensional space of all the possiblestructures. Those researchers brave enough to tackle this challengehave done so by reaching for complex algorithms -- such as geneticalgorithms, which appeal to evolution to breed ever betterstructures (with better taken to mean more stable). However, Ihave discovered to my surprise, and to others', that the very simplestalgorithm -- throw the collection of atoms into a box, and move theatoms downhill on the energy landscape -- is remarkably effectiveif it is repeated many times.This approach needs no prior knowledge of chemistry. Indeed thescientist is taught chemistry by its results -- this is critical ifthe method is to be used to predict the behaviour of matter underextreme conditions, where learned intuition will typically fail.I have used this approach, which I call random structure searching to predict the structure of crystals ex nihilo. My firstapplication of it has been to silane at very high pressures, and thestructure I predicted has recently been seen in experiments. Butprobably the most impressive application so far has been to predictingthe structure of hydrogen at the huge pressures found in the gas giantplanets, where it may be a room temperature superconductor.In the course of my fellowship I will extend this work to try toanticipate the structure of matter in the newly discovered exoplanets,to try to discover and design materials with extreme (and hopefully,extremely useful) properties, and to help pharmaceutical researchersunderstand the many forms that their drug molecules adopt when theycrystallise.
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