Best of both worlds: Hybrid approach sheds light on crystal structure solution

December 11, 2012

Understanding the arrangement of atoms in a solid -- one of solids' fundamental properties -- is vital to advanced materials research. For decades, two camps of researchers have been working to develop methods to understand these so-called crystal structures. "Solution" methods, championed by experimental researchers, draw on data from diffraction experiments, while "prediction" methods of computational materials scientists bypass experimental data altogether.

While progress has been made, computational scientists still cannot make crystal structure predictions routinely. Now, drawing on both prediction and solution methods, Northwestern University researchers have developed a new code to solve crystal structures automatically and in cases where traditional experimental methods struggle.

Key to the research was integrating evidence about solids' symmetry -- the symmetrical arrangement of atoms within the crystal structure -- into a promising computational model.

"We took the best of both worlds," said Chris Wolverton, professor of materials science and engineering at Northwestern's McCormick School of Engineering and expert in computational materials science. "Computational materials scientists had developed a great optimization algorithm, but it failed to take into account some important facts gathered by experimentalists. By simply integrating that information into the algorithm, we can have a much fuller understanding of crystal structures."

The resulting algorithm could allow researchers to understand the structures of new compounds for applications ranging from hydrogen storage to lithium-ion batteries.

A paper describing the research, "A Hybrid Computational-Experimental Approach for Automated Crystal Structure Solution," was published November 25 in the journal Nature Materials.

While both computational and experimental researchers have made strides in determining the crystal structure of materials, their efforts have some limitations. Diffraction experiments are labor-intensive and have high potential for human error, while most existing computational approaches neglect potentially valuable experimental input.

When computational and experimental research is combined, however, those limitations can be overcome, the researchers found.

In their research, the Northwestern authors seized onto an important fact: that while the precise atomic arrangements for a given solid may be unknown, experiments have revealed the symmetries present in tens of thousands of known compounds. This database of information is useful in solving the structures of new compounds.

The researchers were able to revise a useful model -- known as the genetic algorithm, which mimics the process of biological evolution -- to take those data into account.

In the paper, the researchers used this technique to analyze the atomic structure of four technologically relevant solids whose crystal structure has been debated by scholars -- magnesium imide, ammonia borane, lithium peroxide, and high-pressure silane -- and demonstrated how their method would solve their atomic structures.

Bryce Meredig (PhD '12) was the paper's lead author.
-end-


Northwestern University

Related Algorithm Articles from Brightsurf:

CCNY & partners in quantum algorithm breakthrough
Researchers led by City College of New York physicist Pouyan Ghaemi report the development of a quantum algorithm with the potential to study a class of many-electron quantums system using quantum computers.

Machine learning algorithm could provide Soldiers feedback
A new machine learning algorithm, developed with Army funding, can isolate patterns in brain signals that relate to a specific behavior and then decode it, potentially providing Soldiers with behavioral-based feedback.

New algorithm predicts likelihood of acute kidney injury
In a recent study, a new algorithm outperformed the standard method for predicting which hospitalized patients will develop acute kidney injury.

New algorithm could unleash the power of quantum computers
A new algorithm that fast forwards simulations could bring greater use ability to current and near-term quantum computers, opening the way for applications to run past strict time limits that hamper many quantum calculations.

QUT algorithm could quash Twitter abuse of women
Online abuse targeting women, including threats of harm or sexual violence, has proliferated across all social media platforms but QUT researchers have developed a sophisticated statistical model to identify misogynistic content and help drum it out of the Twittersphere.

New learning algorithm should significantly expand the possible applications of AI
The e-prop learning method developed at Graz University of Technology forms the basis for drastically more energy-efficient hardware implementations of Artificial Intelligence.

Algorithm predicts risk for PTSD after traumatic injury
With high precision, a new algorithm predicts which patients treated for traumatic injuries in the emergency department will later develop posttraumatic stress disorder.

New algorithm uses artificial intelligence to help manage type 1 diabetes
Researchers and physicians at Oregon Health & Science University have designed a method to help people with type 1 diabetes better manage their glucose levels.

A new algorithm predicts the difficulty in fighting fire
The tool completes previous studies with new variables and could improve the ability to respond to forest fires.

New algorithm predicts optimal materials among all possible compounds
Skoltech researchers have offered a solution to the problem of searching for materials with required properties among all possible combinations of chemical elements.

Read More: Algorithm News and Algorithm Current Events
Brightsurf.com is a participant in the Amazon Services LLC Associates Program, an affiliate advertising program designed to provide a means for sites to earn advertising fees by advertising and linking to Amazon.com.