Science Success Story

Experimental Introduction

Introducing Experimental Data into Molecular Simulations on XSEDE Resource Improves Predictions of Metallic Glass Structure

By Ken Chiacchia, Pittsburgh Supercomputing Center

 A phosphorus atom (top, center) rattling inside a cage of palladium and nickel, from the AIFEAR simulations.


Metallic glass has great strength and flexibility, and can be engineered for specific uses. These properties make it useful for medical devices, electrical sensors, and even sporting goods. But scientists don't yet agree on how the atoms in metallic glasses are arranged. This limits the ability to engineer new metallic glasses for expanded uses.

Full video of simulation above

Ohio University scientists employed the XSEDE-allocated Bridges platform to carry out a new type of molecular simulation on a metallic glass that introduces lab-derived data into the simulation process. By providing a powerful resource capable of running not-universally available software, and at no cost to the researchers, XSEDE allowed them to obtain simulations that agreed with lab results better than former methods. The new simulations also predicted unexpected properties that may help guide future applications of the material.

Why It's Important

Amorphous solids—in particular a type called metallic glass—have a strange, not-quite-regular molecular structure. Materials scientists can exploit that irregular structure, "tuning" the properties of metallic-glass materials. This gives these materials many practical uses. Some of these substances serve as strong but flexible components in medical devices. Others can function as pressure-sensitive electrical triggers. They underlie promising advances in nanotechnology. Some are even used in sporting goods.

"There's an interesting material—a bulk metallic glass—with three different kinds of atoms: palladium, nickel, and phosphorus in a particular composition … It's very hard to understand its structure. With three kinds of atoms, lots of interactions are possible. What is the physical arrangement of these atoms that really happens in nature? If we knew that, we really could learn something about its properties, thermal and electronic, and how to apply them."— David Drabold, Ohio University

Scientists don't agree on exactly how the atoms are arranged in metallic glasses. X-ray or neutron diffraction experiments in the laboratory are usually the highest standard for determining atomic arrangements. But these methods provide inconclusive results because of the materials' irregular structure. Computer simulations are limited by the massive complexity of the problem. Still, knowing their atomic arrangement would allow scientists to better engineer their properties. Graduate students Bishal Bhattarai (now a postdoctoral fellow at Missouri University of Science and Technology) and Rajendra Thapa, working with Ohio University's David Drabold, decided to apply a new molecular simulation method called ab initio force enhanced atomic refinement (AIFEAR) to the problem. To run it, they turned to the XSEDE-allocated Bridges platform at the Pittsburgh Supercomputing Center.

How XSEDE Helped

Amorphous materials have an unusual structure, half-way between crystal and liquid. In crystals, the atoms are arranged in a strict, repeating pattern. This makes crystals hard but also brittle, since the slightest irregularity is a weak point. Amorphous materials have microscopic, crystal-like bits surrounded by more liquid structure. This gives the materials some of the strength of crystals, but with flexibility as well.

The presence of islands of regular structure within disordered regions makes these materials difficult to study in the lab and difficult to simulate in the computer. To overcome these limitations, the Ohio University scientists used AIFEAR. This new method for simulating the material adjusts the emerging composition with partial information gleaned from laboratory results while finding a good energy minimum. The simulation cycles in a loop, re-forming the atomic structure with more experimental data over and over until another cycle can't reduce the atoms' excess energy. The scientists' intention was to improve on the previous simulation method, melt-quench, which optimized its predictions using similar cycles of melting and solidifying the material but without the added laboratory data.

"We start with a random model, and refine it by alternating conjugate gradient minimization and experimental data fitting until some convergence is met as we move on through the AIFEAR steps, we get closer and closer to the experimental information and at the same time reach a good energy minimum."— Rajendra Thapa, Ohio University

Bridges proved an important tool for using AIFEAR to study the metallic glass Pd40Ni40P20. This mixture of palladium, nickel, and phosphorus has proved useful in a number of real-world applications. In addition to offering computing power, Bridges can run a powerful molecular simulation package called VASP that the scientists needed to make AIFEAR work.

The Bridges simulations predicted chemical properties that matched experimental diffraction results better than melt-quench simulations. AIFEAR's more economical computing also allowed it to simulate a larger system (200 to 300 atoms, as opposed to 100 to 200) than melt-quench, and it ran at least 4 to 5 times quicker than melt-quench. Finally, the computing time on the NSF-funded Bridges came without cost to the researchers, saving the scientists tens of thousands of dollars compared with other systems available. The team published their results in Modeling and Simulation in Materials Science and Engineering in July 2019.

"This work was all XSEDE-based, other than some little stuff we ran locally on workstations. The excellent XSEDE facilities gave us the power we needed to bring to bear in this problem. [When previously available systems became unavailable], XSEDE was there, and immediately gave us startup time. Very quickly, we were able to write the proposal and get it supported. It really is a refreshingly efficient system, yet still with rigor … I suppose $20,000 of cash might have bought a functionally similar machine. But that's not even right. After all, there is the nontrivial detail that these machines need power, maintenance, fixing etc. At a time when support staff are being cut, it is extremely valuable to have access to great facilities that are maintained by professionals."— David Drabold, Ohio University

One additional AIFEAR finding, not predicted by earlier melt-quench simulations, was that in some conditions the phosphorus atoms in the material would "rattle" inside a cage of palladium and nickel. This interesting property could give the substance unexpected properties in absorbing and releasing heat that materials scientists might be able to exploit in the future. The team plans more extensive simulation with AIFEAR to better understand and engineer the material.

The work was funded by the NSF, Grant Numbers DMR 1506836 and DMR 1507670. The work used the Extreme Science and Engineering Discovery Environment (XSEDE), which is supported by National Science Foundation grant number ACI-1548562. Specifically, it used the Bridges system, which is supported by NSF award number ACI-1445606, at the Pittsburgh Supercomputing Center (PSC).

Read the paper here.

At a Glance

  • Metallic glass is useful in many practical applications, including medicine, electronics, nanotechnology and even sporting goods
  • Scientists don't agree on how the atoms in metallic glasses are arranged, limiting the ability to engineer new metallic glasses for expanded uses
  • Ohio University scientists employed XSEDE resources to carry out a new type of molecular simulation on a metallic glass that introduces lab-derived data in the simulation process
  • The method better agreed with lab results than former simulation methods, and predicted unexpected properties that may help guide future applications of the material