Network science is the means by which mathematicians and software designers develop complicated social networks like Facebook. In any case, a group of Florida State University analysts has discovered that these equations can inform engineers a great deal regarding the composition of various materials.
Utilizing network science – some portion of a bigger mathematical field called graph theory – FAMU-FSU Professor of Mechanical Engineering William Oates, previous graduate student Peter Woerner and Associate Professor Kunihiko “Sam” Taira mapped long range atomic forces onto an incredibly complex graph to simulate macroscopic material behavior.
The group at that point created and connected a technique that enormously disentangles the graph so different scientists could replicate the procedure with different materials.
The work is published in the journal PLOS ONE.
Oates said utilizing graph theory enables scientists to more readily see how the molecules that form a material work on a macroscopic level.
“All atoms have electrons and nuclei with positive charges, they create forces between the ions,” Oates said. “Trying to describe that as a global structure is challenging. There are methods to model molecules, but the challenge is how to describe macroscopic behavior. Knowing how the molecules interact is only half of the problem. Network science provides a unique bridge that allows us to take molecule dynamics to the macroscopic world.”
At last, analysts want to see all the atomic interactions in a given material with the goal that they can see how and why materials carry on in certain ways, Oates said. However, when people monitor all the atomic interactions in a material, it turns into an enormous issue to illuminate on a PC.
Oates’ group attempted to make it an a lot littler issue.
In taking a gander at a graph that demonstrates the atoms in a material, Oates said to consider atoms and the forces between them as beads and springs. The atomic charges interface these beads, and they vibrate in complicated ways – some quicker and some slower.
For engineering purposes, it wasn’t important to monitor every one of the forces. In this way, the group connected a technique to make sense of how the forces in the graph could be reconnected without making errors.
Utilizing that knowledge, their algorithm erased certain atomic forces inside the graph and revamped it so they kept significant data while making it simpler to compute macroscopic behavior.
“You cut out the unimportant stuff and keep the important parts to make the simulations run substantially faster,” Oates said. “That was really the goal — to simplify it in order to accelerate computational materials research.”
Oates’ research is funded by the National Science Foundation’s EAGER program, a one-year infusion of funding that enables a faculty member to seek after a high-risk however possibly transformative research thought.
This first study was to a greater degree a proof of idea, he said. He will presently take a gander at whether this graph theoretic strategy can advise scientists how to make a material progressively proficient or how it may transport vitality quicker.
“We might be able to use these network models to help facilitate that design process,” Oates said.
Aditya Nair, a doctoral student in the FAMU-FSU College of Engineering, additionally added to this study.