Nanometer-sized flakes of molybdenum disulfide compared to grain boundaries predicted by simulation (insert).

© Institute of High Performance Computing (IHPC) and the Institute of Materials Research and Engineering (IMRE)

Simulating the shapes of nanoflakes

20 Sep 2020

New computer models show how semiconductor flakes with fancy shapes grow from simple starting points and rules.

Have you ever been told that every snowflake is unique? By the tiniest of degrees perhaps, but within each snowflake lies a universal six-sided symmetry that emerges from the orderly pattern of water molecules as they crystallize.

At the nanoscale, we can also find three-sided symmetry in the shapes of nanometer-sized flakes of molybdenum disulfide (MoS2), a promising semiconductor material for the next generation of lighter and faster electronic devices. These ‘nanoflakes’ merge with nearby neighbors as they grow, forming complex clusters of multiple ‘grains’ with different crystal orientations.

To predict how grain boundaries form and spread as nanoflakes grow, researchers led by Yong-Wei Zhang at the A*STAR Institute of High Performance Computing (IHPC) developed computer simulations providing molecule-by-molecule replays of nanoflake growth.

Shuai Chen, a Scientist at IHPC, and colleagues accomplished this by using a probabilistic ‘kinetic Monte Carlo’ technique, which starts with multiple initial MoS2 ‘seeds,’ or nuclei, and then randomly adds atoms to available edges at rates consistent with experiments.

“Unlike in other models, we gave each nucleus its own lattice, letting each grain preserve its initial orientation as it grows. While this increases the computational cost greatly with each additional nucleus, it allows us to accurately predict the behavior of multi-grain growth and grain boundary formation,” Chen said.

From different starting configurations, the researchers were able to grow complicated shapes like bowties, hexagons and six-pointed stars, and even merge two triangular crystals to resemble the “fast-forward” icon. These shapes matched observations from various MoS2-growing experiments—including those seen by collaborator Dongzhi Chi at the A*STAR Institute of Materials Research and Engineering (IMRE).

“We also showed that crystals meeting head-on had straight, smooth grain boundaries, while crystals growing at a glancing angle developed jagged grain boundaries instead,” Chen said, noting that the grain boundaries where these different orientations meet are useful in some semiconductor devices and harmful for others.

The researchers have also simulated the effects of changing the molybdenum-to-sulfur input ratio or growing large single-grain flakes on terraced substrates. They ultimately hope to extend this method to both multi-layered structures and etching processes, creating a truly versatile toolkit for modeling semiconductor crystal flake growth.

The A*STAR researchers contributing to this research are from the Institute of High Performance Computing (IHPC) and the Institute of Materials Research and Engineering (IMRE).

Want to stay up to date with breakthroughs from A*STAR? Follow us on Twitter and LinkedIn!


Chen, S., Gao, J., Srinivasan, B.M., Zhang, G., Yang, M., et al. Revealing the Grain Boundary Formation Mechanism and Kinetics during Polycrystalline MoS2 Growth. ACS Appl. Mater. Interfaces 11 (49), 46090-46100 (2019) | article

About the Researchers

Yong-Wei Zhang

Deputy Executive Director

Institute of High Performance Computing
Yong-Wei Zhang is the Deputy Executive Director of the Institute of High Performance Computing (IHPC) at A*STAR Singapore. He received his PhD from Northwestern Polytechnical University, China, and subsequently worked in both China and the US before arriving in Singapore. His research interest lies in using theoretical and computational tools to study the relationship between the structure and properties of materials, with applications in material design, manufacturing and engineering.

Shuai Chen

Research Scientist

Institute of High Performance Computing
Shuai Chen is a Research Scientist at A*STAR’s Institute of High Performance Computing (IHPC). He obtained his PhD degree in mechanical engineering from Tsinghua University, China, and subsequently joined IHPC in 2016. Chen’s research interests are focused on using multiscale computational tools to investigate the growth, structure and property of materials, including 2D materials, high-entropy alloys and polymers.

This article was made for A*STAR Research by Wildtype Media Group