Simulations Help Identify Conditions For Self-Assembly of Nanoparticles with 10x Resolution
Researchers at the NSF-funded Nanosystems Engineering Research Center (NERC) for Nanomanufacturing Systems for Mobile Computing and Mobile Energy Technologies (NASCENT), headquartered at the University of Texas at Austin, ran computer simulations that template patterns relatively inexpensively, providing a way to directly self-assemble nanoparticles in areas with 10x resolution of the initial mask.
The ERC’s simulations identified conditions in which 10-fold patterning of random access memory (RAM) occurs with high precision and low variability. RAM is essential to mobile electronic devices, which rely on the ability of nanoparticles to be arranged over large areas—a task made difficult because nanoparticles left alone will self-assemble in defective patterns.
This project addresses NASCENT’s main thrust of creating high-throughput, reliable, and versatile nanomanufacturing systems for mobile devices. Directed self-assembly has been demonstrated as a viable way to arrange block polymers on surfaces with desired structures. However, little is known about how to direct particles to self-assemble on surfaces with precision.
The Center created computer simulations that rapidly and relatively inexpensively explore how particles are directed to self-assemble into desired structures. This computer simulation tool is being used to understand how to guide the placement of rectangular particles, which are especially useful in bit-patterned media that forms essential components of mobile electronic devices.