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NSFOffice Of The Director

EPSCoR Research Fellows: NSF: Block Copolymer Complexes for the Rectification of Lithographic Nanopatterns

Active
Institution
Iowa State University, IA
Principal investigator
Boyce S Chang
Funding
$300K
Duration
2027–2028
Open portfolio

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Abstract

This Research Infrastructure Improvement (RII) EPSCoR Research Fellows project provides a fellowship to an Assistant Professor and training for a graduate student at the Iowa State University. This work is conducted in collaboration with Dr. Gregory Doerk at Brookhaven National Laboratory. Through the fellowship, the PI will develop polymers and processing methods to improve the quality of nanoscale semiconductor patterns made by conventional lithography. To attain this goal, the project will utilize combinatorial methods, which enable the comprehensive examination over a large parameter space that encompasses polymer composition, process condition, and template dimension. The project will combine polymer science with high-throughput data collection to enhance the fundamental understanding of polymer self-assembly and leverage them to advance semiconductor manufacturing. The project will strengthen collaboration and workforce development in advanced manufacturing. This project will investigate the directed self-assembly of block copolymer complexes for the rectification of low symmetry lithographic patterns. The research will identify complex formulations that form adaptive self-assembled morphologies and tolerate variations in pattern geometry and duty cycle. High-throughput sampling and combinatorial methods will be used to rapidly screen polymer formulations and identify complexes with dimensionally tolerant morphologies. Knowledge develop from this work will advance the fundamental understanding of polymers and soft nanolithography using advanced polymer deposition and templated assembly. The fellowship will enhance research infrastructure by advancing faculty expertise in designing combinatorial studies, provide graduate student training in constructing tools for automated sampling, and large data analysis including machine learning. The proposed training activities will create new opportunities for connecting faculty, graduate, undergraduate, and high school students through conferences, research seminars, course development, and outreach activities. The findings from this work will contribute to the development of semiconductors and manufacturing of advanced materials. This project is supported by the EPSCoR Research Infrastructure Improvement Program: EPSCoR Research Fellows (ERF), which supports early- and mid-career investigators in eligible jurisdictions to develop collaborations at the nation’s private, government or academic research institutions. This award reflects NSF's statutory mission and has been deemed worthy of support through evaluation using the Foundation's intellectual merit and broader impacts review criteria.

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Office Of The Director01002627DB NSF RESEARCH & RELATED ACTIVITEPSCoR RII: EPSCoR Research Feworkforcelargeschoolrapidlyconnectingconventionalmorphologiesreflectsbroaderlithographic

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