In operando Characterization of Polymer Matrix Composites
This grant studies real-time characterization of polymer composites during manufacturing to improve processes like 3D printing by linking processing to material properties.
This grant is no longer accepting proposals
NRC Research Associateship Programs has archived this opportunity.
Funder: NRC Research Associateship Programs
Due Dates: February 1, 2025 | May 1, 2025 | August 1, 2025 | November 1, 2025
Funding Amounts: Base stipend approximately $95,000/year plus $5,000 travel allowance; supplements based on experience; typical tenure 2-3 years.
Summary: Supports postdoctoral and senior researchers in real-time characterization of polymer matrix composites during manufacturing to improve advanced processes like 3D printing by linking processing conditions to material microstructure and performance.
Key Information: Open to U.S. citizens; requires Ph.D. or equivalent; advanced characterization techniques include X-ray/neutron scattering, electron microscopy, AFM, and rheology; relocation and health insurance benefits provided.
Description
This fellowship opportunity focuses on advancing the understanding and manufacturing of polymer matrix composites, particularly high-temperature polymer thermosets. The research aims to develop and validate advanced capabilities that relate fundamental processing principles to the evolution of micro- and nanostructure, cure chemistry, filler alignment, and their impact on mechanical performance of composite parts.
The project emphasizes in operando (real-time) characterization of polymer/filler interactions and morphology evolution during manufacturing processes such as 3D printing and resin transfer molding. State-of-the-art techniques employed include:
- X-ray and neutron scattering (including synchrotron radiation experiments)
- Electron microscopy
- Atomic force microscopy (AFM)
- Rheology
The goal is to enable more robust, efficient, and advanced manufacturing processes by linking processing conditions directly to material properties and performance.
