ENG-EAM: Parallax Additive Manufacturing of Sustainable Electrical Interconnects

NSF Award Search · 01002627DB NSF RESEARCH & RELATED ACTIVIT · $400,000 · view on nsf.gov ↗

Abstract

This project will improve the fabrication precision of volume additive manufacturing by controlling residual stress through improved CAD tools, mechanical modeling, and materials. Volume additive manufacturing is a relatively new polymer additive manufacturing method that projects hundreds of three-dimensional light fields into a container of photosensitive resin. These light fields overlap within the resin, solidifying the part by exceeding a total exposure threshold in the desired shape. This process is orders of magnitude faster and provides better material uniformity than traditional layer-by-layer processes. However, parts fabricated by volumetric exposure have lower stiffness before post processing and are thus subject to greater deformation, reducing shape accuracy. This project will improve part fidelity by studying residual stress development, focusing on one volumetric manufacturing architecture, parallax volume additive manufacturing. Improved dimensional accuracy and reduced stress will extend the applicability of volumetric additive manufacturing to meet the needs of high precision, high volume industrial production such as high bandwidth electronic connectors. The hundreds of images projected into the resin container are found by solving a very large inverse problem using the mathematics of computed tomography. To make this problem computationally tractable, current algorithms ignore the inevitable stresses that develop during polymerization and post-processing steps. This project will build a finite element model as a digital twin, comparing this to the Virtual Volumetric Additive Manufacturing model created at Lawrence Livermore National Laboratory. Simplified models of viscoelasticity will be implemented to find a minimal description of the fabrication process. This model will be implemented in a new image generation algorithm that provides greater computational efficiency by representing fields in basis sets developed for computer image

Key facts

NSF award ID
2430936
Awardee
University of Colorado at Boulder (CO)
SAM.gov UEI
SPVKK1RC2MZ3
PI
Robert R McLeod
Primary program
01002627DB NSF RESEARCH & RELATED ACTIVIT
All programs
MATERIALS PROCESSING AND MANFG, Materials Engineering, Advanced Materials Processing, Advanced Manufacturing, UNDERGRADUATE EDUCATION, GRADUATE INVOLVEMENT, MANUFACTURING
Estimated total
$400,000
Funds obligated
$400,000
Transaction type
Standard Grant
Period
05/01/2026 → 04/30/2029