Project Grant 2213842

Award Date 9/1/22
Completion Date 8/31/25
Dollars Obligated $400K
Federal Grant Program
47.070
Assistance Type
Project Grant
Place of Performance
College Station, TX 77843, USA
Similar Awards
This National Science Foundation Project Grant of $215,000 supports research at the University of California, Los Angeles from September 2022 to August 2025 under the Computer and Information Science and Engineering program (CFDA 47.070). The award funds collaborative research to advance 3D printing capabilities for creating interactive devices with enhanced visual feedback through passive light-transfer properties. Researchers will characterize light-transfer materials and microstructures to...
This $399,161 National Science Foundation project grant supports research at the University of Texas at Austin to develop new algorithms and simulations for co-designing the geometry and fabrication plans for direct-ink writing 3D printing. Funded under the Computer and Information Science and Engineering program (CFDA 47.070), this three-year award will transform additive manufacturing design tools by allowing users to specify an object's desired mechanical behavior and automatically...
This $225,000 National Science Foundation project grant supports research at the Texas A&M Engineering Experiment Station to develop 3D printing techniques for macroscopic polymeric structures with engineered molecular ordering defined at the sub-micrometer scale. The research aims to create materials with unusual optical and mechanical properties through control of molecular structure and composition in printable materials. Specifically, the project will control interplay between surface...
This $250,000 National Science Foundation (NSF) Technology, Innovation, and Partnerships project grant to Texas A&M Engineering Experiment Station will support the development and commercialization of a microscale three-dimensional (3D) printer for multi-materials. The two-year project aims to advance the miniaturization of systems and products by addressing the growing need for manufacturing smaller devices through the scale-up of laser-based micro and nanoscale 3D printing with...
This five-year Project Grant from the National Science Foundation's Division of Information and Intelligent Systems and Computer and Information Science and Engineering program (CFDA 47.070) provides $330,293 to Texas A&M Engineering Experiment Station (doing business as Tees) to develop novel methods for sparse sampling and reconstruction in computer graphics rendering. The award seeks to dramatically reduce the number of photons required to generate high-quality images through...
This Project Grant award of $313,716 from the National Science Foundation (NSF) Engineering Program (CFDA 47.041) supports fundamental research on additive manufacturing of optical hybrid materials (OHM) at Texas A&M Engineering Experiment Station (Tees). The project aims to understand how compositional doping influences OHM hybrid structures and develop a spatially resolved optical analysis system to identify key factors affecting these materials under extreme gradients. The successful...
This $600,000 Project Grant award from the National Science Foundation (NSF) Engineering program (CFDA 47.041) supports research at the University of California, San Diego (UCSD) to develop additive and subtractive manufacturing processes for printing high-resolution, biomechanical sensors into functional tissue constructs. Specifically, the project aims to engineer photolabile ferroelectric bioinks containing piezoelectric nanoparticles and electrochromic dyes within a hydrogel. These...
This three-year, $443,320 project grant from the National Science Foundation's Division of Computer and Network Systems will support the development of robust methods for embedding identifying information in 3D printed objects through coding theory techniques. Funded under the Computer and Information Science and Engineering program, the grant recipient—the Washington University Office of Sponsored Research Services—will analyze error patterns that can arise from physical tampering with 3D...
This $432,461 National Science Foundation project grant supports research at the University of Texas at Arlington to develop new 2D material programming techniques enabling scalable and customizable 3D manufacturing of soft conductive materials. Funded under the NSF Engineering program (CFDA 47.041), the three-year award period from September 2022 to August 2025 will support the research team's work exploring how to program 2D ionic liquid-based polymers for 3D manufacturing and control their...
This $800,000 Project Grant awarded by the National Science Foundation's (NSF) Mathematical and Physical Sciences program (CFDA 47.049) will enable Iowa State University of Science and Technology to develop new materials and manufacturing methods for 3D printing multi-material objects with varying mechanical properties. The key objectives are to use machine learning to create resins enabling extreme mechanical contrast, develop a multi-material 3D printing process using photoswitches, and...

This three-year, $399,750 Project Grant from the National Science Foundation's Division of Information and Intelligent Systems, under the Computer and Information Science and Engineering program (CFDA 47.070), will support the development of programmable visual capabilities for 3D printed objects through light-transfer techniques. The grant recipient, Texas A&M Engineering Experiment Station (doing business as Tees), will conduct material experiments to characterize light-transfer properties for sensing, communicating and displaying digital information without batteries. Researchers will work with domain experts and students to design prototypes utilizing these properties. Toolkits will be created to facilitate non-expert design of interactive devices conveying embedded information through visual literacy principles. The work aims to advance 3D printing capabilities for everyday smart objects while fostering consideration of visual design. Rigorous evaluation and user studies will validate the techniques and tools in serving this goal.

Generated 1/7/24, 12:19 PM