SBIR/STTR Research Award
SBIR Phase II: Model-Based Control for Chemical-Mechanical Planarization of Copper/low-k Films
Award amount
$476,695Program and phase
SBIR · Phase IIAward year
2009Award details
- Awarding agency
- National Science Foundation
- Branch
- Not reported
- Recipient company
- SC SOLUTIONS, INC.
- Proposal award date
- Not reported
- Contract end date
- Not reported
- UEI
- MGPZGMNLJ8R9
- Solicitation number
- NSF 07-551
- Topic code
- EL
Research abstract
This award is funded under the American Recovery and Reinvestment Act of 2009 (Public Law 111-5). This Small Business Innovation Research (SBIR) Phase II project will develop a commercial prototype of a real-time model-based controller software for next-generation Chemical-Mechanical Planarization(CMP) systems used in semiconductor wafer manufacturing. Planarization is an enabling step for semiconductor interconnects that is critical to the industry's keeping up with Moore's law. Future technology nodes of 32 nm and below require improved level of performance in planarization technology. Smaller dimensions and the use of more delicate low-k films pose increasingly stringent requirements on planarization performance. The successful development of the proposed controller software will help extend planarization to new levels of performance for 32 nm technology and beyond. The copper planarization market is anticipated to reach $824 million in 2009, and a next-generation CMP controller product will have a significant impact on the future of this market. The proposed innovations will help to accelerate the adoption of new dielectric structures in next-generation semiconductor devices.
Technology keywords
Not reported
Other awards by this recipient
Verified by the same UEI. These are other public SBIR/STTR award pages, not a merged company record.
- Quantum Control Optimization Methods
- Quantum Control Optimization Methods
- Use of High-Resolution Imaging Techniques for Condition Assessment and Damage Detection of Bridges
- Software Tools for Scalable Quantum Validation and Verification
- Digital Twins for Bridge Management through the Integrating of Computer Vision and Finite Element Models