Bid opportunityOpen
Semiconductor Process Residual Gas Analyzer
COMMERCE, DEPARTMENT OF › NATIONAL INSTITUTE OF STANDARDS AND TECHNOLOGY › DEPT OF COMMERCE NIST
Response deadlineSep 14, 2026 10:00 AM EDT
View official notice on SAM.gov ↗ (opens in a new tab)
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Key decision factors
- Response deadline
- Sep 14, 2026 10:00 AM EDT
- Posted
- Aug 31, 2026 12:00 AM EDT
- Notice type
- Solicitation
- Set-aside
- Not provided or not applicable
- NAICS
- 334516
- PSC
- 6640
- Place of performance
- Gaithersburg, Maryland
- Current status
- Open
Notice details
- Official status
- Open
- Normalized group
- Bid opportunity
- Notice ID
- c2d8306f9f524c509e8d9f56ca1c9f02
- Solicitation number
- 1333ND26QNB640573
Description
Displayed as sanitized plain text from SAM.gov. Retrieved Sep 1, 2026 10:24 PM EDT.
SOLICITATION 1333ND26QNB640573 Semiconductor Process Residual Gas Analyzer This is a solicitation for commercial items prepared in accordance with the format in RFO Subpart 12.2, as supplemented with additional information included in this notice. This announcement constitutes the only solicitation; quotations are being requested, and a separate written document will not be issued. This solicitation is a Request for Quotation (RFQ). The associated North American Industrial Classification System (NAICS) code for this procurement is 334516 – Analytical Laboratory Instrument Manufacturing with a Small Business size standard of 1,000 Employees. This requirement will be a Full and Open Competition. The Chemical Process and Nuclear Measurements Group is seeking a semiconductor-grade Process Residual Gas Analyzer (RGA) for use on flow systems, including an ALD reactor, as part of a CHIPS R&D Metrology program. This program focuses on developing digital twin technology for semiconductor manufacturing equipment. The flow systems, equipped with in situ and inline sensors, are used to acquire process data on thin film growth characterization. The RGA will serve as an online process diagnostic. The RGA must be compatible with low-volatility organometallic and metal halide precursors and process gases. The data and models generated by this project will lead to improvements in process optimization and control, ultimately resulting in cost savings for the US semiconductor industry.
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No major pursuit restriction detected
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