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Automated In-situ Large-area De-processing of ICs with High Throughput

Award Information
Agency: Department of Defense
Branch: Defense Microelectronics Activity
Contract: HQ072720C0005
Agency Tracking Number: 20-0D0
Amount: $999,638.00
Phase: Phase II
Program: STTR
Solicitation Topic Code: DMEA18B-001
Solicitation Number: 18.B
Solicitation Year: 2018
Award Year: 2020
Award Start Date (Proposal Award Date): 2020-03-18
Award End Date (Contract End Date): 2022-03-31
Small Business Information
10501 Research Rd SE Suite C
Albuquerque, NM 87123
United States
DUNS: 153582200
HUBZone Owned: No
Woman Owned: No
Socially and Economically Disadvantaged: No
Principal Investigator
 Michael Strizich
 (505) 765-2498
Business Contact
 Marq Smith
Phone: (505) 765-2495
Research Institution
 University of Florida
 Navid Asadi Navid Asadi
207 Grinter Hall
Gainsville, FL 32611
United States

 (352) 294-1075
 Nonprofit College or University

Phase II is the continuing effort to demonstrate the feasibility of producing an automated delayering and imaging system with end point detection, material density detection with built in neural network error correction. This process, coined fast Automated Delayering-Image Capture System (ADICS) leverages off of the existing Pix2Net which is a proven automated imaging 3D microchip reconstruction software suite. This will provide a fast track to a system that automates both the delayering and imaging in situ with initial feasibility studies done on commercially available dual beam Focused Ion Beam (FIB) / Scanning Electron Microscope (SEM) system, and more specialized wide spot FIB systems. MSI’s proven reverse engineering workflow and existing Pix2Net™ software tool suite has enabled rapid extraction of IC feature sets to form a comprehensive ‘signature’ for IP analysis verification, complete GDS II and design extractions. Despite this success, automated delayering of the microchip has been elusive. A significant opportunity exists leveraging off of the existing Pix2Net™ software suite, were the in situ removal of layers, end point detection, and image capture can be automated and incorporated into a new API leveraging off of the Pix2Net™ workflow.

* Information listed above is at the time of submission. *

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