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Scanning Tunneling Microscope based Hydrogen Depassivation Lithography Automation Via Artificial Intelligence

Award Information
Agency: Department of Energy
Branch: N/A
Contract: DE-SC0019691
Agency Tracking Number: 242220
Amount: $149,915.00
Phase: Phase I
Program: STTR
Solicitation Topic Code: 16a
Solicitation Number: DE-FOA-0001940
Solicitation Year: 2019
Award Year: 2019
Award Start Date (Proposal Award Date): 2019-02-19
Award End Date (Contract End Date): 2020-02-18
Small Business Information
1301 North Plano Road
Richardson, TX 75081-2426
United States
DUNS: 796537269
HUBZone Owned: No
Woman Owned: No
Socially and Economically Disadvantaged: No
Principal Investigator
 Ehud Fuchs
 (972) 792-1663
Business Contact
 John Randall
Phone: (972) 792-1648
Research Institution
 Oak Ridge National Laboratory
1 Bethel Valley Road
Oak Ridge, TN 37830-8050
United States

 Federally Funded R&D Center (FFRDC)

Atomically Precise Manufacturing will bring enormous energy savings through improved efficiency in power generation and use, via light weighting, reduced friction and wear, and a host of other improvements in materials and active mechanisms. Atomically Precise Manufacturing will bring considerable benefit to our technology, economy, and standard of living. However, significant technological development will be required before Atomically Precise Manufacturing can be realized as a reliable and efficient manufacturing process. A promising technology that is being used to develop Atomically Precise Manufacturing is Scanning Tunneling Microscope (STM) based hydrogen depassivation lithography that can make atomically precise patterns on surfaces. However, hydrogen depassivation lithography is in early stages of transitioning from a microscope technology to a lithography technology. Currently a human expert is required to look at images and make some judgement calls about how to complete the patterning process. To get the human out of the loop so that the patterning process can be automated, faster, and more reliable, Artificial Intelligence guided by physics of the system will be developed to provide the required image analysis capabilities. In Phase I, Zyvex Labs will work with applied Artificial Intelligence experts at Oak Ridge National Lab to develop an AI STM image analysis capability that can identify key features on the Si (100) 2X1 H passivated surfaces. This will allow automated assessment of the lithography process as it is being carried out so that conditions may be optimized even in the face of tip variation and surface defects to create atomically precise patterns. The image analysis will also enable error detection and correction processes to approach patterning perfection. Using these capabilities we will develop sophisticated and adaptable automation processes. If successfully developed, Artificial Intelligence guided hydrogen depassivation lithography will initially make small but extremely valuable products like solid state Analog Quantum Simulation devices to better understand quantum physics and help bring the expected amazing range benefits of quantum materials to the general public, and perhaps a little further down the road the spectacular benefits of quantum computation and communication. Even though massively parallel hydrogen depassivation lithography will be developed, it will still have limited throughput capabilities that can be leveraged by using hydrogen depassivation lithography to make nanoimprint or even roll to roll templates that will dramatically reduce the cost of making extremely accurate patterns at the nanoscale and above. One example application would be Atomically Precise membrane filters which will dramatically reduce manufacturing costs in chemical, petrochemical, and pharmaceutical processing.

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

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