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NSF · NSFNSF

PFI-TT: Active Acoustic Noise Cancellation and Control for Scanning Probe Microscopy

Jason R Osborne·Rutgers University New Brunswick, NJ·2023–2026·ACTIVE
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INSTITUTION

Rutgers University New Brunswick, NJ

PRINCIPAL INVESTIGATOR

Jason R Osborne

FUNDING

$250K

YEAR

2023

MOONBASE SCORE

67/100

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Abstract

The broader impact/commercial potential of this Partnerships for Innovation - Technology Translation (PFI-TT) project is to create a technology to eliminate image distortions in scanning probe microscopes (SPM). An SPM is an instrument used for studying surfaces at the nanoscale level. The proposed technology is disruptive compared to existing noise isolation approaches as it is based on novel computer algorithms instead of bulky and costly hardware solutions. The success of the project will enable SPMs to attain sub-nanometer accuracy. The proposed solution is crucial for SPM companies to expand their footprints in the semiconductor and chip making industries. The proposed project aims to accomplish the following tasks: (1) achieve acoustic noise cancellation when the signal to noise ratio is low (as in cleanroom nanometrology application), by combining data-driven Kalman and Wiener filtering, sensing enhancement, and iterative optimization and adaptation together; (2) achieve acoustic noise control for in-liquid imaging of live biological species, by capturing and accounting for the hydrodynamic force effects; and (3) integrate the proposed algorithms into the software of commercial SPM systems. The proposed research features a holistic approach combining both online control and offline filtering, a data-driven, dynamics-based framework that eliminates the performance-robustness trade-off, a new SPM imaging mode that is robust to acoustic noise, and a gradient-based coherence minimization methodology that optimizes the performance with little to no need for a priori knowledge of the noise and the SPM system. This award reflects NSF's statutory mission and has been deemed worthy of support through evaluation using the Foundation's intellectual merit and broader impacts review criteria.

Active Acoustic Noise CancellationScanning Probe MicroscopySub-nanometer AccuracyKalman FilteringWiener FilteringNoise Control AlgorithmsNanometrologyHydrodynamic Force EffectsData-driven FrameworkSemiconductor Industry

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