Mechanical design of a flexural nanopositioning stage system for hard x-ray nanofocusing at the Advanced Photon Source 32-ID-C station

Shu, Deming; Andrade, Vincent De; Anton, Jayson; Kearney, Steven; Fezzaa, Kamel; Bean, Sunil; Deriy, Alex; Liu, Wenjun; Mäser, J.; Lai, Barry; Tischler, J. Z.; Carlo, Francesco De

doi:10.1117/12.2529384

Cited by 6 publications

(4 citation statements)

References 4 publications

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“…The reported distances are relative to the center of the undulator. In experimental hutch B, we built a Kirkpatrick-Baez (KB) mirror focusing system composed of an outward-reflecting, horizontally focusing bendable mirror using a flexure bender [24] and the upward-reflecting bimorph mirror for vertically focusing. Both mirrors were operated at a grazing angle of 3 mrad.…”

Section: Methodsmentioning

confidence: 99%

A real-time machine-learning-driven control system of a deformable mirror for achieving aberration-free hard X-ray wavefronts

Rebuffi¹,

Li²,

Qiao³

et al. 2023

Preprint

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A neural-network machine learning model is developed to control a bimorph adaptive mirror to achieve and preserve aberration-free coherent X-ray wavefronts at synchrotron radiation and free electron laser beamlines. The controller is trained on a mirror actuator response directly measured at a beamline with a real-time single-shot wavefront sensor, which uses a coded mask and wavelet-transform analysis. The system has been successfully tested on a bimorph deformable mirror at the 28-ID IDEA beamline of the Advanced Photon Source at Argonne National Laboratory. It achieved a response time of a few seconds and maintained desired wavefront shapes (e.g., a spherical wavefront) with sub-wavelength accuracy at 20 keV of X-ray energy. This result is significantly better than what can be obtained using a linear model of the mirror’s response. The developed system has not been tailored to a specific mirror and can be applied, in principle, to different kinds of bending mechanisms and actuators.

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Section: Methodsmentioning

confidence: 99%

A real-time machine-learning-driven control system of a deformable mirror for achieving aberration-free hard X-ray wavefronts

Rebuffi¹,

Li²,

Qiao³

et al. 2023

Preprint

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“…APS 32-ID full field imaging and transmission X-ray microscopy supports two experimental stations: 32-ID-B and 32-ID-C. 32-ID-C is designed to be a high-speed microscopy beamline with 2D imaging. , 32-ID-B features phase-contrast at 8 keV energy, 30 nm resolution, and has also XANES technique capabilities . The imaging time is a bit slower than that of the NSLS II 18-ID.…”

Section: Applications Of X-ray Ct To In Situ and Operando Studies In ...mentioning

confidence: 99%

X-ray Tomography Applied to Electrochemical Devices and Electrocatalysis

Lang,

Kulkarni,

Foster

et al. 2023

Chem. Rev.

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“…The monochromator was tuned to an energy of 20 keV (𝜆 = 0.062 nm) using the 5 th harmonic of the undulator. In experimental hutch B, we assembled a KB mirror focusing system consisting of an outboard-reflecting, horizontally focusing bendable mirror using an in-house flexure bender design [26] and an upward-reflecting PZT (lead zirconate titanate) bimorph mirror manufactured by JTEC Corporation (Osaka, Japan) for vertical focusing.…”

Section: -Id-b Beamlinementioning

confidence: 99%

AutoFocus: AI-driven alignment of nanofocusing X-ray mirror systems

Rebuffi,

Kandel,

Shi

et al. 2023

Preprint

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We describe the application of aan AI-driven system to autonomously align and focus complex x-ray mirror systems . The system has been developed and studied on a digital twin of nanofocusing X-ray beamlines, built using advanced optical simulation tools calibrated with wavefront sensing data collected at the beamline.We experimentally demonstrated that the system is systematically capable of positioning a focused beam on the sample, both by simulating the life cycle of the beamline with random perturbations due to typical variations in the light source and optical elements over time, and by conducting similar tests on an actual focusing system.

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Mechanical design of a flexural nanopositioning stage system for hard x-ray nanofocusing at the Advanced Photon Source 32-ID-C station

Cited by 6 publications

References 4 publications

A real-time machine-learning-driven control system of a deformable mirror for achieving aberration-free hard X-ray wavefronts

A real-time machine-learning-driven control system of a deformable mirror for achieving aberration-free hard X-ray wavefronts

X-ray Tomography Applied to Electrochemical Devices and Electrocatalysis

AutoFocus: AI-driven alignment of nanofocusing X-ray mirror systems

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