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Machine Learning-Driven Automated Scanning Probe Microscopy for Ferroelectrics
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- Journal:
- / Volume 28 / Issue S1 / August 2022
- Published online by Cambridge University Press:
- 22 July 2022, pp. 2924-2926
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- August 2022
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Python and FPGA-based Workflow for Automated and Interoperable Scanning Probe Microscopy
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- Journal:
- / Volume 28 / Issue S1 / August 2022
- Published online by Cambridge University Press:
- 22 July 2022, pp. 3114-3115
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- August 2022
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Role of Defects and Structure Evolution across Ferroelectric Phase Transitions Studied by Quantitative Aberration-Corrected STEM
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- Journal:
- / Volume 28 / Issue S1 / August 2022
- Published online by Cambridge University Press:
- 22 July 2022, pp. 2360-2361
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- August 2022
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From Event Detection to Physical Hypothesis Learning via Automated and Autonomous Microscopy
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- Journal:
- / Volume 28 / Issue S1 / August 2022
- Published online by Cambridge University Press:
- 22 July 2022, pp. 2062-2063
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- August 2022
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Automated Experiment in SPM: Bayesian Optimization for efficient searching of parameter space to maximize functional response
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- Journal:
- / Volume 27 / Issue S1 / August 2021
- Published online by Cambridge University Press:
- 30 July 2021, pp. 470-471
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- August 2021
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Quantitative Aberration-Corrected STEM for Studies of Oxide Superlattices and Topological Defects in Layered Ferroelectrics
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- Journal:
- / Volume 26 / Issue S2 / August 2020
- Published online by Cambridge University Press:
- 30 July 2020, pp. 1194-1195
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- August 2020
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Bayesian Microscopy: Model Selection for Extracting Weak Nonlinearities from Scanning Probe Microscopy Data
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- Journal:
- / Volume 26 / Issue S2 / August 2020
- Published online by Cambridge University Press:
- 30 July 2020, pp. 2126-2127
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- August 2020
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