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ANDiE: the Autonomous Neutron Diffraction Explorer.

ANDiE the Autonomous Neutron Diffraction Explorer is a tool for autonomously discovering the magnetic transition temperature and transition dynamics of a material from neutron diffraction experiments. The Jupyter notebooks used to implement ANDiE can be found here: https://github.com/usnistgov/ANDiE-v1_0 The Jupyter notebooks contained therein are of ANDiE as implemented at the WAND2 instrument at the HB-2C beamline at the High-Flux Isotope Reactor (HFIR) at Oak Ridge National Laboratory (ORNL). The outputs of the cells are consistent with the autonomous experiment run as performed on 7/24/2021 and subsequent post-processing analysis for a powder sample Fe1.09Te on WAND2. The powder diffraction data for the autonomous experiments with Fe1.09Te and MnO powder samples, as well as ad hoc collected data for Fe1.09Te are available in the "ANDiE data.zip" folder. The data is in .xye format with 'x' being the diffraction angle (2?) in degrees, 'y' being the neutron intensity, and 'e' being the error in that intensity. The "List of Experiments.csv" file provides the metadata (including the sample temperature) about each diffraction measurement in "ANDiE data.zip" "Thermal_Outputs_run1_2021-08-02.p", "Isothermal_Outputs_run1_2021-08-02.p", and "Isothermal_1peak_Outputs_run1_2021-08-02.p" are example inference output files as generated by ANDiE for the autonomously collected data of the Fe1.09Te sample. These files are in the form of Pickled (Python 3.9) Pandas DataFrames. They are used as inputs to for the post-processing hypothesis testing step of ANDiE.

About this Dataset

Updated: 2024-02-22
Metadata Last Updated: 2021-08-23 00:00:00
Date Created: N/A
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Data Provided by:
Autonomous Experiments
Dataset Owner: N/A

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Table representation of structured data
Title ANDiE: the Autonomous Neutron Diffraction Explorer.
Description ANDiE the Autonomous Neutron Diffraction Explorer is a tool for autonomously discovering the magnetic transition temperature and transition dynamics of a material from neutron diffraction experiments. The Jupyter notebooks used to implement ANDiE can be found here: https://github.com/usnistgov/ANDiE-v1_0 The Jupyter notebooks contained therein are of ANDiE as implemented at the WAND2 instrument at the HB-2C beamline at the High-Flux Isotope Reactor (HFIR) at Oak Ridge National Laboratory (ORNL). The outputs of the cells are consistent with the autonomous experiment run as performed on 7/24/2021 and subsequent post-processing analysis for a powder sample Fe1.09Te on WAND2. The powder diffraction data for the autonomous experiments with Fe1.09Te and MnO powder samples, as well as ad hoc collected data for Fe1.09Te are available in the "ANDiE data.zip" folder. The data is in .xye format with 'x' being the diffraction angle (2?) in degrees, 'y' being the neutron intensity, and 'e' being the error in that intensity. The "List of Experiments.csv" file provides the metadata (including the sample temperature) about each diffraction measurement in "ANDiE data.zip" "Thermal_Outputs_run1_2021-08-02.p", "Isothermal_Outputs_run1_2021-08-02.p", and "Isothermal_1peak_Outputs_run1_2021-08-02.p" are example inference output files as generated by ANDiE for the autonomously collected data of the Fe1.09Te sample. These files are in the form of Pickled (Python 3.9) Pandas DataFrames. They are used as inputs to for the post-processing hypothesis testing step of ANDiE.
Modified 2021-08-23 00:00:00
Publisher Name National Institute of Standards and Technology
Contact mailto:[email protected]
Keywords Autonomous Experiments , Neutron Diffraction , Machine Learning , Active Learning , Artificial Intelligence
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}

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