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Dynamic Graph Sequence Data from Simulated Neutron Reflectometry Measurements

  • Eiffert, Brett | Oak Ridge National Laboratory
  • Zhang, Chen | Oak Ridge National Laboratory
  • Doucet, Mathieu | Oak Ridge National Laboratory
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Overview

Description

This dataset comprises dynamic graph sequences derived from simulated in-situ neutron reflectometry measurements, capturing the gradual evolution of a layer structure over time. Each graph sequence represents a synthetic sample, with node features detailing the scattering vector and corresponding reflectivity measurements, while adjacency matrices have corresponding reference material parameters attached as metadata. The dataset spans multiple sets, each with a different number of sequences, offering a comprehensive basis for training models that handle dynamic input sequences with embedded physics. This dataset is particularly suited for tackling inverse problems with hidden physical states that evolve over time, challenges that are typically difficult to address using conventional iterative fitting methods.

Funding resources

DOE contract number

DE-AC05-00OR22725

Originating research organization

Oak Ridge National Laboratory (ORNL), Oak Ridge, TN (United States)

Sponsoring organization

USDOE; ORNL Laboratory Directed Research and Development (LDRD)

Details

DOI

10.13139/OLCF/2437682

Release date

September 26, 2024

Dataset

Dataset type

ND Numeric Data

Software

HDF5 and Parquet readers needed for reading the data. DGL and PyTorch are recommended for training.

Acknowledgements

Papers using this dataset are requested to include the following text in their acknowledgements:

*Support for 10.13139/OLCF/2437682 is provided by the U.S. Department of Energy, project CADES, LDRD AI Initiative under Contract DE-AC05-00OR22725. This research used resources of the Oak Ridge Leadership Computing Facility, which is a DOE Office of Science User Facility.

Category

  • 36 MATERIALS SCIENCE

Keywords

  • reflectometry,
  • energy materials,
  • thin films