Graphene STEM Standard Datasets

Dyck, Ondrej

doi:10.13139/ORNLNCCS/1773705

Title: Graphene STEM Standard Datasets

Dataset
Other Related Research

Abstract

Graphene STEM datasets created by Ondrej Dyck. Datasets from July 2, 2018 C1 ArO graphene box1 lot 4670 (high res images, 100kV video graphene degradation).

Authors:

Dyck, Ondrej

ORNL-OLCF

Publication Date:: Wed Apr 14 00:00:00 EDT 2021

Research Org.:: Oak Ridge National Laboratory (ORNL), Oak Ridge, TN (United States). Oak Ridge Leadership Computing Facility (OLCF); Oak Ridge National Laboratory (ORNL), Oak Ridge, TN (United States)

Sponsoring Org.:: Office of Science (SC)

OSTI Identifier:: 1773705

DOI:: https://doi.org/10.13139/ORNLNCCS/1773705

Citation Formats


                    Dyck, Ondrej. Graphene STEM Standard Datasets.  United States: N. p., 2021. 
        Web.  doi:10.13139/ORNLNCCS/1773705.

Copy to clipboard


                    Dyck, Ondrej. Graphene STEM Standard Datasets.  United States.  doi:https://doi.org/10.13139/ORNLNCCS/1773705

Copy to clipboard


                    Dyck, Ondrej. 2021.  
"Graphene STEM Standard Datasets".  United States.  doi:https://doi.org/10.13139/ORNLNCCS/1773705.  https://www.osti.gov/servlets/purl/1773705. Pub date:Wed Apr 14 00:00:00 EDT 2021

Copy to clipboard


                    
@article{osti_1773705,

  title        = {Graphene STEM Standard Datasets},

  author       = {Dyck, Ondrej},

  abstractNote = {Graphene STEM datasets created by Ondrej Dyck. Datasets from July 2, 2018 C1 ArO graphene box1 lot 4670 (high res images, 100kV video graphene degradation).},

  doi          = {10.13139/ORNLNCCS/1773705},

  journal      = {},

  number       = ,

  volume       = ,

  place        = {United States},

  year         = {Wed Apr 14 00:00:00 EDT 2021},

  month        = {Wed Apr 14 00:00:00 EDT 2021}

}

Copy to clipboard

Dataset:

View Dataset

DOI: https://doi.org/10.13139/ORNLNCCS/1773705

Save / Share:

Export Metadata

Save to My Library

Similar records in DOE Data Explorer and OSTI.GOV collections:

Sm-BFO STEM Datasets

Dataset Nelson, Christopher ; Takeuchi, Ichiro ; Zhang, Ziaohang

Sm-doped BiFeO3 STEM datasets collected by Chris Nelson. Sample created at University of Maryland.
Defects in MX2 Phases (DMX) Dataset: STEM Digital Twins

Dataset Fuhr, Addis ; Ganesh, Panchapakesan ; Vasudevan, Rama K ; ...

DFT is used to optimize defects in monolayer MX2 phases. We calculate ~600 optimized defect structures, then use multislice simulations in abTEM to generate STEM digital twins, which can be used to train experimental ML. The reference paper for procedures and demonstration of their utility is https://arxiv.org/abs/2305.02917, and the images here correspond with the discussed "Messy" dataset.
DEEPEN Global Standardized Categorical Exploration Datasets for Magmatic Plays

Dataset Taverna, Nicole ; Caliandro, Nils ; King, Rachel

DEEPEN stands for DE-risking Exploration of geothermal Plays in magmatic ENvironments. As part of the development of the DEEPEN 3D play fairway analysis (PFA) methodology for magmatic plays (conventional hydrothermal, superhot EGS, and supercritical), weights needed to be developed for use in the weighted sum of the different favorability index models produced from geoscientific exploration datasets. This was done using two different approaches: one based on expert opinions, and one based on statistical learning. This GDR submission includes the datasets used to produce the statistical learning-based weights. While expert opinions allow us to include more nuanced information in the weights,more »« less
Multi-Species Complex and Standard Metabolomic Samples with Verified Truth Annotations Dataset

Dataset Degnan, David J ; Bramer, Lisa M ; Flores, Javier E ; ...

This dataset contains 4523251 (~6.35 GB) metabolite-spectra matches following identification with CoreMS. Data were manually curated as true positives, true negatives, or unknowns. Calculations for spectral similarity scores were carried out with two methods for a total of ~12.7 GB (6.35 * 2) of data. They are all .tsv files, though can easily be changed to .txt. The file types are: * human cerebrospinal fluid (CSF), human blood plasma human urine: already published here https://www.nature.com/articles/s41597-021-00894-y, • purchased FAMES standards • fungi species (A. niger, A. nidulans, T. reesei) • soil crust
Dataset: NewBio_SwgMxgWillowOnly

Dataset Davis, Maggie

Similar Records