Add DOIs and bibtex entries to paper, arXiv and Zenodo

Signed-off-by: Håkon Wiik Ånes <hwaanes@gmail.com>

README.md

@@ -1,8 +1,47 @@
 # Correlated grain/particle analysis from directly combined EBSD/BSE data
 
-Zenodo DOI coming after first `release' of repository.
+Zenodo DOI for this repository coming.
 
-This repository contains Jupyter notebook files, MATLAB scripts, and other files, apart from the raw BSE images and EBSD datasets, which are necessary to reproduce the results and figures in the paper *"Correlated subgrain and particle analysis of a recovered Al-Mn alloy by directly combining EBSD and backscatter electron imaging"*, which was recently submitted to *Materials Characterization*. The paper preprint is available on [arXiv](https://doi.org/10.48550/arXiv.2205.05514). The raw EBSD and BSE data used in the paper is available on [Zenodo](https://doi.org/10.5281/zenodo.6470217).
+This repository contains Jupyter notebook files, MATLAB scripts, and other files, apart from the raw BSE images and EBSD datasets, which are necessary to reproduce the results and figures in the paper *"Correlated subgrain and particle analysis of a recovered Al-Mn alloy by directly combining EBSD and backscatter electron imaging"*, which is published in *Materials Characterization* ([doi](https://doi.org/10.1016/j.matchar.2022.112228)):
+
+```bibtex
+@article{aanes2022correlated,
+  author   = {Håkon W. Ånes and Antonius T. J. {van Helvoort} and Knut Marthinsen},
+  title    = {Correlated subgrain and particle analysis of a recovered AlMn alloy by directly combining EBSD and backscatter electron imaging},
+  doi      = {10.1016/j.matchar.2022.112228},
+  issn     = {1044-5803},
+  pages    = {112228},
+  journal  = {Materials Characterization},
+  keywords = {Electron backscatter diffraction, Texture analysis, Particle analysis, Image registration, Data fusion},
+  year     = {2022},
+}
+
+```
+
+The paper preprint is available on *arXiv* ([doi](https://doi.org/10.48550/arXiv.2205.05514)):
+
+```bibtex
+@article{anes2022correlated_arxiv,
+  author  = {{\AA}nes, H{\aa}kon Wiik and van Helvoort, Antonius TJ and Marthinsen, Knut},
+  title   = {Correlated subgrain and particle analysis of a recovered Al-Mn alloy by directly combining EBSD and backscatter electron imaging},
+  doi     = {10.48550/arXiv.2205.05514},
+  journal = {arXiv preprint arXiv:2205.05514},
+  year    = {2022},
+}
+```
+
+The raw EBSD and BSE data used in the paper is available on *Zenodo* ([doi](https://doi.org/10.5281/zenodo.6470217)):
+
+```bibtex
+@dataset{aanes2022correlated_data,
+  author    = {Håkon Wiik Ånes and Antonius T. J. van Helvoort and Knut Marthinsen},
+  title     = {{Electron backscatter diffraction data and backscatter electron images from a cold-rolled and recovered Al-Mn alloy}},
+  doi       = {10.5281/zenodo.6470217},
+  note      = {{The data was acquired while Håkon Wiik Ånes received financial support from the Norwegian University of Science and Technology (NTNU) through the NTNU Aluminium Product Innovation Centre (NAPIC).}},
+  publisher = {Zenodo},
+  year      = {2022},
+}
+```
 
 The contents in this repository is licensed under the GPLv3+, since many of the softwares used have the same license.
 
@@ -19,7 +58,7 @@ pip install -r requirements.txt
 ```
 
 * `ebsd1_dewrap.ipynb`: EBSD datasets acquired with a NORDIF detector are sometimes written with the last column of patterns as the first column. This notebook checks if this is the case, places the patterns correctly in the map, and writes them to an HDF5 file in the kikuchipy h5ebsd format.
-* `ebsd2_preprocess.ipynb`: Generate indexing-independent views of an EBSD dataset (mean intensity map, virtual backscatter electron images, image quality map, and average neighbour dot product map) and calibrate the detector-sample geometry via projection center (PC) optimization with the [PyEBSDIndex Python package](https://github.com/USNavalResearchLaboratory/PyEBSDIndex) (cubic materials only!). An average PC is used in dictionary indexing.
+* `ebsd2_preprocess.ipynb`: Generate indexing-independent views of an EBSD dataset (mean intensity map, virtual backscatter electron images, image quality map, and average neighbour dot product map) and calibrate the detector-sample geometry via projection center (PC) optimization with the [PyEBSDIndex Python package](https://github.com/USNavalResearchLaboratory/PyEBSDIndex). An average PC is used in dictionary indexing.
 * `ebsd3_dictionary_indexing.ipynb`: Obtain crystal orientations from the EBSD patterns via dictionary indexing (DI) as implemented in kikuchipy. Requires an Al master pattern generated with EMsoft.
 * `ebsd4_refinement.ipynb`: Refine crystal orientations obtained from DI.
 * `generate_figures_in_paper.ipynb`: Generate final figures used in the paper.
@@ -30,11 +69,11 @@ Installation of packages has been tested to work on Linux (Ubuntu 22.04) and Win
 
 ### matlab_scripts
 
-MATLAB packages used in the scripts are [MTEX](https://mtex-toolbox.github.io/) and [export_fig](https://se.mathworks.com/matlabcentral/fileexchange/23629-export_fig).
+MATLAB packages used in the scripts are [MTEX](https://mtex-toolbox.github.io/) and [export_fig](https://mathworks.com/matlabcentral/fileexchange/23629-export_fig).
 
 * `estimate_gnd.m`: Estimate geometrically necessary disloations prior to grain and texture analysis.
 * `orientation_analysis.m`: Correlated analysis of subgrains and particles based on the multimodal dataset, specifically dispersoids at subgrain boundaries and subgrains at constituent particles.
 
 ### data
 
-The control points and processed BSE images (reference images) and EBSD intensity maps (sensed images) used in image registration are included in this directory. The raw EBSD datasets and BSE images are available on [Zenodo](https://doi.org/10.5281/zenodo.6470217).
+The control points and processed BSE images (reference images) and EBSD intensity maps (sensed images) used in image registration are included in this directory.