New publication in ACS Applied Materials & Interfaces

| categories: news, publication | tags: | View Comments

Titania can be grown as an epitaxial thin film on many perovskites. The structure of the film depends on the perovskite, as well as the orientation of the surface the film grows on. In this work, we show which factors determine this, including epitaxial strain, and interface energies. In general no single factor determines all the behavior, but when considered collectively, our computational analysis correctly predicts which thin film polymorph is observed experimentally most of the time.

@article{xu-2017-first-princ,
  author =       {Xu, Zhongnan and Salvador, Paul A. and Kitchin, John R.},
  title =        {First-Principles Investigation of the Epitaxial Stabilization
                  of Oxide Polymorphs: \ce{TiO2} on \ce{(Sr,Ba)TiO3}},
  journal =      {ACS Applied Materials \& Interfaces},
  volume =       0,
  number =       {ja},
  pages =        {null},
  year =         2017,
  doi =          {10.1021/acsami.6b11791},
  url =          {https://doi.org/10.1021/acsami.6b11791},
  eprint =       { https://doi.org/10.1021/acsami.6b11791 },
  note =         {PMID: 28004912},
}

Copyright (C) 2017 by John Kitchin. See the License for information about copying.

org-mode source

Org-mode version = 9.0.3

Read and Post Comments

Using Twitter cards for better tweets

| categories: publication | tags: | View Comments

@article{thirumalai-2015-pt-pd,
  author =       "Hari Thirumalai and John R. Kitchin",
  title =        {The Role of Vdw Interactions in Coverage Dependent Adsorption
                  Energies of Atomic Adsorbates on Pt(111) and Pd(111)},
  journal =      "Surface Science ",
  pages =        " - ",
  year =         2015,
  doi =          {10.1016/j.susc.2015.10.001},
  url =
                  "http://www.sciencedirect.com/science/article/pii/S0039602815003052",
  issn =         "0039-6028",
}

See it here: http://www.sciencedirect.com/science/article/pii/S0039602815003052.

The main goal of this post is to test run using a Twitter card to make better tweets about publications.

This post did not work quite like I anticipated, mostly because of the way I publish my blog which focuses only on the HTML body. The meta tags that are needed for Twitter do not seem to get put in the header as needed. If I do a regular org export with HTML_HEAD options to get this page: http://kitchingroup.cheme.cmu.edu/publications/twitter-card.html, it did work. The page is pretty bare, but it could be embellished without much work.

Tweeting that URL led to this tweet:

On Twitter, this showed an image of the picture on the page, and linked directly to the page I made. The image is sized a little large and doesn't fit in card quite right, but this is probably fixable. This whole process could be smoothed out a lot with a custom export to get the twitter meta tags in the right place, and maybe provide links to bibtex files, analytics, etc. Sounds like a fun project ;)

Copyright (C) 2016 by John Kitchin. See the License for information about copying.

org-mode source

Org-mode version = 8.3.5

Read and Post Comments

New publication in ACS Catalysis

| categories: news, publication | tags: | View Comments

DFT calculations are not exact, and the uncertainties in a calculation can impact conclusions you draw from the results. In this work, we quantify the uncertainty in the adsorption energies on Pt(111) and (100) of oxygenated intermediates relevant to the oxygen reduction reaction mechanism. We then propagate these uncertainties to the volcano plot of activity that results from them, and show how this approach helps inform us about the reliability of the predicted trends.

@article{deshpande16_quant_uncer_activ_volcan_relat,
  author =       {Siddharth Deshpande and John R. Kitchin and Venkatasubramanian
                  Viswanathan },
  title =        {Quantifying Uncertainty in Activity Volcano Relationships for
                  Oxygen Reduction Reaction},
  journal =      {ACS Catalysis},
  volume =       0,
  number =       {ja},
  pages =        {null},
  year =         2016,
  doi =          {10.1021/acscatal.6b00509},
  URL =          { https://doi.org/10.1021/acscatal.6b00509 },
  eprint =       { https://doi.org/10.1021/acscatal.6b00509 },
}

Copyright (C) 2016 by John Kitchin. See the License for information about copying.

org-mode source

Org-mode version = 8.3.4

Read and Post Comments

New publication in International Journal of Digital Libraries

| categories: news, publication | tags: | View Comments

We have a new paper out on using org-mode in publishing. The idea is to use org-mode to automate data embedding in publications. For example, in org-mode tables can serve as data sources. We show how you can automatically embed the tables as csv files in PDF or HTML when the org-file is exported. Similarly, all the code blocks are embedded as extractable files at export time. This increases the reusability of the data and code in papers.

Check out the preprint here: https://github.com/KitchinHUB/kitchingroup-66

@Article{Kitchin2016,
  author =       "Kitchin, John R. and Van Gulick, Ana E. and Zilinski, Lisa D.",
  title =        "Automating data sharing through authoring tools",
  journal =      "International Journal on Digital Libraries",
  year =         "2016",
  pages =        "1--6",
  abstract =     "In the current scientific publishing landscape, there is a
                  need for an authoring workflow that easily integrates data and
                  code into manuscripts and that enables the data and code to be
                  published in reusable form. Automated embedding of data and
                  code into published output will enable superior communication
                  and data archiving. In this work, we demonstrate a proof of
                  concept for a workflow, org-mode, which successfully provides
                  this authoring capability and workflow integration. We
                  illustrate this concept in a series of examples for potential
                  uses of this workflow. First, we use data on citation counts
                  to compute the h-index of an author, and show two code
                  examples for calculating the h-index. The source for each
                  example is automatically embedded in the PDF during the export
                  of the document. We demonstrate how data can be embedded in
                  image files, which themselves are embedded in the document.
                  Finally, metadata about the embedded files can be
                  automatically included in the exported PDF, and accessed by
                  computer programs. In our customized export, we embedded
                  metadata about the attached files in the PDF in an Info field.
                  A computer program could parse this output to get a list of
                  embedded files and carry out analyses on them. Authoring tools
                  such as Emacs + org-mode can greatly facilitate the
                  integration of data and code into technical writing. These
                  tools can also automate the embedding of data into document
                  formats intended for consumption.",
  issn =         "1432-1300",
  doi =          "10.1007/s00799-016-0173-7",
  url =          "https://doi.org/10.1007/s00799-016-0173-7"
}

Copyright (C) 2016 by John Kitchin. See the License for information about copying.

org-mode source

Org-mode version = 8.3.4

Read and Post Comments

New publication in AICHE J.

| categories: news, publication | tags: | View Comments

This paper uses a kernel regression method trained on a large set of DFT calculations from the Materials Project to design new materials. A notable feature of this approach is it opens the door to inverse design, since the mathematical form of the regression is accessible. In the paper we predict electronic properties and elastic constants for a large number of metal oxides. Congratulations Bruno for this work!

See the paper here: http://onlinelibrary.wiley.com/doi/10.1002/aic.15251/full

@article {AIC:AIC15251,
  author =       {Calfa, Bruno A. and Kitchin, John R.},
  title =        {Property prediction of crystalline solids from composition and
                  crystal structure},
  journal =      {AIChE Journal},
  issn =         {1547-5905},
  url =          {https://doi.org/10.1002/aic.15251},
  doi =          {10.1002/aic.15251},
  pages =        {n/a--n/a},
  keywords =     {crystal property prediction, data analytics, kernel
                  regression, crystal composition and structure, exhaustive
                  enumeration algorithm},
  year =         {2016},
}

Copyright (C) 2016 by John Kitchin. See the License for information about copying.

org-mode source

Org-mode version = 8.2.10

Read and Post Comments

« Previous Page -- Next Page »