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  • What do analyses of city size distributions have in common?

    Authors: Clémentine Cottineau
    DOI: 10.1007/s11192-021-04256-8
    Submitted by clementinecottineau      
      Mean reproducibility score:   8.0/10   |   Number of reviews:   1
    Why should we attempt to reproduce this paper?

    This article was meant to be entirely reproducible, with the data and code published alongside the article. It is however not embedded within a container (e.g. Docker). Will it past the reproducibility test tomorrow? next year? I'm curious.

  • Accelerating the prediction of large carbon clusters via structure search: Evaluation of machine-learning and classical potentials

    Authors: Bora Karasulu, Jean-Marc Leyssale, Patrick Rowe, Cedric Weber, Carla de Tomas
    DOI: 10.1016/j.carbon.2022.01.031
    Submitted by bkarasulu    
    Number of reviews:   1
    Why should we attempt to reproduce this paper?

    This paper presents a fine example of high-throughput computational materials screening studies, mainly focusing on the carbon nanoclusters of different sizes. In the paper, a set of diverse empirical and machine-learned interatomic potentials, which are commonly used to simulate carbonaceous materials, is benchmarked against the higher-level density functional theory (DFT) data, using a range of diverse structural features as the comparison criteria. Trying to reproduce the data presented here (even if you only consider a subset of the interaction potentials) will help you devise an understanding as to how you could approach a high-throughput structure prediction problem. Even though we concentrate here on isolated/finite nanoclusters, AIRSS (and other similar approaches like USPEX, CALYPSO, GMIN, etc.,) can also be used to predict crystal structures of different class of materials with applications in energy storage, catalysis, hydrogen storage, and so on.

  • New Insight into the Stability of CaCO3 Surfaces and Nanoparticles via Molecular Simulation

    Authors: A. Matthew Bano, P. Mark Rodger, and David Quigley
    DOI: 10.1021/la501409j
    Submitted by dquigley      

    Why should we attempt to reproduce this paper?

    The negative surface enthalpies in figure 5 are surprising. At least one group has attempted to reproduce these using a different code and obtained positive enthalpies. This was attributed to the inability of that code to independently relax the three simulation cell vectors resulting in an unphysical water density. This demonstrates how sensitive these results can be to the particular implementation of simulation algorithms in different codes. Similarly the force field used is now very popular. Its functional form and full set of parameters can be found in the literature. However differences in how different simulation codes implement truncation, electrostatics etc can lead to significant difference in results such as these. It would be a valuable exercise to establish if exactly the same force field as that used here can be reproduced from only its specification in the literature. The interfacial energies of interest should be reproducible with simulations on modest numbers of processors (a few dozen) with run times for each being 1-2 days. Each surface is an independent calculation and so these can be run concurrently during the ReproHack.

  • Investigation into the annotation of protocol sequencing steps in the sequence read archive

    Authors: Alnasir, Jamie, and Hugh P. Shanahan.
    Submitted by hub-admin  

    Why should we attempt to reproduce this paper?

    Metadata annotation is key to reproducibility in sequencing experiments. Reproducing this research using the scripts provided will also show the current level of annotation in years since 2015 when the paper was published.

    Tags: Python SQL
  • Analytical solutions for the isobaric evaporation of pure cryogens in storage tanks

    Authors: Felipe Huerta, Velisa Vesovic,
    DOI: 10.1016/j.ijheatmasstransfer.2019.118536
    Submitted by hub-admin    

    Why should we attempt to reproduce this paper?

    1. Because it contains customized numerical methods to implement analytical solutions for an engineering problem relevant to cryogenic storage. This will become increasingly relevant in the future with the increase in the use of liquid hydrogen and LNG as fuel. 2. The storage tank is implemented as a Class and there is an opportunity to understand the object oriented programming mindset of the authors. 3. In the provided Jupyter Notebook, thermodynamic data for nitrogen and methane are provided which enable the users the quick implementation. 4. To reproduce some of the figures and results, the storage tanks need to be modified with inputs available in the paper.

    Tags: Python Matlab
  • Good Me Bad Me: Prioritization of the Good-Self During Perceptual Decision-Making

    Authors: Hu, C.-P., Lan, Y., Macrae, C. N., & Sui, J.
    DOI: 10.1525/collabra.301
    Submitted by hub-admin    
      Mean reproducibility score:   7.0/10   |   Number of reviews:   1
    Why should we attempt to reproduce this paper?

    It'll a great helpful to independently check the scientific record I've published, so that errors, if there are any, could be corrected. Also, I will learn how to share the data in a more accessible to other if you could give me feedback.

    Tags: Python R Matlab
  • Cell Contractility Facilitates Alignment of Cells and Tissues to Static Uniaxial Stretch

    Authors: Rens, E. G., & Merks, R. M. H.
    Submitted by hub-admin    
      Mean reproducibility score:   1.0/10   |   Number of reviews:   2
    Why should we attempt to reproduce this paper?

    This paper shows a fun and interesting simulation result. I find it (of course) very important that our results are reproducible. In this paper, however, we did not include the exact code for these specific simulations, but the results should be reproducible using the code of our previous paper in PLOS Computational Biology (Van Oers, Rens et al. https://doi.org/10.1371/journal.pcbi.1003774). I am genuinely curious to see if there is sufficient information for the Biophys J paper or if we should have done better. Other people have already successfully built upon the 2014 (PLOS) paper using our code; see e.g., https://journals.aps.org/pre/abstract/10.1103/PhysRevE.97.012408 and https://doi.org/10.1101/701037).

    Tags: C Matlab

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