Papers



Submit a Paper!

Browse ReproHack papers

  • Droplet impact onto a spring-supported plate: analysis and simulations

    Authors: Michael J. Negus, Matthew R. Moore, James M. Oliver, Radu Cimpeanu
    DOI: https://doi.org/10.1007/s10665-021-10107-5
    Submitted by MNegus      
      Mean reproducibility score:   8.0/10   |   Number of reviews:   1
    Why should we attempt to reproduce this paper?

    The direct numerical simulations (DNS) for this paper were conducted using Basilisk (http://basilisk.fr/). As Basilisk is a free software program written in C, it can be readily installed on any Linux machine, and it should be straightforward to then run the driver code to re-produce the DNS from this paper. Given this, the numerical solutions presented in this paper are a result of many high-fidelity simulations, which each took approximately 24 CPU hours running between 4 to 8 cores. Hence the difficulty in reproducing the results should mainly be in the amount of computational resources it would take, so HPC resources will be required. The DNS in this paper were used to validate the presented analytical solutions, as well as extend the results to a longer timescale. Reproducing these numerical results will build confidence in these results, ensuring that they are independent of the system architecture they were produced on.

  • 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.

  • Encapsulated Nanowires: Boosting Electronic Transport in Carbon Nanotubes

    Authors: Andrij Vasylenko, Jamie Wynn, Paulo Medeiros, Andrew J Morris, Jeremy Sloan, David Quigley
    DOI: 10.1103/PhysRevB.95.121408
    Submitted by dquigley      
      Mean reproducibility score:   5.0/10   |   Number of reviews:   2
    Why should we attempt to reproduce this paper?

    DFT calculations are in principle reproducible between different codes, but differences can arise due to poor choice of convergence tolerances, inappropriate use of pseudopotentials and other numerical considerations. An independent validation of the key quantities needed to compute electrical conductivity would be valuable. In this case we have published our input files for calculating the four quantities needed to parametrise the transport simulations from which we compute the electrical conductivity. These are specifically electronic band structure, phonon dispersions, electron-phonon coupling constants and third derivatives of the force constants. Each in turn in more sensitive to convergence tolerances than the last, and it is the final quantity on which the conclusions of the paper critically depend. Reference output data is provided for comparison at the data URL below. We note that the pristine CNT results (dark red line) in figure 3 are an independent reproduction of earlier work and so we are confident the Boltzmann transport simulations are reproducible. The calculated inputs to these from DFT (in the case of Be encapsulation) have not been independently reproduced to our knowledge.

  • Optimizing the Use of Carbonate Standards to Minimize Uncertainties in Clumped Isotope Data

    Authors: Ilja J. Kocken, Inigo A. Müller, Martin Ziegler
    DOI: 10.1029/2019GC008545
    Submitted by japhir      

    Why should we attempt to reproduce this paper?

    Even though the approach in the paper focuses on a specific measurement (clumped isotopes) and how to optimize which and how many standards we use, I hope that the problem is general enough that insight can translate to any kind of measurement that relies on machine calibration. I've committed to writing a literate program (plain text interspersed with code chunks) to explain what is going on and to make the simulations one step at a time. I really hope that this is understandable to future collaborators and scientists in my field, but I have not had any code review internally and I also didn't receive any feedback on it from the reviewers. I would love to see if what in my mind represents "reproducible code" is actually reproducible, and to learn what I can improve for future projects!

Search for papers

Filter by tags

Python R GDAL GEOS GIS Shiny PROJ Galaxies Astronomy HPC Databases Binder Social Science Stata make Computer Science Jupyter Notebook tidyverse emacs literate earth sciences clumped isotopes org-mode geology eyetracking LaTeX Git ArcGIS Docker Drake SVN knitr C Matlab Mathematica Meta-analysis swig miniconda tensorflow keras Pandas SQL neuroscience robotics deep learning planner reiforcement learning Plasma physics Hybrid-PIC EPOCH Laser Gamma-ray X-ray radiation Petawatt Fortran plasma PIC physics Monte Carlo Atomistic Simulation LAMMPS Electron Transport DFT descriptors interatomic potentials machine learning Molecular Dynamics Python scripting AIRSS structure prediction density functional theory high-throughput machine-learning RNA bioinformatics CFD Fluid Dynamics OpenFOAM C++ DNS Mathematics Droplets Basilisk Particle-In-Cell psychology Stan Finance SAS Replication crisis Economics Malaria consumer behavior number estimation mental arithmetic psychophysics Archaeology Precipitation Epidemiology Parkrun Health Health Economics HTA plumber science of science Zipf networks city size distribution urbanism literature review Preference Visual Questionnaire Mann-Whitney Correlation Conceptual replication Cognitive psychology Multinomial processing tree (MPT) modeling #urbanism #R k-means cluster analysis city-regions Urban Knowledge Systems Topic modelling Planning Support Systems Software Citation Quarto snakemake Numerical modelling Ocean climate physical oceanography apptainer oceanography All tags Clear tags

Key

  Associated with an event
  Available for general review
  Public reviews welcome