Papers



Submit a Paper!

Browse ReproHack papers

  • 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.

  • Growth Dynamics of Independent Gametophytes of Pleurosoriopsis makinoi ( Polypodiaceae)

    Authors: Atsushi Ebihara, Joel H. Nitta, Yurika Matsumoto, Yuri Fukazawa, Marie Kurihara, Hitomi Yokote, Kaoru Sakuma, Otowa Azakami, Yumiko Hirayama, Ryoko Imaichi
    Submitted by joelnitta    
      Mean reproducibility score:   10.0/10   |   Number of reviews:   1
    Why should we attempt to reproduce this paper?

    It uses the drake R package that should make reproducibility of R projects much easier (just run make.R and you're done). However, it does depend on very specific package versions, which are provided by the accompanying docker image.

    Tags: R Docker Drake

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 R package structural equation modeling bayes factor Forest Simulations Models of forest dynamics multi-lab study mice mechanics growth Tissue Cells Clustering Expectation-Maximization bootstrapping R software Position Weight Matrices singularity neuroimaging effect size biology replicability cancer reproducibility csv osf preclinical research genomics All tags Clear tags

Key

  Associated with an event
  Available for general review
  Public reviews welcome