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  • Collection |

    This collection focuses on the development and application of novel machine learning approaches to study the geometric, thermodynamic, kinetic, and electronic properties of defects in the solid state.

    Image: © A. Hartung / Stock.adobe.com
    Open for submissions

  • Collection |

    This collection is dedicated to tracking the latest developments and publishing intriguing investigations pertaining to transport mechanisms within energy materials.

    Image: Just for temporal use
    Open for submissions

  • Collection |

    Under extreme pressure, matter can exhibit novel or counter-intuitive phenomena such as superconductivity at unusually high-temperature, unexpected chemical stoichiometries and reaction kinetics, or new material phases.

    Image: Lars Plöger, Pixabay

  • Collection |

    This collection of papers brings together recent works published in npj Computational Materials that contribute towards high-throughput materials discovery. *Above image is a schematic of a high-throughput process for identifying transparent conductors, shown in the review paper G. Brunin etal., npj Computational Materials, 5 (2019) and originally published in R. Woods-Robinson et al., Chemistry of Materials, 30 (2018).

    Image: *Above image is an illustration of an abstract molecules network from Alfred Pasieka/Science Photo Library via Getty Images.

  • Collection |

    This collection brings together recent works published in npj Computational Materials that contribute towards the design of high performance thermoelectric materials.

    Image: *Above image shows the calculated partial charge density on the close-packed Se-Se-Se plane for thermoelectric Cu2SnSe3 doped for optimal performance, shown in the review paper J. Yang et al., npj Computational Materials, 2 (2016) and originally published in L. Xi et al., Physical Review B, 86 (2012).