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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 |

    The integration of computational material methods, artificial intelligence technology, and advanced in-situ experimental characterization techniques constitutes a foundational approach for unraveling the microstructural transport mechanisms within energy materials. The recent surge in mechanism elucidation, powered by these integrated methodologies, is widely acknowledged as a pivotal avenue for material innovations, consequently propelling advancements in new energy applications. This collection is dedicated to tracking the latest developments and publishing intriguing investigations pertaining to transport mechanisms within energy materials.

    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).