Computational methods articles within Nature

Featured

• Article
  29 November 2023 | Open Access

  An autonomous laboratory for the accelerated synthesis of novel materials

  An autonomous laboratory, the A-Lab, is presented that combines computations, literature data, machine learning and active learning, which discovered and synthesized 41 novel compounds from a set of 58 targets after 17 days of operation.

  • Nathan J. Szymanski
  • , Bernardus Rendy
  •  & Gerbrand Ceder

• Article
  08 November 2023 | Open Access

  Predicting crystal form stability under real-world conditions

  Accuracy of free-energy calculations can be improved by constructing an experimental benchmark for solid–solid free-energy differences, quantifying statistical errors for the computed free energies and placing both hydrate and anhydrate crystal structures on the same energy landscape.

  • Dzmitry Firaha
  • , Yifei Michelle Liu
  •  & Marcus A. Neumann

• Article | 05 October 2022

  Low-hysteresis shape-memory ceramics designed by multimode modelling

  Combining computational thermodynamics and data science tools with lattice engineering enables the design of shape-memory ceramics with reduced hysteresis.

  • Edward L. Pang
  • , Gregory B. Olson
  •  & Christopher A. Schuh

• Article | 15 January 2020

  Archimedean lattices emerge in template-directed eutectic solidification

  Directional solidification of a simple AgCl-KCl lamellar eutectic material is modified by the presence of a pillar template, leading to disordered, trefoil, quatrefoil, cinquefoil and hexafoil mesostructures.

  • Ashish A. Kulkarni
  • , Erik Hanson
  •  & Paul V. Braun

• Letter | 12 August 2019

  Position and momentum mapping of vibrations in graphene nanostructures

  Investigation of a free-standing graphene monolayer using a technique based on transmission electron microscopy allows identification of atomic vibrations characteristic of the bulk or the edge of the sample.

  • Ryosuke Senga
  • , Kazu Suenaga
  •  & Thomas Pichler

• Letter | 03 July 2019

  Unsupervised word embeddings capture latent knowledge from materials science literature

  Natural language processing algorithms applied to three million materials science abstracts uncover relationships between words, material compositions and properties, and predict potential new thermoelectric materials.

  • Vahe Tshitoyan
  • , John Dagdelen
  •  & Anubhav Jain

• Letter | 27 September 2017

  Probing the limits of metal plasticity with molecular dynamics simulations

  The limits of dislocation-mediated metal plasticity are studied by using in situ computational microscopy to reduce the enormous amount of data from fully dynamic atomistic simulations into a manageable form.

  • Luis A. Zepeda-Ruiz
  • , Alexander Stukowski
  •  & Vasily V. Bulatov

• Letter | 15 June 2017

  Slush-like polar structures in single-crystal relaxors

  Molecular dynamics simulations of the Pb(Mg_1/3,Nb_2/3)O₃–PbTiO₃ relaxor reveal a multi-domain state analogous to the slush state of water that provides an explanation for the unusual properties of relaxors.

  • Hiroyuki Takenaka
  • , Ilya Grinberg
  •  & Andrew M. Rappe

• Letter | 15 June 2016

  Intrinsic ferroelectric switching from first principles

  Molecular dynamics simulations of 90° domain walls in PbTiO₃ are used to construct a nucleation-and-growth-based analytical model that quantifies the dynamics of many types of domain walls in various ferroelectrics, suggesting intrinsic domain-wall motion as a universal mechanism for ferroelectric switching.

  • Shi Liu
  • , Ilya Grinberg
  •  & Andrew M. Rappe

• News & Views | 19 December 2012

  Trustworthy predictions

  A method has been developed to compute the precise quantum-mechanical properties of certain insulators. This approach avoids the uncertainties that are intrinsic to predictions made using existing approaches. See Article p.365

  • Paul R. C. Kent

• News & Views | 21 November 2012

  Substitution with vision

  A method has been developed for predicting the stability and elasticity of certain alloys for millions of atomic configurations of the materials. This approach should help to identify materials with optimized properties. See Letter p.740

  • Gus L. W. Hart