Insight 27 May 2021

Computational Materials Design

Computation plays a vital role in the analysis of the materials that are needed to address current complex needs such as energy, information technology, or operations under extreme conditions. This Insight discusses the role of simulation for the understanding of material behaviour, and how these approaches may be used to enable materials design.

Content

Computational materials design
- Stephen Shevlin
- Bruno Castro
- Xin Li
Editorial27 May 2021 Nature Materials
Discovering and understanding materials through computation

This Perspective provides an overview of the different approaches used to understand the behaviour of materials at different length scales and timescales through computation, and outlines future challenges in the description of complex systems or ultrafast non-equilibrium behaviour.
- Steven G. Louie
- Yang-Hao Chan
- Diana Y. Qiu
Perspective27 May 2021 Nature Materials
Electronic-structure methods for materials design

Simulations can be used to accelerate the characterization and discovery of materials. Here we Review how electronic-structure methods such as density functional theory work, what properties they can be used to predict and how they can be used to design materials.
- Nicola Marzari
- Andrea Ferretti
- Chris Wolverton
Review Article27 May 2021 Nature Materials
Machine-learned potentials for next-generation matter simulations

Materials simulations are now ubiquitous for explaining material properties. This Review discusses how machine-learned potentials break the limitations of system-size or accuracy, how active-learning will aid their development, how they are applied, and how they may become a more widely used approach.
- Pascal Friederich
- Florian Häse
- Alán Aspuru-Guzik
Review Article27 May 2021 Nature Materials
From predictive modelling to machine learning and reverse engineering of colloidal self-assembly

This Review provides an overview of computational tools and strategies, from simulation methods to machine learning and reverse-engineering approaches, used for the design of soft materials made from self-assembling colloids and nanoparticles.
- Marjolein Dijkstra
- Erik Luijten
Review Article27 May 2021 Nature Materials
Mesoscopic and multiscale modelling in materials

Multiscale modelling is a powerful tool to simulate materials behaviour, which has important features across multiple length and time scales. This Review provides an overview of multiscale computation methods and discusses their development for use in material design.
- Jacob Fish
- Gregory J. Wagner
- Sinan Keten
Review Article27 May 2021 Nature Materials

Computational Materials Design

Content

Computational materials design

Discovering and understanding materials through computation

Electronic-structure methods for materials design

Machine-learned potentials for next-generation matter simulations

From predictive modelling to machine learning and reverse engineering of colloidal self-assembly

Mesoscopic and multiscale modelling in materials

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