Themed collection Materials Informatics

7 items
Open Access Editorial

Introduction to Materials Informatics

Krishna Rajan, Jörg Behler and Chris J. Pickard introduce the Materials Advances themed collection on Materials Informatics.

Graphical abstract: Introduction to Materials Informatics
From the themed collection: Materials Informatics
Open Access Paper

Single-bonded nitrogen chain and porous nitrogen layer via Ce–N compounds

We explored the phase diagram of Ce–N compounds, and identified several interesting poly-nitrogen species, including the infinite helical chain, and porous poly-nitrogen layer.

Graphical abstract: Single-bonded nitrogen chain and porous nitrogen layer via Ce–N compounds
From the themed collection: Materials Informatics
Open Access Paper

Diamond-XII: a new type of exotic cubic carbon allotrope

Structural candidates for the super-size cubic carbon phase discovered in the Popigai crater are proposed. They are superhard transparent insulators as the discovered sample and their simulated XRD can partially explain the experimental results.

Graphical abstract: Diamond-XII: a new type of exotic cubic carbon allotrope
From the themed collection: Materials Informatics
Open Access Paper

Theoretical design of two-dimensional AMInP2X3Y3 (AM = Li, Na, K; X/Y = S, Se, Te) monolayers for highly efficient excitonic solar cells

Two-dimensional alkali metal indium phosphorus trichalcogenides AMInP2X3Y3 monolayers are regarded as promising candidates for use in photovoltaic solar cells.

Graphical abstract: Theoretical design of two-dimensional AMInP2X3Y3 (AM = Li, Na, K; X/Y = S, Se, Te) monolayers for highly efficient excitonic solar cells
From the themed collection: Materials Informatics
Open Access Paper

Experimental absence of the non-perovskite ground state phases of MaPbI3 explained by a Funnel Hopping Monte Carlo study based on a neural network potential

Funnel Hopping Monte Carlo simulations of MaPbI3 show that the delta phases which have a lower energy than the perovskite phases are only thermodynamically preferred up to 200 K. This explains the absence of the delta phases in experiments.

Graphical abstract: Experimental absence of the non-perovskite ground state phases of MaPbI3 explained by a Funnel Hopping Monte Carlo study based on a neural network potential
From the themed collection: Materials Informatics
Open Access Paper

ICHOR: a modern pipeline for producing Gaussian process regression models for atomistic simulations

There is now a highly automated electronic tool (called ICHOR) that facilitates the construction and validation of actively learnt machine learning models (Gaussian process regression) for molecules and molecular clusters.

Graphical abstract: ICHOR: a modern pipeline for producing Gaussian process regression models for atomistic simulations
From the themed collection: Materials Informatics
Open Access Paper

Selected machine learning of HOMO–LUMO gaps with improved data-efficiency

Selected machine learning (SML) relies on prior data classification and leads to improved data-efficiency for modeling molecular electronic properties, such as HOMO–LUMO-gaps.

Graphical abstract: Selected machine learning of HOMO–LUMO gaps with improved data-efficiency
From the themed collection: Materials Informatics
7 items

About this collection

Guest Edited by Professor ‪Chris Pickard  (University of Cambridge, UK), Professor Jörg Behler (Georg-August-Universität Göttingen, Germany), and Professor Krishna Rajan (University at Buffalo, USA)

The discipline of Materials Informatics has emerged from a fusion of increasing availability of materials data, high throughput experimental and computational methods, first principles and other advanced materials models, and machine learning. It has been fuelled by the dramatic growth in available computational power, and its ubiquity.

In this Themed Collection we have featured articles from across the wide diversity of Materials Informatics, ranging from novel computational and experimental methods to state-of-the-art applications.

Spotlight

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