Perspective: Interactive material property databases through aggregation of literature data

Ram Seshadri,Taylor D Sparks

doi:10.1063/1.4944682

Abstract

Searchable, interactive, databases of material properties, particularly those relating to functional materials (magnetics, thermoelectrics, photovoltaics, etc.) are curiously missing from discussions of machine-learning and other data-driven methods for advancing new materials discovery. Here we discuss the manual aggregation of experimental data from the published literature for the creation of interactive databases that allow the original experimental data as well additional metadata to be visualized in an interactive manner. The databases described involve materials for thermoelectric energy conversion, and for the electrodes of Li-ion batteries. The data can be subject to machine-learning, accelerating the discovery of new materials.

Highlights

Over the last decade, there has been an increased effort to integrate and enhance collaboration between computational and experimental materials science
We discuss the manual aggregation of experimental data from the published literature for the creation of interactive databases that allow the original experimental data as well additional metadata to be visualized in an interactive manner
Integrated Computational Materials Engineering (ICME) creates virtual testing and design packages across multiple length and time scales with an emphasis on process engineering and material variation.[1,2]

Summary

INTRODUCTION

There has been an increased effort to integrate and enhance collaboration between computational and experimental materials science. There have been significant advances in identifying materials descriptors and structure-property relationships in a wide variety of materials systems for many different applications.[6,7,8,9] Likewise, the tools and software packages, such as density functional theory (DFT),[10,11] for simulated experiments have improved by considering simplified models and potentials,[7,12,13,14] as well as preliminary screening techniques[15,16,17,18] making high-throughput computational modeling more viable Notwithstanding these developments, one of the greatest remaining challenges is the creation of materials property databases that meet the requirements necessary to advance the Materials Genome Initiative and that are based on experimental data. We describe some of the advantages and shortcomings of current approaches for building interactive databases of materials properties and outline some of the best practices, opportunities, and remaining challenges that lie ahead in this emerging field of materials informatics

APPROACHES FOR AGGREGATING DATA FROM LITERATURE

CHALLENGES AND OPPORTUNITIES

Findings

CONCLUDING REMARKS