Computational prediction of new auxetic materials

Dagdelen, John; Montoya, Joseph; de Jong, Maarten; Persson, Kristin

doi:10.1038/s41467-017-00399-6

Title: Computational prediction of new auxetic materials

Journal Article · Tue Aug 22 00:00:00 EDT 2017 · Nature Communications

DOI:https://doi.org/10.1038/s41467-017-00399-6· OSTI ID:1399000

Dagdelen, John ^[1]; Montoya, Joseph ^[1]; de Jong, Maarten ^[1]; Persson, Kristin ^[2]

Lawrence Berkeley National Lab. (LBNL), Berkeley, CA (United States)
Lawrence Berkeley National Lab. (LBNL), Berkeley, CA (United States); Univ. of California, Berkeley, CA (United States)

Auxetics comprise a rare family of materials that manifest negative Poisson’s ratio, which causes an expansion instead of contraction under tension. Most known homogeneously auxetic materials are porous foams or artificial macrostructures and there are few examples of inorganic materials that exhibit this behavior as polycrystalline solids. It is now possible to accelerate the discovery of materials with target properties, such as auxetics, using high-throughput computations, open databases, and efficient search algorithms. Candidates exhibiting features correlating with auxetic behavior were chosen from the set of more than 67 000 materials in the Materials Project database. Poisson’s ratios were derived from the calculated elastic tensor of each material in this reduced set of compounds. We report that this strategy results in the prediction of three previously unidentified homogeneously auxetic materials as well as a number of compounds with a near-zero homogeneous Poisson’s ratio, which are here denoted “anepirretic materials”.

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Research Organization:: Lawrence Berkeley National Laboratory (LBNL), Berkeley, CA (United States)

Sponsoring Organization:: USDOE Office of Science (SC), Basic Energy Sciences (BES)

Grant/Contract Number:: AC02-05CH11231

OSTI ID:: 1399000

Journal Information:: Nature Communications, Vol. 8, Issue 1; ISSN 2041-1723

Publisher:: Nature Publishing GroupCopyright Statement

Country of Publication:: United States

Language:: English

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Cited by: 90 works

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