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Title: Computational prediction of new auxetic materials

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”.
Authors:
 [1] ;  [1] ;  [1] ;  [2]
  1. Lawrence Berkeley National Lab. (LBNL), Berkeley, CA (United States)
  2. Lawrence Berkeley National Lab. (LBNL), Berkeley, CA (United States); Univ. of California, Berkeley, CA (United States)
Publication Date:
Grant/Contract Number:
AC02-05CH11231
Type:
Accepted Manuscript
Journal Name:
Nature Communications
Additional Journal Information:
Journal Volume: 8; Journal Issue: 1; Journal ID: ISSN 2041-1723
Publisher:
Nature Publishing Group
Research Org:
Lawrence Berkeley National Lab. (LBNL), Berkeley, CA (United States)
Sponsoring Org:
USDOE Office of Science (SC), Basic Energy Sciences (BES) (SC-22)
Country of Publication:
United States
Language:
English
Subject:
36 MATERIALS SCIENCE; 97 MATHEMATICS AND COMPUTING
OSTI Identifier:
1399000

Dagdelen, John, Montoya, Joseph, de Jong, Maarten, and Persson, Kristin. Computational prediction of new auxetic materials. United States: N. p., Web. doi:10.1038/s41467-017-00399-6.
Dagdelen, John, Montoya, Joseph, de Jong, Maarten, & Persson, Kristin. Computational prediction of new auxetic materials. United States. doi:10.1038/s41467-017-00399-6.
Dagdelen, John, Montoya, Joseph, de Jong, Maarten, and Persson, Kristin. 2017. "Computational prediction of new auxetic materials". United States. doi:10.1038/s41467-017-00399-6. https://www.osti.gov/servlets/purl/1399000.
@article{osti_1399000,
title = {Computational prediction of new auxetic materials},
author = {Dagdelen, John and Montoya, Joseph and de Jong, Maarten and Persson, Kristin},
abstractNote = {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”.},
doi = {10.1038/s41467-017-00399-6},
journal = {Nature Communications},
number = 1,
volume = 8,
place = {United States},
year = {2017},
month = {8}
}