APS March Meeting 2014
Volume 59, Number 1
Monday–Friday, March 3–7, 2014;
Denver, Colorado
Session A31: Focus Session: Computational Discovery and Design of New Materials I
8:00 AM–11:00 AM,
Monday, March 3, 2014
Room: 607
Sponsoring
Units:
DMP DCOMP
Chair: Bruce Harmon, Iowa State University
Abstract ID: BAPS.2014.MAR.A31.1
Abstract: A31.00001 : Materials Discovery via CALYPSO Methodology
8:00 AM–8:36 AM
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Abstract
Author:
Yanming Ma
(State Key Lab of Superhard Materials, Jilin University)
Materials design has been the subject of topical interests in materials and
physical sciences for long. Atomistic structures of materials occupy a
central and often critical role, when establishing a correspondence between
materials performance and their basic compositions. Theoretical prediction
of atomistic structures of materials with the only given information of
chemical compositions becomes crucially important, but it is extremely
difficult as it basically involves in classifying a huge number of energy
minima on the lattice energy surface. To tackle the problems, we have
developed an efficient CALYPSO (Crystal structural AnLYsis by Particle Swarm
Optimization) approach [1-2] for structure prediction from scratch based on
particle swarm optimization algorithm by taking the advantage of swarm
intelligence and the spirit of structures smart learning. The method has
been coded into CALYPSO software (http://www.calypso.cn) which is free for
academic use.
Currently, CALYPSO method is able to predict structures of three-dimensional
crystals, isolated clusters or molecules [3], surface reconstructions [4],
and two-dimensional layers [5]. The applications of CALYPSO into purposed
materials design of layered materials [6], high-pressure superconductors
[7], and superhard materials [8] were successfully made. Our design of
superhard materials [8] introduced a useful scheme, where the hardness value
has been employed as the fitness function. This strategy might also be
applicable into design of materials with other desired functional properties
(e.g., thermoelectric figure of merit, topological Z2 number, etc.). For
such a structural design, a well-understood structure to property
formulation is required, by which functional properties of materials can be
easily acquired at given structures. An emergent application is seen on
design of photocatalyst materials.\\[4pt]
[1] Y. Wang, J. Lv, L.Zhu, and Y. Ma, Phys. Rev. B, 2010, 82, 094116.\\[0pt]
[2] Y. Wang, J. Lv, L.Zhu, and Y. Ma, Comput. Phys. Commun. 183, 2063 (2012).\\[0pt]
[3] J. Lv, Y. Wang, L.Zhu, and Y. Ma, J. Chem. Phys. 137, 084104 (2012).\\[0pt]
[4] S. Lu, Y. Wang, H. Liu, M. Miao, and Y. Ma, Nature Commun. (in review).\\[0pt]
[5] Y. Wang, et al., J. Chem. Phys. 137, 224108 (2012).\\[0pt]
[6] X. Luo, et al., J. Am. Chem. Soc. 133, 16285 (2011).\\[0pt]
[7] H. Wang, J. S. Tse, K. Tanaka, T. Iitaka, and Y. Ma, Proc. Natl. Acad. Sci. USA, 2012, 109, 6463-6466.\\[0pt]
[8] X. Zhang, et al., J. Chem. Phys. 138, 114101 (2013).
To cite this abstract, use the following reference: http://meetings.aps.org/link/BAPS.2014.MAR.A31.1