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008181129s2017 ||| | | | eng d
020 ▼a 9780438120266
035 ▼a (MiAaPQ)AAI10902771
040 ▼a MiAaPQ ▼c MiAaPQ ▼d 248032
0491 ▼f DP
0820 ▼a 620.11
1001 ▼a Ashton, Michael.
24510 ▼a Computational Methods for the Discovery and Characterization of Two-Dimensional Materials.
260 ▼a [S.l.] : ▼b University of Florida., ▼c 2017
260 1 ▼a Ann Arbor : ▼b ProQuest Dissertations & Theses, ▼c 2017
300 ▼a 116 p.
500 ▼a Source: Dissertation Abstracts International, Volume: 79-11(E), Section: B.
5021 ▼a Thesis (Ph.D.)--University of Florida, 2017.
520 ▼a Computational methods centered around density-functional theory (DFT) calculations are performed to discover and characterize a large number of two-dimensional (2D) materials. The first class of 2D materials discussed are the transition metal ca
520 ▼a Next, a topology-scaling algorithm is used to identify layered bulk materials in the Materials Project online database. More than 800 layered materials were identified by the algorithm, and calculations are performed to determine the energy requ
520 ▼a A few of the materials identified by the topology-scaling algorithm are then investigated in detail. A family of binary group IV-V 2D materials based on SiP, which was found by the algorithm, have two nearly degenerate polymorphs with significan
520 ▼a Another group of materials identified in the search are the iron dihalides, which are half-metallic. The magnetic structure of these materials is investigated in detail, revealing that they are xy magnets with Berezinki-Kosterlitz-Thouless trans
590 ▼a School code: 0070.
650 4 ▼a Materials science.
690 ▼a 0794
71020 ▼a University of Florida. ▼b Materials Science and Engineering.
7730 ▼t Dissertation Abstracts International ▼g 79-11B(E).
773 ▼t Dissertation Abstract International
790 ▼a 0070
791 ▼a Ph.D.
792 ▼a 2017
793 ▼a English
85640 ▼u http://www.riss.kr/pdu/ddodLink.do?id=T15000378 ▼n KERIS
980 ▼a 201812 ▼f 2019
990 ▼a 관리자 ▼b 관리자