journal article·2020-03-02

Introducing Open Boundary Conditions in Modeling Nonperiodic Materials and Interfaces: The Impact of the Periodicity Assumption

James Charles, Sabre Kais, Tillmann Kubis

ACS Materials Letters· Volume 2· Issue 3
Publisher page

Abstract

Simulations are essential to accelerate the discovery of new materials and to gain full understanding of known ones. Although hard to realize experimentally, periodic boundary conditions are omnipresent in material simulations. In this work, we introduce ROBIN (recursive open boundary and interfaces), the first method allowing open boundary conditions in material and interface modeling. The computational costs are limited to solving quantum properties in a focus area that allows explicitly discretizing millions of atoms in real space and to consider virtually any type of environment (be it periodic, regular, or random). The impact of the periodicity assumption is assessed in detail with silicon dopants in graphene. Graphene was confirmed to produce a band gap with periodic substitution of 3% carbon with silicon in agreement with published periodic boundary condition calculations. Instead, 3% randomly distributed silicon in graphene only shifts the energy spectrum. The predicted shift agrees quantitatively with published experimental data. Key insight of this assessment is, assuming periodicity elevates a small perturbation of a periodic cell into a strong impact on the material property prediction. Periodic boundary conditions can be applied on truly periodic systems only. More general systems should apply an open boundary method for reliable predictions.
Source: openalex_inverted_index · Quality: baseline

Research context

OpenAlex topics: Graphene research and applications · Advanced Chemical Physics Studies · Chemical and Physical Properties of Materials

SciVX discovery tags are terminology-based. OpenAlex topics are source-provided classifications.

Affiliations

School of Electrical and Computer Engineering, Purdue University, West Lafayette, Indiana 47907, United States

Department of Physics and Astronomy, Purdue University, West Lafayette, Indiana United States

Department of Chemistry, Purdue University, West Lafayette, Indiana United States

Network for Computational Nanotechnology, Purdue University, West Lafayette, Indiana 47907, United States

Center for Predictive Materials and Devices, Purdue University, West Lafayette, Indiana 47907, United States

Purdue Institute of Inflammation, Immunology, and Infectious Disease, West Lafayette, Indiana 47907, United States

Funding

Division of Emerging Frontiers in Research and Innovation

References (64)

Show source-provided references
1. 10.1038/s41578-019-0101-810.1038/s41578-019-0101-8 ↗
2. 10.1557/mrs2006.17410.1557/mrs2006.174 ↗
3. 10.1088/2515-7639/ab084b10.1088/2515-7639/ab084b ↗
4. 10.1038/s41598-019-39278-z10.1038/s41598-019-39278-z ↗
5. 10.1038/srep1937510.1038/srep19375 ↗
6. 10.1038/s41586-018-0337-210.1038/s41586-018-0337-2 ↗
7. 10.1016/j.pmatsci.2018.05.00410.1016/j.pmatsci.2018.05.004 ↗
8. 10.1038/s41524-016-0001-z10.1038/s41524-016-0001-z ↗
9. 10.1103/PhysRevLett.102.02610110.1103/PhysRevLett.102.026101 ↗
10. 10.1039/C9NR04096J10.1039/C9NR04096J ↗
11. 10.1103/PhysRevLett.102.01640210.1103/PhysRevLett.102.016402 ↗
12. 10.1002/wcms.112510.1002/wcms.1125 ↗
13. 10.1063/1.486366510.1063/1.4863665 ↗
14. 10.1109/TNANO.2011.216616410.1109/TNANO.2011.2166164 ↗
15. 10.1021/nn100712q10.1021/nn100712q ↗
16. 10.1039/b820003c10.1039/b820003c ↗
17. 10.1103/PhysRevB.95.08531010.1103/PhysRevB.95.085310 ↗
18. 10.1007/s11467-013-0340-x10.1007/s11467-013-0340-x ↗
19. 10.1039/C5NR06345K10.1039/C5NR06345K ↗
20. 10.1088/0953-8984/21/39/39550210.1088/0953-8984/21/39/395502 ↗
21. 10.1088/0965-0393/17/8/08400310.1088/0965-0393/17/8/084003 ↗
22. 10.1016/j.physb.2003.09.11110.1016/j.physb.2003.09.111 ↗
23. 10.1103/PhysRevB.96.23520310.1103/PhysRevB.96.235203 ↗
24. Kadanoff L. P. · 1994
25. 10.1103/PhysRevB.66.08532610.1103/PhysRevB.66.085326 ↗
26. 10.1103/PhysRevB.69.23310110.1103/PhysRevB.69.233101 ↗
27. 10.1103/PhysRevB.97.12531010.1103/PhysRevB.97.125310 ↗
28. 10.1103/PhysRevB.87.24540710.1103/PhysRevB.87.245407 ↗
29. 10.1103/PhysRevB.92.03543510.1103/PhysRevB.92.035435 ↗
30. 10.1103/PhysRevB.88.07531710.1103/PhysRevB.88.075317 ↗
31. 10.1063/1.503321610.1063/1.5033216 ↗
32. 10.1126/science.108157210.1126/science.1081572 ↗
33. 10.1063/1.480963810.1063/1.4809638 ↗
34. 10.1006/spmi.2000.092010.1006/spmi.2000.0920 ↗
35. 10.1016/S0370-1573(01)00029-110.1016/S0370-1573(01)00029-1 ↗
36. 10.1109/JQE.2011.213051210.1109/JQE.2011.2130512 ↗
37. 10.1063/1.490250410.1063/1.4902504 ↗
38. 10.1016/j.physrep.2004.03.00210.1016/j.physrep.2004.03.002 ↗
39. Wang Y. · 16th International Workshop on Computational Electronics · 2013 · 42
40. 10.1109/JPROC.2008.92735510.1109/JPROC.2008.927355 ↗
41. 10.1103/PhysRevB.77.11511910.1103/PhysRevB.77.115119 ↗
42. 10.1063/1.36539410.1063/1.365394 ↗
43. 10.1063/1.362461210.1063/1.3624612 ↗
44. 10.1016/j.jcp.2017.01.02410.1016/j.jcp.2017.01.024 ↗
45. 10.1007/s10825-013-0458-710.1007/s10825-013-0458-7 ↗
46. 10.1016/j.jcp.2005.11.01010.1016/j.jcp.2005.11.010 ↗
47. Klimeck, G. Nanoelectronic Modeling Lecture 21: Recursive Green Function Algorithm, 2010. https://nanohub.org/resources/8388.
48. Klimeck, G. Numerical Aspects of NEGF: The Recursive Green Function Algorithm, 2004. https://nanohub.org/resources/165.
49. 10.1088/1742-6596/696/1/01201910.1088/1742-6596/696/1/012019 ↗
50. Brázdová V. · 201310.1002/9783527671816 ↗
51. 7.33 ISMEAR, SIGMA tag. https://cms.mpi.univie.ac.at/vasp/guide/node124.html (accessed 2019-09-05).
52. 10.1002/qua.2300310.1002/qua.23003 ↗
53. Supriyo D. · 1997
54. 10.1039/c2nr11728b10.1039/c2nr11728b ↗
55. 10.1039/C2RA22664B10.1039/C2RA22664B ↗
56. 10.1038/nmat122310.1038/nmat1223 ↗
57. 10.1016/j.jconrel.2008.02.00710.1016/j.jconrel.2008.02.007 ↗
58. 10.1039/C0SC00416B10.1039/C0SC00416B ↗
59. 10.1103/PhysRevB.99.16543010.1103/PhysRevB.99.165430 ↗
60. 10.1103/PhysRevB.95.07542010.1103/PhysRevB.95.075420 ↗
61. 10.1038/d41586-018-07848-210.1038/d41586-018-07848-2 ↗
62. 10.1103/PhysRevB.69.11520110.1103/PhysRevB.69.115201 ↗
63. 10.1016/S0040-6090(98)01297-810.1016/S0040-6090(98)01297-8 ↗
64. Papior, N.; Calogero, G.; Leitherer, S.; Brandbyge, M. Removing All Periodic Boundary Conditions: Efficient Non-Equilibrium Green Function Calculations. arXiv (Cond-Mat Physicsphysics), 2019, 190511113. https://arxiv.org/abs/1905.11113.10.1103/PhysRevB.100.195417 ↗