OPTIMIZING THE THERMAL TRANSPORT PROPERTIES OF SINGLE LAYER (2D) TRANSITION METAL DICHALCOGENIDES (TMD)

Year 2019, Volume: 20 Issue: 3, 373 - 392, 26.09.2019

Yenal Karaaslan , Haluk Yapıcıoğlu , Cem Sevik

https://doi.org/10.18038/estubtda.593234

Cited By: 2

Abstract

In order to
characterize thermal dependent physical properties of materials, potentially to
be used in technological applications, an accurate interatomic-potential
parameter set is a must. In general, conjugate-gradient methods and more
recently, metaheuristics such as genetic algorithms are employed in determining
these interatomic potentials, however, especially the use of metaheuristics
specifically designed for optimization of real valued problems such as particle
swarm and evaluation strategies are limited in the mentioned problem. In
addition, some of these parameters are conflicting in nature, for which multi
objective optimization procedures have a great potential for better
understanding of these conflicts. In this respect, we aim to present a widely
used interatomic potential parameter set, the Stillinger–Weber potential,
obtained through three different optimization methods (particle swarm
optimization, PSO, covariance matrix adaptation evolution strategies, CMA-ES,
and non-dominated sorting genetic algorithm, NSGA-III) for two-dimensional materials
MoS₂, WS₂, WSe₂, and MoSe₂. These
two-dimensional transition metal dichalcogenides are considered as a case
mainly due to their potential in a variety of promising technologies for next
generation flexible and low-power nanoelectronics, (such as photonics,
valleytronics, sensing, energy storage, and optoelectronic devices) as well as
their excellent physical properties (such as electrical, mechanical, thermal,
and optical properties) different from those of their bulk counterparts. The
results show that the outputs of all optimization methods converge to ideal
values with sufficiently long iterations and at different trials. However, when
we consider the results of the statistical analyses of different trials under
similar conditions, we observe that the method with the lowest error rate is
the CMA-ES.

Keywords

Particle Swarm Optimization, Covariance Matrix Adaptation Evolution Strategies, NSGA-III, Two-dimensional Transition Metal Dichalcogenides, Stillinger-Weber potential

Supporting Institution

TÜBİTAK

Project Number

116F445

Thanks

This work was supported by the Scientific and Technological Research Council of Turkey (TÜBİTAK), Grant No: MFAG-116F445.

References

• Referans1 Chhowalla, M., et al., The chemistry of two-dimensional layered transition metal dichalcogenide nanosheets. Nature Chemistry, 2013. 5: p. 263.
• Referans 2 Radisavljevic, B., et al., Single-layer MoS2 transistors. Nat Nanotechnol, 2011. 6(3): p. 147-50.
• Referans3 Lopez-Sanchez, O., et al., Ultrasensitive photodetectors based on monolayer MoS2. Nat Nanotechnol, 2013. 8(7): p. 497-501.
• Referans4 Cao, T., et al., Valley-selective circular dichroism of monolayer molybdenum disulphide. Nature Communications, 2012. 3: p. 887.
• Referans5 Jariwala, D., et al., Emerging Device Applications for Semiconducting Two-Dimensional Transition Metal Dichalcogenides. ACS Nano, 2014. 8(2): p. 1102-1120.
• Referans6 Wang, Q.H., et al., Electronics and optoelectronics of two-dimensional transition metal dichalcogenides. Nature Nanotechnology, 2012. 7: p. 699.
• Referans7 Radisavljevic, B., M.B. Whitwick, and A. Kis, Small-signal amplifier based on single-layer MoS2. Applied Physics Letters, 2012. 101(4): p. 043103.
• Referans8 Liu, H. and P.D. Ye, MoS2 Dual-Gate MOSFET With Atomic-Layer-Deposited Al2O3 as Top-Gate Dielectric. IEEE Electron Device Letters, 2012. 33(4): p. 546-548.
• Referans9 Fang, H., et al., High-performance single layered WSe(2) p-FETs with chemically doped contacts. Nano Lett, 2012. 12(7): p. 3788-92.
• Referans10 Pumera, M., Graphene-based nanomaterials for energy storage. Energy & Environmental Science, 2011. 4(3): p. 668-674.
• Referans11 Wang, H., H. Feng, and J. Li, Graphene and Graphene-like Layered Transition Metal Dichalcogenides in Energy Conversion and Storage. Small, 2014. 10(11): p. 2165-2181.
• Referans12 Huang, J.-K., et al., Large-Area Synthesis of Highly Crystalline WSe2 Monolayers and Device Applications. ACS Nano, 2014. 8(1): p. 923-930.
• Referans13 Gutiérrez, H.R., et al., Extraordinary Room-Temperature Photoluminescence in Triangular WS2 Monolayers. Nano Letters, 2013. 13(8): p. 3447-3454.
• Referans14 Hohenberg, P. and W. Kohn, Inhomogeneous Electron Gas. Physical Review, 1964. 136(3B): p. B864-B871.
• Referans15 Aykol, M. and C. Wolverton, Local environment dependent GGA+U method for accurate thermochemistry of transition metal compounds. Physical Review B, 2014. 90(11): p. 115105.
• Referans16 Payam, N. and J.S. David, Thermal conductivity of single-layer WSe 2 by a Stillinger–Weber potential. Nanotechnology, 2017. 28(7): p. 075708.
• Referans17 Rapaport, D.C., The Art of Molecular Dynamics Simulation. 2 ed. 2004, Cambridge: Cambridge University Press.
• Referans18 Andrei, N., Conjugate gradient Algorithms for Molecular Formation under pairwise Potential Minimization, in Proceedings of the Fifth Workshop on Mathematical Modelling of Environmental and Life Sciences Problems. 2006: Romania.
• Referans19 Solomon, J., et al., Method and advantages of genetic algorithms in parameterization of interatomic potentials: Metal oxides. Computational Materials Science, 2014. 81: p. 453-465.
• Referans20 Voglis, C., et al., A parallel hybrid optimization algorithm for fitting interatomic potentials. Applied Soft Computing, 2013. 13(12): p. 4481-4492.
• Referans21 Tersoff, J., New empirical model for the structural properties of silicon. Physical Review Letters, 1986. 56(6): p. 632-635.
• Referans22 Liang, T., S.R. Phillpot, and S.B. Sinnott, Parametrization of a reactive many-body potential for Mo--S systems. Physical Review B, 2009. 79(24): p. 245110.
• Referans23 Stillinger, F.H. and T.A. Weber, Computer simulation of local order in condensed phases of silicon. Physical Review B, 1985. 31(8): p. 5262-5271.
• Referans24 Ichimura, M., Stillinger-Weber potentials for III–V compound semiconductors and their application to the critical thickness calculation for InAs/GaAs. physica status solidi (a), 1996. 153(2): p. 431-437.
• Referans25 Blöchl, P.E., Projector augmented-wave method. Physical Review B, 1994. 50(24): p. 17953-17979.
• Referans26 Kresse, G. and J. Hafner, Ab initio molecular dynamics for open-shell transition metals. Physical Review B, 1993. 48(17): p. 13115-13118.
• Referans27 Kresse, G. and J. Furthmüller, Efficient iterative schemes for ab initio total-energy calculations using a plane-wave basis set. Physical Review B, 1996. 54(16): p. 11169-11186.
• Referans28 Baroni, S., et al., Phonons and related crystal properties from density-functional perturbation theory. Reviews of Modern Physics, 2001. 73(2): p. 515-562.
• Referans29 Togo, A., F. Oba, and I. Tanaka, First-principles calculations of the ferroelastic transition between rutile-type and ${\text{CaCl}}_{2}$-type ${\text{SiO}}_{2}$ at high pressures. Physical Review B, 2008. 78(13): p. 134106.
• Referans30 Kennedy, J.F., R.C. Eberhart, and Y. Shi, Swarm intelligence. The Morgan Kaufmann series in evolutionary computation. 2001, San Francisco: Morgan Kaufmann Publishers. xxvii, 512 p.
• Referans31 Clerc, M. and J. Kennedy, The particle swarm - explosion, stability, and convergence in a multidimensional complex space. Trans. Evol. Comp, 2002. 6(1): p. 58-73.
• Referans32 Bäck, T., C. Foussette, and P. Krause, Contemporary evolution strategies. 2013, New York, NY: Springer Berlin Heidelberg. pages cm.
• Referans33 Bäck, T., Evolutionary algorithms in theory and practice : evolution strategies, evolutionary programming, genetic algorithms. 1996, New York: Oxford University Press. xii, 314 p.
• Referans34 Hansen, N. and A. Ostermeier. Adapting arbitrary normal mutation distributions in evolution strategies: the covariance matrix adaptation. in Proceedings of IEEE International Conference on Evolutionary Computation. 1996.
• Referans35 Hansen, N. and A. Ostermeier, Completely Derandomized Self-Adaptation in Evolution Strategies. Evolutionary Computation, 2001. 9(2): p. 159-195.
• Referans36 Hansen, N. and S. Kern. Evaluating the CMA Evolution Strategy on Multimodal Test Functions. in Parallel Problem Solving from Nature - PPSN VIII. 2004. Berlin, Heidelberg: Springer Berlin Heidelberg.
• Referans37 Kresse, G. and J. Furthmüller, Efficiency of ab-initio total energy calculations for metals and semiconductors using a plane-wave basis set. Computational Materials Science, 1996. 6(1): p. 15-50.
• Referans38 Gale, J.D. and A.L. Rohl, The General Utility Lattice Program (GULP). Molecular Simulation, 2003. 29(5): p. 291-341.
• Referans39 Deb, K. and H. Jain, An Evolutionary Many-Objective Optimization Algorithm Using Reference-Point-Based Nondominated Sorting Approach, Part I: Solving Problems With Box Constraints. IEEE Transactions on Evolutionary Computation, 2014. 18(4): p. 577-601.