Modeling the elastic properties of the ternary III–V alloys InGaAs, InAlAs and GaAsSb using Tersoff potentials for binary compounds

Detz, Hermann; Strasser, G.

doi:10.1088/0268-1242/28/8/085011

Cited by 9 publications

(9 citation statements)

References 33 publications

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“…Here, the ARTICLE plane-strain modulus can be represented by E = E/ (1 À v 2 ), where E and v are Young's modulus and Poisson's ratio, respectively. The experimentally obtained wavelengths of the wrinkles fit well with the calculated wavelengths (eq 1) for InGaAs nanomembranes with h f = 42 nm, E f = 65.8 GPa, 43 and v f = 0.33 as a function of PDMS modulus with v s = 0.5 (Figure 3d), suggesting that eq 1 holds even for damped sinusoidal wrinkles. The damped sinusoidal wrinkles showed a decaying amplitude profile, where the amplitude decayed from the center to the edge of the wrinkled domain, as marked with A 1 , A 2 , and A 3 in Figure 3c.…”

Section: Resultssupporting

confidence: 76%

Vacuum-Induced Wrinkle Arrays of InGaAs Semiconductor Nanomembranes on Polydimethylsiloxane Microwell Arrays

Lim

Lee

et al. 2014

ACS Nano

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Tunable surface morphology in III-V semiconductor nanomembranes provides opportunities to modulate electronic structures and light interactions of semiconductors. Here, we introduce a vacuum-induced wrinkling method for the formation of ordered wrinkles in InGaAs nanomembranes (thickness, 42 nm) on PDMS microwell arrays as a strategy for deterministic and multidirectional wrinkle engineering of semiconductor nanomembranes. In this approach, a vacuum-induced pressure difference between the outer and inner sides of the microwell patterns covered with nanomembranes leads to bulging of the nanomembranes at the predefined microwells, which, in turn, results in stretch-induced wrinkle formation of the nanomembranes between the microwells. The direction and geometry of the nanomembrane wrinkles are well controlled by varying the PDMS modulus, depth, and shape of microwells, and the temperature during the transfer printing of nanomembrane onto heterogeneous substrates. The wrinkling method shown here can be applied to other semiconductor nanomembranes and may create an important platform to realize unconventional electronic devices with tunable electronic properties.

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Section: Resultssupporting

confidence: 76%

Vacuum-Induced Wrinkle Arrays of InGaAs Semiconductor Nanomembranes on Polydimethylsiloxane Microwell Arrays

Lim

Lee

et al. 2014

ACS Nano

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“…This potential was later adapted to the most common III–V materials . Although all of these parameter sets were fitted for binary compounds, the extension to ternary alloys was proven to be a good approximation with typical errors around 5% concerning hydrostatic deformations and around 10% in the case of shear stress ().…”

Section: Modeling Methodsmentioning

confidence: 99%

“…Moves increasing the energy may be accepted at a finite probability, by comparing a random number with an Arrhenius term. This method was proven to lead to reliable convergence in the case of bulk material . The acceptance probability can be further reduced in order to match experimental data regarding the thermal expansion coefficient ().…”

Section: Modeling Methodsmentioning

confidence: 99%

“…Chemical bonds between the individual atoms are modeled through empirical interaction potentials , also called force fields, which allow a dramatic reduction of the computational effort, compared to DFT. Such models were successfully applied for structural simulations of Si,

{Si}_{1 - normalx} {Ge}_{x}

, as well as to III–V materials and their alloys . Recently, even the behavior of dopant atoms in III–V materials was investigated on an atomistic scale ().…”

Section: Introductionmentioning

confidence: 99%

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Atomistic modeling of interfaces in III–V semiconductor superlattices

Maier

Detz

2016

Phys. Status Solidi B

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Semiconductor heterostructures are well characterized experimentally and provide a solid basis for electronic and optoelectronic devices ranging from single interface to complex superlattice structures. Yet, structural and electronic models commonly describe the material properties in a continuum approach, which neglects the crystalline structure, as well as potential local variations of the composition and resulting strain. Empirical interaction potentials provide an efficient way to model chemical bonds and therefore allow a structural description of multi‐layer structures. This work provides a detailed introduction on methods to minimize the total energy of semiconductor heterostructures at an atomistic level. We present an algorithm to minimize the total energy and generate optimized interface configurations. The relaxed structures are then evaluated with respect to interfacial strain, where different strain calculation methods are evaluated and compared with experimental data.

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“…Of more direct importance to our interest in doped InGaAs materials, Detz and Strasser recently tested Tersoff models for InGaAs, InAlAs, and GaAsSb for their ability to reproduce elastic properties, as well as predict bulk and shear moduli. 18 In this paper, we will briefly describe the Tersoff potential model (providing more background details in the Supplemental Information), and the fitting procedure used to obtain Tersoff parameters for Si-X interactions (Si-As, Si-In, Si-Ga) from the ab initio database of properties that we created for this purpose (Table 1). We validate the parameter sets by their ability to reproduce commonly encountered thermodynamic properties such as cohesive energy, bond lengths and elastic properties that were used in the parameter fitting (Section 2).…”

Section: Extension To Inas Was Made Bymentioning

confidence: 99%

Energetics of neutral Si dopants in InGaAs: Anab initioand semiempirical Tersoff model study

et al. 2015

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A roadblock in utilizing III-V semiconductors for scaled-down electronic devices is its poor dopant activation. As a first step to unravel the dopant behavior in InGaAs, we studied the tendency for dopant formation computationally using two approaches: ab initio and semiempirical methods. We studied a number of structural possibilities such as the impact of local sites, local and global environments, etc. We will show that the dopant we considered here, Si, has discrete preferences for certain sites and the nature of its surroundings. Substitutional defects are clearly preferred over interstitial locations. We shall show that cation ordering has an impact on dopant energetics. Critically, for large-scale simulations of dopant diffusion in InGaAs alloys, we also present a parameterization of the Abell-Tersoff semi-empirical potential for pairwise interactions between silicon atoms and each of the elements comprising InGaAs. In the absence of experimental data, reference parameters for estimating the Tersoff values were obtained using ab initio pseudopotential calculations (DFT+GGA). These sets of Tersoff parameters were optimized to describe the bulk structural properties of the mostly theoretical alloys, Si-As, Si-Ga and SI-In. We demonstrate the transferability of these parameters by predicting formation energies of extrinsic point "defects" of Si on a variety of sites in ternary InGaAs alloys with different local compositional configurations, both random and ordered. Tersoff model predictions of the extrinsic "substitution energy" of a Si dopant on a cationic lattice site were found to be independent of the composition of the dopant's 2 nd nearest neighbors, but was affected by the strain induced by a local arrangement of In and Ga cationic atoms. This finding is important since common deposition processes used to create InGaAs may lead to specifically ordered patterns within the cation sub-lattice.

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Modeling the elastic properties of the ternary III–V alloys InGaAs, InAlAs and GaAsSb using Tersoff potentials for binary compounds

Cited by 9 publications

References 33 publications

Vacuum-Induced Wrinkle Arrays of InGaAs Semiconductor Nanomembranes on Polydimethylsiloxane Microwell Arrays

Vacuum-Induced Wrinkle Arrays of InGaAs Semiconductor Nanomembranes on Polydimethylsiloxane Microwell Arrays

Atomistic modeling of interfaces in III–V semiconductor superlattices

Energetics of neutral Si dopants in InGaAs: Anab initioand semiempirical Tersoff model study

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