Characterizing the nature of virtual amorphous silicon

Choudhary, Devashish; Clancy, Paulette

doi:10.1063/1.1888566

Cited by 13 publications

(11 citation statements)

References 41 publications

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“…The electronic density of states calculated with DFT/PBE for the lowest energy configuration gives a band gap that is a factor of 1.48 larger than that calculated for the crystal at the same level of theory. While the calculated band gaps are known to be too small in DFT/PBE, this ratio is in excellent agreement with the ratio of experimentally determined band gaps, 1.55 (see [38]). Two defect peaks are found in the gap, 0.09 and 0.15eV above the valence band edge, presumably corresponding to the coordination defects.…”

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confidence: 84%

Optimal atomic structure of amorphous silicon obtained from density functional theory calculations

2017

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Atomic structure of amorphous silicon consistent with several reported experimental measurements has been obtained from annealing simulations using electron density functional theory calculations and a systematic removal of weakly bound atoms. The excess energy and density with respect to the crystal are well reproduced in addition to radial distribution function, angular distribution functions, and vibrational density of states. No atom in the optimal configuration is locally in a crystalline environment as deduced by ring analysis and common neighbor analysis, but coordination defects are present at a level of 1%-2%. The simulated samples provide structural models of this archetypal disordered covalent material without preconceived notion of the atomic ordering or fitting to experimental data.Amorphous silicon (a-Si) is the archetypal disordered covalently bonded material. It is also widely used for industrial purposes, with numerous applications in electronics and photovoltaics. Both aspects have triggered an intense research activity during the last few decades. a-Si can be obtained using several preparation techniques, including ion implantation, laser melting followed by fast quenching, various growth methods, and indentation [1][2][3][4][5][6]. The characteristics of the a-Si samples depend on the preparation method [7]. For example, vapor deposition often gives samples that include voids. Also, a-Si obtained by ion implantation tends to include a significant amount of coordination defects. But, annealing of the various types of samples seems to bring them closer to some common, ideal a-Si structure. The nature of this state is, however, a matter of long standing controversy. In addition to gaining an understanding of the basic characteristics of covalently bonded disordered networks, good structural models are an important prerequisite for theoretical investigations of the electronic and mechanical properties of such materials [8].Several different procedures have been proposed to generate realistic atomic scale models of a-Si. One approach is to generate a continuous random network (CRN) which can be built using various algorithms to give a structure with only 4-fold coordinated atoms, i.e. containing no coordination defects [9][10][11]. Another structural model involves nanoscopic crystal grains embedded in a disordered matrix. Arguments in favor of the latter have recently been presented in connection with an analysis of ion implantation samples [5,12]. Finally, constraints derived from experimental data have been used to guide the construction of a-Si models [13][14][15].Most of the proposed models have been able to reproduce well some of the measured structural features such as the radial distribution function (RDF) and bond angle distributions. The RDF, however, cannot discriminate between the various topological networks [12], and detailed information about the angular distributions is hard to obtain from experiments. To progress further in the search for an optimal a-Si model, Drabold recently pro...

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confidence: 84%

Optimal atomic structure of amorphous silicon obtained from density functional theory calculations

2017

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“…In an SGMD simulation, the system undergoes an accelerated systematic motion, which is defined by the local averaging time, t L , while maintaining a desired temperature. Many applications have demonstrated that SGMD simulations have an enhanced conformational search ability (Choudhary & Clancy 2005a; 2005b; Lung et al 2001; Sheng et al 2010a; 2010b; Varady et al 2002; Wu & Wang 2000; 2001; Wu et al 2002). Shinoda and Mikami extended SGMD to the NPT ensemble (Shinoda & Mikami 2001) and later combined it with the rigid body dynamics (Shinoda & Mikami 2003).…”

Section: History Of the Sgmd And Sgld Methodsmentioning

confidence: 99%

“…The self-guided molecular dynamics (SGMD) (Wu & Wang 1998; 1999) and the self-guided Langevin dynamics (SGLD) (Wu & Brooks 2003; Wu & Brooks 2011a; 2011b) simulation methods were developed for an efficient conformational search and have found many applications to study rare events, such as protein folding (Lee & Chang 2010; Lee & Olson 2010; Wen et al 2004; Wen & Luo 2004; Wu & Sung 1999; Wu & Brooks 2004; Wu & Wang 2000; 2001; Wu et al 2002), and ligand binding (Lung et al 2001; Varady et al 2002; Yang et al 2004), docking (Chandrasekaran et al 2009), conformational transitions (Damjanovic et al 2009; Damjanovic et al 2008a; Damjanovic et al 2008b; Pendse et al 2010), crystallization (Abe & Jitsukawa 2009; Choudhary & Clancy 2005a; 2005b; Tsuru et al 2010; Wu & Wang 1999), and surface absorption (Sheng et al 2010a; 2010b)…”

Section: The Conformational Search Problemmentioning

confidence: 99%

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Efficient and Unbiased Sampling of Biomolecular Systems in the Canonical Ensemble: A Review of Self‐Guided Langevin Dynamics

Damjanović

Brooks

2012

Advances in Chemical Physics

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“…Another common and simpler procedure for generating a-Si using MD simulations is by the quenching of l -Si [13,27,[47][48][49][50], which resembles the preparation of a-Si by pulsed energy melting techniques. Typical cooling rates used in this computational procedure are of the order of 10 13 − 10 14 K/s [13,27,47,48], while few studies have characterized samples generated with slower cooling rates [49][50][51]. These cooling rates are comparable (and some of them larger) to cooling rates experimentally achieved in pulsed energy melting techniques [4,6].…”

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confidence: 99%

Generation of amorphous Si structurally compatible with experimental samples through the quenching process: A systematic molecular dynamics simulation study

Santos

Aboy

Marqués

et al. 2019

Journal of Non-Crystalline Solids

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The construction of realistic atomistic models for amorphous solids is complicated by the fact that they do not have a unique structure. Among the different computational procedures available for this purpose, the melting and rapid quenching process using molecular dynamics simulations is commonly employed as it is simple and physically based. Nevertheless, the cooling rate used during quenching strongly affects the reliability of generated samples, as fast cooling rates result in unrealistic atomistic models. In this study, we have determined the conditions to be fulfilled when simulating the quenching process with molecular dynamics for obtaining amorphous Si (a-Si) atomistic models structurally compatible with experimental samples. We have analyzed the structure of samples generated with cooling rates ranging from 3.3 10 10 to 8.5 10 14 K/s. The obtained results were compared with experimental data available in the literature, and with samples generated by other state-of-the-art and more sophisticated computational procedures. For cooling rates below 10 11 K/s, a-Si samples generated had structural parameters within the range of experimental samples, and comparable to those obtained from other refined modeling procedures. These computationally slow cooling rates are of the same order of magnitude than those experimentally achieved with pulsed energy melting techniques. Samples obtained with faster cooling rates can be further relaxed with annealing simulations, resulting in structural parameters within the range of experimental samples. Nevertheless, the required annealing times are on the order of microseconds, which makes this annealing step non practical from a computational point of view.

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Characterizing the nature of virtual amorphous silicon

Cited by 13 publications

References 41 publications

Optimal atomic structure of amorphous silicon obtained from density functional theory calculations

Optimal atomic structure of amorphous silicon obtained from density functional theory calculations

Efficient and Unbiased Sampling of Biomolecular Systems in the Canonical Ensemble: A Review of Self‐Guided Langevin Dynamics

Generation of amorphous Si structurally compatible with experimental samples through the quenching process: A systematic molecular dynamics simulation study

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