Structure Of Amorphous Silicon Research Articles

Understanding Defects in Amorphous Silicon with Million-Atom Simulations and Machine Learning.

The structure of amorphous silicon (a-Si) is widely thought of as a fourfold-connected random network, and yet it is defective atoms, with fewer or more than four bonds, that make it particularly interesting. Despite many attempts to explain such "dangling-bond" and "floating-bond" defects, respectively, a unified understanding is still missing. Here, we use advanced computational chemistry methods to reveal the complex structural and energetic landscape of defects in a-Si. We study an ultra-large-scale, quantum-accurate structural model containing a million atoms, and thousands of individual defects, allowing reliable defect-related statistics to be obtained. We combine structural descriptors and machine-learned atomic energies to develop a classification of the different types of defects in a-Si. The results suggest a revision of the established floating-bond model by showing that fivefold-bonded atoms in a-Si exhibit a wide range of local environments-analogous to fivefold centers in coordination chemistry. Furthermore, it is shown that fivefold (but not threefold) coordination defects tend to cluster together. Our study provides new insights into one of the most widely studied amorphous solids, and has general implications for understanding defects in disordered materials beyond silicon alone.

Understanding Defects in Amorphous Silicon with Million‐Atom Simulations and Machine Learning

AbstractThe structure of amorphous silicon (a‐Si) is widely thought of as a fourfold‐connected random network, and yet it is defective atoms, with fewer or more than four bonds, that make it particularly interesting. Despite many attempts to explain such “dangling‐bond” and “floating‐bond” defects, respectively, a unified understanding is still missing. Here, we use advanced computational chemistry methods to reveal the complex structural and energetic landscape of defects in a‐Si. We study an ultra‐large‐scale, quantum‐accurate structural model containing a million atoms, and thousands of individual defects, allowing reliable defect‐related statistics to be obtained. We combine structural descriptors and machine‐learned atomic energies to develop a classification of the different types of defects in a‐Si. The results suggest a revision of the established floating‐bond model by showing that fivefold‐bonded atoms in a‐Si exhibit a wide range of local environments–analogous to fivefold centers in coordination chemistry. Furthermore, it is shown that fivefold (but not threefold) coordination defects tend to cluster together. Our study provides new insights into one of the most widely studied amorphous solids, and has general implications for understanding defects in disordered materials beyond silicon alone.

Silicon Fresnel Zone Plate Metalens with Subwavelength Gratings.

Metalenses are planar optical components that have demonstrated immense potential for integrated optics. In particular, they are capable of high-efficiency subwavelength focusing without the bulkiness of traditional lenses. Dielectric metalenses operating in the C-band typically employ relatively tall, amorphous silicon structures arranged in a periodic array. Phase control spanning from 0 to 2π is accessed by varying the geometry of these scattering structures. The full 2π phase range is necessary to impose a hyperbolic focusing phase profile, but this is difficult to achieve without custom fabrication practices. In this work, we propose a binary phase Fresnel zone plate metalens designed for the standard 500 nm silicon-on-insulator platform. Our design uses subwavelength gratings with trapezoidal segmentation to form concentric rings. The effective index of the grating is set with the duty cycle using a single full-etch step to form the binary phase profile of the zone plate. The metalens design can be easily tuned to achieve longer focal lengths at different wavelengths. It offers a simple platform for high-throughput wavelength-scale focusing elements in free-space optics, including for microscopy and medical imaging.

Получение цветного наноструктурированного слоя аморфного кремния при травлении в хлорсодержащей плазме

It is shown that in the self-forming mode in the plasma etching process of amorphous silicon structures (α-Si)/SiO2/Si and (α-Si)/Pt/SiO2 /Si in chlorine-containing plasma (Cl2/Ar), it is possible to obtain a multicolored surface from nanoconus and nanowire structures of α-Si.The mechanism of formation of such structures during plasma chemical etching is discussed. The reflection spectra of colored films are given. The bright colors of the surface are caused by the resonant reflection of light in the layers of nanoconus and nanowire structures of α-Si with a sublayer of α-Si nanometer thickness.

Plasmonic enhanced photo-electrochemical water splitting on amorphous silicon structures

The application of metal nanoparticles to promote chemical reactions by catalysis is an important approach for increasing the reaction rate. For light-assisted water splitting, the utilisation of plasmonic resonance has the capability to further increase the water dissociation by means of plasmonic scattering or plasmonic catalysis. In this study, Au and Ag nanoparticles were prepared on amorphous silicon and characterised by optical, morphological, and photo-electrochemical approaches. The influence of various contributions to the reaction rate related to the presence of the nanoparticles is analysed. A significant increase of current under light conditions was achieved for both Au- and Ag-based amorphous structures. The chemical catalysis supported by plasmonic catalysis was suggested as a dominant source of the increased reaction rate. While the Au nanoparticles coverage of the surface remains the same during the characterisation, the stability of Ag nanoparticles is the key issue for practical application. Prepared Au nanoparticles exhibited stability in a harsh environment giving the perspective for practical utilisation for water splitting structures, while Ag nanoparticles showed significantly lower stability.

Low‐Temperature Synthesis of Amorphous Silicon and Its Ball‐in‐Ball Hollow Nanospheres as High‐Performance Anodes for Sodium‐Ion Batteries

AbstractSilicon is widely developed and deemed as a hopeful anode material for lithium‐ion batteries. However, till now there is very little literature devoted to its study for sodium‐ion batteries (SIBs). One possible reason is the preparation difficultly of carefully crafted amorphous silicon (a‐Si) structures by a facile and low‐cost method. Another reason is that a‐Si suffers from large volume expansion, slow sodium diffusion kinetics, and poor electrical conductivity. Herein, a new method called as “sodiothermic reduction” is used to prepare a‐Si hollow nanospheres at a much lower temperature. Moreover, an a‐Si‐based composite with yolk‐shell structure is designed via atomic layer deposition of alumina, in situ chemical polymerization of pyrrole, and dilute HCl etching. The obtained composite as an anode material for SIBs displays a great initial discharge capacity of 645.6 mAh g–1 at 100 mA g–1, superior long steadiness up to 5000 cycles at 800 mA g–1, and preeminent rate capability (646.4, 193.5, 138.6, 105, 77.5 mAh g–1 at 100, 400, 800, 1500, 3000 mA g–1, respectively). In situ transmission electron microscopy observation on the structure evolution and finite element analysis of the stress–strain behavior are combined to further prove the merits of the well‐designed yolk–shell structure.

Chirality-selective all-dielectric metasurface structural color display

The polarization dependent switchable structural coloration has shown a prominence for its unnecessity of changing the structure itself to achieve tunable color displays. Nevertheless, a chirality-selective structural color display has been rarely elucidated. Here, we suggest a chirality-selective reflective structural color display under perpendicularly incident light based on all-dielectric metasurfaces. We first investigate a chiral response of a subwavelength thickness two-dimensional (2D) amorphous silicon (Si) structure. The multipole decomposition followed by the electromagnetic field distribution analysis explained the chirality-selective response of the metasurface with the chirality-selective excitation of magnetic dipole (MD) and electric quadrupole (EQ). We then analyzed the structural dependence of MD and EQ, finding a group of metasurfaces which can span the entire visible spectrum under left circularly polarized (LCP) light and show dark, faded colors under right circularly polarized (RCP) light. Our result provides design criteria for chirality-selective all-dielectric structural color displays, applicable to energy and time efficient real-time color switching displays.

Distilling nanoscale heterogeneity of amorphous silicon using tip-enhanced Raman spectroscopy (TERS) via multiresolution manifold learning

Accurately identifying the local structural heterogeneity of complex, disordered amorphous materials such as amorphous silicon is crucial for accelerating technology development. However, short-range atomic ordering quantification and nanoscale spatial resolution over a large area on a-Si have remained major challenges and practically unexplored. We resolve phonon vibrational modes of a-Si at a lateral resolution of <60 nm by tip-enhanced Raman spectroscopy. To project the high dimensional TERS imaging to a two-dimensional manifold space and categorize amorphous silicon structure, we developed a multiresolution manifold learning algorithm. It allows for quantifying average Si-Si distortion angle and the strain free energy at nanoscale without a human-specified physical threshold. The multiresolution feature of the multiresolution manifold learning allows for distilling local defects of ultra-low abundance (< 0.3%), presenting a new Raman mode at finer resolution grids. This work promises a general paradigm of resolving nanoscale structural heterogeneity and updating domain knowledge for highly disordered materials.

Molecular dynamic investigation of the structure and stress in crystalline and amorphous silicon during lithiation

Silicon (Si) is a promising anode material for lithium-ion batteries with a high specific capacity, but the severe volume expansion and mechanical stress generated during electrochemical cycling hinders its practical application. Considering the coupled effect between electrochemical reaction and mechanical stress, the structure and stress evolution in lithiated crystalline and amorphous Si was investigated using molecular dynamics simulation. The results show that the lithiation in both crystalline and amorphous Si is featured by the shift of the phase boundary. Lithiation is favoured along 〈1 1 0〉 crystallographic orientation in crystalline Si due to the atomic channels along this direction. The lithiation induced compressive stress is accumulated at the Si-Li phase boundary of crystalline Si and reaches −6 GPa, which slows down the lithiation process. On the other hand, the stress in amorphous Si can be mitigated through deformation at the phase boundary, and the lithiation speed is higher than that in crystalline Si. The lithiation in crystalline Si is related to a peeling-off mechanism, and Si clusters form and disintegrate during lithiation. More Si clusters are generated during the lithiation in crystalline Si than in amorphous Si.

Deep-learning approach to the structure of amorphous silicon

We present a deep-learning approach for modeling the atomic structure of amorphous silicon ($a$-Si). While accurate models of disordered systems require an ab initio description of the energy landscape which severely limits the attainable system size, large-scale models rely on empirical potentials, at the price of reduced reliability and a computational load that is still restricting for many purposes. In this paper, we explore an approach based on deep learning, particularly generative modeling that could reconcile both requirements of accuracy and efficiency by learning structural features from data. When trained on a set of observations, such models can generate new structures very efficiently with the desired level of accuracy, as determined by the data set. We first validate our approach by training a convolutional neural network to approximate the potential-energy surface of $a$-Si, as given by the Stillinger-Weber potential, which results in a root-mean-square error of 5.05 meV per atom---about $0.16%$ of the atomic energy. We then train a deep generative model, the Wasserstein autoencoder, for the generation of $a$-Si configurations. Our approach leads to models which exhibit some of the essential features of $a$-Si while possessing too much structural disorder, thus suggesting that the method is viable; we indicate avenues for improving it towards the generation of state-of-the-art structures.

Dependence of a cooling rate on structural and vibrational properties of amorphous silicon: A neural network potential-based molecular dynamics study.

Amorphous materials have variable structural order, which has a significant influence on their electronic, transport, and thermal properties. However, this difference in structure has rarely been investigated by atomistic modeling. In this study, a high-quality machine-learning-based interatomic potential was used to generate a series of atomic structures of amorphous silicon with different degrees of disorder by simulated cooling from the melt with different cooling rates (1011-1015 K/s). We found that the short- and intermediate-range orders are enhanced with decreasing cooling rate, and the influence of the structural order change is in excellent agreement with the experimental annealing process in terms of the structural, energetic, and vibrational properties. In addition, by comparing the excess energies, structure factors, radial distribution functions, phonon densities of states, and Raman spectra, it is possible to determine the corresponding theoretical model for experimental samples prepared with a certain method and thermal history.

Quantifying Chemical Structure and Machine‐Learned Atomic Energies in Amorphous and Liquid Silicon

AbstractAmorphous materials are being described by increasingly powerful computer simulations, but new approaches are still needed to fully understand their intricate atomic structures. Here, we show how machine‐learning‐based techniques can give new, quantitative chemical insight into the atomic‐scale structure of amorphous silicon (a‐Si). We combine a quantitative description of the nearest‐ and next‐nearest‐neighbor structure with a quantitative description of local stability. The analysis is applied to an ensemble of a‐Si networks in which we tailor the degree of ordering by varying the quench rates down to 1010 K s−1. Our approach associates coordination defects in a‐Si with distinct stability regions and it has also been applied to liquid Si, where it traces a clear‐cut transition in local energies during vitrification. The method is straightforward and inexpensive to apply, and therefore expected to have more general significance for developing a quantitative understanding of liquid and amorphous states of matter.

Quantifying Chemical Structure and Machine-Learned Atomic Energies in Amorphous and Liquid Silicon.

Amorphous materials are being described by increasingly powerful computer simulations, but new approaches are still needed to fully understand their intricate atomic structures. Here, we show how machine‐learning‐based techniques can give new, quantitative chemical insight into the atomic‐scale structure of amorphous silicon (a‐Si). We combine a quantitative description of the nearest‐ and next‐nearest‐neighbor structure with a quantitative description of local stability. The analysis is applied to an ensemble of a‐Si networks in which we tailor the degree of ordering by varying the quench rates down to 1010 K s−1. Our approach associates coordination defects in a‐Si with distinct stability regions and it has also been applied to liquid Si, where it traces a clear‐cut transition in local energies during vitrification. The method is straightforward and inexpensive to apply, and therefore expected to have more general significance for developing a quantitative understanding of liquid and amorphous states of matter.

Effect of etching time on structure of p-type porous silicon

Porous silicon (PSi) is a semiconductor produced by a dissolution p-type silicon wafers in hydrofluoric acid (HF) solution by applying a positive potential to a silicon electrode. We investigate the effect of etching time on morphology, structure and photoluminescence of PSi produced by a solution of hydrofluoric acid (HF) and methanol without UV irradiation. We found that surface structure depends strongly on etching time. From Fourier transform infrared spectroscopy and grazing incidence X-ray diffraction we suggest formation towards less-ordered amorphous phase of PSi. All samples reveal red-band photoluminescence. Although we observe different morphology of samples (channel-like morphology versus nanometer-sized hillocks morphology) slight effect on PL active structures (small red shift) was observed. We suggest that source of luminescence in our experiment is hydrogenated amorphous silicon structures and various HySiOx complexes. We cannot rule out the effect of SixFyO complexes. Surface morphology has small effect on photoluminescence.

Effects of Hydrogen-Dilution on Opto-Structural Properties of Hot-wire CVD Grown a-Si:H/nc-Si:H Multilayer for Photovoltaics

The multilayered thin film structure of amorphous silicon (a-Si:H) and nanocrystalline silicon (nc-Si:H) provides the possibility of bandgap tuning for fabrication of multijunction solar cells. This paper communicates a detailed analysis of optical and structural properties of a-Si:H/nc-Si:H multilayer thin films by hot-wire chemical vapor deposition at low hydrogen (H2) and silane (SiH4) flow rates. A set of multilayer films with 25 bilayers of a-Si:H/nc-Si:H are prepared using different hydrogen-dilution of SiH4 in the alternating nc-Si:H layers. The first and the second order Raman scattering studies reveal the presence of mixed phases of silicon in the nc-Si:H layers. Raman and XRD investigation of the films confirm the presence of different sizes of the silicon nanocrystals. The optical spectroscopic analysis instead of FTIR analysis of multilayer films is utilized uniquely to determine the hydrogen content in the a-Si:H/nc-Si:H multilayers and is related to the amorphous phase of the films. No significant change in hydrogen content is observed and the amorphous phase is found to decrease with increase in hydrogen dilution. Further, no quantum size effect (QSE) was observed due to the large growth time of nc-Si:H layers. Thus the experimental result shows that the bandgap of multilayer films decreases due to reduction in amorphous silicon phase, ineffective QSE and relative loss of hydrogen content.

Nano-fabrication of depth-varying amorphous silicon crescent shell array for light trapping

We report a new structure of depth controllable amorphous silicon (a-Si) crescent shells array, fabricated by the SiO2 monolayer array assisted deposition of a-Si by plasma enhanced chemical vapor deposition and nanosphere lithography, for high-efficiency light trapping applications. The depth of the crescent shell cavity was tailored by selective etching of a-Si layer of the SiO2/a-Si core/shell nanoparticle array with a varied etching time. The morphological changes of the crescent shells were examined by scanning electron microscopy and atomic force microscopy. A simple model is developed to describe the geometrical evolution of the a-Si crescent shells. Spectroscopic measurements and finite difference time domain simulations were conducted to examine the optical performance of the crescent shells. Results show that these nanostructures all have a broadband high efficiency absorption and that the light trapping capability of these crescent shell structures depends on the excitation of depths-regulated optical resonance modes. With an appropriate selection of process parameters, the structure of crescent a-Si shells may be fine-tuned to achieve an optimal light trapping capacity.

CNT/Cu Electrodes: A Versatile Platform for High Performance Silicon and Sulfur Based Binder Free Electrodes in Li-Ion Battery

Silicon based anode has attracted considerable attention to replace graphite as a high-energy density anode material for the next generation lithium ion batteries due to the high theoretical specific capacity of silicon (~4200 mAh/g). However, bulk crystalline silicon exhibits poor performance due to colossal volumetric expansion (~400%) following reaction with lithium. The past decade has witnessed different approaches to address and counter the issue of mechanical degradation of silicon anodes. These approaches involve the use of silicon nanoparticles [1], composite structures of amorphous silicon [2], active-inactive matrix [3], electrodeposited thin films and VACNT-Si hetero-structures [4-6]. On the other hand, the cathode systems are restricted due to low capacities (160-190mAh/g) and sulfur has been shown as a promising alternative with a theoretical capacity of ~1600mAh/g. However, sulfur cathode suffers from polysulfide dissolution and electrode passivation which results in poor performance, high capacity fade and subsequent failure of the electrodes. [7-10] In the present work, a promising anode material for Li-ion batteries consisting of active material deposited on carbon nanotubes (CNT) has been synthesized as a viable electrode generated by a commerically viable facile electrodeposition (ED) process. At first, a thin layer of catalyst M on Cu substrate (denoted as M-Cu) has been developed using a high throughput solution based coating technique. The SEM image and EDAX mapping (Fig 1a) of M-Cu confirms that a distinct layer (<1µ) of catalyst M is coated on the Cu foil. Subsequently, a forest of carbon nanotubes (CNTs)is grown on the M-Cu substrate by CVD technique using a mixture of cost effective carbon precursors and argon at varying temperatures and times. The SEM image of the CNT/M-Cu (Fig 1b) shows the formation of CNTs well adhered to the M/Cu substrate. The thickness of the CNT layer varies from ~30µ to ~200µ depending on the deposition time. Amorphous Si is deposited on the CNT/M-Cu by a commerically viable electrodeposition process using a non aqueous ionic electrolyte consisiting of silicon containing precursors. The SEM analysis of the Si deposited CNT/M-Cu (Fig 1c and Fig 1d) shows a uniform film of Si deposited on the CNTs with the size of the silicon particles being < 100nm. Furthermore, the CNT/Cu substrate was used to develop S/CNT nanostructured composite on Cu substrate as the cathode. The electrodes of these nanocomposites (Si/CNT and S/CNT) were initially tested in a half cell configuration within the voltage range of 0.01V – 1V vs. Li/Li+in their respective electrolyte system without addition of any binder. The electrodeposited Si on CNT/M-Cu (denoted as ED-Si/CNT) was tested as an anode in Li/Li+ electrochemical cell without any further addition of additives. The ED-Si/CNT electrodes show a first cycle discharge and charge capacity of ~ 3435 mAh/g and ~2050 mAh/g, respectively, with a first cycle irreversible (FIR) loss of ~35-45% (Fig 1e) at a charge/discharge current rate of ~300mA/g. The ED-Si/CNT also shows an excellent capacity retention with a stable capacity of ~1870 mAh/g up to 70 cyles (Fig. 1e). The electrochemical performance of S/CNT binderless electrode shall be reported and discussed along with complete characterization of the electrodes using Raman Spectroscopy, X-ray Diffraction, TEM and XPS to understand the behavior of these respective electrode system with respect to Li/Li+system. Acknowledgement: The authors gratefully acknowledge financial support of the DOE-BATT (DE-AC02-05CHl1231), DOE-PNNL and NSF (CBET-1511390) programs. The authors also acknowledge the Edward R. Weidlein Chair Professorship funds and the Center for Complex Engineered Multifunctional Materials (CCEMM) for support of this research.

Structural simplicity as a restraint on the structure of amorphous silicon

Understanding the structural origins of the properties of amorphous materials remains one of the most important challenges in structural science. In this study we demonstrate that local 'structural simplicity', embodied by the degree to which atomic environments within a material are similar to each other, is powerful concept for rationalising the structure of canonical amorphous material amorphous silicon (a-Si). We show, by restraining a reverse Monte Carlo refinement against pair distribution function (PDF) data to be simpler, that the simplest model consistent with the PDF is a continuous random network (CRN). A further effect of producing a simple model of a-Si is the generation of a (pseudo)gap in the electronic density of states, suggesting that structural homogeneity drives electronic homogeneity. That this method produces models of a-Si that approach the state-of-the-art without the need for chemically specific restraints (beyond the assumption of homogeneity) suggests that simplicity-based refinement approaches may allow experiment-driven structural modelling techniques to be developed for the wide variety of amorphous semiconductors with strong local order.

Ultrafast emission decay with high emission efficiency of quantum dots in plasmonic–dielectric metasubstrates

We report on the ultrafast decay of quantum dots that reaches nearly 430 ps without reduction in the emission intensity when near a metasubstrate of simple geometry. By implementing a layered structure of amorphous silicon sandwiched between two gold layers, the balance between plasmonic near field enhancement and energy transfer of the quantum dots has been shifted. This is achieved by tailoring the amount of Förster resonance energy transfer (FRET) to the top Au layer and plasmonic near field enhancement by the bottom Au layer. We also study the impact of deposition of Al oxide on the top Au layer, forming a charge barrier junction that can suppress Auger recombination of quantum dots. The results show that such a barrier can increase emission efficiency of the metastructure without significant reduction in the decay rate. We study the impact of formation of small nanoislands to contiguous islands via variation of the thickness of the top Au layer, and discuss how such morphologies determine the amount of FRET, screening of plasmonic field from the bottom Au layer, and enhancement of emission due to their own plasmonic fields.

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

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.