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The energy of each volume-optimized sample as compared to quartz. The data representation is the same as in Fig. 2. The relative energy difference is significantly greater for the BKS potential than for the DFT methods. The trend in energy is very similar for the LDA and GGA, with the difference from quartz being slightly larger using the LDA for eight out of the ten samples studied. Energy for DFT-optimized quartz is from work by Demuth et al. ͑ Ref. 55 ͒ .
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Multiple small samples of amorphous silica have been generated and optimized using classical dynamics and the van Beest-Kramer-van Santen BKS empirical potential function. The samples were subsequently opti-mized and annealed using density functional theory DFT with both the local density and the generalized gradient approximations. A thorough anal...
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... that after repeated applications of the ART, the system could have found a more stable, defect-free state, but this was not pursued. The efficacy of the ART may be affected by the size of the region allowed to rearrange. Theories on glass aging 50 indicate that within a glass, transformation of larger regions may lead to lower-energy states, while transformation of smaller regions can lead to higher- energy states. Results of the high-temperature annealing and the ART simulations indicate that the generated systems are in relatively deep local minima, and significant atomic rearrangement is required to decrease the system energy any further. The periodic boundary conditions and the small system size used in this study introduce constraints that are not present for larger-scale simulations. To test how well the small systems capture the characteristics of a larger glass, the structures of the small glasses were compared with a larger sample. The larger glass system was made up of 1479 atoms, or 493 SiO 2 units. It was prepared by the same classical annealing methods as the smaller samples, using the same classical potential ͑ the BKS potential ͒ with the exception that the cutoff length was set to 9 Å. The sample was quenched from the melt in two ways; the first at constant volume, such that the density was 2.20 g / cm 3 ; and the second at constant pressure using the Berendsen barostat. 51 The NPT run resulted in a glass that was 2.33 g / cm 3 , 6% denser than the NVT run. The 1479-atom glass contained about 1% defects, in the form of overcoordinated or undercoordinated atoms. The coordination number was determined by counting atoms at less than a specified cutoff distance that defines bonding between atom pairs. The cutoffs used to define bonding were r Si-Si = 2.5 Å, r Si-O = 1.9 Å, and r O-O = 2.0 Å. No O - O or Si- Si bonds were found. About 1% of the rings found in the system were three- membered rings. This population of defects and small rings is typical for the types and amounts of defects found in samples generated using the BKS potential. 31 The large simulation results are used to determine the quality of the small glass samples as a group. The ability of the BKS potential to generate good glass structures has been shown elsewhere. 31,52,53 A thorough analysis of the structural characteristics of the ten small glass samples was carried out, and compared to the same characteristics of the larger glass. For any given samples, optimization using different potentials did not change the connectivity of the network, but other structural characteristics were affected. Distributions of the Si- O bond lengths, first O - O and Si- Si pair distributions, the O - Si- O and Si- O - Si bond angles, and the torsion angle and ring size distribution were determined. The ring sizes are given in terms of the number of silicon atoms in a ring, so for example a ring with six Si and six O atoms is considered to be a six-member ring. Where available, data were compared to experimental quantities. The average total distribution functions ͑ TDF’s ͒ of the optimized structures were compared to the TDF of a larger glass sample, and to experimental neutron diffraction data. 54 In addition, analysis was done at the the level of the tetrahedral unit. The intra-tetrahedral tilt and twist angle distributions were examined. Descriptions of these quantities are given below. Figure 2 shows the histogram of the change in volume per SiO 2 unit for the ten samples volume optimized ͑ VO ͒ using the BKS potential, LDA, and GGA, compared to the change in volume in the larger glass sample. The change in volume per SiO 2 unit is reported with respect to the initial fixed volume of 2.20 g / cm 3 . Every sample decreased in volume. The relative trend for the LDA and GGA was similar, with LDA leading to significantly greater change ͑ and thus smaller cell sizes ͒ for each glass. The density after relaxation with DFT-LDA ranges from 2.37 to 2.45 g / cm , while optimal densities obtained with DFT-GGA ranges from 2.24 to 2.33 g / cm 3 . This density difference, of about 6.5%, is consistent with previous DFT calculations performed on a wide variety of crystalline silica polymorphs, in which the optimal cell volumes are found to be smaller for the LDA than the GGA. 55 LDA calculations result in densities that are about 1% higher than experimental densities for low-density crystalline silica polymorphs. 55 The relative volume change of each sample was qualitatively the same using the BKS potential. The density changes were similar in magnitude to the results obtained with the LDA, with a greater spread in volume, 2.33– 2.52 g / cm 3 , and higher average density. As pointed out above, the density for the larger-sample BKS potential also increased. Note that the density of silica obtained from simulations is strongly dependent on the short- range potential cutoff and whether or not corrections to the energy at the cutoff are included. 32,34 Figure 3 shows the histogram of the relative energy for the ten samples volume optimized using the BKS potential, the LDA, and the GGA. The relative energies per SiO 2 unit of the optimized structures are compared to one another where the reference energy is that of quartz calculated using the same method. The trend in relative energy is very similar for the LDA and GGA, with the difference from quartz being slightly larger using the LDA for eight out of the ten samples studied. Optimization using the BKS potential results in a different trend of relative energy. There is no clear correla- tion between the relative sample energy and optimum sample density. Previous work has shown that for fixed identical volumes, optimization with the LDA or GGA results in nearly identical coordinates for crystalline polymorphs of silica. 55 This is not the case for amorphous silica. Figure 4 shows the scatter of Si- O bond lengths versus Si- O - Si angles plotted for both LDA and GGA optimized glass 6 at a fixed volume of 2.20 g / cm 3 . It is apparent that the system undergoes a nearly uniform shift to shorter bond lengths and wider Si- O - Si bond angles in going from the GGA to the LDA. The average Si- O, O - O, and Si- Si pair distribution functions are evaluated as experimental values derived from neutron scattering experiments to produce total distribution functions. Individual features are discussed below. Data are shown in Table I. Figure 5 shows a comparison of the average silicon- oxygen bond length distributions of the ten 72-atom glass samples with the bond length distribution for the 1479-atom glass. The bond length distributions for the large and small configurations quenched with the BKS potential are quite similar. Results for the LDA at fixed volume are similar to the BKS potential. The DFT-GGA results give slightly longer bond lengths, by about 0.01 Å on average, than the BKS potential. This is due to the difference in interatomic forces, rather than the size of the system. Optimizing the cell volume, or allowing the cell volume to relax resulted in slightly shorter average bond lengths for all the configurations, and narrower bond length distributions, for the small systems. This effect was most pronounced for DFT-LDA, which also had the greatest degree of change in the volume. Figures 6 and 7 show the first peak in the O - O and Si- Si pair distribution functions, respectively. Optimization of the volume causes a shift toward closer distances, and a slight narrowing of all the first-neighbor distributions. At fixed volume, O - O distances are closest for the LDA. Distributions are widest for the BKS potential. Differences in the Si- Si distances are extremely small. Distributions for the larger glass are slightly wider than for the small samples using any method. Optimization of the volume causes a shift toward closer Si- Si distances. This is expected due to the smaller cell volumes after optimization. This structural characteristic can be most easily related to the Si- O - Si bond angle distribution ͑ BAD ͒ ; however, this angle is also affected by bond lengths, and changes in local torsion or twisting between neighboring silica tetrahedra. Total distributions functions were constructed for each silica sample at fixed density of 2.20 g / cm 3 , with peaks for the structural data broadened using the formulation sug- gested by Wright. 25 Figure 8 shows a comparison of the constructed results with neutron scattering experiments. 25,54 The average TDFs for the small samples were truncated at a distance of 5 Å. The fit to the experimental data for the 1479-atom glass is similar to results obtained for other simulations, with an R x factor of about 8. 54 As the composite curves for the smaller glasses may only be considered to 5 Å, the comparison of the TDF to experimental data may only be considered qualitatively at this time. It is evident that the average TDF for the 72-atom systems is more similar to the TDF for the 1479- atom glass than to the experimental data. This may indicate that there is some underlying bias in the structures due to the choice of the initial empirical potential, the small size of the systems, and the glass-cooling algorithm employed. Never- theless, the results indicate that the volume-optimized samples have too-close distances for both the O - O and Si- Si peaks. The average O - Si- O, and Si- O - Si bond angle distribution, Si- O - Si- O torsion angle distribution ͑ TAD ͒ , and ring structure are examined and compared with the results for the larger glass. These structures may be inferred experimentally from neutron scattering, and Raman spectroscopy, but are challenging to measure directly. Data for the O - Si- O and Si- O - Si BADs are shown in Table II. Analysis is also performed at the level of tetrahedral structural units. Individual features are described and discussed below. Figure 9 shows the average oxygen-silicon-oxygen BAD of the small glasses, and the quenched ...
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... To characterize the nature of the bonding in amorphous Ti 2 C-MXene and its crystal counterpart, we have calculated the bond order (BO). The amorphous Ti 2 C produced in this work differs from both the traditional amorphous materials and the 2D phases of those, such as vitreous silica [23] or amorphous phases of graphene. [16] The [Ti 6 C] octahedra in MXenes are connected by sharing three M atoms, meaning that it is difficult for [Ti 6 C] octahedron to twist like a silicon oxygen tetrahedron after heating up. ...
The emergence of amorphous 2D materials has opened up new avenue for materials science and nanotechnology in the recent years. Their unique disordered structure, excellent large‐area uniformity, and low fabrication cost make them important for various industrial applications. However, there have no reports on the amorphous MXene materials. In this work, the amorphous Ti2C–MXene (a‐Ti2C–MXene) model is built by ab initio molecular dynamics (AIMD) approach. This model is a unique amorphous model, which is totally different from continuous random network (CRN) model for silicate glass and amorphous model for amorphous 2D BN and graphene. The structure analysis shows that the a‐Ti2C–MXene composited by [Ti5C] and [Ti6C] cluster, which are surrounded by the region of mixed cluster [TixC], [Ti–Ti] cluster, and [C–C] cluster. There is a high chemical activity for hydrogen evolution reaction (HER) in a‐Ti2C–MXene with |ΔGH| 0.001 eV, implying that they serve as the potential boosting HER performance. The work provides insights that can pave the way for future research on novel MXene materials, leading to their increased applications in various fields.
... The results indicate that both higher temperature and amorphization lead to an increase in Si-O bond length and a decrease in O-Si-O angle, consistent with previous works. 19,[56][57][58][59][60][61] The Si-O bond lengths vary from 1.60 to 1.63 Å as the temperature increases from 700 to 1000 K, which agrees with neutron scattering experimental results. 62 The O-Si-O bond angles remain within a narrow range of 109.0 • ± 0.2 • in all studied models. ...
The atomic scale solid–liquid interfacial process dominates the macro‐dissolution of silica, yet its direct experimental observation is challenging. Here we employed the reactive molecular dynamics to model this process in alkaline condition. An elevated temperature strategy under canonical ensemble (NVT) was applied to accelerate the process for sufficient sampling at temporal domain. A stepwise transformation from fully linked SiO4 network (Q³ and Q⁴) to reduced linkage and eventually aqueous species (Q⁰) was revealed. The simulated dissolution rate agrees well with the value predicted by empirical model. By tracing hydrogen atoms, we found that the dehydroxylated silica surfaces in alkaline electrolyte solutions underwent a transition from Si–O–Si bond cleavage‐dominated (mainly reacted with OH⁻) to hydroxylation‐dominated surface reactions. The free‐energy reconstruction of well‐tempered metadynamics reveals that 1500 K accelerates dissolution without altering the reaction pathways. These findings offer novel insights into the evolution of atomic‐scale surface configurations during the dissolution kinetics of silica.
... While ab initio techniques and first-principles calculations can be used 22,23 to get an understanding of a system, they quickly become computationally expensive given the large unit cells of silica polymorphs and the number of possible configurations. Furthermore, ab initio simulations of silica are often limited by length-time scales, that circumscribe them for the dynamics of small clusters 24,25 . Faster models are required to access longer time scales and accurately capture the dynamical evolution of the structural features like the angular distribution between the tetrahedral units and even features such as charge distribution, when subject to external stimuli [26][27][28] . ...
Silica is an abundant and technologically attractive material. Due to the structural complexities of silica polymorphs coupled with subtle differences in Si–O bonding characteristics, the development of accurate models to predict the structure, energetics and properties of silica polymorphs remain challenging. Current models for silica range from computationally efficient Buckingham formalisms (BKS, CHIK, Soules) to reactive (ReaxFF) and more recent machine-learned potentials that are flexible but computationally costly. Here, we introduce an improved formalism and parameterization of BKS model via a multireward reinforcement learning (RL) using an experimental training dataset. Our model concurrently captures the structure, energetics, density, equation of state, and elastic constants of quartz (equilibrium) as well as 20 other metastable silica polymorphs. We also assess its ability in capturing amorphous properties and highlight the limitations of the BKS-type functional forms in simultaneously capturing crystal and amorphous properties. We demonstrate ways to improve model flexibility and introduce a flexible formalism, machine-learned ML-BKS, that outperforms existing empirical models and is on-par with the recently developed 50 to 100 times more expensive Gaussian approximation potential (GAP) in capturing the experimental structure and properties of silica polymorphs and amorphous silica.
... Therefore, the MXene may have decomposed before reaching the melting temperature. Different from the connection of (SiO 4 ) tetrahedra in classical amorphous SiO 2 by bridging oxygen, [9] the (M 6 C) octahedra in MXenes are connected by sharing three M atoms, meaning that it is difficult for an (M 6 C) octahedron to twist like a (SiO 4 ) tetrahedron upon heating. Thus, it is hard to synthesize amorphous MXenes by traditional preparation methods. ...
Recently, novel amorphous nanomaterials formed by introducing atomic irregular arrangement factors have been successfully fabricated, showing superior performance in catalysis, energy storage, and mechanics. Among them, 2D amorphous nanomaterials are the stars, as they combine the benefits of both 2D structure and amorphous. Up to now, many research studies have been published on the study of 2D amorphous materials. However, as one of the most important parts of 2D materials, the research on MXenes mainly focuses on the crystalline counterpart, while the study of highly disordered forms is much less. This work will provide insight into the possibility of MXenes amorphization, and discusses the application prospect of amorphous MXenes materials.
... 27 To generate the amorphous silica structures, we performed a melt-quench method by first-principles MD calculations. [28][29][30][31][32] We melted both models at 5000 K for 10 ps (1 fs  10 000 steps) and decreased the temperature from 5000 to 0 K at a rate of À 50 K/ps. Then, structural optimization calculations were performed for each structure, and we investigated the characteristic local structures. ...
Potassium-ion electrets, which mainly consist of amorphous silica and permanently store negative charge, are vital elements of small autonomous vibration-powered generators. However, negative charge decay is sometimes observed to cause issues for applications. In this study, we propose an improved guideline for the fabrication of potassium-ion electrets by first-principles calculations based on density functional theory, which shows that yield reduction can be suppressed by additional oxidation. Moreover, we experimentally confirm that the additional oxidation step effectively extends the lifetime of potassium-ion electrets.
... From eq 1, the available "reactive area" per 0.169 mol from 0.169 mol dm −3 (SiO 2 ) amorphous silica particle of radius 17.5 nm dispersion is 8 × 10 5 cm 2 . If a tetrahedrally coordinated structure of both species of dissolved SiO 2 is assumed with a distance between the O atoms of 0.26 nm, 58 a tetrahedral base area of ∼0.03 nm 2 can be estimated. The 0.002 mol dm −3 dissolved SiO 2 (0.012%) in equilibrium with the silica dispersion will have a "reactive area" of 3.6 × 10 5 cm 2 per 0.002 mol SiO 2 if every Langmuir pubs.acs.org/Langmuir ...
The interaction of amorphous silica nanoparticles with phospholipid monolayers and bilayers has received a great deal of interest in recent years and is of importance for assessing potential cellular toxicity of such species, whether natural or synthesized for the purpose of nanomedical drug delivery and other applications. This present communication studies the rate of silica nanoparticle adsorption on to phospholipid monolayers in order to extract a heterogeneous rate constant from the data. This rate constant relates to the initial rate of growth of an adsorbed layer of nanoparticles as SiO2 on a unit area of the monolayer surface from unit concentration in dispersion. Experiments were carried out using the system of dioleoyl phosphatidylcholine (DOPC) monolayers deposited on Pt/Hg electrodes in a flow cell. Additional studies were carried out on the interaction of soluble silica with these layers. Results show that the rate constant is effectively constant with respect to silica nanoparticle size. This is interpreted as indicating that the interaction of hydrated SiO2 molecular species with phospholipid polar groups is the molecular initiating event (MIE) defined as the initial interaction of the silica particle surface with the phospholipid layer surface promoting the adsorption of silica nanoparticles on DOPC. The conclusion is consistent with the observed significant interaction of soluble SiO2 with the DOPC layer and the established properties of the silica-water interface.
... Classical force fields and DFT methods complemented each other in the melting-quenching procedure to obtain an amorphous state, but DFT methods are often used only for local energy optimization after classical MD as in Ref. [6] where the SIESTA code [7] is used for the energy optimization. In Ref. [8], silica glass is obtained from melts of various density using classical MD with BKS potentials, where the BKS abbreviation corresponds to names of authors of Ref. [9], but then glass samples are annealed at 3000 K by ab initio MD employing the VASP program (Vienna ab initio simulation program) [10][11][12]. In contrast to quartz crystal containing only 6-and 8-membered rings, glass samples prepared in Ref. [8] contain rings of a wide range of sizes, constructed from 3 to 13 SiO 4 -tetrahedra. ...
... In Ref. [8], silica glass is obtained from melts of various density using classical MD with BKS potentials, where the BKS abbreviation corresponds to names of authors of Ref. [9], but then glass samples are annealed at 3000 K by ab initio MD employing the VASP program (Vienna ab initio simulation program) [10][11][12]. In contrast to quartz crystal containing only 6-and 8-membered rings, glass samples prepared in Ref. [8] contain rings of a wide range of sizes, constructed from 3 to 13 SiO 4 -tetrahedra. Densities of amorphous (glassy) states of silicon dioxide obtained in [5,6,8] are close to the experimental value of 2.20-2.14 ...
... In contrast to quartz crystal containing only 6-and 8-membered rings, glass samples prepared in Ref. [8] contain rings of a wide range of sizes, constructed from 3 to 13 SiO 4 -tetrahedra. Densities of amorphous (glassy) states of silicon dioxide obtained in [5,6,8] are close to the experimental value of 2.20-2.14 g/cm 3 (at T=0) [5], 2.18-2.23 g/cm 3 (using different DFT methods) [6] and 2.24-2.33 ...
Ab initio molecular dynamics modeling in the NPT ensemble is used to obtain amorphous states by melting SiO2, ZrO2 and HfO2 crystals. A wide range of melt stabilization temperatures are used. Two types of SiO2 amorphous states are obtained. For melt temperatures below 4500 K, a perfect silica glass is obtained without any point defects. For melt temperatures above 4500 K, silica point defects such as threefold coordinated oxygen atoms, edge-sharing SiO4-tetrahedra, and others together with a wide range of Si-O-Si rings including 3-, and 4-membered rings appear. When the temperature of the melt exceeds the ZrO2 and HfO2 crystal melting point by 100 – 400 K, a sharp drop in the density of amorphous states is observed, accompanied by a decrease in atomic coordination, but this does not lead to the formation of defect states in the depth of the band gap of hafnium and zirconium dioxides.
... For this reason it is sufficient to consider only one of the two torsion angles which we will call ω. From the analysis reported in the literature [38,41], it is found that ω varies as a function of the Si-O-Si bond angle and that, for θ in the 140-160°range, it has three maxima of around 60°, 180°, and 300°. These values correspond to the three staggered conformations of the O 3 Si-O-SiO 3 moiety, as viewed along the Si-Si axis, and are such that next-nearest-neighbor oxygen atoms are at a maximum distance. ...
Due to its unique properties, amorphous silicon dioxide (a-SiO2) or silica is a key material in many technological fields, such as high-power laser systems, telecommunications, and fiber optics. In recent years, major efforts have been made in the development of highly transparent glasses, able to resist ionizing and non-ionizing radiation. However the widespread application of many silica-based technologies, particularly silica optical fibers, is still limited by the radiation-induced formation of point defects, which decrease their durability and transmission efficiency. Although this aspect has been widely investigated, the optical properties of certain defects and the correlation between their formation dynamics and the structure of the pristine glass remains an open issue. For this reason, it is of paramount importance to gain a deeper understanding of the structure–reactivity relationship in a-SiO2 for the prediction of the optical properties of a glass based on its manufacturing parameters, and the realization of more efficient devices. To this end, we here report on the state of the most important intrinsic point defects in pure silica, with a particular emphasis on their main spectroscopic features, their atomic structure, and the effects of their presence on the transmission properties of optical fibers.
... Many models for describing silica have been proposed for fixed-charge force fields, 20-33 reactive potentials, [34][35][36][37][38][39][40][41][42] and electronic structure-based interactions. 38,[43][44][45][46][47][48][49][50][51][52][53][54][55] Each of these approaches has advantages and disadvantages depending upon the phenomena that are of interest. ...
... 35 Other reactive force fields include one based on the dissociative water model by Garofalini and co-workers, 40,41 which was used to examine the dissolution of a-SiO 2 silica in water. 42 Electronic structure-based descriptions of silica surfaces using periodic boundary conditions are becoming increasingly accessible, 38,[43][44][45][46][47][48][49][50][51][52][53]55 providing better insight into reactivity of silica surfaces. They are still limited, however, to relatively small system sizes and timescales of not more than a few tens of picoseconds. ...
... It is considered as the archetypal network glass. Its structural [3][4][5][6][7][8][9][10][11] and dynamical [12][13][14][15][16][17][18][19][20][21] properties have been extensively studied both theoretically [8][9][10][11][12][13][14][15][16][17] and experimentally [4][5][6][7][18][19][20][21], but persistent challenges remain. Many computer-simulation-based structural models have been performed for creating realistic structural models of amorphous silica. ...
... It is considered as the archetypal network glass. Its structural [3][4][5][6][7][8][9][10][11] and dynamical [12][13][14][15][16][17][18][19][20][21] properties have been extensively studied both theoretically [8][9][10][11][12][13][14][15][16][17] and experimentally [4][5][6][7][18][19][20][21], but persistent challenges remain. Many computer-simulation-based structural models have been performed for creating realistic structural models of amorphous silica. ...
... This can be explained by the lack of a Si-Si short-range attraction term in the BKS potential. First-principles calculations [8] performed on smaller samples (72 atoms) of amorphous silica have also shown smaller values for the Si-Si distances (3.1 Å) compared to those found with the BKS potential (3.12 Å). A densification can also decrease the Si-Si pair distances. ...
Ten small size samples of amorphous silica containing 78 atoms have been prepared using classical molecular dynamics and the van Beest-Kramer-van Santen (BKS) empirical potential. Our final goal is to use such samples in a forthcoming publication to compute accurately the thermal properties of silica from first principles calculations. The structural characteristics of these ten samples are in good agreement with experimental data. Dynamical properties, like the mean-square displacement, the vibrational density of states or the dynamic structure factor, have also been investigated and compare relatively well with data from neutron scattering experiments. These small dynamically stable structures can therefore be used subsequently to study more complicated physical properties, like the thermal conductivity or the diffusivity at a reduced computational cost.
