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Results for “optimized energy density functionals”

Search indexed NASA NTRS and DOE OSTI research on propulsion, heat transfer, battery materials and energy systems. Follow report and document links to the original sources.

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At least 577 records · Page 32
All sourcesNASA NTRSDOE OSTI
DOE OSTI2016

A polymer dataset for accelerated property prediction and design

Emerging computation- and data-driven approaches are particularly useful for rationally designing materials with targeted properties. Generally, these approaches rely on identifying structure-property relationships by learning from a dataset of sufficiently large number of relevant materials. The learned information can then be used to predict the properties of materials not already in the dataset, thus accelerating the materials design. Herein, we develop a dataset of 1,073 polymers and related materials and make it available at http://khazana.uconn.edu/. This dataset is uniformly prepared using first-principles calculations with structures obtained either from other sources or by using structure search methods. Because the immediate target of this work is to assist the design of high dielectric constant polymers, it is initially designed to include the optimized structures, atomization energies, band gaps, and dielectric constants. As a result, it will be progressively expanded by accumulating new materials and including additional properties calculated for the optimized structures provided.

36 MATERIALS SCIENCE↗
DOE OSTI2015

Thermodynamic and achievable efficiencies for solar-driven electrochemical reduction of carbon dioxide to transportation fuels

Thermodynamic, achievable, and realistic efficiency limits of solar-driven electrochemical conversion of water and carbon dioxide to fuels are investigated as functions of light-absorber composition and configuration, and catalyst composition. The maximum thermodynamic efficiency at 1-sun illumination for adiabatic electrochemical synthesis of various solar fuels is in the range of 32–42%. Single-, double-, and triple-junction light absorbers are found to be optimal for electrochemical load ranges of 0–0.9 V, 0.9–1.95 V, and 1.95–3.5 V, respectively. Achievable solar-to-fuel (STF) efficiencies are determined using ideal double- and triple-junction light absorbers and the electrochemical load curves for CO 2 reduction on silver and copper cathodes, and water oxidation kinetics over iridium oxide. The maximum achievable STF efficiencies for synthesis gas (H 2 and CO) and Hythane (H 2 and CH 4 ) are 18.4% and 20.3%, respectively. Whereas the realistic STF efficiency of photoelectrochemical cells (PECs) can be as low as 0.8%, tandem PECs and photovoltaic (PV)-electrolyzers can operate at 7.2% under identical operating conditions. Finally, we show that the composition and energy content of solar fuels can also be adjusted by tuning the band-gaps of triple-junction light absorbers and/or the ratio of catalyst-to-PV area, and that the synthesis of liquid products and C 2 H 4 have high profitability indices.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2025

Processability and Material Behavior of NiTi Shape Memory Alloys Using Wire Laser-Directed Energy Deposition (WL-DED)

Utilizing additive manufacturing (AM) techniques with shape memory alloys (SMAs) like NiTi shows great promise for fabricating highly flexible and functionally superior 3D metallic structures. Compared to methods relying on powder feedstocks, wire-based additive manufacturing processes provide a viable alternative, addressing challenges such as chemical composition instability, material availability, higher feedstock costs, and limitations on part size while simplifying process development. This study presented a novel approach by thoroughly assessing the printability of Ni-rich Ni55.94Ti (Wt. %) SMA using the wire laser-directed energy deposition (WL-DED) technique, addressing the existing knowledge gap regarding the laser wire-feed metal additive manufacturing of NiTi alloys. For the first time, the impact of processing parameters—specifically laser power (400–1000 W) and transverse speed (300–900 mm/min)—on single-track fabrication using NiTi wires in the WL-DED process was examined. An optimal range of process parameters was determined to achieve high-quality prints with minimal defects, such as wire dripping, stubbing, and overfilling. Building upon these findings, we printed five distinct cubes, demonstrating the feasibility of producing nearly porosity-free specimens. Notably, this study investigated the effect of energy density on the printed part density, impurity pick-up, transformation temperature, and hardness of the manufactured NiTi cubes. The results from the cube study demonstrated that varying energy densities (46.66–70 J/mm3) significantly affected the quality of the deposits. Lower to intermediate energy densities achieved high relative densities (>99%) and favorable phase transformation temperatures. In contrast, higher energy densities led to instability in melt pool shape, increased porosity, and discrepancies in phase transformation temperatures. These findings highlighted the critical role of precise parameter control in achieving functional NiTi parts and offer valuable insights for advancing AM techniques in fabricating larger high-quality NiTi components. Additionally, our research highlighted important considerations for civil engineering applications, particularly in the development of seismic dampers for energy dissipation in structures, offering a promising solution for enhancing structural performance and energy management in critical infrastructure.

Dabbaghi, Hediyeh↗
DOE OSTI2023

Crystal structure of meglumine diatrizoate, (C 7 H 18 NO 5 )(C 11 H 8 I 3 N 2 O 4 )

The crystal structure of meglumine diatrizoate has been solved and refined using synchrotron X-ray powder diffraction data and optimized using density functional theory techniques. Meglumine diatrizoate crystallizes in space group P2 1 (#4) with a = 10.74697(4), b = 6.49364(2), c = 18.52774(7) Å, β = 90.2263(3), V = 1292.985(5) Å 3 , and Z = 2. Two different crystal structures, which yielded essentially identical refinement residuals and positions of the non-H atoms, were obtained. The differences were in the H atom positions and the hydrogen bonding. One structure was 123.0 kJ/mol/cell lower in energy than the other and was adopted for the final description. The crystal structure consists of alternating double layers of cations and anions along the c-axis. The hydrogen bonds link the cations and anions into a three-dimensional framework. Each of the hydrogen atoms on the ammonium nitrogen of the cation acts as a donor in a strong N–H∙∙∙O hydrogen bond. One of these is to a hydroxyl group of another cation, and the other is to the carboxylate group of the anion. Each of the amide nitrogen atoms of the anion forms a strong N–H∙∙∙O intermolecular hydrogen bond, one to a carbonyl and the other to a carboxylate group. The powder pattern has been submitted to ICDD for inclusion in the Powder Diffraction File™ (PDF®).

36 MATERIALS SCIENCE↗
DOE OSTI2023

Investigating magnetic van der Waals materials using data-driven approaches

In this work, we investigate magnetic monolayers of the form A i A ii B 4 X 8 based on the well-known intrinsic topological magnetic van der Waals (vdW) material MnBi 2 Te 4 (MBT) using first-principles calculations and machine learning techniques. We select an initial subset of structures to calculate the thermodynamic properties, electronic properties, such as the band gap, and magnetic properties, such as the magnetic moment and magnetic order using density functional theory (DFT). Data analytics approaches are used to gain insight into the microscopic origin of materials’ properties. The dependence of materials’ properties on chemical composition is also explored. For example, we find that the formation energy and magnetic moment depend largely on A and B sites whereas the band gap depends on all three sites. Finally, we employ machine learning tools to accelerate the search for novel vdW magnets in the MBT family with optimized properties. Finally, this study creates avenues for rapidly predicting novel materials with desirable properties that could enable applications in spintronics, optoelectronics, and quantum computing.

36 MATERIALS SCIENCE↗
DOE OSTI2014

The structure of carbon monoxide adsorbed on the NaCl(100) surface—A combined LEED and DFT-D/vdW-DF study

The structure of the first layer CO adsorbed on NaCl(100) is investigated experimentally by means of quantitative low-energy electron diffraction at 25 K, and theoretically by means of density functional theory. Consistent with earlier helium atom diffraction results, the monolayer structure has p(2×1) symmetry with a glide-plane along the longer axis of the unit cell. The structure analysis confirms the binding of CO via the carbon end to the NaCl(100) surface. The vertical distance of carbon above Na{sup +} is 2.58 ± 0.08 Å, in good agreement with geometry optimizations based on dispersion-corrected density functional theory, and 0.15 Å lower than predicted in calculations based on the nonlocal van der Waals density functional.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2020

Influence of Vegetation Canopy Architecture on Dynamics of Spatiotemporal Light Distribution and its Effect on Land-Biosphere-Atmosphere Fluxes of Energy, Carbon, and Water

The dynamic spatiotemporal distribution of light and micro climatic variables (wind speed, atmospheric CO 2 concentration, humidity, pressure, and air temperature) within the plant canopy as determined by the canopy architecture play a critical role in land-biosphere-atmosphere (LBA) photosynthetic carbon uptake, transpiratory water loss and energy partitioning. Vegetation models that include effects of sun and shade flecks, leaf temperature and energy balance partitioning between sensible and latent heat fluxes, and reduced turbulent mixing in dense vegetation canopies can accurately predict canopy performance, particularly its shaded leaves, which can constitute 80% of leaf area and contribute up to 50% of carbon update and 65% of water loss. However, current vegetation models with their bulk characterization of shaded leaves poorly represent the complex three dimensional (3D) canopy architecture are insufficient to capture the spatiotemporal dynamics of shaded leaves. Here, we propose to employ an x-ray computed tomography (XCT) imaging technique in combination with an automated, high throughput, image processing pipeline (3DArch, to be developed) to obtain an explicit 3D triangulated surface mesh of a plant canopy (Fig 1). 3DArch would provide a much needed technological jump in 3D LBA modeling where computer generated artificial 3D models suffer from lack of high resolution detailed canopy architecture parameters. The 3D canopy surface mesh output from 3DArch is coupled with an explicit 3D forward ray tracing model (fastTracer) to obtain a high resolution representation of the dynamic spatiotemporal light environment within the canopy over the course of a day (Fig 1). The results from the light attenuation model are then coupled with a process based multi-scale bio-physical canopy and leaf model of photosynthesis (PlantGro) to get fluxes of carbon, water and energy at the leaf and canopy scale, in addition to estimating whole plant carbon uptake, and water loss. Our proposed model framework would be the first of its kind to provide a breakthrough capability in the field of process-based plant modeling that bridges the key technological gap in shaded leaf modeling through explicit representation of 3D canopy architecture. Computer generated artificial 3D model canopy simulations on grasses show that the canopy light distribution does not follow an exponential behavior as assumed in most 1D vegetation models, but rather exhibits a heterogeneous behavior, with a small but significant portion of interior canopy leaves experiencing peak light levels due to sun flecks while the rest of the canopy receives substantially lower light levels. These results indicate a bias in traditional models that overestimates shaded leaf contribution towards whole canopy photosynthesis by up to 15% and underestimate transpiration by up to 12% with an associated increase in sensible heat fluxes since photosynthesis, transpiration and energy partitioning are tightly coupled processes. However, these test results need to be validated using the 3D architecture obtained from a real plant imaged in 3D using 3DArch, rather than an artificial model plant. Our proposed model framework would allow us to identify inefficiencies in canopy light distribution and prescribe optimal canopy architectures (leaf optical properties, leaf area, leaf angles, row spacing, planting density, etc.) to traditional and genetic engineering based crop breeders, for maximizing target functions such as light use efficiency, water use efficiency, drought tolerance, crop yield, crop resilience etc., with important applications in biofuel crops such as sorghum, and switchgrass. Our model can also be applied for designing optimal canopy architecture that increase surface albedo as a mitigation strategy for global warming and projections of crop yield for future food and water security under climate change.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2019

Using Willingness to Pay to Forecast the Adoption of Solar Photovoltaics: A ''Parameterization + Calibration'' Approach

Distributed energy resources, such as rooftop solar photovoltaics (PV), are likely to comprise a substantial fraction of new generation capacity in the United States. However, forecasting technology adoption based on people's willingness to pay (WTP) faces two major challenges: the stated-intention and omitted-variable biases. Previous solar adoption literature has neglected to address these two biases altogether. Here, we adopt a 'parameterization + calibration' approach to address both biases and estimate customers' WTP for PV. After collecting survey data on respondents' WTP for adopting PV, we characterize its empirical cumulative density function using a gamma distribution. We further calibrate the gamma distribution parameters using a national distributed PV adoption simulation model, finding the parameters that produce the best fit between simulated and historic solar adoption. We then show that the calibrated gamma distribution improves the raw WTP data after correcting for the two biases. Finally, we use our optimally-calibrated WTP to forecast market demand for residential PV at the county-level of the United States in 2020. Improving estimates of customer willingness to pay has significant implications for policy directly, e.g. estimating the effect of a proposed policy on technology adoption, and other regulatory processes that use forecasting, e.g. integrated resource planning.

14 SOLAR ENERGY↗
DOE OSTI2018

Quantum Chemical Calculation of p K a s of Environmentally Relevant Functional Groups: Carboxylic Acids, Amines, and Thiols in Aqueous Solution

Developing accurate quantum chemical approaches for calculating p K a s is of broad interest. Useful accuracy can be obtained by using density functional theory (DFT) in combination with a polarizable continuum solvent model. However, some classes of molecules present problems for this approach, yielding errors greater than 5 p K units. Various methods have been developed to improve the accuracy of the combined strategy. These methods perform well but either do not generalize or introduce additional degrees of freedom, increasing the computational cost. The Solvation Model based on Density (SMD) has emerged as one of the most commonly used continuum solvent models. Nevertheless, for some classes of organic compounds, e.g., thiols, the p K a s calculated with the original SMD model show errors of 6–10 p K units, and we traced these errors to inaccuracies in the solvation free energies of the anions. To improve the accuracy of p K a s calculated with DFT and the SMD model, we developed a scaled solvent-accessible surface approach for constructing the solute–solvent boundary. By using a “direct” approach, in which all quantities are computed in the presence of the continuum solvent, the use of thermodynamic cycles is avoided. Furthermore, no explicit water molecules are required. Three benchmark data sets of experimentally measured p K a values, including 28 carboxylic acids, 10 aliphatic amines, and 45 thiols, were used to assess the optimized SMD model, which we call SMD with a scaled solvent-accessible surface (SMD sSAS ). Of the methods tested, the M06-2X density functional approximation, 6-31+G(d,p) basis set, and SMD sSAS solvent model provided the most accurate p K a s for each set, yielding mean unsigned errors of 0.9, 0.4, and 0.5 p K units, respectively, for carboxylic acids, aliphatic amines, and thiols. As a result, this approach is therefore useful for efficiently calculating the p K a s of environmentally relevant functional groups.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2021

Achieving performance portability in Gaussian basis set density functional theory on accelerator based architectures in NWChemEx

The numerical integration of the exchange–correlation (XC) potential is one of the primary computational bottlenecks in Gaussian basis set Kohn–Sham density functional theory (KS-DFT). To achieve optimal performance and accuracy, care must be taken in this numerical integration to preserve local sparsity as to allow for near linear weak scaling with system size. This leads to an integration scheme with several performance critical kernels which must be hand optimized for each architecture of interest. As the set of available accelerator hardware goes more diverse, a key challenge for developers of KS-DFT software is to maintain performance portability across a wide range of computational architectures. In this article, we examine a modular software design pattern which decouples the implementation details of performance critical kernels from the expression of high-level algorithmic workflows in a device-agnostic language such as C++; thus allowing for developers to target existing and emerging accelerator hardware within a single code base. We consider the efficacy of such a design pattern in the numerical integration of the XC potential by demonstrating its ability to achieve performance portability across a set of accelerator architectures which are representative of those on current and future U.S. Department of Energy Leadership Computing Facilities.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2016

Study of CdTe/CdS solar cell at low power density for low-illumination applications

In this paper, we numerically investigate CdTe/CdS PV cell properties using a simulation program Solar Cell Capacitance Simulator in 1D (SCAPS-1D). A simple structure of CdTe PV cell has been optimized to study the effect of temperature, absorber thickness and work function at very low incident power. Objective of this research paper is to build an efficient and cost effective solar cell for portable electronic devices such as portable computers and cell phones that work at low incident power because most of such devices work at diffused and reflected sunlight. In this report, we simulated a simple CdTe PV cell at very low incident power, which gives good efficiency.

14 SOLAR ENERGY↗
DOE OSTI2015

A Strategy to Stabilize Kesterite CZTS for High-Performance Solar Cells

Cu 2 ZnSnS 4–x Se x (CZTS) is an important semiconductor with significant potential for applications in the next generation of solar cells. CZTS has an optimal band gap (~1.5 eV) and contains no expensive or toxic elements. However, CZTS-based solar cells suffer from low efficiency because of poor crystal quality, which is partly caused by secondary phase formation during synthesis. In this work, we use density functional theory+U calculations to systematically investigate the stabilities of three CZTS phases: kesterite, stannite, and wurtzite. In agreement with previous experiment and theory, we confirm that these three phases have very similar formation energies. This finding is consistent with the known difficulties in synthesizing pure kesterite CZTS, the phase that is desirable for photovoltaic applications. To overcome this problem, we characterize surfaces and interfaces of CZTS and are able to identify certain “beneficial surfaces” that could be exploited to potentially provide extra stability for the kesterite phase. We propose the zinc blende ZnS (001) surface as a substrate to induce formation of these beneficial surfaces and to stabilize the kesterite phase, thereby serving as an effective crystallization template for the fabrication of high-performance CZTS solar cells.

14 SOLAR ENERGY↗
DOE OSTI2022

Facilitating Hydrogen Dissociation over Dilute Nanoporous Ti–Cu Catalysts

The dissociation of H 2 is an essential elementary step in many industrial chemical transformations, typically requiring precious metals. Here, we report a hierarchical nanoporous Cu catalyst doped with small amounts of Ti (npTiCu) that increases the rate of H 2 –D 2 exchange by approximately one order of magnitude compared to the undoped nanoporous Cu (npCu) catalyst. The promotional effect of Ti was measured via steady-state H 2 –D 2 exchange reaction experiments under atmospheric pressure flow conditions in the temperature range of 300–573 K. Pretreatment with flowing H 2 is required for stable catalytic performance, and two temperatures, 523 and 673 K, were investigated. The experimentally determined H 2 –D 2 exchange rate is 5–7 times greater for npTiCu vs the undoped Cu material under optimized pretreatment and reaction temperatures. The H 2 pretreatment leads to full reduction of Cu oxide and partial reduction of surface Ti oxide species present in the as-prepared catalyst as demonstrated using in situ ambient pressure X-ray photoelectron spectroscopy and X-ray absorption spectroscopy. The apparent activation energies and pre-exponential factors measured for H 2 –D 2 exchange are substantially different for Ti-doped vs undoped npCu catalysts. Density functional theory calculations suggest that isolated, metallic Ti atoms on the surface of the Cu host can act as the active surface sites for hydrogen recombination. Furthermore, the increase in the rate of exchange above that of pure Cu is caused primarily by a shift in the rate-determining step from dissociative adsorption on Cu to H/D atom recombination on Ti-doped Cu, with the corresponding decrease in activation entropy that it produces.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2022

A combined theoretical and experimental study of small anthracene–water clusters

Water-cluster interactions with polycyclic aromatic hydrocarbons (PAHs) are of paramount interest in many chemical and biological processes. Here we report a study of anthracene monomers and dimers with water (up to four)-cluster systems utilizing molecular beam vacuum-UV photoionization mass spectrometry and density functional calculations. Structural loss in photoionization efficiency curves when adding water indicates that various isomers are generated, while theory indicates only a slight shift in energy in photoionization states of different isomers. Calculations reveal that the energetic tendency of water is to remain clustered and not to disperse around the PAH. Theoretically, we observe water confinement exclusively in the case of four water clusters and only when the anthracenes are in a cross configuration due to optimal OH∙∙∙π interactions, indicating dependence on the size and structure of the PAH. Furthermore theory sheds light on the structural changes that occur in water upon ionization of anthracene, due to the optimal interactions of the resulting hole and water hydrogen atoms.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2020

A charge-density-based general cation insertion algorithm for generating new Li-ion cathode materials

Future lithium (Li) energy storage technologies, in particular solid-state configurations with a Li metal anode, opens up the possibility of using cathode materials that do not necessarily contain Li in its as-made state. To accelerate the discovery and design of such materials, we develop a general, chemically, and structurally agnostic methodology for identifying the optimal Li sites in any crystalline material. For a given crystal structure, we attempt multiple Li insertions at symmetrically in-equivalent positions by analyzing the electronic charge density obtained from first-principles density functional theory. In this report, we demonstrate the effectiveness of this procedure in successfully identifying the positions of the Li ion in well-known cathode materials using only the empty host (charged) material as guidance. Furthermore, applying the algorithm to over 2000 candidate cathode empty host materials we obtain statistics of Li site preferences to guide future developments of novel Li-ion cathode materials, particularly for solid-state applications.

25 ENERGY STORAGE↗
DOE OSTI2018

Efficient Oxygen Electrocatalysis by Nanostructured Mixed-Metal Oxides

Oxygen electrocatalysis plays a critical role in the efficiency of important energy conversion and storage systems. While many efforts have focused on designing efficient electrocatalysts for these processes, optimal catalysts that are inexpensive, active, selective, and stable are still being searched. Nonstoichiometric, mixed-metal oxides present a promising group of electrocatalysts for these processes due to the versatility of the surface composition and fast oxygen conducting properties. Herein, we demonstrate, using a combination of theoretical and experimental studies, the ability to develop design principles that can be used to engineer oxygen electrocatalysis activity of layered, mixed ionic-electronic conducting Ruddlesden– Popper (R–P) oxides. We show that a density function theory (DFT) derived descriptor, O 2 binding energy on a surface oxygen vacancy, can be effective in identifying efficient R–P oxide structures for oxygen reduction reaction (ORR). Using a controlled synthesis method, well-defined nanostructures of R–P oxides are obtained, which along with thermochemical and electrochemical activity studies are used to validate the design principles. This has led to the identification of a highly active ORR electrocatalyst, nanostructured Co-doped lanthanum nickelate oxide, which when incorporated in solid oxide fuel cell cathodes significantly enhances the performance at intermediate temperatures (~550 °C), while maintaining long-term stability. Here, the reported findings demonstrate the effectiveness of the developed design principles to engineer mixed ionic-electronic conducting oxides for efficient oxygen electrocatalysis, and the potential of nanostructured Co-doped lanthanum nickelate oxides as promising catalysts for oxygen electrocatalysis.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2015

Size and structure effects of Pt{sub N} (N = 12 − 13) clusters for the oxygen reduction reaction: First-principles calculations

Size and structure effects on the oxygen reduction reaction on Pt{sub N} clusters with N = 12–13 atoms have been investigated using periodic density functional theory calculations with the generalized gradient approximation. To describe the catalytic activity, we calculated the O and OH adsorption energies on the cluster surface. The oxygen binding on the 3-fold hollow sites on stable Pt{sub 12−13} cluster models resulted more favorable for the reaction with O, compared with the Pt{sub 13}(I{sub h}) and Pt{sub 55}(I{sub h}) icosahedral particles, in which O binds strongly. However, the rate-limiting step resulted in the removal of the OH species due to strong adsorptions on the vertex sites, reducing the utility of the catalyst surface. On the other hand, the active sites of Pt{sub 12−13} clusters have been localized on the edge sites. In particular, the OH adsorption on a bilayer Pt{sub 12} cluster is the closest to the optimal target; with 0.0-0.2 eV weaker than the Pt(111) surface. However, more progress is necessary to activate the vertex sites of the clusters. The d-band center of Pt{sub N} clusters shows that the structural dependence plays a decisive factor in the cluster reactivity.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2015

Crystal orbital study on the double walls made of nanotubes encapsulated inside zigzag carbon nanotubes

The structure stabilities and electronic properties are investigated by using ab initio self-consistent-field crystal orbital method based on density functional theory for the one-dimensional (1D) double-wall nanotubes made of n-gon SiO{sub 2} nanotubes encapsulated inside zigzag carbon nanotubes. It is found that formation of the combined systems is energetically favorable when the distance between the two constituents is around the Van der Waals scope. The obtained band structures show that all the combined systems are semiconductors with nonzero energy gaps. The frontier energy bands (the highest occupied band and the lowest unoccupied band) of double-wall nanotubes are mainly derived from the corresponding carbon nanotubes. The mobilities of charge carriers are calculated to be within the range of 10{sup 2}–10{sup 4} cm{sup 2} V{sup −1} s{sup −1} for the hybrid double-wall nanotubes. Young’s moduli are also calculated for the combined systems. For the comparison, geometrical and electronic properties of n-gon SiO{sub 2} nanotubes are also calculated and discussed. - Graphical abstract: Structures and band structures of the optimum 1D Double walls nanotubes. The optimized structures are 3-gon SiO2@(15,0), 5-gon SiO2@(17,0), 6-gon SiO2@(18,0) and 7-gon SiO2@(19,0). - Highlights: • The structure and electronic properties of the 1D n-gon SiO{sub 2}@(m,0)s are studied using SCF-CO method. • The encapsulation of 1D n-gon SiO{sub 2} tubes inside zigzag carbon nanotubes can be energetically favorable. • The 1D n-gon SiO{sub 2}@(m,0)s are all semiconductors. • The mobility of charge carriers and Young’s moduli are calculated.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗