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Results for “template free alignment”

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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11 records
All sourcesNASA NTRSDOE OSTI
DOE OSTI2022

Soft-Shear-Aligned Vertically Oriented Lamellar Block Copolymers for Template-Free Sub-10 nm Patterning and Hybrid Nanostructures

The template-free unidirectional alignment of lamellar block copolymers (l-BCPs) for sub-10 nm high-resolution patterning and hybrid multicomponent nanostructures is important for technological applications. Here we demonstrate a modified soft-shear directed self-assembly (SDSA) approach for aligning pristine l-BCPs and l-BCPs with incorporated polymer grafted nanoparticles (PGNPs), as well as the l-BCPs conversion to aligned gold nanowires, and hybrid of metallic gold nanowire and dielectric silica nanoparticle in the form of line-dot nanostructures. The smallest patterns have a half-pitch as small as 9.8 nm. In all cases, soft-shear is achieved using a high molecular mass polymer topcoat layer, with support on a neutral bottom layer. We also show that the hybrid line-dot nanostructures have a red-shifted plasmonic response in comparison to the neat gold nanowires. These template-free aligned BCPs and nanowires have potential use in nanopatterning applications and the line-dot nanostructures should be useful in the plasmonic sensing of biomolecules and other molecular species based on the plasmonic response of the nanowires.

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

MULTICOM2 open-source protein structure prediction system powered by deep learning and distance prediction

Protein structure prediction is an important problem in bioinformatics and has been studied for decades. However, there are still few open-source comprehensive protein structure prediction packages publicly available in the field. In this paper, we present our latest open-source protein tertiary structure prediction system—MULTICOM2, an integration of template-based modeling (TBM) and template-free modeling (FM) methods. The template-based modeling uses sequence alignment tools with deep multiple sequence alignments to search for structural templates, which are much faster and more accurate than MULTICOM1. The template-free (ab initio or de novo) modeling uses the inter-residue distances predicted by DeepDist to reconstruct tertiary structure models without using any known structure as template. In the blind CASP14 experiment, the average TM-score of the models predicted by our server predictor based on the MULTICOM2 system is 0.720 for 58 TBM (regular) domains and 0.514 for 38 FM and FM/TBM (hard) domains, indicating that MULTICOM2 is capable of predicting good tertiary structures across the board. It can predict the correct fold for 76 CASP14 domains (95% regular domains and 55% hard domains) if only one prediction is made for a domain. The success rate is increased to 3% for both regular and hard domains if five predictions are made per domain. Moreover, the prediction accuracy of the pure template-free structure modeling method on both TBM and FM targets is very close to the combination of template-based and template-free modeling methods. This demonstrates that the distance-based template-free modeling method powered by deep learning can largely replace the traditional template-based modeling method even on TBM targets that TBM methods used to dominate and therefore provides a uniform structure modeling approach to any protein. Finally, on the 38 CASP14 FM and FM/TBM hard domains, MULTICOM2 server predictors (MULTICOM-HYBRID, MULTICOM-DEEP, MULTICOM-DIST) were ranked among the top 20 automated server predictors in the CASP14 experiment. After combining multiple predictors from the same research group as one entry, MULTICOM-HYBRID was ranked no. 5. The source code of MULTICOM2 is freely available at https://github.com/multicom-toolbox/multicom/tree/multicom_v2.0 .

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2023

Stable Supercapacity of Binder-Free TiO 2 (B) Epitaxial Electrodes for All-Solid-State Nanobatteries

Owing to its pseudocapacitive, unidimensional, rapid ion channels, TiO 2 (B) is a promising material for application to battery electrodes. In this study, we align these channels by epitaxially growing TiO 2 (B) films with the assistance of an isostructural VO 2 (B) template layer. In a liquid electrolyte, binder-free TiO 2 (B) epitaxial electrodes exhibit a supercapacity near the theoretical value of 335 mA h g –1 and an excellent charge–discharge reproducibility for ≥200 cycles, which outperform those of other TiO 2 (B) nanostructures. For the all-solid-state configuration employing the LiPON solid electrolyte, excellent stability persists. Our findings suggest excellent potential for miniaturizing all-solid-state nanobatteries in self-powered integrated circuits.

25 ENERGY STORAGE↗
DOE OSTI2021

Improving protein tertiary structure prediction by deep learning and distance prediction in CASP14

Abstract Substantial progresses in protein structure prediction have been made by utilizing deep‐learning and residue‐residue distance prediction since CASP13. Inspired by the advances, we improve our CASP14 MULTICOM protein structure prediction system by incorporating three new components: (a) a new deep learning‐based protein inter‐residue distance predictor to improve template‐free (ab initio) tertiary structure prediction, (b) an enhanced template‐based tertiary structure prediction method, and (c) distance‐based model quality assessment methods empowered by deep learning. In the 2020 CASP14 experiment, MULTICOM predictor was ranked seventh out of 146 predictors in tertiary structure prediction and ranked third out of 136 predictors in inter‐domain structure prediction. The results demonstrate that the template‐free modeling based on deep learning and residue‐residue distance prediction can predict the correct topology for almost all template‐based modeling targets and a majority of hard targets (template‐free targets or targets whose templates cannot be recognized), which is a significant improvement over the CASP13 MULTICOM predictor. Moreover, the template‐free modeling performs better than the template‐based modeling on not only hard targets but also the targets that have homologous templates. The performance of the template‐free modeling largely depends on the accuracy of distance prediction closely related to the quality of multiple sequence alignments. The structural model quality assessment works well on targets for which enough good models can be predicted, but it may perform poorly when only a few good models are predicted for a hard target and the distribution of model quality scores is highly skewed. MULTICOM is available at https://github.com/jianlin-cheng/MULTICOM_Human_CASP14/tree/CASP14_DeepRank3 and https://github.com/multicom-toolbox/multicom/tree/multicom_v2.0 .

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2023

Electrochemically Grown Ultrathin Platinum Nanosheet Electrodes with Ultralow Loadings for Energy-Saving and Industrial-Level Hydrogen Evolution

Nanostructured catalyst-integrated electrodes with remarkably reduced catalyst loadings, high catalyst utilization and facile fabrication are urgently needed to enable cost-effective, green hydrogen production via proton exchange membrane electrolyzer cells (PEMECs). Herein, benefitting from a thin seeding layer, bottom-up grown ultrathin Pt nanosheets (Pt-NSs) were first deposited on thin Ti substrates for PEMECs via a fast, template- and surfactant-free electrochemical growth process at room temperature, showing highly uniform Pt surface coverage with ultralow loadings and vertically well-aligned nanosheet morphologies. Combined with an anode-only Nafion 117 catalyst-coated membrane (CCM), the Pt-NS electrode with an ultralow loading of 0.015 mg Pt cm -2 demonstrates superior cell performance to the commercial CCM (3.0 mg Pt cm -2 ), achieving 99.5% catalyst savings and more than 237-fold higher catalyst utilization. The remarkable performance with high catalyst utilization is mainly due to the vertically well-aligned ultrathin nanosheets with good surface coverage exposing abundant active sites for the electrochemical reaction. Overall, this study not only paves a new way for optimizing the catalyst uniformity and surface coverage with ultralow loadings but also provides new insights into nanostructured electrode design and facile fabrication for highly efficient and low-cost PEMECs and other energy storage/conversion devices.

42 ENGINEERING↗
DOE OSTI2024

Designing Ta C Virtual Substrates for Vertical Al x Ga 1 − x N Power Electronics Devices

Power electronics are critical for a sustainable energy future, playing a key role in electrification and integration of renewable energy sources into the grid. Advances in ultrawide band gap materials are needed to handle higher powers in smaller form factors while reducing electrical and thermal losses. High Al content Al x Ga 1 − x N is theoretically capable of meeting these demands, but its impact in power electronics has been severely restricted by a lack of substrates that can satisfy conductivity, lattice matching, and/or thermal expansion requirements. We demonstrate that electrically conductive Ta C can be used as a virtual substrate for Al x Ga 1 − x N heteroepitaxy. Scaleably sputtered Ta C grown on Al 2 O 3 , followed by high-temperature face-to-face annealing, produces a thin film Ta C template with an effective hexagonal lattice constant matched to Al 0.70 Ga 0.30 N . Annealing of the Ta C promotes recrystallization, significantly improving crystallinity and reducing crystalline defects from as-deposited columnar grains to a step-and-terrace surface morphology, enabling the subsequent growth of high-quality Al 0.70 Ga 0.30 N by molecular beam epitaxy. X-ray diffraction and scanning transmission electron microscopy confirm that the Al x Ga 1 − x N layer is heteroepitaxially aligned, strain-free, and lattice-matched, transitioning abruptly from Ta C to Al x Ga 1 − x N without intermediate phases. These results demonstrate Ta C virtual substrates as electrically conductive, lattice-matched, and thermally compatible templates for vertical Al x Ga 1 − x N devices that can meet the growing power needs of a sustainable energy future. Published by the American Physical Society 2024

36 MATERIALS SCIENCE↗
DOE OSTI2022

Achieving High-Resolution Hard X-ray Microscopy using Monolithic 2D Multilayer Laue Lenses

This article introduces the 2D multilayer Laue lens (MLL) nanofocusing optics recently developed for high-resolution hard X-ray microscopy. The new optics utilized a micro-electro-mechanical-system (MEMS)-based template to accommodate two linear MLL optics in a pre-aligned configuration. Angular misalignment between the two lenses was controlled in tens of millidegrees, and the lateral position error was on a micrometer scale. Using the developed 2D MLLs, an astigmatism-free point focus of approximately 14 nm by 13 nm in horizontal and vertical directions, respectively, at 13.6 keV photon energy was obtained. In conclusion, the success of 2D MLL optics with an approaching 10 nm resolution is a significant step forward for the development of high-resolution hard X-ray microscopy and applications of MLL optics in the hard X-ray community.

36 MATERIALS SCIENCE↗
DOE OSTI2022

Superhydrophilicity of $α$-alumina surfaces results from tight binding of interfacial waters to specific aluminols

Understanding the microscopic driving force of water wetting is challenging and important for design of materials. The relations between structure, dynamics and hydrogen bonds of interfacial water can be investigated using molecular dynamics simulations. Here, contact angles at the alumina (0001) and ($11\bar{2}0$) surfaces are studied using both classical molecular dynamics simulations and experiments. To test the superhydrophilicity, the free energy cost of removing waters near the interfaces are calculated using the density fluctuations method. The strength of hydrogen bonds is determined by their lifetime and geometry. Both surfaces are superhydrophilic and the (0001) surface is more hydrophilic. Interactions between surfaces and interfacial waters promote a templating effect whereby the latter are aligned in a pattern that follows the underlying lattice of the surfaces. Translational and rotational dynamics of interfacial water molecules are slower than in bulk water. Hydrogen bonds between water and both surfaces are asymmetric, water-to-aluminol ones are stronger than aluminol-to-water ones. Molecular dynamics simulations eliminate the impacts of surface contamination when measuring contact angles and the results reveal the microscopic origin of the macroscopic superhydrophilicity of alumina surfaces: strong water-to-aluminol hydrogen bonds.

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

PDBspheres: a method for finding 3D similarities in local regions in proteins

Abstract We present a structure-based method for finding and evaluating structural similarities in protein regions relevant to ligand binding. PDBspheres comprises an exhaustive library of protein structure regions (‘spheres’) adjacent to complexed ligands derived from the Protein Data Bank (PDB), along with methods to find and evaluate structural matches between a protein of interest and spheres in the library. PDBspheres uses the LGA (Local–Global Alignment) structure alignment algorithm as the main engine for detecting structural similarities between the protein of interest and template spheres from the library, which currently contains >2 million spheres. To assess confidence in structural matches, an all-atom-based similarity metric takes side chain placement into account. Here, we describe the PDBspheres method, demonstrate its ability to detect and characterize binding sites in protein structures, show how PDBspheres—a strictly structure-based method—performs on a curated dataset of 2528 ligand-bound and ligand-free crystal structures, and use PDBspheres to cluster pockets and assess structural similarities among protein binding sites of 4876 structures in the ‘refined set’ of the PDBbind 2019 dataset.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2023

Recycling the Energy of Indoor Light: Highly Efficient Organic Photovoltaics via a Ternary Strategy

A ternary approach in organic photovoltaics (OPV) is simple and reliable to effectively tune the optical, electrical and morphological properties of the photoactive layer for high efficiency as well as long-term stability under 1 sun. However, there have been few papers reporting spectra and weak illumination compared to outdoor light. In this study, by using two compatible 16 structures, we demonstrate a simultaneous modulation of light absorption and molecular donor polymers (PM7 and PM7 D1) with slightly-different band gaps and similar chemical packing under ambient conditions, which resulted in efficient indoor OPVs exhibiting power conversion efficiency (PCE) over 20% under 1000 lux of warm white light-emitting diode (2900 K). From morphological analysis, we infer that PM7 serves to seed nucleation of PM7 D1 in the ternary blend, templating its crystallization and alignment along the PM7 backbone. Such templating effect leads to increased domain spacing and relative degree of crystallinity (rDoC) compared to those of each binary system. We further show that higher rDoC helps suppress both bimolecular and trap-assisted recombination of photogenerated charges in the ternary devices. As a result, the complementary absorption and synergistic molecular assembly of the two donor polymers enhance the short-circuit current density as to increase the average PCEs from 9.6 to 10.3% under 1 sun and from 18.7 to 20.0% under 1000 lux. We envision that our strategy of incorporating both a planar and a flexible donor polymer with similar chemical structures can be generally applicable to attain a high performance ternary OPV under both 1 sun and indoor light.

14 SOLAR ENERGY↗
DOE OSTI2025

Mechanism of Mesoscale Woodpile Development via Photoelectrochemical Deposition of Se–Te

A combination of experiments and optical modeling provided insight into the mechanism of mesoscale woodpile formation in response to an orthogonal shift in polarization during photoelectrochemical deposition of Se–Te. Cathodic deposition of semiconducting Se–Te using spatially uniform, linearly polarized illumination produced arrays of lamellae that were aligned parallel to the optical E-field oscillation. Continued deposition in conjunction with an orthogonal shift in the polarization direction then produced aligned bridging features that spanned the void space between, and were orthogonal to, the preexisting lamellae. The height and pitch, respectively, in each layer of the woodpile were a function of the charge density and illumination wavelength during deposition. A Monte Carlo model, in which material addition was scaled by the absorption magnitude obtained from electromagnetic simulations, produced morphologies that were nominally identical to those observed experimentally. Here, the formation of mesoscale woodpiles is consistent with a mechanism that involves a series of spontaneously initiated, concerted light–matter interactions during the photoelectrochemical deposition process.

absorption↗