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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 703 records · Page 39
All sourcesNASA NTRSDOE OSTI
DOE OSTI2018

Theoretical and experimental investigations on H2 sensing properties of flower-like titanium dioxide

Highlights: • Flower-like rutile TiO{sub 2} has been successfully synthesized. • The unique nanostructure show an great enhanced gas-sensing performance. • A sensing mechanism based on our calculation was proposal. - Abstract: Microstructure and gas sensing properties of partly agglomerating flower-like rutile TiO{sub 2} obtained using a one-pot hydrothermal method was investigated. Test results exhibited an excellent sensitivity to H{sub 2} gas and stable reproducibility. Further, we performed a first principles calculation of an established surface model to delve into the sensing mechanism. Adsorbed oxygen preferred to locate upon the Ti{sub 5c} site, while the electronic structure of surface had rather weak changes after hydrogen adsorption. This simulation may pave a new path to further discover the sensing mechanism of rutile TiO{sub 2}-based gas sensor.

77 NANOSCIENCE AND NANOTECHNOLOGY↗
DOE OSTI2021

Mol* Viewer: modern web app for 3D visualization and analysis of large biomolecular structures

Abstract Large biomolecular structures are being determined experimentally on a daily basis using established techniques such as crystallography and electron microscopy. In addition, emerging integrative or hybrid methods (I/HM) are producing structural models of huge macromolecular machines and assemblies, sometimes containing 100s of millions of non-hydrogen atoms. The performance requirements for visualization and analysis tools delivering these data are increasing rapidly. Significant progress in developing online, web-native three-dimensional (3D) visualization tools was previously accomplished with the introduction of the LiteMol suite and NGL Viewers. Thereafter, Mol* development was jointly initiated by PDBe and RCSB PDB to combine and build on the strengths of LiteMol (developed by PDBe) and NGL (developed by RCSB PDB). The web-native Mol* Viewer enables 3D visualization and streaming of macromolecular coordinate and experimental data, together with capabilities for displaying structure quality, functional, or biological context annotations. High-performance graphics and data management allows users to simultaneously visualise up to hundreds of (superimposed) protein structures, stream molecular dynamics simulation trajectories, render cell-level models, or display huge I/HM structures. It is the primary 3D structure viewer used by PDBe and RCSB PDB. It can be easily integrated into third-party services. Mol* Viewer is open source and freely available at https://molstar.org/.

Sehnal, David↗
DOE OSTI2023

Exploring the Performance Boundaries of a Small Reconfigurable Multi-Mission UAV through Multidisciplinary Analysis

The performance of a small reconfigurable unmanned aerial vehicle (UAV) is evaluated, combining a multidisciplinary approach in the computational analysis of additive manufactured structures, fluid dynamics, and experiments. Reconfigurable UAVs promise cost savings and efficiency, without sacrificing performance, while demonstrating versatility to fulfill different mission profiles. The use of computational fluid dynamics (CFD) in UAV design produces higher accuracy aerodynamic data, which is particularly important for complex aircraft concepts such as blended wing bodies. To address challenges relating to anisotropic materials, the Tsai–Wu failure criterion is applied to the structural analysis, using CFD solutions as load inputs. Aerodynamic performance results show the low-speed variant attains an endurance of 1 h, 48 min, whereas its high-speed counterpart is 29 min at a 66.7% higher cruise speed. Each variant serves different aspects of small UAS deployment, with low speed envisioned for high-endurance surveying, and high speed for long-range or time-critical missions such as delivery. The experimental and simulation results suggest room for design iteration, in wing area and geometry adjustments. Structural simulations demonstrated the need for airframe improvements to the low-speed configuration. This paper highlights the potential of reconfigurable UAVs to be useful across multiple industries, advocating for further research and design improvements.

42 ENGINEERING↗
DOE OSTI2022

Predictive coarse-grained (CG) modeling of morphologies in polymer nanocomposites with specific and directional intermolecular interactions (Final Report)

The overarching goal of the proposed work was to develop predictive models for investigating structure and dynamics in soft materials with chemistries that have specific and directional molecular interactions. The motivation behind studying materials with specific and directional interactions lies in the many desirable features these interactions provide when designing novel soft materials. Soft materials with specific and direction interactions (such as hydrogen bonds or H-bonds) can have a) thermally reversible phase behavior with different functions with varying temperature, b) precisely tuned nanostructure with desirable geometries that afford unique physical properties (e.g., color response, mechanical properties) and c) well-mixed/blended morphologies that are useful for variety of applications in energy field (e.g., materials for batteries require use of blended polymers where one domain gives superior mechanical properties and one domain promotes electrical conduction). Notably, biology makes extensive use of specific and directional interactions, in many cases based on H-bonds, to construct materials with precisely defined architectures and properties. Engineered soft materials with precisely tuned nanostructures and improved processiblity through thermoresponsive phase behavior are useful in numerous applications that are relevant to the Department of Energy (DOE) including high efficiency electronic devices, light-weight high-strength composite materials for batteries and fuel cells, and polymer membranes for separations, etc. While past computational studies have been tremendously useful in understanding molecular phenomena and guiding synthesis of new macromolecular soft materials for a wide variety of applications, the inability to capture small scale specific and directional interactions alongside macromolecular length and time scales represented a key limitation of most studies to date. Our work in this project addressed this grand challenge in computational materials chemistry, i.e., ability to model the anisotropic, directional, and specific interactions that govern the behavior of many macromolecular soft matter systems of interest, thus, has greatly expanded the predictive potential of simulations. Specifically the key outcomes were: successful development of new coarse-grained (CG) polymer models to study generic and specific polymer chemistries in which hydrogen-bonding interactions are dominant. These CG models were then used in molecular simulations to study structure and thermodynamics in polymer nanocomposites and blends; some studies were conducted in collaboration with experimentalists. We also published a perspective and a viewpoint which included some of the work we completed in this DOE project; we believe these perspective and viewpoint articles guide other researchers in the soft materials community on how to extend the computational approaches and models we have developed for the purposes of their studies.

36 MATERIALS SCIENCE↗
DOE OSTI2022

Using Machine Learning to Greatly Accelerate Path Integral Ab Initio Molecular Dynamics

Ab initio molecular dynamics (AIMD) has become one of the most popular and robust approaches for modeling complicated chemical, liquid, and material systems. However, the formidable computational cost often limits its widespread application in simulations of the largest-scale systems. Furthermore, the situation becomes even more severe in cases where the hydrogen nuclei may be better described as quantized particles using a path integral representation. Here, we present a computational approach that combines machine learning with recent advances in path integral contraction schemes, and we achieve a 2 orders of magnitude acceleration over direct path integral AIMD simulation while at the same time maintaining its accuracy.

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

Atomic structure and grain shape evolution of nanodiamond during annealing in oxidizing atmosphere from neutron diffraction and MD simulations

In this work, real space pair-distribution function (PDF) analysis in conjunction with molecular dynamics (MD) simulations was applied to characterize crystal structure, shape and surface structure of diamond nanoparticles annealed in air up to 880 °C. MD simulated models of individual nanodiamond particles of various shapes and sizes were used to calculate theoretical radial distribution functions G(r) for powders with different grain size distributions. The calculated curves, showing distinct differences for the explored parameter space, were compared to the experimental G(r) functions obtained from neutron scattering for annealed detonated nanodiamond samples in a search for a model best describing the actual powders. It was found that as-synthesized nanodiamond grains are terminated by equally abundant (100), (110) and (111) crystallographic faces and their structure does not change upon annealing in air up to 280 °C. The shape and size of grains annealed above 480 °C changes due to surface etching. The etching rate differs between crystals faces and depends on temperature, resulting in the observed differences in grain shape. Below 680 °C the share of the (110) facets gradually increases and at 680 °C the grains become rhombic dodecahedra terminated solely by (110) surfaces. Further increase of the annealing temperature promotes formation of (111) surfaces and at 880 °C the preferred grain shape becomes an octahedron terminated by a variant of (111) surfaces possessing three dangling sp3 bonds per atom. At lower temperatures all grains become smaller and the size distribution moves towards the lower values. Furthermore, as the annealing temperature increases, the smallest grains disappear entirely and the average grain size grows back.

36 MATERIALS SCIENCE↗
DOE OSTI2018

Critical Factors in Computational Characterization of Hydrogen Storage in Metal–Organic Frameworks

Inconsistencies in high-pressure H2 adsorption data and a lack of comparative experiment–theory studies have made the evaluation of both new and existing metal–organic frameworks (MOFs) challenging in the context of hydrogen storage applications. In this work, we performed grand canonical Monte Carlo (GCMC) simulations in nearly 500 experimentally refined MOF structures to examine the variance in simulation results because of the equation of state, H 2 potential, and the effect of density functional theory structural optimization. We find that hydrogen capacity at 77 K and 100 bar, as well as hydrogen 100-to-5 bar deliverable capacity, is correlated more strongly with the MOF pore volume than with the MOF surface area (the latter correlation is known as the Chahine’s rule). The tested methodologies provide consistent rankings of materials. In addition, four prototypical MOFs (MOF-74, CuBTC, ZIF-8, and MOF-5) with a range of surface areas, pore structures, and surface chemistries, representative of promising adsorbents for hydrogen storage, are evaluated in detail with both GCMC simulations and experimental measurements. Simulations with a three-site classical potential for H 2 agree best with our experimental data except in the case of MOF-5, in which H 2 adsorption is best replicated with a five-site potential. However, for the purpose of ranking materials, these two choices for H 2 potential make little difference. Here more significantly, 100 bar loading estimates based on more accurate equations of state for the vapor–liquid equilibrium yield the best comparisons with the experiment.

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

Lattice Structured Lightweight Structural Materials

The development of lightweight structural materials is crucial for enhancing the performance and deployment feasibility of fission batteries. This study aims to produce lightweight structural materials whose strength-to-weight ratios exceed those of current widely used structural materials. To achieve this, advanced modeling and simulation tools were employed to design lattice structures with different lattice parameters and different lattice types. A process was successfully developed for transforming lattice-structured models into Multiphysics Object Oriented Simulation Environment (MOOSE) inputs. Finite element modeling (FEM) was used to simulate the uniaxial tensile testing of the lattice-structured parts to investigate the stress distribution at a given displacement. The modeling results showed that the lattice-structured sample displayed a lower Young’s modulus in comparison to the solid material; the increase in solid shell thickness and blend radius enhances the mechanical performance; and the effect of unit cell size on macro scale stress is minimal. Tensile testing was conducted on the solid and lattice-structured materials fabricated by laser powder bed fusion (LPBF) additive manufacturing. The experimental results agreed well with the model prediction. The approach of using modeling as a guiding tool for preliminary material design can significantly save time and cost for new material development.

lightweight material↗
DOE OSTI2023

Structure and dynamics of $\mathrm{Fe_{90}}$$\mathrm{Si_3}$$\mathrm{O_7}$ liquids close to Earth's liquid core conditions

Using an artificial neural-network machine learning interatomic potential, we have performed molecular dynamics simulations to study the structure and dynamics of $\mathrm{Fe_{90}}$$\mathrm{Si_3}$$\mathrm{O_7}$ liquid close to the Earth's liquid core conditions. Here, the simulation results reveal that the short-range structural order (SRO) in the $\mathrm{Fe_{90}}$$\mathrm{Si_3}$$\mathrm{O_7}$ liquid is very strong. About 80% of the atoms are arranged in crystallinelike SRO motifs. In particular, ~ $70$% of Fe-centered clusters can be classified as either hexagonal-close-packed-like or icosahedrallike SRO motifs. The SRO clusters centered on Fe, Si, or O atoms are strongly intermixed and homogenously distributed throughout the liquid. The atomic structure of the liquid and the fractions of dominant SRO clusters are not sensitive to pressure/temperature used in the simulations except that the SRO of the O-centered clusters is enhanced close to inner core pressures. The O-diffusion coefficient is about two to three times larger than the Fe and Si ions and increases more rapidly in the deeper core regions.

75 CONDENSED MATTER PHYSICS, SUPERCONDUCTIVITY AND↗
DOE OSTI2017

All-Atom Molecular Dynamics Study of Water–Dodecane Interface in the Presence of Octanol

In this work, classical atomistic molecular dynamics (MD) simulations were performed to investigate the structural properties of octanol at water/dodecane interface. Multiple combinations of simulation conditions and force fields were employed in order to :obtain high fidelity interfacial structure. The analysis of noncovalent interactions shows that the convergence of interfacial octanol distribution requires a simulation time scale larger than 100 ns. Finite size effect diminishes with increasing dimension of simulation box both laterally and vertically. In the largest simulated systems with vanishing finite size effect, the additive CHARMM force field shows similar interfacial aggregation behavior with the DRUDE polarizable model. Self-assembly of octanol molecules at water/oil interface is observed, expected to reduce;the free energy barrier between water phase and oil phase. This work provides an MD simulation benchmark for structural study of complex liquid/liquid interface with cosurfactant reducing interfacial tension between two immiscible phases.

Qiao, Baofu↗
DOE OSTI2020

Short-wavelength-sensitive 2 (Sws2) visual photopigment models combined with atomistic molecular simulations to predict spectral peaks of absorbance

For many species, vision is one of the most important sensory modalities for mediating essential tasks that include navigation, predation and foraging, predator avoidance, and numerous social behaviors. The vertebrate visual process begins when photons of the light interact with rod and cone photoreceptors that are present in the neural retina. Vertebrate visual photopigments are housed within these photoreceptor cells and are sensitive to a wide range of wavelengths that peak within the light spectrum, the latter of which is a function of the type of chromophore used and how it interacts with specific amino acid residues found within the opsin protein sequence. Minor differences in the amino acid sequences of the opsins are known to lead to large differences in the spectral peak of absorbance (i.e. the λ max value). In our prior studies, we developed a new approach that combined homology modeling and molecular dynamics simulations to gather structural information associated with chromophore conformation, then used it to generate statistical models for the accurate prediction of λ max values for photopigments derived from Rh1 and Rh2 amino acid sequences. In the present study, we test our novel approach to predict the λ max of phylogenetically distant Sws2 cone opsins. To build a model that can predict the λ max using our approach presented in our prior studies, we selected a spectrally-diverse set of 11 teleost Sws2 photopigments for which both amino acid sequence information and experimentally measured λ max values are known. The final first-order regression model, consisting of three terms associated with chromophore conformation, was sufficient to predict the λ max of Sws2 photopigments with high accuracy. This study further highlights the breadth of our approach in reliably predicting λ max values of Sws2 cone photopigments, evolutionary-more distant from template bovine RH1, and provided mechanistic insights into the role of known spectral tuning sites.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2026

Planetary Boundary-Layer Height (PBLHT) Value-Added Product: Remote-Sensing Retrievals

The planetary boundary layer (PBL) is fundamental to numerous atmospheric processes, including aerosol mixing and transport, cloud evolution, and precipitation formation. A critical parameter in these studies is the PBL height (PBLHT). This vertical depth is essential for characterizing PBL structures in numerical simulations and serves as a primary metric for estimating flux exchanges between the Earth’s surface and the atmosphere. Radiosonde (SONDE) observations provide high-vertical-resolution measurements of temperature and moisture profiles and are widely used to estimate PBLHT (Liu and Liang 2010, Seidel et al. 2010). The U.S. Department of Energy Atmospheric Radiation Measurement (ARM) User Facility’s PBLHT value-added product (VAP) for radiosonde measurements, known as PBLHTSONDE, applies three commonly used methods—the Heffter (1980) method, the Liu and Liang (2010) method, and the bulk Richardson number approach (Seibert et al. 2000)—to derive PBLHT. The PBLHTSONDE VAP operates routinely at ARM observatories and mobile facilities, with data available from the ARM Data Center shortly after sounding observations are collected (Sivaraman et al. 2013). However, radiosonde observations are limited by their low temporal resolution. Most stations launch soundings only twice daily, which constrains the ability to investigate and characterize the temporal evolution of the PBL using radiosonde data alone. The use of continuous remote-sensing observations provides high temporal resolution of PBLHT estimates. These observations include aerosol lidars (Dang et al. 2019, Su et al. 2020), Doppler lidar (DL; Tucker et al. 2009, Krishnamurthy et al. 2021), and water vapor and/or temperature lidars and radiometers (Turner et al. 2014). These observations provide valuable data on the PBL’s thermodynamic properties (e.g., water vapor and/or temperature lidars and radiometers), dynamic properties (e.g., DL), and distribution of tracer substances (e.g., aerosol lidars), all of which can be used to estimate PBLHT. ARM developed PBLHT estimates from the micropulse lidar (MPL; PBLHTMPL), Doppler lidar (PBLHTDL), and combined Raman lidar (RL)/atmospheric emitted radiance interferometer (AERI) thermodynamic profiles (PBLHTTHERMO). Each estimate captures different physical characteristics of the boundary layer—aerosol tracers, vertical velocity turbulence, and thermodynamic structure—and exhibits distinct strengths and limitations depending on the PBL regime and time of day. In addition, the ARM ceilometer (CEIL) provides three potential PBLHT candidates derived from the vendor's built-in algorithm. Building on these individual retrievals, ARM developed the PBLHTBEML VAP, which combines the four remote-sensing-based estimates with ancillary meteorological variables using the machine learning approach of Zhang et al. (2025) to produce a best-estimate PBLHT at 10-minute resolution.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2020

CP2K: An Electronic Structure and Molecular Dynamics Software Package - Quickstep: Efficient and Accurate Electronic Structure Calculations

CP2K is an open source electronic structure and molecular dynamics software package to perform atomistic simulations of solid-state, liquid, molecular and biological systems. It is especially aimed at massively-parallel and linear-scaling electronic structure methods and state-of-the-art ab-initio molecular dynamics simulations. Excellent performance for electronic structure calculations is achieved using novel algorithms implemented for modern high-performance computing systems. This review revisits the main capabilities of CP2K to perform efficient and accurate electronic structure simulations. The emphasis is put on density functional theory and multiple post-Hartree-Fock methods using the Gaussian and plane wave approach and its augmented all-electron extension. TDK has received funding from the European Research Council (ERC) under the European Union's Horizon 2020 research and innovation programme (grant agreement No. 716142). VRR has been supported by the Swiss National Science Foundation in the form of Ambizione grant No. PZ00P2 174227 and RZK by the Natural Sciences and Engineering Research Council of Canada (NSERC) through Discovery Grants (RGPIN-2016-0505). GKS and CJM are supported by the US Department of Energy, Office of Science, Office of Basic Energy Sciences, Division of Chemical Sciences, Geosciences, and Biosciences. UK based work was funded under the embedded CSE programme of the ARCHER UK National Supercomputing Service (http://www.archer.ac.uk), grants eCSE03-011, eCSE06-6, eCSE08-9, eCSE13-17 and the EPSRC (EP/P022235/1) grant “Surface and Interface Toolkit for the Materials Chemistry Community". Computational resources were provided by the Swiss National Supercomputing Centre (CSCS) and Compute Canada. The generous allocation of computing time on the FPGA-based supercomputer “Noctua" at PC2 is kindly acknowledged.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2018

Structures and diffusion of two-dimensional dusty plasmas on one-dimensional periodic substrates

Using numerical simulations, we examine the structure and diffusion of a two-dimensional dusty plasma (2DDP) in the presence of a one-dimensional periodic substrate (1DPS) as a function of increasing substrate strength. Both the pair correlation function perpendicular to the substrate modulation and the mean-squared displacement (MSD) of dust particles are calculated. It is found that both the structure and dynamics of 2DDP exhibit strong anisotropic effects, due to the applied 1DPS. As the substrate strength increases from zero, the structure order of dusty plasma along each potential well of 1DPS increases first probably due to the competition between the interparticle interactions and the particle-substrate interactions, and then decreases gradually, which may be due to the reduced dimensionality and the enhanced fluctuations. The obtained MSD along potential wells of 1DPS clearly shows three processes of diffusion in our studied 2DDP. Finally, between the initial ballistic and finally diffusive motion, there is the intermediate subdiffusion discovered here, which may result from the substrate-induced distortion of the caging dynamics.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗
DOE OSTI2020

Multimodal Nanoscale Tomographic Imaging for Battery Electrodes

Accurate representations of the 3D structure within a lithium-ion battery are key to understanding performance limitations. However, obtaining exact reconstructions of electrodes, where the active particles, the carbon black and polymeric binder domain, and the pore space are visualized is challenging. In this work, it is shown that multimodal imaging can be used to overcome this challenge. High-resolution ptychographic X-ray computed tomography are combined with lower resolution but higher contrast transmission X-ray tomographic microscopy to obtain 3D reconstructions of pristine and cycled graphite-silicon composite electrodes. This cross-correlation enables quantitative analysis of the surface of active particles, including the heterogeneity of carbon-black and binder domain and solid-electrolyte interphase coverage. Capturing the active particles as well as the carbon black-binder domain allows using these segmented structures for electrochemical simulations to highlight the influence of the particle embedding on local state of charge heterogeneities.

25 ENERGY STORAGE↗
DOE OSTI2020

Deactivation of Cu-Exchanged Automotive-Emission NH 3 -SCR Catalysts Elucidated with Nanoscale Resolution Using Scanning Transmission X-ray Microscopy

To gain insight into the underlying mechanisms of catalyst durability for the selective catalytic reduction (SCR) of NO x with an ammonia reductant, we employed scanning transmission X-ray microscopy (STXM) to study Cu-exchanged zeolites with the CHA and MFI framework structures before and after simulated 135 000-mile aging. X-ray absorption near-edge structure (XANES) measurements were performed at the Al K- and Cu L-edges. The local environment of framework Al, the oxidation state of Cu, and geometric changes were analyzed, showing a multi-factor-induced catalytic deactivation. In Cu-exchanged MFI, a transformation of Cu II to Cu I and Cu x O y was observed. We also found a spatial correlation between extra-framework Al and deactivated Cu species near the surface of the zeolite as well as a weak positive correlation between the amount of CuI and tri-coordinated Al. By inspecting both Al and Cu in fresh and aged Cu-exchanged zeolites, we conclude that the importance of the preservation of isolated Cu II sites trumps that of Brønsted acid sites for NH 3 -SCR activity.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2019

The energy budget and figure of Earth during recovery from the Moon-forming giant impact

Quantifying the energy budget of Earth in the first few million years following the Moon-forming giant impact is vital to understanding Earth's initial thermal state and the dynamics of lunar tidal evolution. After the impact, the body was substantially vaporized and rotating rapidly, very different from the planet we know today. The subsequent evolution of Earth's energy budget, as the body cooled and angular momentum was transferred during lunar tidal recession, has not been accurately calculated with all relevant energy components included. In this work, we use giant impact simulations and planetary structure models to calculate the energy budget at stages in Earth's evolution. We show that the figure and internal structure of Earth changed substantially during its post-impact evolution and that changes in kinetic, potential, and internal energy were all significant. These changes have important implications for the dynamics of tidal recession and the thermal structure of early Earth.

58 GEOSCIENCES↗