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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 109 records · Page 6
All sourcesNASA NTRSDOE OSTI
DOE OSTI2025

Extending quantum-mechanical benchmark accuracy to biological ligand-pocket interactions

Predicting the binding affinity of ligands to protein pockets is key in the drug design pipeline. The flexibility of ligand-pocket motifs arises from a range of attractive and repulsive electronic interactions during binding. Accurately accounting for all interactions requires robust quantum-mechanical (QM) benchmarks, which are scarce for ligand-pocket systems. Additionally, disagreement between “gold standard” Coupled Cluster (CC) and Quantum Monte Carlo (QMC) methods casts doubt on many benchmarks for larger non-covalent systems. We introduce the “QUantum Interacting Dimer” (QUID) benchmark framework containing 170 non-covalent (non-)equilibrium systems modeling chemically and structurally diverse ligand-pocket motifs. Symmetry-adapted perturbation theory shows that QUID broadly covers non-covalent binding motifs and energetic contributions. Robust binding energies are obtained using complementary CC and QMC methods, achieving agreement of 0.5 kcal/mol. The benchmark data analysis reveals that several dispersion-inclusive density functional approximations provide accurate energy predictions, though their atomic van der Waals forces differ in magnitude and orientation. Contrarily, semiempirical methods and empirical force fields require improvements in capturing non-covalent interactions (NCIs) for out-of-equilibrium geometries. The wide span of NCIs, highly accurate interaction energies, and analysis of molecular properties take QUID beyond the “gold standard” for QM benchmarks of ligand-protein systems.

Puleva, Mirela [University of Luxembourg, Luxembou↗
DOE OSTI2025

Dispersive Dark Excitons in van der Waals Ferromagnet CrI 3

Spin-flip dark excitons are optical-dipole-forbidden quasiparticles with remarkable potential in optoelectronics, especially when they are realized within cleavable van der Waals materials. Despite this potential, dark excitons have not yet been definitively identified in ferromagnetic van der Waals materials. Here, we report two dark excitons in a model ferromagnetic material CrI 3 using high-resolution resonant inelastic x-ray scattering and show that they feature narrower linewidths compared to the bright excitons previously reported in this material. These excitons are shown to have spin-flip character, to disperse as a function of momentum, and to change through the ferromagnetic transition temperature. Given the versatility of van der Waals materials, these excitons hold promise for new types of magneto-optical functionality.

75 CONDENSED MATTER PHYSICS, SUPERCONDUCTIVITY AND↗
DOE OSTI2025

Magnetic dynamics in NiTiO 3 honeycomb antiferromagnet using neutron scattering

The ilmenite NiTiO 3 consists of a buckled honeycomb lattice, with the Ni spins aligned ferromagnetically in-plane and antiferromagnetically out-of-plane. Using neutron spectroscopy, the magnetic structure and the dynamics were investigated as a function of temperature. Dispersive acoustic bands and nearly dispersionless optical bands at ≈ 3.7 meV are described by a highly anisotropy Heisenberg model with stronger antiferromagnetic (AFM) out-of-plane, weaker ferromagnetic (FM) in-plane interactions and an anisotropy gap of 0.95 meV. Furthermore, the order parameter yields a critical exponent between the Heisenberg and two-dimensional Ising models, consistent with highly anisotropic Heisenberg systems. The frustration parameter ≈ 2 supports a weakly frustrated system.

Antiferromagnets↗
DOE OSTI2020

Area-selective atomic layer deposition enabled by competitive adsorption

In this work, we investigate the atomic layer deposition (ALD) of ZrO2 thin films on Cu and SiO2 substrates, using Zr[N(C2H5CH3)]4 as the thin-film precursor, and H2O or O2 as the coreactants. Here, we introduce 3-hexyne as a coadsorbate molecule during the thin-film precursor half-cycle and examine its effect on the selectivity of growth. We find that 3-hexyne strongly inhibits growth on Cu, while having essentially no effect on the growth on SiO2. Calculations using dispersion-inclusive density functional theory verify that 3-hexyne undergoes sp → sp2 rehybridization on Cu, which results in strong chemisorption on the metal surface, while only binding weakly to SiO2 via nonbonded van der Waals/dispersion interactions. After 10 cycles of ALD using 3-hexyne as the coadsorbate, we observed the deposition of ∼1.5 nm of ZrO2 on SiO2. On a Cu substrate, we only detected <0.15 nm of ZrO2 after the same number of cycles of ALD. At this point in the process, we find evidence of the formation of cuprous oxide (Cu2O) from in situ x-ray photoelectron spectroscopy and a significant increase in the roughness of the Cu substrate. We conclude that both factors likely contribute to the loss of selectivity due to the formation of sites (e.g., Cu2O) that bind 3-hexyne less strongly and/or an increase in the density of highly reactive sites (e.g., steps, kinks) that promote dissociative chemisorption of the thin-film precursor.

Suh, Taewon (ORCID:0000000163823811)↗
DOE OSTI2024

Machine-Learned Force Field Modeling of Metal Organic Frameworks for CO2 Direct Air Capture

To cope with legacy greenhouse gas emissions and to achieve net-zero emissions by 2050, the U.S. Department of Energy (DOE) is funding efforts to develop direct air capture (DAC), a method for removing CO2 directly from air. Metal organic frameworks (MOFs) have been well studied as DAC sorbent materials due to their tunable structural and compositional properties. Thermodynamic simulations using force fields are often used to provide predictions of a material’s performance in many separations. However, these force fields often make assumptions about bonds and the physics of the adsorption process. A new class of force fields called machine-learned force fields (MLFFs) use machine learning to form quantitative relationships between a material’s chemical structure and the forces and energies predicted by more accurate quantum mechanical calculations, such as dispersion-corrected density functional theory (DFT). In this work, models were developed to achieve DFT-level accuracy for the forces and energies associated with MOF flexibility and CO2 adsorption using MLFFs. These methods were parametrized based on thousands of DFT calculations of CO2 in flexible MOFs and used to predict MOF structural properties as well as CO2 adsorption in several MOFs.

Findley, John↗
DOE OSTI2024

Machine-Learned Force Field Modeling of Metal Organic Frameworks for CO2 Direct Air Capture

To cope with legacy greenhouse gas emissions and to achieve net-zero emissions by 2050, the U.S. Department of Energy (DOE) is funding efforts to develop direct air capture (DAC), a method for removing CO2 directly from air. Metal organic frameworks (MOFs) have been studied as DAC sorbent materials because of their structural and chemical diversity. Thermodynamic calculations using classical force fields are often used to screen MOFs for their performance in separations such as CO2 capture. Machine-learned force fields (MLFFs) can use machine learning to form quantitative relationships between a material’s chemical structure and the forces and energies predicted by more accurate quantum mechanical calculations, such as dispersion-corrected density functional theory (DFT). These descriptions of forces and energies can be used to improve the accuracy of adsorption calculations. In this work, MLFF models were developed for MOFs to achieve DFT-level accuracy for the forces and energies associated with MOF flexibility and CO2 adsorption. These methods were parametrized based on thousands of DFT calculations of CO2 in flexible MOFs and used to predict MOF structural properties as well as CO2 adsorption properties.

Findley, John↗
DOE OSTI2024

Machine Learned Force Field Modeling of Metal Organic Frameworks for CO2 Direct Air Capture

Direct air capture (DAC) is a method for removing CO2 directly from air. Metal organic frameworks (MOFs) have been studied as DAC sorbent materials because of their structural and chemical diversity. Thermodynamic calculations using classical force fields are often used to evaluate MOFs for their performance in separations such as CO2 capture. Machine-learned force fields (MLFFs) can use machine learning to form quantitative relationships between a material’s chemical structure and the forces and energies predicted by more accurate quantum mechanical calculations, such as dispersion-corrected density functional theory (DFT). These descriptions of forces and energies can be used to improve the accuracy of adsorption calculations. In this work, classical models were used to pre-screen MOFs for CO2 capture. DFT calculations were then used to examine the adsorption mechanism. Next, MLFF models were developed for MOFs to achieve DFT-level accuracy for the forces and energies associated with MOF flexibility and CO2 adsorption. These methods were parametrized based on thousands of DFT calculations of CO2 in flexible MOFs and used to predict MOF structural properties as well as CO2 adsorption properties.

Findley, John↗
DOE OSTI2023

A density functional theory analysis of the adsorption and surface chemistry of inorganic iodine species on graphitea

In the event of a nuclear accident, fission products may be released into the environment. The release of 131 I is of particular concern to human health. Iodine can be captured using a number of materials and frequently, this is accomplished with activated carbon impregnated with organic bases. Previous studies have used DFT and the graphite (0001) surface as a surrogate for adsorption, those studies focus on the species I • , I 2 , and CH 3 I. In this work we perform an ab initio study of the adsorption onto the surface of a graphite sheet of I 2 , CH 3 I, and inorganic acidic iodine species (HI, HOI, HIO 2 , and HIO 3 ), which were selected to examine the possible effect of oxidation state on adsorption. The PBE exchange-correlation functional with D3 dispersion was employed. It was found that for molecular iodine, the iodine atoms tended to either situate above the center of a hexagonal site on the graphite or directly atop a carbon atom with the lighter components resting closer to the graphite. For each species the relative binding energies spanned the range of 21–33 kJ mol -1 and graphite-iodine distance was in the range of 3.52–3.93 Å. In all cases we found no significant charge transfer between the iodine species and the graphite, thus we conclude that all the iodine species studied undergo strong physisorption to the graphite.

Ritzmann, Andrew M.↗
DOE OSTI2023

How Accurate Can Crystal Structure Predictions Be for High-Energy Molecular Crystals?

Molecular crystals have shallow potential energy landscapes, with multiple local minima separated by very small differences in total energy. Predicting molecular packing and molecular conformation in the crystal generally requires ab initio methods of high accuracy, especially when polymorphs are involved. We used dispersion-corrected density functional theory (DFT-D) to assess the capabilities of an evolutionary algorithm (EA) for the crystal structure prediction (CSP) of well-known but challenging high-energy molecular crystals (HMX, RDX, CL-20, and FOX-7). While providing the EA with the experimental conformation of the molecule quickly re-discovers the experimental packing, it is more realistic to start instead from a naïve, flat, or neutral initial conformation, which reflects the limited experimental knowledge we generally have in the computational design of molecular crystals. By doing so, and using fully flexible molecules in fully variable unit cells, we show that the experimental structures can be predicted in fewer than 20 generations. Nonetheless, one must be aware that some molecular crystals have naturally hindered evolutions, requiring as many attempts as there are space groups of interest to predict their structures, and some may require the accuracy of all-electron calculations to discriminate between closely ranked structures. To save resources in this computationally demanding process, we showed that a hybrid xTB/DFT-D approach could be considered in a subsequent study to push the limits of CSP beyond 200+ atoms and for cocrystals.

42 ENGINEERING↗
DOE OSTI2020

Designing Imidazolium Poly(amide-amide) and Poly(amide-imide) Ionenes and Their Interactions with Mono- and Tris(imidazolium) Ionic Liquids

Here we introduce the synthesis and thermal properties of a series of sophisticated imidazolium ionenes with alternating amide-amide or amide-imide backbone functionality, and investigate the structural effects of mono(imidazolium) and unprecedented tris(imidazolium) ionic liquids (ILs) in these ionenes. The new set of poly(amide-amide) (PAA) and poly(amide-imide) (PAI) ionenes represent the intersection of conventional high-performance polymers with the ionene archetype–presenting polymers with alternating functional and ionic elements precisely sequenced along the backbone. The effects of polymer composition on the thermal properties and morphology were analyzed. Five distinct polymer backbones were synthesized and combined with a stoichiometric equivalent of the IL 1-benzyl-3-methylimidazolium bistriflimide ([Bnmim][Tf 2 N]), which were studied to probe the self-assembly, structuring, and contributions of intermolecular forces when IL is added. Furthermore, three polyamide (PA) or polyimide (PI) ionenes with simpler xylyl linkages were interfaced with [Bnmim][Tf 2 N] as well as a novel amide-linked tris(imidazolium) IL, to demonstrate the structural changes imparted by the inclusion of functional, ionic additives dispersed within the ionene matrix. This work highlights the possibilities for utilizing concepts from small molecules which exhibit supramolecular self-assembly to guide creative design and manipulate the structuring of ionenes.

36 MATERIALS SCIENCE↗
NASA NTRS1973

A study of galaxy groups and clusters - The case for a clumpy intergalactic medium.

A nonuniform model for a dense intergalactic medium is constructed under the assumption that all groups and clusters of galaxies are gravitationally bound by ionized gas. Catalogs by de Vaucouleurs and Abell are utilized to provide an almost complete sample of the spatial distribution of groups and clusters over a wide range of richness, and a distribution function is derived for galaxy groups and clusters as a function of velocity dispersion. A simple scaling law is applied to predict velocity dispersions for the very rich Abell clusters. Thermal bremsstrahlung emission from the intracluster gas accounts for the observed emission over 2 to 10 keV from several rich clusters, and also contributes up to 20% of the diffuse X-ray background over a considerable fraction of the observed range. The amount of X-ray emitting gas is restricted to a small fraction of the virial mass, with the remainder of the binding mass present as cooler ionized clouds. Available soft X-ray and ultraviolet diffuse background observations are used to define a narrow range of permissible temperatures and densities for these clouds.

Silk, J.↗
NASA NTRS1984

Study on spectral/radiometric characteristics of the Thematic Mapper for land use applications

An information theoretic measure of multispectral information content is developed and applied to a simultaneous LANDSAT TM and MSS data set. The entropy based function measures the dispersion and concentration of signal values in various data spaces, irrespective of specific class memberships. It is used to compare the information content of TM and MSS and of various subsets of TM and MSS bans, as well as tasseled cap transformations of the band values. Differences exist between the information measure results and results using variance based measures. System design information capacities and data space volumes are also compared. The results and observations presented are considered preliminary in nature since only one real and one simulated data set are analyzed.

Malila, W. A.↗
NASA NTRS1987

Evidence for turbulence in H II regions

The results of extensive velocity mapping across the face of Galactic H II regions are used to make an accurate determination of velocity dispersions and structure functions for a number of nebulae. A dependence of random velocities upon scale, indicating the presence of turbulence, is found. These relationships are compared with the predictions of models for Kolmogorov turbulence in H II regions, and poor agreement is found. A more general formulation shows that there is no single power law for the velocity-distance relation that fits the observations. From the variations in the shape of the observed structure function, it is concluded that the turbulent energy enters the nebulae at several different scales. It is also found that velocity broadening of the observed lines is significantly greater than would be inferred from the velocity scatter across the face of the nebulae.

O'Dell, C. R.↗
NASA NTRS1990

High-Temperature Materials For Stirling Engines

Heat-resistant piston rings and linings increase engine efficiency. Report discusses research on materials for piston rings and cylinder coatings in automotive Stirling engines. Data from tests show cobalt-based alloy, Stellite 6B, good choice for piston rings and PS200, plasma-sprayed metal-bonded chromium carbide matrix with dispersed solid lubricants, functions well as cylinder coating. Materials make it possible to place piston rings at tops of pistons ("hot" piston rings) instead of at cooler bottoms.

Sliney, Harold E.↗
NASA NTRS1991

Derivation of mid-infrared (5-25 microns) optical constraints of some silicates and palagonite

This study was initially conceived in order to aid in the interpretation of Martian surface and atmospheric aerosol mineralogy. As a result, the minerals included are biased toward samples which represent hydrated and hydroxylated silicates. Due to their physical particle size, clays and other materials, such as palagonite, cannot be prepared using typical preparation techniques. Yet in some cases, such as for Mars, these are the materials of perhaps the greatest interest. In order to obtain a suitable sample of these less cohesive materials for the laboratory measurements, a KBr pellet die was used and a pellet of the pure sample was prepared. For all clays and the palagonite, a pellet with highly reflective surfaces at visible wavelengths was produced. The reflectivities of all samples were determined, and to derive the optical constants of a materials as a function of wavelength, dispersion analysis was used which describes the real and imaginary indices of refraction as the contributions due to a sum of classical oscillators and relates them via Frensel's equations for non-normal incidence, the the measured near-normal reflectivity. The final values that were determined represent averages of several model fits to each data set using the same number of oscillators by varying the high frequency dielectric constant.

Roush, T. L.↗
NASA NTRS2011

Nanoparticle Filtration in a RTM Processed Epoxy/Carbon Fiber Composite

Several epoxy matrix composite panels were fabricated by resin transfer molding (RTM) E862/W resin onto a triaxially braided carbon fiber pre-form. Nanoparticles including carbon nanofiber, synthetic clay, and functionalized graphite were dispersed in the E862 matrix, and the extent of particle filtration during processing was characterized. Nanoparticle dispersion in the resin flashing on both the inlet and outlet edges of the panel was compared by TEM. Variation in physical properties such as Tg and moisture absorption throughout the panel were also characterized. All nanoparticle filled panels showed a decrease in Tg along the resin flow path across the panel, indicating nanoparticle filtration, however there was little change in moisture absorption. This works illustrates the need to obtain good nano-particle dispersion in the matrix resin to prevent particle agglomeration and hence particle filtration in the resultant polymer matrix composites (PMC).

Miller, Sandi G.↗
NASA NTRS2018

Method of Making Dye-Doped Polystyre Microparticles

Various embodiments provide dye-doped polystyrene microspheres generated using dispersion polymerization. Polystyrene microspheres may be doped with fluorescent dyes, such as xanthene derivatives including kiton red 620 (KR620), using dispersion polymerization. Certain functionalities, such as sodium styrene sulfonate, may be used to shift the equilibrium distribution of dye molecules to favor incorporation of the dye into the particles. Polyelectrolyte materials, such as poly(diallyldimethyl ammonium chloride), PolyDADMAC, may be used to electrostatically trap and bind dye molecules within the particles. A buffer may be used to stabilize the pH change of the solution during dye-doped polystyrene microsphere generation and the buffer may be selected depending on the pKa of the dye being incorporated. The various embodiments may provide dye-doped polystyrene microspheres, such as KR620-doped polystyrene microspheres that are non-toxic and non-carcinogenic. These non-toxic and non-carcinogenic dye-doped polystyrene microspheres may be suitable for use in wind tunnel testing.

Wohl, Jr., Christopher J.↗
DOE OSTI2024

Smooth Dispersion Is Physically Appropriate: Assessing and Amending the D4 Dispersion Model

The addition of dispersion corrections to density functionals is essential for accurate energy and geometry predictions. Among them, the D4 scheme is popular due to its low computational cost and high accuracy. However, due to its design, the D4 correction can occasionally lead to anomalies, such as unphysical curvature and bumps in the potential energy surface. We find these anomalies are common in the D4 model, although observable consequences are rarer than in the D3 model for reasons we explain. Nevertheless, we uncover instances of unphysical local minima and stationary points with the D4 scheme and propose two solutions that yield smoother dispersion energy as a function of nuclear position. One is trivial to implement, based on a smoother reparametrization of Gaussian weighting (D4S) to find the effective coordination number. The other replaces Gaussian weighting with soft linear interpolation (D4SL). These new approaches usually remove artificial extremum points, while maintaining accuracy.

Tkachenko, Nikolay V↗