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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 1,351 records · Page 75
All sourcesNASA NTRSDOE OSTI
DOE OSTI2026

Seniority eigenstate configuration interaction

Zero-seniority methods have shown great promise for the description of strongly correlated electronic systems. Other seniority sectors have been much less explored, and in particular, the maximal seniority sector and zero seniority have the same underlying algebraic structure. We introduce a seniority eigenstate configuration interaction in which the wave function is constrained to have good fixed local seniority for each paired orbital, by which we mean we partition orbitals into a pairing set with seniority zero, and a spin set with seniority one. Here, we show how to build the effective Hamiltonian for this ansatz, and demonstrate that high-seniority wave functions have unexpectedly excellent accuracy for strongly correlated fermionic systems, with accuracy competitive with or better than seniority zero for the Hubbard model and for the dissociation of the nitrogen molecule.

74 ATOMIC AND MOLECULAR PHYSICS↗
DOE OSTI2025

Transverse-momentum-dependent pion structures from lattice QCD: Collins-Soper kernel, soft factor, TMDWF, and TMDPDF

We present the first lattice quantum chromodynamics (QCD) calculation of the pion valence-quark transverse-momentum-dependent parton distribution function (TMDPDF) within the framework of large-momentum effective theory (LaMET). Using correlators fixed in the Coulomb gauge (CG), we computed the quasi-TMD beam function for a pion with a mass of 300 MeV, a fine lattice spacing of 𝑎 =0.06 fm, and multiple large momenta up to 3 GeV. The intrinsic soft functions in the CG approach are extracted from form factors with large momentum transfer, and as a byproduct, we also obtain the corresponding Collins-Soper (CS) kernel. Our determinations of both the soft function and the CS kernel agree with perturbation theory at small transverse separations (𝑏 ⊥ ) between the quarks. At larger 𝑏 ⊥ , the CS kernel remains consistent with recent results obtained using both CG and gauge-invariant TMD correlators in the literature. By combining next-to-leading logarithmic factorization of the quasi-TMD beam function and the soft function, we obtain an 𝑥-dependent pion valence-quark TMDPDF for transverse separations 𝑏 ⊥ ≳1 fm. Interestingly, we find that the 𝑏 ⊥ dependence of the phenomenological parametrizations of TMDPDF for moderate values of 𝑥 are in reasonable agreement with our QCD determinations. In addition, we present results for the transverse-momentum-dependent wave function for a heavier pion with 670 MeV mass.

73 NUCLEAR PHYSICS AND RADIATION PHYSICS↗
DOE OSTI2022

The symmetric quasi-classical model using on-the-fly time-dependent density functional theory within the Tamm–Dancoff approximation

The primary computational challenge when simulating nonadiabatic ab initio molecular dynamics is the unfavourable compute costs of electronic structure calculations with molecular size. Simple electronic structure theories, like time-dependent density functional theory within the Tamm–Dancoff approximation (TDDFT/TDA), alleviate this cost for moderately sized molecular systems simulated on realistic time scales. Although TDDFT/TDA does have some limitations in accuracy, an appealing feature is that, in addition to including electron correlation through the use of a density functional, the cost of calculating analytic nuclear gradients and nonadiabatic coupling vectors is often computationally feasible even for moderately sized basis sets. Here in this work, some of the benefits and limitations of TDDFT/TDA are discussed and analysed with regard to its applicability as a ‘back-end’ electronic structure method for the symmetric quasi-classical Meyer–Miller model (SQC/MM). In order to investigate the benefits and limitations of TDDFT/TDA, SQC/MM is employed to predict and analyse a prototypical example of excited-state hydrogen transfer in gas-phase malonaldehyde. Then, the ring-opening dynamics of selenophene are simulated, which highlight some of the deficiencies of TDDFT/TDA. Additionally, some new algorithms are proposed that speed up the calculation of analytic nuclear gradients and nonadiabatic coupling vectors for a set of excited electronic states.

molecular dynamics↗
DOE OSTI2020

Bypassing the Energy Functional in Density Functional Theory: Direct Calculation of Electronic Energies from Conditional Probability Densities

Density functional calculations can fail for want of an accurate exchange-correlation approximation. The energy can instead be extracted from a sequence of density functional calculations of conditional probabilities (CP DFT). Simple CP approximations yield usefully accurate results for two-electron ions, the hydrogen dimer, and the uniform gas at all temperatures. CP DFT has no self-interaction error for one electron, and correctly dissociates H2, both major challenges. For warm dense matter, classical CP DFT calculations can overcome the convergence problems of Kohn-Sham DFT.

75 CONDENSED MATTER PHYSICS, SUPERCONDUCTIVITY AND↗
DOE OSTI2022

Biophysical Characterization of Membrane Proteins Embedded in Nanodiscs Using Fluorescence Correlation Spectroscopy

Proteins embedded in biological membranes perform essential functions in all organisms, serving as receptors, transporters, channels, cell adhesion molecules, and other supporting cellular roles. These membrane proteins comprise ~30% of all human proteins and are the targets of ~60% of FDA-approved drugs, yet their extensive characterization using established biochemical and biophysical methods has continued to be elusive due to challenges associated with the purification of these insoluble proteins. In response, the development of nanodisc techniques, such as nanolipoprotein particles (NLPs) and styrene maleic acid polymers (SMALPs), allowed membrane proteins to be expressed and isolated in solution as part of lipid bilayer rafts with defined, consistent nanometer sizes and compositions, thus enabling solution-based measurements. Fluorescence correlation spectroscopy (FCS) is a relatively simple yet powerful optical microscopy-based technique that yields quantitative biophysical information, such as diffusion kinetics and concentrations, about individual or interacting species in solution. Here, we first summarize current nanodisc techniques and FCS fundamentals. We then provide a focused review of studies that employed FCS in combination with nanodisc technology to investigate a handful of membrane proteins, including bacteriorhodopsin, bacterial division protein ZipA, bacterial membrane insertases SecYEG and YidC, Yersinia pestis type III secretion protein YopB, yeast cell wall stress sensor Wsc1, epidermal growth factor receptor (EGFR), ABC transporters, and several G protein-coupled receptors (GPCRs).

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2026

Collins-type fragmentation energy correlator in semi-inclusive deep inelastic lepton-hadron scattering

We initiate a systematic study of fragmentation energy correlators (FECs), which generalize traditional fragmentation functions and encode non-perturbative information about transverse dynamics in parton fragmentation processes. We define boost-invariant, non-perturbative FECs and derive a corresponding collinear factorization formula. A spin decomposition of the FECs is carried out, analogous to that of transverse-momentum-dependent fragmentation functions. In this work we focus particularly on the Collins-type quark FEC, which is sensitive to chiral symmetry breaking and characterizes the azimuthal asymmetry in the fragmentation of a transversely polarized quark. We perform a next-to-leading-order calculation of the corresponding hard coefficient in semi-inclusive deep-inelastic scattering for the quark non-singlet component, thereby validating the consistency of our theoretical framework.

Deep Inelastic Scattering or Small-x Physics↗
DOE OSTI2022

SPARC: Structural properties associated with residue constraints

SPARC facilitates the generation of plausible hypotheses regarding underlying biochemical mechanisms by structurally characterizing protein sequence constraints. Such constraints appear as residues co-conserved in functionally related subgroups, as subtle pairwise correlations (i.e., direct couplings), and as correlations among these sequence features or with structural features. SPARC performs three types of analyses. First, based on pairwise sequence correlations, it estimates the biological relevance of alternative conformations and of homomeric contacts, as illustrated here for death domains. Second, it estimates the statistical significance of the correspondence between directly coupled residue pairs and interactions at heterodimeric interfaces. Third, given molecular dynamics simulated structures, it characterizes interactions among constrained residues or between such residues and ligands that: (a) are stably maintained during the simulation; (b) undergo correlated formation and/or disruption of interactions with other constrained residues; or (c) switch between alternative interactions. We illustrate this for two homohexameric complexes: the bacterial enhancer binding protein (bEBP) NtrC1, which activates transcription by remodeling RNA polymerase (RNAP) containing σ 54 , and for DnaB helicase, which opens DNA at the bacterial replication fork. Based on the NtrC1 analysis, we hypothesize possible mechanisms for inhibiting ATP hydrolysis until ADP is released from an adjacent subunit and for coupling ATP hydrolysis to restructuring of σ 54 binding loops. Based on the DnaB analysis, we hypothesize that DnaB ‘grabs’ ssDNA by flipping every fourth base and inserting it into cavities between subunits and that flipping of a DnaB-specific glutamine residue triggers ATP hydrolysis.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2023

Automated phase segmentation and quantification of high-resolution TEM image for alloy design

In the alloy design and development process, a wealth of atomically resolved structural high-resolution transmission electron microscopy (HRTEM) images are produced. Identifying the different nano-precipitate phases and tracking their evolution under various compositions and during manufacturing or post-processing requires hundreds of HRTEM images and thousands of precipitates. The nanoscopic phase information labeling and analysis purely relies on humans are prohibitively costly and time-consuming, sometimes not reliable because of the lack of authoritative knowledge. Here, in this work, we develop a novel unsupervised machine learning approach coupled with adaptive computer vision techniques with features in the Fourier space to automatically determine the number of phases and segment/quantify the phases with nanoscale resolution, allowing for quantitative correlation between nanostructure formation, processing and functional properties. To automate the phase extraction/quantification and ascertain its applicability, we have applied the developed framework to the HRTEM images from several alloy systems, processing conditions, image magnifications, and phase types and morphologies (precipitates, nano-twins, stacking faults, crystalline matrix, and amorphous structures) for verification. This study paves the road for compression, visualization, and translation of raw image structural data into physically relevant information in real-time with minimal human supervision. It shows the promise of enabling high-throughput materials characterization for the acceleration of alloy manufacturing and design.

36 MATERIALS SCIENCE↗
DOE OSTI2024

Quenching of the quantum p -strength in light exotic nuclei

One-nucleon spectroscopic overlaps, their strength or spectroscopic factors (SFs), and nucleon removal cross sections for light nuclei in the mass range A≤12 were evaluated using the fully correlated Quantum Monte Carlo (QMC) wave functions (WFs). Harder (AV18+UX) and softer (NV2+3) bare interactions were used providing consistent results. The SFs were also taken from simple Shell Model (SM) calculations. This structure information was incorporated in the standard three-body Faddeev/Alt-Grassberger-Sandhas reaction formalism to evaluate the (p,pN) cross sections. The results further our understanding of the quenching of the quantum p-shell strength obtained from structure and reactions. We have found the ratios of the total QMC sums of SFs to the SM ones to be uniform and ∼ 3/4. The corresponding ratios of the sums Below Particle Threshold (BPT) of SFs, as well as of total cross sections, deviate strikingly from the uniform trend in some special cases. We find these ratios to be close to unit for 9 Li → 8 Li + n and 9 C → 8 B + p. In contrast, they are strongly reduced for 11 C → 10 C + n and 11 B → 10 Be + p mirror transitions, resulting from the quenching of the strength for low-lying 2 + final state transitions. The QMC theoretical cross section BPT for 11 C(p,pn) is about two times smaller than the experimental data.

(p,pN) reactions↗
DOE OSTI2023

In-situ observation of single-phase compositionally-complex oxide formation during high-pressure and high-temperature synthesis

Compositionally-complex oxides (CCOs) with equal or non-equal atomic ratios of multi-principal cations are single-phase solid solutions and possess unique structural characteristics and correlated possibilities for tailorable and exceptional functionalities. However, breakdown of single-phase structure and phase separation impair widespread adoption of CCOs under in-service environments. Here, in-situ phase transformation during high-pressure and high-temperature synthesis of an exemplary CCO (CeZrHf) 0.852 (YbY) 0.148 O 2-δ is for the first time clarified by using synchrotron X-ray energy dispersive diffraction. During synthesizing at ~4.5 GPa inside a large-volume press, ZrO 2 and HfO 2 gradually initiate lattice diffusion as monoclinic (022) and (220) peaks collapse and merge completely at 973 K; CeO 2 starts diffusing as the dramatic intensity change of cubic (220) peak above 1073 K, causing a metastable phase formation; single-phase solid solution ultimately forms at 1673 K. Importantly, the results revealed provide in-depth understanding of phase transformation dynamics and insights for novel design paradigm of CCOs.

36 MATERIALS SCIENCE↗
DOE OSTI2020

Third-Order Møller–Plesset Theory Made More Useful? The Role of Density Functional Theory Orbitals

The practical utility of Møller–Plesset (MP) perturbation theory is severely constrained by the use of Hartree–Fock (HF) orbitals. It has recently been shown that the use of regularized orbital-optimized MP2 orbitals and scaling of MP3 energy could lead to a significant reduction in MP3 error. In this work, we examine whether density functional theory (DFT)-optimized orbitals can be similarly employed to improve the performance of MP theory at both the MP2 and MP3 levels. We find that the use of DFT orbitals leads to significantly improved performance for prediction of thermochemistry, barrier heights, noncovalent interactions, and dipole moments relative to the standard HF-based MP theory. Indeed, MP3 (with or without scaling) with DFT orbitals is found to surpass the accuracy of coupled-cluster singles and doubles (CCSD) for several data sets. We also found that the results are not particularly functional sensitive in most cases (although range-separated hybrid functionals with low delocalization error perform the best). As such, MP3 based on DFT orbitals thus appears to be an efficient, noniterative O(N 6 ) scaling wave-function approach for single-reference electronic structure computations. Scaled MP2 with DFT orbitals is also found to be quite accurate in many cases, although modern double hybrid functionals are likely to be considerably more accurate.

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

Unraveling Anion-Specific Inhibition and Structural Modulation of Gibbsite Crystallization: Implications for Aluminum Mobility in Natural and Engineered Systems

Gibbsite (α-Al(OH) 3 , sometimes designated as γ-Al(OH) 3 ) plays a crucial role in the chemistry of aluminum in the environment and industry, yet its crystallization behavior under multianionic conditions is not well understood. Here, in this study, we investigate how six common anions─fluoride (F – ), chloride (Cl – ), bromide (Br – ), nitrate (NO 3 – ), sulfate (SO 4 2– ), and phosphate (PO 4 3– )─influence the mineralization, structure, and morphology of gibbsite at room temperature. The results show that PO 4 3– , SO 4 2– , and F – strongly inhibit gibbsite formation, stabilizing amorphous or alternative crystalline phases such as nordstrandite and cryolite. On the contrary, Cl – , Br – , and NO 3 – allow partial to complete crystallization of gibbsite without significant morphological changes. Solid-state 27 Al magic angle spinning nuclear magnetic resonance provides crucial insight into aluminum coordination environments in both crystalline and amorphous phases, distinguishing between octahedral, pentahedral, and tetrahedral Al species. The density functional theory calculations reveal a direct correlation between the Al–X bond strength and the inhibition of crystallization, following the order: PO 4 3– > SO 4 2– > F – > NO 3 – > Cl – > Br – . These findings offer molecular-scale insights into anion-specific effects on aluminum hydroxide nucleation and transformation, improving the understanding of gibbsite formation and aluminum cycling in soils, phosphate retention, contaminant immobilization, and waste treatment strategies in nuclear and industrial settings. These insights can also guide the controlled synthesis of aluminum hydroxide materials with tailored crystallinity and morphology via liquid-assisted methods.

Anions effect↗
DOE OSTI2025

Electron Transfer Theory Elucidates the Hidden Role Played by Triethylamine and Triethanolamine during Photocatalysis

Triethylamine (TEA) and triethanolamine (TEOA) are renowned, in part, for their ability to reductively quench excited states by outer-sphere electron transfer with vast and still growing applications as sacrificial electron donors for photocatalytic systems. Upon amine oxidation, the resulting TEA •+ and TEOA •+ radical cations undergo proton transfer (or hydrogen atom transfer), resulting in the formation of a chemical reductant that has an α-carbon centered radical adjacent to the nitrogen center (TEA • and TEOA • ). In this contribution, we have electrochemically and spectroscopically characterized a set of electron acceptors which, upon accepting an electron, are a series of photocatalysts, [ReCl(R 1 R 2 -bpy)(CO) 3 ] •– , where R 1 and R 2 are electron-donating and electron-withdrawing groups in the 4,4′- and 5,5′-positions on the bipyridyl ligand. Here, we substantiated the formation of the electron donors, TE(O)A • , by spin trapping electron paramagnetic resonance spectroscopy, where TE(O)A • reacts with 2,4,6-tri-tert-butylnitrosobenzene to generate N-centered and O-centered radical adducts. Having established the chemical behaviors of the electron acceptors and donors individually, the electron transfer rate constants were determined across a 1.43 V range in driving force. The redox potential of TEA • was benchmarked to within ±80 mV on an absolute scale in V vs Fc + /Fc in CH 3 CN by using an empirical rate vs free-energy correlation, electron transfer theory, and density functional theory calculations. The equilibrium potentials for TEA • and TEOA • were determined to be −1.98 V and −1.76 V, respectively. Based on the kinetic and thermochemical analysis presented for TEA • and TEOA • , these transient radicals can be broadly considered strong homogeneous chemical reductants within the wider context of photoredox potentials. Thus, this work clarifies a frequently unnoticed secondary function for these sacrificial electron donors during photocatalysis and rationalizes the possibility of a one-photon/two-electron conversion process that is dependent on the free-energy exchange between TE(O)A • and photocatalysts.

38 RADIATION CHEMISTRY, RADIOCHEMISTRY, AND NUCLEA↗
DOE OSTI2021

Gaussian process analysis of electron energy loss spectroscopy data: multivariate reconstruction and kernel control

Abstract Advances in hyperspectral imaging including electron energy loss spectroscopy bring forth the challenges of exploratory and physics-based analysis of multidimensional data sets. The multivariate linear unmixing methods generally explore similarities in the energy dimension, but ignore correlations in the spatial domain. At the same time, Gaussian process (GP) explicitly incorporate spatial correlations in the form of kernel functions but is computationally intensive. Here, we implement a GP method operating on the full spatial domain and reduced representations in the energy domain. In this multivariate GP, the information between the components is shared via a common spatial kernel structure, while allowing for variability in the relative noise magnitude or image morphology. We explore the role of kernel constraints on the quality of the reconstruction, and suggest an approach for estimating them from the experimental data. We further show that spatial information contained in higher-order components can be reconstructed and spatially localized.

36 MATERIALS SCIENCE↗
DOE OSTI2024

Unlocking the potential: machine learning applications in electrocatalyst design for electrochemical hydrogen energy transformation

Machine learning (ML) is rapidly emerging as a pivotal tool in the hydrogen energy industry for the creation and optimization of electrocatalysts, which enhance key electrochemical reactions like the hydrogen evolution reaction (HER), the oxygen evolution reaction (OER), the hydrogen oxidation reaction (HOR), and the oxygen reduction reaction (ORR). This comprehensive review demonstrates how cutting-edge ML techniques are being leveraged in electrocatalyst design to overcome the time-consuming limitations of traditional approaches. ML methods, using experimental data from high-throughput experiments and computational data from simulations such as density functional theory (DFT), readily identify complex correlations between electrocatalyst performance and key material descriptors. Leveraging its unparalleled speed and accuracy, ML has facilitated the discovery of novel candidates and the improvement of known products through its pattern recognition capabilities. This review aims to provide a tailored breakdown of ML applications in a format that is readily accessible to materials scientists. Hence, we comprehensively organize ML-driven research by commonly studied material types for different electrochemical reactions to illustrate how ML adeptly navigates the complex landscape of descriptors for these scenarios. We further highlight ML's critical role in the future discovery and development of electrocatalysts for hydrogen energy transformation. Potential challenges and gaps to fill within this focused domain are also discussed. As a practical guide, we hope this work will bridge the gap between communities and encourage novel paradigms in electrocatalysis research, aiming for more effective and sustainable energy solutions.

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

Iron-assisted growth of anisotropic ZnO nanostructures

Anisotropic nanostructures offer a promising pathway to modulate structure-function relationships of materials. However, the correlation between growth direction of high-quality anisotropic nanostructures, the synthesis conditions and mechanisms controlling their growth, and their magnetic and optical properties remain underexplored. In this study, we developed an iron-assisted anisotropic growth method to form zinc oxide nanostructures on the O-polar (0001̄) surface, resulting in two distinct ZnO-based nanostructures: hand-shaped nanostructures and truncated hexagonal nanopyramids. In contrast to most reports of anisotropic nanostructure synthesis, which primarily focus on morphology control through ligand-ligand interactions, the current study probes the effects of doping on anisotropic growth, and how doping, along with ligand-ligand interactions and facet-specific ligand binding, control nanostructure morphology. The reaction mechanisms leading to formation of these novel structures were thoroughly probed by systematically manipulating synthesis parameters. A two-step formation mechanism was identified: first, a hexagonal platform forms through an initial homogeneous nucleation process, followed by secondary heterogeneous nucleation, which results in metastable secondary nanostructures growing on the oxygen-rich template. Optical and magnetic properties of these Fe/ZnO nanostructures were characterized. Our findings provide a new strategy that uses a magnetic element as a dopant to build new nanostructures of ZnO with controllable size and shape growing on an oxygen-rich crystal plane. These materials could have applications in novel technologies where both optoelectronic and magnetic properties are of interest.

Xuan, Zhengxi↗
DOE OSTI2025

Atomistic characterization of hydration-dependent fuel cell ionomer nanostructure: validation by vibrational spectroscopy

The development of Nafion alternatives for fuel cells and electrolyzers requires a fundamental understanding of hydration-dependent ion-exchange site acid/base chemistry. We present here reactive force field (ReaxFF) molecular dynamics (MD) simulations of Nafion at varying molar water/ion-exchange-site ratios (λ), which we correlate to our experimental and density functional theory-based vibrational spectra. ReaxFF describes the formation and breaking of covalent bonds, enabling simulations of proton exchange between sulfonic acid/sulfonate groups and water/hydronium. Our MD simulations determine the λ-dependent equilibrium proportions of protonated and deprotonated sites. We find that protonated sites persist across all λ from 0 to 20, challenging the widely accepted notion that all sites are ionized above a threshold λ value (e.g., 3 or 4). Our simulations generate hundreds of realistic exchange site environments, the characterization of which are based on 6 Å radii sulfur-centered ‘inner-spheres’. These inner- and outer-sphere regions elucidate an interplay of stereoelectronic factors that influence protonation states, including the number of inner-sphere waters (Λ). Our simulations produce broad λ-dependent distributions of Λ values, representing non-uniform exchange site hydration. Moreover, we demonstrate that these distributions are specific to both protonated and deprotonated sites, with significant overlap between the two distributions for all non-zero λ. These distributions underpin the IR spectra of hydrated membranes, with each exchange site contributing an IR spectrum characteristic of its protonation state and Λ. We expect that these nanostructural characterizations of Nafion exchange sites will contribute to the development of new ionomers.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗