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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 OSTI2026

Beta-delayed gamma spectra compilation and analysis following the thermal-neutron induced fission of 235 U, 239,241 Pu

The integral gamma and electron spectra emitted by fission products, also known as delayed gamma and electron spectra, were measured at Oak Ridge National Laboratory in the 1970s for the thermal-neutron induced fission of 235 U and 239,241 Pu. Scintillator detectors were used to measure these spectra, data used later on to obtain decay heat values - that is, the spectra mean values per unit time as function of time - work that was published in the Nuclear Science and Technology journal; the spectral data, however, was only published in laboratory reports. Here, in this work, we analyze the gamma spectra data using modern methods and nuclear databases to reveal the signature of individual fission products as well as to gauge the performance of the ENDF/B-VIII.0 decay data sub-library, concluding about possible future enhancements in predictive capabilities.

73 NUCLEAR PHYSICS AND RADIATION PHYSICS↗
DOE OSTI2024

Exploring the Computational Aspects of Propylene Oligomerization Catalysis Using M′ 2 M Type Trimetallic MOF Nodes

Metal-organic frameworks have emerged as promising materials in the field of catalysis. They offer an optimal ground for screening catalysts and tailoring their catalytic properties. Here, in this work, via density functional theory (DFT) calculations, we investigated the catalytic activity of the trimetallic MOF nodes, M' 2 M for propylene oligomerization, by varying the active metal M from Sc to Cu with M' being Fe, aiming to grasp the impact of altering the active atoms on the catalyst's activity. Additionally, we examined how substituting the spectator atom, M', with other transition metals, i.e., from Sc to Cu, affects these energy barriers, keeping Ni as the active metal. We proposed several cases with lower or comparable energy barriers to the experimentally reported Fe 2 Ni trimetallic MOF node. In addition, we found a correlative relationship between spin-density from natural population analysis and energy barriers in the realm of C-C bond formation, whereby an elevation in spin-density is found to be inversely proportional to the magnitude of the energy barriers. Moreover, we calculated the energy barriers for C-C coupling and beta-hydride elimination using multireference NEVPT2 calculations on top of the CASSCF wave function to validate the rate-determining step that is predicted by DFT.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2026

Local Chain Dynamics in Sequence-Controlled Polymers as a Tunable Handle for Rare Earth Sequestration

Chain dynamics govern the intricate behaviors of proteins, underpinning functions such as catalysis, recognition, and stimulus response, and are an increasingly appreciated aspect of structure–function relationships. Analogously, manipulating chain dynamics and structure in abiotic polymers via sequence control is an exciting, yet underexplored, strategy for improving material functions. In this work, we report a systematic study relating the sequence of polymeric sequestrants to their structure and dynamics, as well as to their binding affinity and selectivity for model substrates, rare earth elements (REEs). A series of sequence-controlled polymers with metal chelating, solubilizing, and structure forming monomers was synthesized via multiblock polymerization, yielding compositionally identical polymers with spectroscopically resolved domains and distinct morphologies. Using a combination of small-angle X-ray scattering and 19 F NMR relaxometry measurements, we connected differences in polymer structure and dynamics to polymer sequence variables such as the patchiness (density) of the structure forming monomer and the location of the chelating monomer. Furthermore, we found that, relative to calcium, all polymers in the series collapse more and have slower dynamics when binding REEs (lanthanum and lutetium) , though the extent of these effects were sequence-dependent and localized to specific domains within the polymer. Notably, sequence-controlled polymers that exhibited the largest conformational and dynamic changes upon binding REEs also bound REEs with the greatest affinity and modest selectivity. Collectively, these results correlate monomer patterning with dynamics, morphology, and REE binding performance en route to the development of efficient and selective macromolecular chelators.

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

Dehydrogenation vs Apparent Hydrogenation: Unraveling the Mechanisms of He and O 2 Plasma Etching on Colloidal Nanocrystal Films

Removing organic ligands from colloidal nanoparticles is critical for fabricating solid-state devices, yet accurately quantifying this removal remains a significant analytical challenge. Here, we establish a robust and accessible method for this quantification by calibrating Raman spectroscopy against precise ion beam analysis (IBA) for nanoparticle assemblies (CNAs) processed by helium (He) and oxygen (O 2 ) plasmas. We demonstrate that the calibration curves are remarkably independent of plasma power and pressure, depending critically only on the choice of feed gas. He plasma induces rapid dehydrogenation and cross-linking, evidenced by a much faster decrease in the C–H Raman signal relative to the actual carbon loss. Conversely, O 2 plasma leads to a surprising “apparent hydrogenation”, where the carbon backbone is removed significantly faster than the C–H signal diminishes. This counterintuitive effect is explained by a serial mechanism of oxidative fragmentation; β-scission cleaves the alkyl chains, and subsequent stabilization steps enrich the remaining film with hydrogen-rich methyl-terminated fragments, while carbon is efficiently removed as volatile CO. This work provides calibrated functions that enable the rapid determination of absolute carbon content in processed CNAs using simple Raman spectroscopy with uncertainties of ∼8% for O 2 and ∼12% for He plasma, offering a vital tool for both process diagnostics and fundamental studies of plasma–matter interactions in colloidal nanocrystal films.

Animal feed↗
DOE OSTI2025

Reticular Structural Diversification of Zirconium Metal–Organic Frameworks Through Angular Ligand Configuration Control

Reticular chemistry offers practical guidelines for enlarging and enriching the arsenal of metal–organic frameworks (MOFs). However, reticular expansion to access mesoporous structures remains challenging due to limitations in achieving precise control over both the size and configuration during building units’ extension. Herein, we combine ligand isomerization and functionalization strategies to regulate the ligand configuration by systematically replacing aryl C–H groups with N atoms, resulting in angular dicarboxylate ligands with various symmetries. The assembly between a 4,4′-(pyridine-2,6-diyl)dibenzoic acid ligand (1N, C 2 symmetry) and 12-connected Zr 6 cluster leads to the formation of a pseudo ftw topology framework (NU-2611), where one pair of nose-to-nose 1N ligands resembles a tetra-topic ligand. When a 6,6′-(1,3-phenylene)dinicotinic acid ligand (2N, C S symmetry) was used, another pseudo ftw network NU-2612 was obtained with a 2-fold framework interpenetration. Interestingly, the planar [2,2′:6′,2″-terpyridine]-5,5″-dicarboxylic acid ligand (3N, C 2V symmetry) yielded an intriguing mesoporous Zr-MOF with kag topology. NU-2613 represents the first example of kag Zr-MOF designed to include large, well-defined mesopores. The diversity of these MOFs was further enhanced through post-synthetic metalation of linkers. Particularly, metalation of the chelating 3N ligand with Fe 3+ in NU-2613 enables efficient catalytic transformation within the functionalized channels. This work contributes insight into the reticular expansion of Zr-MOFs by finely-tuning the ligand planarity, advancing the structure diversification of mesoporous frameworks for specific applications.

Cluster chemistry↗
DOE OSTI2024

Probing plexciton emission from 2D materials on gold nanotrenches

Probing strongly coupled quasiparticle excitations at their intrinsic length scales offers unique insights into their properties and facilitates the design of devices with novel functionalities. In this work, we investigate the formation and emission characteristics of plexcitons, arising from the interaction between surface plasmons in narrow gold nanotrenches and excitons in monolayer WSe 2 . We study this strong plasmon–exciton coupling in both the far-field and the near-field. Specifically, we observe a Rabi splitting in the far-field reflection spectra of about 80 meV under ambient conditions, consistent with our theoretical modeling. Using a custom-designed near-field probe, we find that plexciton emission originates predominantly from the lower-frequency branch, which we can directly probe and map its local field distribution. We precisely determine the plexciton's spatial extension, similar to the trench width, with nanometric precision by collecting spectra at controlled probe locations. Our work opens exciting prospects for nanoscale mapping and engineering of plexcitons in complex nanostructures with potential applications in nanophotonic devices, optoelectronics, and quantum electrodynamics in nanoscale cavities.

36 MATERIALS SCIENCE↗
DOE OSTI2025

The molecular basis of Human FN3K mediated phosphorylation of glycated substrates

Abstract Glycation, a non-enzymatic post-translational modification occurring on proteins, can be actively reversed via site-specific phosphorylation of the fructose-lysine moiety by FN3K kinase, to impact the cellular function of the target protein. A regulatory axis between FN3K and glycated protein targets has been associated with conditions like diabetes and cancer. However, the molecular basis of this relationship has not been explored so far. Here, we determined a series of crystal structures of HsFN3K in the apo-state, and in complex with different nucleotide analogs together with a sugar substrate mimic to reveal the features important for its kinase activity and substrate recognition. Additionally, the dynamics in sugar substrate binding during the kinase catalytic cycle provide important mechanistic insights into HsFN3K function. Our structural work provides the molecular basis for rational small molecule design targeting FN3K.

Science & Technology - Other Topics↗
DOE OSTI2025

Pressure-induced structural phase transitions in CrSBr

There is growing interest in combining chemical complexity with external stimuli like pressure, field, and light for property control in van der Waals solids. This is because extreme conditions trigger the development of new states of matter and functionality. In this work, we bring together synchrotron-based infrared absorption, Raman scattering, and diamond anvil cell techniques with first-principles calculations of the lattice dynamics and energy landscape to reveal the series of structural phase transitions in CrSBr. By tracking how the phonons change under pressure, we uncover a remarkable chain of complex symmetry modifications, interlayer interactions, and chemical reactions. A group-subgroup analysis suggests that CrSBr undergoes an orthorhombic Pmmn → monoclinic P2/m transition at 7.6 GPa, and based upon a comparison with model oxychlorides like FeOCl and CrOCl, we propose that changes in the pendant halide groups drive the system to a P2 1 /m-like space group above 15.3 GPa. Compression above 20.2 GPa is irreversible, resulting in the formation of an entirely new compound that is metastable for months. This work opens the door to the use of pressure and possibly strain to control the properties of CrSBr.

Microscopy↗
DOE OSTI2024

Hierarchical Ion Interactions in the Direct Air Capture of CO 2 at Air/Aqueous Interfaces

The direct air capture (DAC) of CO 2 using aqueous solvents is plagued by slow kinetics and interfacial barriers that limit effectiveness in combating climate change. Functionalizing air/aqueous surfaces with charged amphiphiles shows promise in accelerating DAC; however, insight into these interfaces and how they evolve in time remains poorly understood. Specifically, competitive ion interactions between DAC reagents and reaction products feedback onto the interfacial structure, thereby modulating interfacial chemical composition and overall function. In this work, we probe the role of glycine amino acid anions (Gly - ), an effective CO 2 capture reagent, that promotes the organization of cationic oligomers at air/aqueous interfaces. These surfaces are probed with vibrational sum frequency generation spectroscopy and molecular dynamics simulations. Our findings demonstrate that the competition for surface sites between Gly - and captured carbonaceous anions (HCO 3 - , CO 3 2 -, carbamates) drives changes in surface hydration, which in turn tunes oligomer ordering. This phenomenon is related to a hierarchical ordering of anions at the surface that are electrostatically attracted to the surface and their ability to compete for interfacial water. These results point to new ways to tune interfaces for DAC via stratification of ions based on relative surface propensities and specific ion effects.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2024

A combinatorially complete epistatic fitness landscape in an enzyme active site

Protein engineering often targets binding pockets or active sites which are enriched in epistasis—nonadditive interactions between amino acid substitutions—and where the combined effects of multiple single substitutions are difficult to predict. Few existing sequence-fitness datasets capture epistasis at large scale, especially for enzyme catalysis, limiting the development and assessment of model-guided enzyme engineering approaches. We present here a combinatorially complete, 160,000-variant fitness landscape across four residues in the active site of an enzyme. Assaying the native reaction of a thermostable β-subunit of tryptophan synthase (TrpB) in a nonnative environment yielded a landscape characterized by significant epistasis and many local optima. These effects prevent simulated directed evolution approaches from efficiently reaching the global optimum. There is nonetheless wide variability in the effectiveness of different directed evolution approaches, which together provide experimental benchmarks for computational and machine learning workflows. The most-fit TrpB variants contain a substitution that is nearly absent in natural TrpB sequences—a result that conservation-based predictions would not capture. Thus, although fitness prediction using evolutionary data can enrich in more-active variants, these approaches struggle to identify and differentiate among the most-active variants, even for this near-native function. Overall, this work presents a large-scale testing ground for model-guided enzyme engineering and suggests that efficient navigation of epistatic fitness landscapes can be improved by advances in both machine learning and physical modeling.

biocatalysis↗
DOE OSTI2025

Spatiotemporal forecasting of the edge localized modes in tokamak plasmas using neural networks

Artificial intelligence techniques have been increasingly adopted by the plasma and fusion science to address problems like plasma reconstruction, surrogate modeling, and tokamak/stellarator optimization. A key focus in sustained fusion research is the prediction and mitigation of edge-localized-modes (ELMs), instabilities that occur in short, periodic bursts and can cause erosion to the tokamak vessel wall. Recent research has demonstrated the power of neural networks in approximating continuous functions. In this work, we build spatiotemporal forecasting models that can predict the onset of ELMs and their evolution at early stages. We leverage recent advances in generative modeling, sequence-to-sequence modeling, and Fourier neural operators to propose architectures and training strategies that can learn to forecast short to long term dynamics of the noisy signals due to ELMs. We benchmark the developed model against a state-of-the-art foundation model using the beam emission spectroscopy (BES) data that captures the plasma fluctuations due to ELMs over a 8 x 8 spatial grid. Our models demonstrate high accuracy, outperforming the baselines, in predicting the evolution of BES signals during ELM events. Furthermore, the developed models exhibit high accuracy in predicting the rapid rise and relaxation of the signals due to ELMs within 30–80 µs.

edge localized modes↗
DOE OSTI2026

Materializing Inter-Channel Relationships With Multi-Density Woodcock Tracking

Volume rendering techniques for scientific visualization have recently shifted toward Monte Carlo (MC) methods for their flexibility and robustness, but their use in multi-channel visualization remains underexplored. Traditional multi-channel volume rendering often relies on arbitrary, non-physically based color blending functions that hinder interpretation. Here, we introduce multi-density Woodcock tracking, a simple extension of Woodcock tracking that leverages an MC method to produce high-fidelity, physically grounded multi-channel renderings without arbitrary blending. By generalizing Woodcock’s distance tracking, we provide a unified blending modality that also integrates blending functions from prior works. We further implement effects that enhance boundary and feature recognition. By accumulating frames in real-time, our approach delivers high-quality visualizations with perceptual benefits, demonstrated on diverse datasets.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2025

Deuteron-induced reactions on natural Zr from threshold to 50 MeV: production of 86g Y

Two stacks of thin Zr foils were irradiated with 30 and 50 MeV deuterons, respectively, using the Lawrence Berkeley National Laboratory 88-Inch Cyclotron, and 19 excitation functions for nat Zr(d,x) reactions were measured over a beam energy range of 6.3–47.64 MeV, where the independent cross sections for nat Zr(d,x) 88 Nb and nat Zr(d,x) 86m,g Y were measured for the first time. The well-characterized nat Fe(d,x) 56 Co, nat Ni(d,x) 56 Co, nat Ni(d,x) 58 Co, nat Ni(d,x) 61 Cu, nat Ti(d,x) 46 Sc and nat Ti(d,x) 48 V monitor reactions were used to determine the deuteron beam current throughout the stacks. All cross sections were determined using High Purity Germanium (HPGe) detector γ-ray spectroscopy. A variance minimization technique was employed to simultaneously constrain the deuteron beam currents with multiple monitor reactions, thus reducing systematic uncertainties. An additional 16 channels are reported for reactions on the nickel, titanium, and iron monitor foils, leading to a total of 35 excitation functions, with seven reaction channels reported for the first time in this work. The measured excitation functions are compared to calculations provided by the reaction modeling codes TALYS – 2.0, ALICE – 2020, CoH – 3.5.3 and EMPIRE – 3.2.3, as well as the TENDL – 2023 data library. The degree of agreement between theory and experiments is discussed. The possible production of the important PET radionuclide 86g Y via the nat Zr(d,x) route was critically examined. The physical yields for nat Zr(d,x) 86 Y and other yttrium isotopes produced were calculated and compared to other production pathways. Due to high-level of associated radionuclide impurities, this route cannot deliver 86g Y suitable for medical applications.

86gY↗
DOE OSTI2024

Empirical correlations between the function of entropy ( Z S ) and net artificial viscous work in a shock physics hydrocode

Entropy is a state variable that may be obtained from any thermodynamically complete equation of state (EOS). However, hydrocode calculations that output the entropy often contain numerical errors; this is not because of the EOS, but rather the solution techniques that are used in hydrocodes (especially Eulerian) such as convection, remapping, and artificial viscosity. Here, in this work, empirical correlations are investigated to reduce the errors in entropy without altering the solution techniques for the conservation of mass, momentum, and energy. Specifically, these correlations are developed for the function of entropy Z S , and they depend upon the net artificial viscous work, as determined via Sandia National Laboratories’ shock physics hydrocode CTH. These results are a continuation of a prior effort to implement the entropy-based CREST reactive burn model in CTH, and they are presented here to stimulate further interest from the shock physics community. Future work is planned to study higher-dimensional shock waves, shock wave interactions, and possible ties between the empirical correlations and a physical law.

75 CONDENSED MATTER PHYSICS, SUPERCONDUCTIVITY AND↗
DOE OSTI2025

Untangling Sources of Error in the Density-Functional Many-Body Expansion

The many-body expansion provides a framework for data-driven applications of electronic structure theory, including parametrization of classical force fields and machine learning. In this article, we demonstrate that its use significantly amplifies quadrature grid errors when modern density-functional approximations are employed. Standard grids that work well in conventional density-functional calculations result in runaway error accumulation when used with the many-body expansion. At the same time, delocalization error is also exacerbated, leading to exaggerated estimates of nonadditive n-body interactions. This is illustrated for anion–water clusters using the SCAN, r2SCAN, ωB97X-V and ωB97M-V functionals. By employing dense quadrature grids, the inherent self-interaction error is exposed, which can then be mitigated using a variety of other strategies.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2024

Synthesis and characterization of low-dimensional N-heterocyclic carbene lattices

The covalent interaction of N-heterocyclic carbenes (NHCs) with transition metal atoms gives rise to distinctive frontier molecular orbitals (FMOs). These emergent electronic states have spurred the widespread adoption of NHC ligands in chemical catalysis and functional materials. Although formation of carbene-metal complexes in self-assembled monolayers on surfaces has been explored, design and electronic structure characterization of extended low-dimensional NHC-metal lattices remains elusive. Here, in this work, we demonstrate a modular approach to engineering one-dimensional (1D) metal-organic chains and two-dimensional (2D) Kagome lattices using the FMOs of NHC–Au–NHC junctions to create low-dimensional molecular networks exhibiting intrinsic metallicity. Scanning tunneling spectroscopy and first-principles density functional theory reveal the contribution of C–Au–C π-bonding states to dispersive bands that imbue 1D- and 2D-NHC lattices with exceptionally small work functions.

Qie, Boyu↗
DOE OSTI2025

Discovery of Stacking Heterogeneity, Layer Buckling, and Residual Water in COF-999-NH 2 and Implications on CO 2 Capture

Covalent organic frameworks (COFs), with their modular architectures and tunable functionalities, provide a versatile platform to design sorbents for the direct capture of CO 2 from air. Here, for this work, we combined density functional theory, molecular dynamics, and grand canonical Monte Carlo simulations with experiment to understand structural factors for furthering COF-999-NH 2 ’s performance as the precursor to COF-999 for direct air CO 2 capture. Small energy differences among laterally shifted stackings suggest intrinsic stacking heterogeneity. The simulations show pronounced layer buckling coupled to extensive amine–nitrile hydrogen bonding and persistent pore water, which initiates undesired polymerization and undermines uptake. The predicted presence of water is confirmed by subsequent experiments. These insights point to a single, actionable design rule: exclude retained water by introducing hydrophobic pore environments to maximize the CO 2 capture efficiency.

adsorption↗
DOE OSTI2025

Heterogeneous Mixtures of Dictionary Functions to Approximate Subspace Invariance in Koopman Operators: Why Deep Koopman Operators Work

Abstract Koopman operators model nonlinear dynamics as a linear dynamic system acting on a nonlinear function as the state. This nonstandard state is often called a Koopman observable and is usually approximated numerically by a superposition of functions drawn from a dictionary . In a widely used algorithm, extended dynamic mode decomposition (EDMD), the dictionary functions are drawn from a fixed class of functions. Deep learning combined with EDMD has been used to learn novel dictionary functions in an algorithm called deep dynamic mode decomposition (deepDMD). The learned representation both (1) accurately models and (2) scales well with the dimension of the original nonlinear system. In this paper, we analyze the learned dictionaries from deepDMD and explore the theoretical basis for their strong performance. We explore State-Inclusive Logistic Lifting (SILL) dictionary functions to approximate Koopman observables. Error analysis of these dictionary functions show they satisfy a property of subspace approximation, which we define as uniform finite approximate closure. Typically, a Koopman dictionary’s nonlinear functions are homogeneous. In this paper, we discover that structured mixing of heterogeneous dictionary functions drawn from different classes of nonlinear functions achieve the same accuracy and dimensional scaling as the deep-learning-based deepDMD algorithm Yeung et al. ( In: 2019 American Control Conference (ACC), 2019). We specifically show this by building a heterogeneous dictionary comprised of SILL functions and conjunctive radial basis functions (RBFs). This mixed dictionary achieves similar accuracy and dimensional scaling to deepDMD with an order of magnitude reduction in parameters, while maintaining geometric interpretability. These results strengthen the viability of dictionary-based Koopman models to solving high-dimensional nonlinear learning problems.

Johnson, Charles A.↗