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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 343 records · Page 19
All sourcesNASA NTRSDOE OSTI
DOE OSTI2022

System and method for sub micron additive manufacturing

An apparatus is disclosed for performing an additive manufacturing operation to form a structure by processing a photopolymer resist material. The apparatus may incorporate a laser for generating a laser beam, and a tunable mask for receiving the laser beam which has an optically dispersive element. The mask splits the laser beam into a plurality of emergent beams each having a subplurality of beamlets of varying or identical intensity, with each beamlet emerging from a unique subsection of illuminated regions of the mask. A collimator collimates at least one of the emergent beams to form a collimated beam. One or more focusing elements focuses the collimated beam into a focused beam which is projected as a focused image plane on or within the resist material. The focused beam simultaneously illuminates a layer of the resist material to process an entire layer in a parallel fashion.

Saha, Sourabh Kumar↗
DOE OSTI2021

Role of the X Coligands in Cyclometalated [Ni(Phbpy)X] Complexes (HPhbpy = 6-Phenyl-2,2'-bipyridine)

The coligand X was varied in the organonickel complexes [Ni(Phbpy)X] (X = F, Cl, Br, I, C 6 F 5 ) carrying the anionic tridentate C^N^N ligand 6-(phen-2-ide)-2,2'-bipyridine (Phbpy – ) to study its effect on electronic structures of these complexes and their activity in Negishi-like C–C cross-coupling catalysis. The complexes were synthesized from the precursor [Ni(COD) 2 ] (COD = 1,5-cyclooctadiene) by chelate-assisted oxidative addition into the phenyl C–X bond of the protoligand 6-(2-halidophenyl)-2,2'-bipyridine) and were obtained as red powders. Protoligands X–Phbpy carrying the halide surrogates X = OMe, OTf (triflate) failed in this reaction. Single-crystal XRD allowed us to add the structures of [Ni(Phbpy)Cl] and [Ni(Phbpy)I] to the previously reported Br derivative. Cyclic voltammetry showed reversible reductions for X = C 6 F 5 , F, Cl, while for Br and I the reversibility is reduced through rapid splitting of X – after reduction (EC mechanism). UV–vis spectroelectrochemistry confirmed the decreasing degree of reversibility along the series C 6 F 5 > F > Cl » Br > I, which parallels the “leaving group character” of the X coligands. This method also revealed mainly bpy centered reduction and essentially Ni(II)/Ni(III) oxidations, as corroborated by DFT calculations. The rather X-invariant long-wavelength UV–vis absorptions and excited states were analyzed in detail using TD-DFT and were consistent with predominant metal to ligand charge transfer (MLCT) character. Initial catalytic tests under Negishi-like conditions showed the complexes to be active as catalysts in C–C cross-coupling reactions but did not display marked differences along the series from Ni–F to Ni–I.

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

Phonon-Mediated Ultrafast Hole Transfer from Photoexcited CdSe Quantum Dots to Black Dye

We have applied non-adiabatic molecular dynamics (NAMD) and Fewest Switching surface hopping (FSSH) method to simulate the energy dissipation and charge transfer processes in the CdSe quantum dot (QD) functionalized by the Black dye. Our calculations reveal ultrafast hole transfer from the photoexcited QD to the dye, despite a significant energy splitting between QD’s and dye’s occupied states. The mechanism of such ultrafast QD-to-dye hole transfer is rationalized by strong non-adiabatic couplings between the delocalized surface orbitals of the QD and the high-frequency vibrations of isothiocyanate ligands of the Black dye. Here, this mechanism is also confirmed by a very rapid lose of coherency of the excitation due to strong electronic couplings with vibrational modes of the dye.

77 NANOSCIENCE AND NANOTECHNOLOGY↗
DOE OSTI2023

Floating zone crystal growth, structure, and properties of a cubic Li 5.5 La 3 Nb 1.5 Zr 0.5 O 12 garnet-type lithium-ion conductor

As a promising candidate for solid-state electrolytes in Li-ion batteries, the garnet-type Li-ion conductor series Li 5+x La 3 Nb 2-x Zr x O 12 (LLNZO) (0 ≤ x ≤ 2) exhibits high ionic conductivity at room temperature. However, no previous single-crystal growth or characterization has been reported for LLNZO compositions 0 ≤ x ≤ 1. To obtain a complete understanding of the trend in the structure–property relationship in this class of materials, we used the floating zone (FZ) method to grow a single crystal of Li 5.5 La 3 Nb 1.5 Zr 0.5 O 12 that was 4 mm in diameter and 10 mm in length. Using Laue neutron single-crystal diffraction, two distinct Li sites were observed: tetrahedral 24d and octahedral 96h sites. The maximum entropy method (MEM) based on neutron single-crystal diffraction data was used to map Li nuclear density and estimate that the bottleneck of Li transport exists between neighboring tetrahedral and octahedral sites, and that Li is delocalized between split octahedral sites. Room-temperature Li-ion conductivity in Li 5.5 La 3 Nb 1.5 Zr 0.5 O 12 measured with electrochemical impedance spectroscopy (EIS) was 1.37 × 10 -4 S cm -1 . The Li migration activation energy was estimated to be 0.50 eV from EIS and 0.47 eV from dielectric relaxation measurements. The Li-ion jump attempt rate was estimated to be 1.47 × 10 12 Hz while the time scale of successful migration is 10 -7 to 10 -6 s.

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

Bardeen-Cooper-Schrieffer pairing of composite fermions

Topological pairing of composite fermions has led to remarkable ideas, such as excitations obeying non-Abelian braid statistics and topological quantum computation. Here, we construct a p-wave paired Bardeen-Cooper-Schrieffer (BCS) wave function for composite fermions in the torus geometry, which is a convenient geometry for formulating momentum space pairing as well as for revealing the underlying composite-fermion Fermi sea. Following the standard BCS approach, we minimize the Coulomb interaction energy at half filling in the lowest and the second Landau levels, which correspond to filling factors ν = 1/2 and ν = 5/2 in GaAs quantum wells, by optimizing two variational parameters that are analogous to the gap and the Debye cut-off energy of the BCS theory. Our results show no evidence for pairing at ν = 1/2 but a clear evidence for pairing at ν = 5/2. To a good approximation, the highest overlap between the exact Coulomb ground state at ν = 5/2 and the BCS state is obtained for parameters that minimize the energy of the latter, thereby providing support for the physics of composite-fermion pairing as the mechanism for the 5/2 fractional quantum Hall effect. We discuss the issue of modular covariance of the composite-fermion BCS wave function, and calculate its Hall viscosity and pair correlation function. By similar methods, we look for but do not find an instability to s-wave pairing for a spin-singlet composite-fermion Fermi sea at half-filled lowest Landau level in a system where the Zeeman splitting has been set to zero.

75 CONDENSED MATTER PHYSICS, SUPERCONDUCTIVITY AND↗
DOE OSTI2026

Adaptive X-ray imaging with reinforcement learning

X-ray imaging is a powerful technique to scan samples in a variety of contexts including biological, environmental and materials science, but commonly requires a synchrotron light source to produce X-rays at sufficient intensity. As these facilities are expensive to operate, the available beam time is limited and always in high demand. Particularly if the illuminated samples are sparse, standard raster scanning methods can be time-consuming, with a majority of that time being spent on areas of the image that carry little information. To increase the efficiency and maximize the information gain for a given time budget, we split the scanning process into a series of steps where previous measurements are used to inform the decision making and adapt the exposure distribution at later stages of the sequence. We formulate this task as a reinforcement learning problem where the goal is to produce a sequence of exposure maps that maximize a predefined scalar metric. We demonstrate the potential of this approach in simulations where the adaptive illumination can accelerate the measurement process by up to an order of magnitude compared with standard raster scanning. Finally, we present the first results from deploying the trained agents on an X-ray fluorescence beamline at the Stanford Synchrotron Radiation Lightsource.

Reinforcement Learning↗
DOE OSTI2026

The Impact of Time-Aware Design Choices in ICS Anomaly Detection

Industrial control systems (ICS) remain vulnerable to increasingly sophisticated cyberattacks, yet evaluating anomaly detection models in these environments is challenging due to temporal dependencies, missing-not-at-random patterns, and extremely imbalanced datasets. These factors make common practices—especially random data splits and na¨ıve imputation— prone to severe temporal leakage, which can inflate reported performance and obscure real-world limitations. In this work, we systematically examine classical machine learning models, temporal deep learning architecture, and tensordecomposition– based methods on a gas-pipeline dataset using a fully temporally separated evaluation pipeline designed to mimic realistic deployment conditions. Our findings show that proper temporal handling and MNAR-aware preprocessing significantly alter the relative performance of popular anomaly-detection methods, providing practical guidance for designing reliable, leakage-resistant ICS intrusion-detection systems.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2023

Sample Type Adaptable RNA depletion performance data [Slides]

Sequencing data was aligned to rRNA data sets QIIME_16S_MiDAS_4.8.1 and SILVA_138.1_LSURef_NR99 using BWA. RNA used was a composite (pool) of wastewater RNA samples collected at LANL between April 2022 and December 2022. RNA sample was split into four aliquots (STAR depletion and STAR depletion no-probe-control as well as RiboZero and RiboZero no-probe-control). All sequencing libraries were prepared from the depleted RNA samples using the same library prep method and sequenced on Illumina platforms.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2021

Spin-free formulation of the multireference driven similarity renormalization group: A benchmark study of first-row diatomic molecules and spin-crossover energetics

We report a spin-free formulation of the multireference (MR) driven similarity renormalization group (DSRG) based on the ensemble normal ordering of Mukherjee and Kutzelnigg (1997). This ensemble averages over all microstates of a given total spin quantum number, and therefore, it is invariant with respect to SU(2) transformations. As such, all equations may be reformulated in terms of spin-free quantities and they closely resemble those of spin-adapted closed-shell coupled cluster (CC) theory. The current implementation is used to assess the accuracy of various truncated MR-DSRG methods (perturbation theory up to third order and iterative methods with single and double excitations) in computing the constants of 33 first-row diatomic molecules. The accuracy trends for these first-row diatomics are consistent with our previous benchmark on a small subset of closed-shell diatomic molecules. We then present the first MR-DSRG application on transition-metal complexes by computing the spin splittings of the [Fe(H 2 O) 6 ] 2+ and [Fe(NH 3 ) 6 ] 2+ molecules. A focal point analysis (FPA) shows that third-order perturbative corrections are essential to achieve reasonably converged energetics. The FPA based on the linearized MR-DSRG theory with one- and two-body operators and up to a quintuple- ζ basis set predicts the spin splittings of [Fe(H 2 O) 6 ] 2+ and [Fe(NH 3 ) 6 ] 2+ to be –35.7 and –17.1 kcal mol –1 , respectively, showing good agreement with the results of local CC theory with singles, doubles, and perturbative triples.

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

Accelerating eigenvalue computation for nuclear structure calculations via perturbative corrections

Subspace projection methods utilizing perturbative corrections have been proposed for computing the lowest few eigenvalues and corresponding eigenvectors of large Hamiltonian matrices. In this paper, we build upon these methods and introduce the term Subspace Projection with Perturbative Corrections (SPPC) method to refer to this approach. We tailor the SPPC for nuclear many-body Hamiltonians represented in a truncated configuration interaction subspace, i.e., the no-core shell model (NCSM). We use the hierarchical structure of the NCSM Hamiltonian to partition the Hamiltonian as the sum of two matrices. The first matrix corresponds to the Hamiltonian represented in a small configuration space, whereas the second is viewed as the perturbation to the first matrix. Eigenvalues and eigenvectors of the first matrix can be computed efficiently. Because of the split, perturbative corrections to the eigenvectors of the first matrix can be obtained efficiently from the solutions of a sequence of linear systems of equations defined in the small configuration space. These correction vectors can be combined with the approximate eigenvectors of the first matrix to construct a subspace from which more accurate approximations of the desired eigenpairs can be obtained. We show by numerical examples that the SPPC method can be more efficient than conventional iterative methods for solving large-scale eigenvalue problems such as the Lanczos, block Lanczos and the locally optimal block preconditioned conjugate gradient (LOBPCG) method. The method can also be combined with other methods to avoid convergence stagnation.

73 NUCLEAR PHYSICS AND RADIATION PHYSICS↗
DOE OSTI2023

Orbital dependent complications for close vs well-separated electrons in diradicals

We investigate two limits in open-shell diradical systems: O3, in which the interesting orbitals are in close proximity to one another, and (C21H13)2, where there is a significant spatial separation between the two orbitals. In accord with earlier calculations, we find that standard density-functional approximations do not predict the open-shell character for the former case but uniformly predict the open-shell character for the latter case. We trace the qualitatively incorrect behavior in O3 predicted by these standard density functional approximations to self-interaction error and use the Fermi–Löwdin-orbital-self-interaction-corrected formalism to determine accurate triplet, closed-shell singlet, and open-shell broken-spin-symmetry electronic configurations. Analysis of the resulting many-electron overlap matrices allows us to unambiguously show that the broken-spin-symmetry configurations do not participate in the representation of the Ms = 0 triplet states and allows us to reliably extract the singlet–triplet splitting in O3 by analyzing the energy as a function of Fermi-orbital-descriptor permutations. The results of these analyses predict the percentage of open-shell character in O3, which agrees well with conventional wavefunction-based methods. While these techniques are expected to be required in cases near the Coulson–Fischer point, we find that they will be less necessary in diradical systems with well-separated electrons, such as (C21H13)2. Results based on energies from self-interaction-corrected generalized gradient, local density, and Hartree–Fock approximations and experimental results are in generally good agreement for O3. These results help form the basis for deriving extended Heisenberg-like Hamiltonians that are needed for descriptions of molecular magnets when there are competing low-energy electronic configurations.

Chemistry↗
DOE OSTI2025

Many-body expansion based machine learning models for octahedral transition metal complexes

Abstract Graph-based machine learning (ML) models for material properties show great potential to accelerate virtual high-throughput screening of large chemical spaces. However, in their simplest forms, graph-based models do not include any 3D information and are unable to distinguish stereoisomers such as those arising from different orderings of ligands around a metal center in coordination complexes. In this work we present a modification to revised autocorrelation descriptors, a molecular graph featurization method, for predicting spin state dependent properties of octahedral transition metal complexes (TMCs). Inspired by analytical semi-empirical models for TMCs, the new modeling strategy is based on the many-body expansion (MBE) and allows one to tune the captured stereoisomer information by changing the truncation order of the MBE. We present the necessary modifications to include this approach in two commonly used ML methods, kernel ridge regression and feed-forward neural networks. On a test set composed of all possible isomers of binary TMCs, the best MBE models achieve mean absolute errors (MAEs) of 2.75 kcal mol −1 on spin-splitting energies and 0.26 eV on frontier orbital energy gaps, a 30%–40% reduction in error compared to models based on our previous approach. We also observe improved generalization to previously unseen ligands where the best-performing models exhibit MAEs of 4.00 kcal mol −1 (i.e. a 0.73 kcal mol −1 reduction) on the spin-splitting energies and 0.53 eV (i.e. a 0.10 eV reduction) on the frontier orbital energy gaps. Because the new approach incorporates insights from electronic structure theory, such as ligand additivity relationships, these models exhibit systematic generalization from homoleptic to heteroleptic complexes, allowing for efficient screening of TMC search spaces.

Meyer, Ralf (ORCID:0000000322360261)↗
DOE OSTI2021

An Adaptive Tracking Algorithm for Convection in Simulated and Remote Sensing Data

A robust and computationally efficient object tracking algorithm is developed by incorporating various tracking techniques. Physical properties of the objects, such as brightness temperature or reflectivity, are not considered. Therefore, the algorithm is adaptable for tracking convection-like features in simulated data and remotely sensed two-dimensional images. In this algorithm, a first guess of the motion, estimated using the Fourier phase shift, is used to predict the candidates for matching. A disparity score is computed for each target–candidate pair. The disparity also incorporates overlapping criteria in the case of large objects. Then the Hungarian method is applied to identify the best pairs by minimizing the global disparity. The high-disparity pairs are unmatched, and their target and candidate are declared expired and newly initiated objects, respectively. They are tested for merger and split on the basis of their size and overlap with the other objects. The sensitivity of track duration is shown for different disparity and size thresholds. The report highlights the algorithm’s ability to study convective life cycles using radar and simulated data over Darwin, Australia. The algorithm skillfully tracks individual convective cells (a few pixels in size) and large convective systems. The duration of tracks and cell size are found to be lognormally distributed over Darwin. The evolution of size and precipitation types of isolated convective cells is presented in the Lagrangian perspective. This algorithm is part of a vision for a modular platform [viz., TINT is not TITAN (TINT) and Tracking and Object-Based Analysis of Clouds (tobac)] that will evolve into a sustainable choice to analyze atmospheric features.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2025

Design Choices in Anomaly Detection for Industrial Control Systems: Insights from Gas Pipeline Data

Industrial control systems (ICS) remain vulnerable to increasingly sophisticated cyberattacks, yet evaluating anomaly detection models in these environments is challenging due to temporal dependencies, missing-not-at-random patterns, and extremely imbalanced datasets. These factors make common practices—especially random data splits and naïve imputation—prone to severe temporal leakage, which can inflate reported performance and obscure real-world limitations. In this work, we systematically examine classical machine learning models, temporal deep learning architecture, and tensor-decomposition–based methods on a gas-pipeline dataset using a fully temporally separated evaluation pipeline designed to mimic realistic deployment conditions. Our findings show that proper temporal handling and MNAR-aware preprocessing significantly alter the relative performance of popular anomaly-detection methods, providing practical guidance for designing reliable, leakage-resistant ICS intrusion-detection systems.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2022

Demonstration of photoreactor platform for on-sun unassisted photoelectrochemical hydrogen generation with tandem III–V photoelectrodes

Photoelectrochemical (PEC) water splitting is a direct solar-driven technology that converts solar energy to storable chemical energy in the form of hydrogen. In addition to semiconductor and catalyst development for improved photoelectrodes, designing reactors for testing and operation of PEC systems under inherently dynamic outdoor solar illumination is necessary to further the commercial viability of PEC technology. Herein, we present a versatile photoreactor system mounted on a solar tracker for outdoor PEC testing and demonstrate unassisted PEC water splitting under real world on-sun conditions. GaInP 2 /GaAs tandem absorber photoelectrodes with a MoS 2 catalyst were fabricated and exhibit >8% solar-to-hydrogen efficiency. On-sun efficiency and stability of the photoelectrodes were characterized on both sunny and partly cloudy days with continuous monitoring of insolation and weather conditions. Furthermore, the versatile photoreactor and outdoor PEC testing capabilities and methods presented here can accelerate the development of other solar fuel generating systems and technologies.

solar fuels↗
DOE OSTI2022

Catalytic Selective Oxidations with Porous Transition Metal Oxides

This final report covers work done concerning oxidation catalysis over the past year. There are three major areas involving synthesis, characterization, and catalysis. The synthetic focus has been on porous metal oxides. Full characterization of these systems using a variety of methods has been done using ex-situ, in situ, and operando conditions. A major goal of the work has been to study the mechanisms of catalytic oxidations including identification of reaction intermediates. Specific applications besides oxidations concern electrocatalytic water splitting, water harvesting, CO 2 capture, and environmental catalysis.

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

FedADMP: A Joint Anomaly Detection and Mobility Prediction Framework via Federated Learning

With the proliferation of mobile devices and smart cameras, detecting anomalies and predicting their mobility are critical for enhancing safety in ubiquitous computing systems. Due to data privacy regulations and limited communication bandwidth, it is infeasible to collect, transmit, and store all data from mobile devices at a central location. To overcome this challenge, we propose FedADMP, a federated learning based joint Anomaly Detection and Mobility Prediction framework. FedADMP adaptively splits the training process between the server and clients to reduce computation loads on clients. To protect the privacy of user data, clients in FedADMP upload only intermediate model parameters to the cloud server. We also develop a differential privacy method to prevent the cloud server and external attackers from inferring private information during the model upload procedure. Extensive experiments using real-world datasets show that FedADMP consistently outperforms existing methods.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2025

Symmetry breaking forms split-off flat bands in quantum oxides controlling metal versus insulator phases

The crystal structure used as input to electronic structure calculation of conventionally bonded solids consists primarily of the standard crystallographic degrees of freedom. Quantum solids sometimes have additional microscopic degrees of freedom (m-DOF) nested within the crystallographic structure. These might include local motifs including positional (Peierls dimers, deformed octahedra, Jahn-Teller distortions), magnetic (local moment configurations) and dipolar (local ferroelectric configurations). Such motifs can be observed experimentally via local probes that avoid averaging, and theoretically as distinct total energy lowering features relative to more simplified “average crystallographic structures”. Here we examine the ability of electronic structure methods independent of strong correlation physics to explain the broad phenomenology of metal-insulator selectivity in quantum oxides by energy-lowering symmetry breaking. We do this by avoiding the restriction of considering only (i) electron-electron interactions in a fixed unresponsive lattice—as done in Mott strong correlation explanations—allowing, however, (ii) local positional and magnetic motifs that coexist within a crystallographic landscape. We find in a broad range of quantum oxides with different symmetry breaking modes the formation of split-off flat bands that can also control metallic versus insulating characteristics. The split-off band effect is common to magnetic and non-magnetic materials, including both binary and ternary oxides. One finds that when such local symmetry breaking motifs are considered in mean-field-like (e.g. density functional theory) electronic structure calculations of quantum oxides, they explain many of the observed trends in metal vs insulator phases discussed otherwise in prior literature via strong correlation in symmetry unbroken view.

75 CONDENSED MATTER PHYSICS, SUPERCONDUCTIVITY AND↗