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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 91 records · Page 5
All sourcesNASA NTRSDOE OSTI
DOE OSTI2022

A finite micro-rotation material point method for micropolar solid and fluid dynamics with three-dimensional evolving contacts and free surfaces

This paper introduces an explicit material point method designed specifically for simulating the micropolar continuum dynamics in the finite deformation and finite microrotation regime. The material point method enables us to simulate large deformation problems while circumventing the potential mesh distortion without remeshing. To eliminate rotational motion damping and loss of angular momentum during the projection, we introduce the mapping for microinertia and angular momentum between particles and grids through the affine particle-in-cell approach. The microrotation and the curvature at each particle are updated through zero-order forward integration of the microgyration and its spatial gradient. We show that the microinertia and the angular momentum are conserved during the projections between particles and grids in our formulation. We verify the formulation and implementation by comparing with the analytical dispersion relation of micropolar waves under the small strain and small microrotation, as well as the analytical soliton solution for solids undergoing large deformation and large microrotation. Additionally we also demonstrate the capacity of the proposed computational framework to handle a wide spectrum of simulations that exhibit size effects in the geometrical nonlinear regime through three representative numerical examples, i.e., a cantilever beam torsion problem, a fragment-impact penetration problem, and a micropolar fluid discharging problem.

42 ENGINEERING↗
DOE OSTI2021

Self-Consistent Field Methods for Excited States in Strong Magnetic Fields: A Comparison Between Energy - and Variance-based Approaches

An efficient implementation of geometrical derivatives at the Hartree–Fock (HF) and current-density functional theory (CDFT) levels is presented for the study of molecular structure in strong magnetic fields. The required integral derivatives are constructed using a hybrid McMurchie–Davidson and Rys quadrature approach, which combines the amenability of the former to the evaluation of derivative integrals with the efficiency of the latter for basis sets with high angular momentum. In addition to its application to evaluating derivatives of four-center integrals, this approach is also applied to gradients using the resolution-of-the-identity approximation, enabling efficient optimization of molecular structure for many-electron systems under a strong magnetic field. The CDFT contributions have been implemented for a wide range of density functionals up to and including the meta-GGA level with current-density dependent contributions and (range-separated) hybrids for the first time. Illustrative applications are presented to the OH and benzene molecules, revealing the rich and complex chemistry induced by the presence of an external magnetic field. Challenges for geometry optimization in strong fields are highlighted, along with the requirement for careful analysis of the resulting electronic structure at each stationary point. The importance of correlation effects is examined by comparison of results at the HF and CDFT levels. The present implementation of molecular gradients at the CDFT level provides a cost-effective approach to the study of molecular structure under strong magnetic fields, opening up many new possibilities for the study of chemistry in this regime.

Comparison↗
DOE OSTI2025

Introducing GPU Acceleration into the Python-Based Simulations of Chemistry Framework

We introduce the first version of GPU4P Y SCF, a module that provides GPU acceleration of methods in P Y SCF. As a core functionality, this provides a GPU implementation of two-electron repulsion integrals (ERIs) for contracted basis sets comprising up to g functions using the Rys quadrature. As an illustration of how this can accelerate a quantum chemistry workflow, we describe how to use the ERIs efficiently in the integral-direct Hartree–Fock build and nuclear gradient construction. Benchmark calculations show a significant speedup of 2 orders of magnitude with respect to the multithreaded CPU Hartree–Fock code of P Y SCF and the performance comparable to other open-source GPU-accelerated quantum chemical packages, including GAMESS and QUICK, on a single NVIDIA A100 GPU.

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

New millimeter-wave diagnostics to locally probe internal density and magnetic field fluctuations in National Spherical Torus Experiment-Upgrade (invited)

A set of new millimeter-wave diagnostics will deliver unique measurement capabilities for National Spherical Torus Experiment-Upgrade to address a variety of plasma instabilities believed to be important in determining thermal and particle transport, such as micro-tearing, global Alfvén eigenmodes, kinetic ballooning, trapped electron, and electron temperature gradient modes. These diagnostics include a new integrated intermediate-k Doppler backscattering (DBS) and cross-polarization scattering (CPS) system (four channels, 82.5–87 GHz) to measure density and magnetic fluctuations, respectively. The system can access reasonably large normalized wavenumbers k θ ρ s ranging from ≤0.5 to 15 (where ion sound gyroradius ρ s = 1 cm and k θ is the binormal density turbulence wavenumber). The system addresses the challenges for making useful DBS/CPS measurements with a remote control of launch polarization (X- or O-mode), probed wavenumber, polarization match of the launch beam with the edge magnetic field pitch angle, and beam steering of the launched beam for wave-vector alignment. In addition, a low-k DBS system consisting of eight fixed frequencies (34–52 GHz) and four tunable frequencies (55–75 GHz) for low-k density turbulence and fast ion physics will be located at a nearby port location. Finally, the combined systems cover the near LCFS and pedestal regions (34–52 GHz), the pedestal or mid-radius (50–75 GHz), and core plasmas (82.5–87 GHz).

47 OTHER INSTRUMENTATION↗
DOE OSTI2026

Strain mapping of three-dimensionally structured two-dimensional materials

Strain plays a crucial role in tuning materials’ properties, influencing their optical, electrical, and chemical performances. In two-dimensional (2D) materials, applied stress often induces out-of-plane deformation, resulting in a more intricate three-dimensional (3D) topography, where mapping the strain remains a challenge due to the limitations of conventional characterization techniques. In this work, we introduce BRIGHT (Bragg-Rod Informed, Gradient-based Height-mapping Technique), an integrated method for reconstructing both the topography and planar strain profile of 3D-structured 2D materials using nanobeam four-dimensional scanning transmission electron microscopy (4D-STEM). We apply BRIGHT to a MoS2-MoSe2 transition metal dichalcogenide (TMD) lateral heterojunctions exhibiting built-in strain and out-of-plane ripples and show that varying heterojunction widths lead to distinct surface morphologies and corresponding changes in the planar strain distribution. These results establish a foundation for more effective strain engineering in 2D materials by accounting for out-of-plane structural features, thereby enabling more precise control of strain-dependent properties.

Mireles, Adan [Rice Univ., Houston, TX (United Sta↗
DOE OSTI2026

Ground and excited state gradients with end-to-end differentiable semiempirical quantum chemistry

Accurate and efficient gradients of molecular energy with respect to nuclear degrees of freedom are essential for geometry optimization and molecular dynamics, including simulations that go beyond the Born–Oppenheimer regime. A common approach involves deriving analytical formulas for new electronic structure methods, which is often conceptually difficult and requires tedious coding. Here, we implement analytical, semi-numerical, and automatic differentiation (AD)-based gradient pathways for semiempirical Hamiltonian models in the PYSEQM software package, leveraging both graphics processing unit (GPU) and central processing unit (CPU) architectures. We further extend these capabilities to excited states calculated using the configuration interaction singles and time-dependent Hartree–Fock ansätze. We benchmark wall time, peak memory usage, and accuracy across three molecular families of varying chemical complexity, including systems of up to a thousand atoms. For ground-state simulations, analytical and AD gradients achieve near-identical GPU runtimes, while semi-numerical gradients are slower on GPU but remain competitive on CPU. For excited states, both analytical and custom AD approaches using implicit differentiation show similar performance and low memory requirements, whereas gradients with full AD are memory-limited. AD gradients match analytical ones in accuracy across all tested systems, aided by a quaternion-based diatomic frame rotation for two-center quantities that ensures smooth energy surfaces. Overall, automatic differentiation emerges as a practical alternative to analytical gradients in semiempirical quantum chemistry, offering high accuracy while allowing seamless integration in AI-driven workflows and popular packages, such as PyTorch and JAX. Our results provide actionable guidance for selecting optimal gradient strategies in large-scale ground- and excited-state molecular dynamics simulations.

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

On-chip optical tweezers based on freeform optics

Since its advent in the 1970s, optical tweezers have been widely deployed as a preferred non-contact technique for manipulating microscale objects. On-chip integrated optical tweezers, which afford significant size, weight, and cost benefits, have been implemented, relying upon near-field evanescent waves. As a result, these tweezers are only capable of manipulation in near-surface regions and often demand high power since the evanescent interactions are relatively weak. We introduce on-chip optical tweezers based on freeform micro-optics, which comprise optical reflectors or refractive lenses integrated on waveguide end facets via two-photon polymerization. The freeform optical design offers unprecedented degrees of freedom to design optical fields with strong three-dimensional intensity gradients, useful for trapping and manipulating suspended particles in an integrated chip-scale platform. We demonstrate the design, fabrication, and measurement of both reflective and refractive micro-optical tweezers. The reflective tweezers feature a remarkably low trapping threshold power, and the refractive tweezers are particularly useful for multiparticle trapping and interparticle interaction analysis. Our integrated micro-optical tweezers uniquely combine a compact footprint, broadband operation, high trapping efficiency, and scalable integration with planar photonic circuits. This class of tweezers is promising for on-chip sensing, cell assembly, particle dynamics analysis, and ion trapping.

Yu, Shaoliang (ORCID:000000026072425X)↗
DOE OSTI2021

Carbon aerogels with integrated engineered macroporous architectures for improved mass transport

Carbon aerogels (CAs) combine unique properties including ultra-high surface area, high electrical conductivity, corrosion resistance, and robust mechanical properties making them ideal materials for electrochemical applications. Traditional CA synthesis results in isotropic, random nanoporous networks that work well for applications relying on diffusional mass transport. However, many applications would benefit from integration of engineered macroporous network structures that enable directed pressure-gradient-driven mass transport. In this study, we report on using 3D-printed sacrificial polymeric templates to generate templated CAs (t-CAs) with integrated engineered nonrandom macroporous network structures. Specifically, we used projection micro-stereo-lithography (PμSL) and two-photon polymerization direct laser writing (2PP-DLW) to fabricate millimeter-to-centimeter-sized 3D sacrificial polymeric templates with features ranging from tens of microns (PμSL) to 100s of nanometers (2PP-DLW). T-CAs were fabricated by infiltrating the templates with resorcinol-formaldehyde (RF) precursor solution, followed by carbonization at 1050 °C to simultaneously convert the RF gel to a CA and decompose the 3D-printed template, leaving an embedded templated macroporous network structure behind. X-ray computer tomography confirms integration of the macroporous architecture defined by the template. The templated macroporous architecture improves mass transport in t-CAs compared to traditional bulk CA as demonstrated by more uniform activation and their response in electrochemical cyclic voltammetry and galvanostatic charge-discharge tests.

36 MATERIALS SCIENCE↗
DOE OSTI2022

Dynamic calibration of differential equations using machine learning, with application to turbulence models

We present a methodology for calibration of parametric ordinary and partial differential equation models, using off-the-shelf software for back-propagation in Neural Networks (NN). As a prototypical example, we consider calibration of a Reynolds-averaged Navier-Stokes (RANS) turbulence closure model, against ground truth data from direct numerical simulations (DNS) of two different turbulent flows. Numerical time integration is represented as a custom NN, where only the RANS model parameters are trainable. A loss function is defined to quantify the mismatch between the NN prediction and the ground truth over a predefined, finite time integration window. This loss function is then minimized using a gradient descent method utilizing the back-propagation algorithm. Furthermore, this dynamic approach to training is to be contrasted with a static approach, wherein a least square regression estimate for parameters is obtained in the limit of an infinitesimal time integration window. In a first test of static and dynamic approaches against ground truth data generated by the model, the former proves to be significantly faster and more accurate than the latter at recovering the parameters. When both calibration approaches are tested against DNS data, for which it is known that the model cannot achieve a perfect fit, the static approach yields a good prediction only for short times, while the dynamic approach results in physical and stable predictions over the entire integration window. After optimization of the dynamic approach for time step, spatial resolution, stability, and physics-based constraints, we obtain a 50% improvement of outcomes over those obtained from the existing, manually calibrated set of parameters, demonstrating the merits of this systematic and automated procedure.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2023

Effect of material composition of diamond field emission array cathodes on quality of transversely shaped beams

Diamond field emitter array field emission cathodes (DFEA FECs) are attractive for the next generation of injectors due to their ability to produce transversely shaped beams without the need for complex masking or laser schemes. However, reliability of this cathode technology remains a challenging issue as principal mechanisms guiding and allowing for output beam shaping remained poorly understood. Here, this paper reports the results of testing two DFEA FECs with the same pattern and emitter tip geometry. Although both cathodes were able to sustain gradients of 44 MV/m and produce maximum output integral charge of 0.5 nC per radio frequency pulse, their emission patterns were different. One cathode did not produce a shaped beam, while the other one did. This difference was explained by the extent of the local variations of the diamond material across the arrays as discovered by spatially resolved Raman spectroscopy. The main practical takeaways were (i) tip sharpness was not a prerequisite for producing a shaped beam and instead (ii) material characteristics resulting in different cathode ballast resistance affected emission spatial uniformity across the array and hence the beam shaping.

36 MATERIALS SCIENCE↗
DOE OSTI2020

Comparison of stellar populations in simulated and real post-starburst galaxies in MaNGA

ABSTRACT Recent integral field spectroscopic (IFS) surveys have revealed radial gradients in the optical spectral indices of post-starburst (PSB) galaxies, which can be used to constrain their formation histories. We study the spectral indices of post-processed mock IFS datacubes of binary merger simulations, carefully matched to the properties of the MaNGA IFS survey, with a variety of black hole (BH) feedback models, progenitor galaxies, orbits, and mass ratios. Based on our simulation sample, we find that only major mergers on prograde–prograde or retrograde–prograde orbits in combination with a mechanical BH feedback model can form galaxies with weak enough ongoing star formation, and therefore absent H α emission, to be selected by traditional PSB selection methods. We find strong fluctuations in nebular emission line strengths, even within the PSB phase, suggesting that H α selected PSBs are only a subsample of the underlying population. The global PSB population can be more robustly identified using stellar continuum-based approaches. The difficulty in reproducing the very young PSBs in simulations potentially indicates that new sub-resolution star formation recipes are required to properly model the process of star formation quenching. In our simulations, we find that the starburst peaks at the same time at all radii, but is stronger and more prolonged in the inner regions. This results in a strong time evolution in the radial gradients of the spectral indices that can be used to estimate the age of the starburst without reliance on detailed star formation histories from spectral synthesis models.

Zheng, Yirui↗
DOE OSTI2020

The functional roles of species in metacommunities, as revealed by metanetwork analyses of bird–plant frugivory networks

Abstract Understanding how biodiversity and interaction networks change across environmental gradients is a major challenge in ecology. We integrated metacommunity and metanetwork perspectives to test species’ functional roles in bird–plant frugivory interactions in a fragmented forest landscape in Southwest China, with consequences for seed dispersal. Availability of fruit resources both on and under trees created vertical feeding stratification for frugivorous birds. Bird–plant interactions involving birds feeding only on‐the‐tree or both on and under‐the‐tree (shared) had a higher centrality and contributed more to metanetwork organisation than interactions involving birds feeding only under‐the‐tree. Moreover, bird–plant interactions associated with large‐seeded plants disproportionately contributed to metanetwork organisation and centrality. Consequently, on‐the‐tree and shared birds contributed more to metanetwork organisation whereas under‐the‐tree birds were more involved in local processes. We would expect that species’ roles in the metanetwork will translate into different conservation values for maintaining functioning of seed‐dispersal networks.

Li, Hai‐Dong↗
DOE OSTI2022

Online Distribution System State Estimation via Stochastic Gradient Algorithm

Distribution network operation is becoming more challenging because of the growing integration of intermittent and volatile distributed energy resources (DERs). This motivates the development of new distribution system state estimation (DSSE) paradigms that can operate at fast timescale based on real-time data stream of asynchronous measurements enabled by modern information and communications technology. To solve the real-time DSSE with asynchronous measurements effectively and accurately, this paper formulates a weighted least squares DSSE problem and proposes an online stochastic gradient algorithm to solve it. The performance of the proposed scheme is analytically guaranteed and is numerically corroborated with realistic data on IEEE 123-bus feeder.

distribution system state estimation↗
DOE OSTI2023

SQMBox: Interfacing a semiempirical integral library to modular ab initio electronic structure enables new semiempirical methods

Ab initio and semiempirical electronic structure methods are usually implemented in separate software packages or use entirely different code paths. As a result, it can be time-consuming to transfer an established ab initio electronic structure scheme to a semiempirical Hamiltonian. Here we present an approach to unify ab initio and semiempirical electronic structure code paths based on a separation of the wavefunction ansatz and the needed matrix representations of operators. With this separation, the Hamiltonian can refer to either an ab initio or semiempirical treatment of the resulting integrals. We built a semiempirical integral library and interfaced it to the GPU-accelerated electronic structure code TeraChem. Equivalency between ab initio and semiempirical tight-binding Hamiltonian terms is assigned according to their dependence on the one-electron density matrix. The new library provides semiempirical equivalents of the Hamiltonian matrix and gradient intermediates, corresponding to those provided by the ab initio integral library. This enables the straightforward combination of semiempirical Hamiltonians with the full pre-existing ground and excited state functionality of the ab initio electronic structure code. We demonstrate the capability of this approach by combining the extended tight-binding method GFN1-xTB with both spin-restricted ensemble-referenced Kohn–Sham and complete active space methods. We also present a highly efficient GPU implementation of the semiempirical Mulliken-approximated Fock exchange. The additional computational cost for this term becomes negligible even on consumer-grade GPUs, enabling Mulliken-approximated exchange in tight-binding methods for essentially no additional cost.

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

Thermal Gradient Effects on Redox Evolution and Volatility-Driven Fractionation in Ternary U/Ce/Cs Condensates

Understanding how thermal history influences redox evolution and chemical fractionation is essential for characterizing high-temperature condensation in complex materials, including nuclear debris. Here, we tested the hypothesis that distinct thermal regimes in a plasma flow reactor influence redox pathways and elemental partitioning in ternary U/Ce/Cs systems. A configurable plasma flow reactor was modified with an external tube furnace to impose two distinct thermal gradients: continuous ambient cooling and a furnace-assisted thermal hold-up near 1400 K followed by rapid cooling. Transmission electron microscopy characterized phase identity, morphology, and nanoscale element distributions, while inductively coupled plasma-mass spectrometry quantified bulk elemental ratios. Across both thermal regimes, uranium and cerium condensed as UO 2 and CeO 2 as dominant refractory oxide products. Uranium partially oxidized to α-UO 3 during extended ambient cooling, while furnace-assisted hold-up preserved UO 2 and produced partial reduction of cerium to Ce 2 O 3 . Cesium remained volatile upstream and condensed later in the reactor, forming Cs 2 O and Cs-uranate phases with the highest incorporation after thermal hold-up. Bulk ICP-MS measurements supported these observations. U/Ce ratios remained comparatively stable and Cs displayed delayed and apparent transient enrichment that matched the nanoscale measurements. This integrated approach provides a quantitative method for linking thermal gradients to redox evolution and volatility-driven fractionation. These results show how the plasma flow reactor can identify where equilibrium descriptions remain adequate and where kinetic effects from residence time and temperature history must be considered when interpreting condensation behavior in multicomponent systems.

and nuclear chemistry↗
DOE OSTI2025

Supporting Information for manuscript: “A latitudinal gradient in S/G lignin monomer ratio driven by laccase in natural poplar variants”

Lignin composition plays a crucial role in plant structural integrity and environmental adaptation. However, the genetic and molecular mechanisms underlying natural variation in lignin composition remain poorly understood. This study investigates the syringyl-to-guaiacyl (S/G) lignin monomer ratio across a natural population of Populus trichocarpa spanning a latitudinal gradient along the Northwest coast of North America. By integrating biochemical, genomic, and geographic analysis, we identify key gene variants associated with S/G ratio differences. These datasets provide valuable insights into the evolutionary and functional genomics of lignin composition and serve as a resource for developing poplar variants optimized for forestry and bioenergy applications.

Poplar, lignin composition, laccases, latitude, ad↗