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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 217 records · Page 12
All sourcesNASA NTRSDOE OSTI
DOE OSTI2020

Simultaneous 10 kHz three-dimensional CH 2 O and tomographic PIV measurements in a lifted partially-premixed jet flame

High-speed, three-dimensional (3D) scalar-velocity field measurements are demonstrated in a lifted partially-premixed dimethyl-ether/air jet flame using simultaneous laser-induced fluorescence (LIF) of formaldehyde (CH 2 O) and tomographic particle image velocimetry (TPIV). The 3D LIF measurements are performed by raster scanning the laser beam from a 100 kHz pulse-burst laser across the probe volume using an acousto-optic deflector. The volumetric reconstruction of the LIF signal from ten parallel planes provides quasi-instantaneous 3D LIF measurements that are synchronized with 10 kHz TPIV measurements. Here, the temporally resolved CH 2 O-LIF and velocity field data are used to analyze Lagrangian particle trajectories and displacement speeds at the base of the lifted flame. The particle trajectories reveal flow structures that are difficult to observe in an Eulerian reference frame. Positive and negative displacement speeds are observed at the CH 2 O-LIF surfaces at the inner and outer regions of the jet flame with a maximum displacement speed of approximately eight times the laminar flame speed of a stoichiometric dimethyl-ether/air mixture. The observations in present study support formation of lean premixed flames near the flame base whose role in flame stabilization should be investigated in more detail.

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

Pu(IV) quantification via visible–near-infrared absorption spectroscopy: tackling interferences using D-optimal design and partial least squares

Here, this study presents a novel analytical approach for quantifying Pu(IV) in glove box environments using fiber-optic-based visible–near-infrared absorption spectroscopy in combination with partial least squares regression (PLSR) and design of experiments. The method addresses significant challenges posed by overlapping spectral features arising from Nd(III), which is a common fission product impurity, and the speciation variability of Pu(IV) nitrato complexes in HNO 3 concentrations ranging from 2.5 to 11 M. A curated training set consisting of data from 20 samples was developed via D-optimal design to enable robust PLSR model calibration for Pu(IV) using the near-infrared band near 1050 nm. The training set was acquired from samples in cuvettes with a 1-cm path length and was used to build the PLSR model. The robustness of the model was validated with data collected using a dip probe with a 1-cm path length and varying Pu(IV) concentrations. The strong performance of the model indicates good model transfer from cuvette to dip probe and highlights the potential for in situ measurements and online monitoring of reactions in a crystallization reactor vessel. The results demonstrate that this combined spectroscopic and chemometric approach can accurately and simultaneously quantify Pu(IV) and HNO 3 , thereby offering a promising tool for real-time monitoring in process environments.

Actinide↗
DOE OSTI2021

HMMR is a downstream target of FOXM1 in enhancing proliferation and partial epithelial-to-mesenchymal transition of bladder cancer cells

Our previous that HMMR upregulation independently predicts poor survival in patients with papillary muscle-invasive bladder cancer (MIBC). In this study, we explored its downstream regulations and the potential transcriptional factors activating its expression. MIBC derived T24 cells, and non-MIBC (NMIBC) derived RT4 cells were used for in vitro and in vivo studies. HMMR expression enhanced cell proliferation, the expression of mesenchymal markers, and cell invasion. It induced the nuclear entry of β-catenin, increased its active form in the nuclear part, and elevated the relative TOP/FOP activity. The promoter region of HMMR has a canonical FKH motif. FOXM1 bound to this site and activated HMMR transcription. HMMR knockdown significantly weakened FOXM1 overexpression induced bladder cancer growth, invasion, partial epithelial-to-mesenchymal transition (pEMT), as well as the activation of the Wnt/β-catenin signaling pathway. In conclusion, the findings in this study expanded our understanding of the mechanisms underlying HMMR dysregulation and the functional role of the FOXM1-HMMR axis in bladder cancer.

60 APPLIED LIFE SCIENCES↗
DOE OSTI2022

Theory of gradient drift instabilities in low-temperature, partially magnetised plasmas

A fluid dispersion theory in partially magnetised plasmas is analysed to examine the conditions under which large-wavelength modes develop in Penning-type configurations, that is, where an electric field is imposed perpendicular to a homogeneous magnetic field. The fluid dispersion relation assuming a slab geometry shows that two types of low-frequency, gradient drift instabilities occur in the direction of the E×B and diamagnetic drifts. One type of instability, observed when the equilibrium electric field and plasma density gradient are in the same direction, is similar to the classic modified Simon–Hoh instability. A second instability is found for conditions in which (i) the diamagnetic drift is in the direction opposite to the E×B drift and (ii) the magnitude of the diamagnetic drift is sufficiently larger than the electron thermal speed. The present fluid dispersion theory suggests that the rotating spokes driven by such fluid instabilities propagate in the same direction as the diamagnetic drift, which can be in the same direction as or opposite to the E×B drift, depending on the plasma conditions. This finding may account for the observation, in some plasma devices, of the rotation of large-scale structures in both the E×B and -E×B directions.

71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗
DOE OSTI2024

Partial Solvation of Lithium Ions Enhances Conductivity in a Nanophase-Separated Polymer Electrolyte

In this study, we demonstrate that a multiblock lithium-ion-conducting polymer can be swollen with ethylene carbonate solvent to increase the conductivity relative to the dry polymer material by nearly 4 orders of magnitude. This increase is due to the partial solvation of lithium ions by ethylene carbonate, which leads to Li + diffusion along the solvent–polymer interface. This differs from the vehicular transport mechanism for lithium ions in pure solvent. We use a combination of broadband dielectric spectroscopy, X-ray scattering, and all-atom molecular dynamics simulations to probe the effect of the solvent on the polymer morphology and to elucidate the mechanism of lithium ion transport.

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

Unimolecular Dynamics of Partially Deuterated Hydroperoxyalkyl Intermediates (•QOOD) in Cyclohexane and Cyclopentane Oxidation

The hydroperoxyalkyl radicals (•QOOH) formed in cyclohexane and cyclopentane oxidation with carbon radical center at the β site relative to the hydroperoxy group have recently been observed through their infrared fingerprint and time- and energy-resolved unimolecular dissociation dynamics to hydroxyl (OH) radical and cyclic ether products. Partial deuteration shifts the IR transitions associated with OH/OD motion to lower frequencies, providing a new window on the IR spectroscopy and unimolecular dynamics of these transient intermediates. Specifically, the overtone OD stretch (2ν OD ) has been identified at 5215.0 cm –1 and 5216.0 cm –1 for the β-QOOD intermediates in cyclohexane and cyclopentane oxidation, respectively. Unimolecular decay rates of the •QOOD intermediates at these energies have been obtained from the time-resolved appearance of OD products. The experimental rates are compared with statistical microcanonical rates evaluated using RRKM theory, including heavy-atom tunneling associated with simultaneous O–O bond elongation and C–O–O angle contraction along the reaction pathway. The experimental rates provide a further test of the previously determined transition state (TS) barriers, which were computed utilizing a benchmarking approach that builds on higher-level reference calculations for the smaller ethane oxidation system. Here, the experimental rate measurements for both •QOOD intermediates agree well with the computed rates after accounting for small changes in zero-point energy and a minor empirical adjustment of the TS barriers in both systems.

Ethers↗
DOE OSTI2023

Relation between the Hydrated Electron Solvation Structure and Its Partial Molar Volume

It is now generally accepted that the hydrated electron occupies a cavity in water, but the size of the cavity and the arrangements of the solvating water molecules are not fully characterized. Here, we use the Kirkwood-Buff (KB) approach to examine how the partial molar volume (V M ) provides insight into these issues. The KB method relates V M to an integral of the electron-water radial distribution function, a key measure of the hydrated electron structure. Here we have applied it to three widely-used pseudopotentials and the results show that V M is a sensitive measure of the fidelity of hydrated electron descriptions. Thus, the measured V M places constraints on the hydrated electron structure that are important in developing and evaluating model descriptions. Importantly, we find that V M does not reflect only the cavity size (and thus should not be used to infer the cavity radius), but is strongly dependent on the extended solvation structure.

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

Surface Redox Pseudocapacitance of Partially Oxidized Titanium Carbide MXene in Water-in-Salt Electrolyte

Achieving pseudocapacitive intercalation in MXenes with neutral aqueous electrolytes and driving reversible redox reactions is scientifically appealing and practically useful. Here, we report that the partial oxidation of MXene intensifies pseudocapacitive Li + intercalation into Ti 3 C 2 T x MXene from neutral water-in-salt electrolytes. An in situ X-ray absorption near-edge structure analysis shows that the Ti oxidation state changes during the Li+ intercalation, indicating the presence of a surface redox reaction. The Ti oxidation/reduction is further confirmed by an in situ extended X-ray absorption fine structure analysis, which shows a reversible contraction/expansion of the Ti–C interatomic distance. The intensified Li + pseudocapacitive intercalation can be explained by the higher oxidation state of Ti at the open circuit potential. Furthermore, this work demonstrates the possibility of tuning the pseudocapacitive intercalation by adjusting the initial oxidation state of the transition metal on the MXene and offers a facile way to enhance the pseudocapacitance of various MXenes.

36 MATERIALS SCIENCE↗
DOE OSTI2021

Numerical and Analytical Modeling of Flow Partitioning in Partially Saturated Fracture Networks

Infiltration processes in fractured-porous media remain a crucial, yet not very well understood component of recharge and vulnerability assessment. Under partially-saturated conditions flows in fractures, percolating fracture networks, and fault zones contribute to the fastest spectrum of infiltration velocities via preferential pathways. Specifically, the partitioning dynamics at fracture intersections determine the magnitude of flow fragmentation into vertical and horizontal components and hence the bulk flow velocity and dispersion of fracture networks. In this work, we derive an approximate analytical solution for the partitioning process and validate it using smoothed particle hydrodynamics simulations. The developed transfer function is conceptually based on simulation results and laboratory experiments carried out in previous works. It allows to efficiently simulate flow through fracture networks with simple cubic structure and arbitrary number of fractures and aperture sizes via linear response theory and convolution of a given input signal. We derive a non-dimensional bulk flow velocity ($\widetilde{v}$) and dispersion coefficient ($\widetilde{D}$) to characterize fracture networks in terms of dimensionless horizontal and vertical time scales $\tau_m$ and $\tau_0$. The dispersion coefficient is shown to strongly depend on the horizontal time scale and converges towards a constant value of $0.08$ within reasonable fluid and geometrical parameter ranges, while the non-dimensional velocity exhibits a characteristic $\widetilde{v} \sim \tau_m^{-1/2}$ scaling. Given that hydraulic information is often only available at limited places within (fractured-porous) aquifer system, such as boreholes or springs, our study intends to provide a rudimentary analytical concept to potentially reconstruct internal fracture network geometries from external boundary information, e.g., the dispersive properties of discharge (groundwater level fluctuations).

42 ENGINEERING↗
DOE OSTI2023

Field-induced partial disorder in a Shastry-Sutherland lattice

Abstract A 2-Q antiferromagnetic order of the ferromagnetic dimers was found below T N = 2.9 K in the Shastry-Sutherland lattice BaNd 2 ZnS 5 by single crystal neutron diffraction. The magnetic order can be understood by the orthogonal arrangement of local Ising Nd spins, identified by polarized neutrons. A field was applied along [1 -1 0] to probe the observed metamagnetic transition in the magnetization measurement. The field decouples two magnetic sublattices corresponding to the propagation vectors q 1 = (½, ½, 0) and q 2 = (−½, ½, 0), respectively. Each sublattice shows a “stripe” order with a Néel-type arrangement in each single layer. The “stripe” order with q 1 remains nearly intact up to 6 T, while the other one with q 2 is suppressed at a critical field H c ~1.7 T, indicating a partial disorder. The H c varies with temperature and is manifested in the H - T phase diagram constructed by measuring the magnetization in BaNd 2 ZnS 5 .

36 MATERIALS SCIENCE↗
DOE OSTI2025

Optical neural engine for solving scientific partial differential equations

Abstract Solving partial differential equations (PDEs) is the cornerstone of scientific research and development. Data-driven machine learning (ML) approaches are emerging to accelerate time-consuming and computation-intensive numerical simulations of PDEs. Although optical systems offer high-throughput and energy-efficient ML hardware, their demonstration for solving PDEs is limited. Here, we present an optical neural engine (ONE) architecture combining diffractive optical neural networks for Fourier space processing and optical crossbar structures for real space processing to solve time-dependent and time-independent PDEs in diverse disciplines, including Darcy flow equation, the magnetostatic Poisson’s equation in demagnetization, the Navier-Stokes equation in incompressible fluid, Maxwell’s equations in nanophotonic metasurfaces, and coupled PDEs in a multiphysics system. We numerically and experimentally demonstrate the capability of the ONE architecture, which not only leverages the advantages of high-performance dual-space processing for outperforming traditional PDE solvers and being comparable with state-of-the-art ML models but also can be implemented using optical computing hardware with unique features of low-energy and highly parallel constant-time processing irrespective of model scales and real-time reconfigurability for tackling multiple tasks with the same architecture. The demonstrated architecture offers a versatile and powerful platform for large-scale scientific and engineering computations.

Tang, Yingheng (ORCID:0009000153622546)↗
DOE OSTI2025

One-shot learning for solution operators of partial differential equations

Learning and solving governing equations of a physical system, represented by partial differential equations (PDEs), from data is a central challenge in many areas of science and engineering. Traditional numerical methods can be computationally expensive for complex systems and require complete governing equations. Existing data-driven machine learning methods require large datasets to learn a surrogate solution operator, which could be impractical. Here, we propose a solution operator learning method that requires only one PDE solution, i.e., one-shot learning, along with suitable initial and boundary conditions. Leveraging the locality of derivatives, we define a local solution operator in small local domains, train it using a neural network, and use it to predict solutions of new input functions via mesh-based fixed-point iteration or meshfree neural-network based approaches. We test our method on various PDEs, complex geometries, and a practical spatial infection spread application, demonstrating its effectiveness and generalization capabilities.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2023

In situ formed partially disordered phases as earth-abundant Mn-rich cathode materials

Abstract Earth-abundant cathode materials are urgently needed to enable scaling of the Li-ion industry to multiply terawatt hours of annual production, necessitating reconsideration of how good cathode materials can be obtained. Irreversible transition metal migration and phase transformations in Li-ion cathodes are typically believed to be detrimental because they may trigger voltage hysteresis, poor kinetics and capacity degradation. Here we challenge this conventional consensus by reporting an unusual phase transformation from disordered Li- and Mn-rich rock salts to a new phase (named δ ), which displays partial spinel-like ordering with short coherence length and exhibits high energy density and rate capability. Unlike other Mn-based cathodes, the δ phase exhibits almost no voltage fade upon cycling. We identify the driving force and kinetics of this in situ cathode formation and establish design guidelines for Li- and Mn-rich compositions that combine high energy density, high rate capability and good cyclability, thereby enabling Mn-based energy storage.

25 ENERGY STORAGE↗
DOE OSTI2020

Structure of Pb(Fe 2/3 W 1/3 )O 3 single crystals with partial cation order

Despite intensive studies on the complex perovskite Pb(Fe 2/3 W 1/3 )O 3 (PFWO) relaxor, understanding the exact nature of its multifunctional properties has remained a challenge for decades. In this work we report a comprehensive structural study of the PFWO single crystals using a combination of synchrotron X-ray diffraction and high-resolution electron microscopy. The set of {h + ½, k + ½, l + ½} superlattice reflections was observed for the first time based on single-crystal synchrotron X-ray experiments (100–450 K) and transmission electron microscopy investigations, which indicates some kind of B-cation ordering in PFWO which had been thought to be totally disordered. It was found that (1) the crystal structure of PFWO should be described by a partly ordered cubic perovskite (i.e. Fm – 3m ), (2) the weak ferromagnetic properties and excess magnetic moment of PFWO can be understood based on non-random distribution of Fe cations between the 4a and 4b sites, and (3) the Pb displacement disorder is present in this material and the cations are probably displaced along the <100> directions. The X-ray diffraction results of this investigation show that partial cation ordering indeed exists in PFWO, which makes it necessary to revisit the generally accepted interpretations of the results obtained up to date. In agreement with X-ray diffraction study the main results of TEM study include: (1) a long range order that can be described with the Fm – 3m symmetry is reliably detected, (2) the coherence length of that long range order is in the order of 1–2 nm and (3) no remarkable chemical inhomogeneity is found in the tested PFWO crystal, excluding the possibility of a compositional ordering arising from substitutional defects in the perovskite structure.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2023

Machine-learning-based spectral methods for partial differential equations

Spectral methods are an important part of scientific computing’s arsenal for solving partial differential equations (PDEs). However, their applicability and effectiveness depend crucially on the choice of basis functions used to expand the solution of a PDE. The last decade has seen the emergence of deep learning as a strong contender in providing efficient representations of complex functions. In the current work, we present an approach for combining deep neural networks with spectral methods to solve PDEs. In particular, we use a deep learning technique known as the Deep Operator Network (DeepONet) to identify candidate functions on which to expand the solution of PDEs. We have devised an approach that uses the candidate functions provided by the DeepONet as a starting point to construct a set of functions that have the following properties: (1) they constitute a basis, (2) they are orthonormal, and (3) they are hierarchical, i.e., akin to Fourier series or orthogonal polynomials. We have exploited the favorable properties of our custom-made basis functions to both study their approximation capability and use them to expand the solution of linear and nonlinear time-dependent PDEs. The proposed approach advances the state of the art and versatility of spectral methods and, more generally, promotes the synergy between traditional scientific computing and machine learning.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2022

A localized view on molecular dissociation via electron-ion partial covariance

Inner-shell photoelectron spectroscopy provides an element-specific probe of molecular structure, as core-electron binding energies are sensitive to the chemical environment. Short-wavelength femtosecond light sources, such as Free-Electron Lasers (FELs), even enable time-resolved site-specific investigations of molecular photochemistry. Here, we study the ultraviolet photodissociation of the prototypical chiral molecule 1-iodo-2-methylbutane, probed by extreme-ultraviolet (XUV) pulses from the Free-electron LASer in Hamburg (FLASH) through the ultrafast evolution of the iodine 4d binding energy. Methodologically, we employ electron-ion partial covariance imaging as a technique to isolate otherwise elusive features in a two-dimensional photoelectron spectrum arising from different photofragmentation pathways. The experimental and theoretical results for the time-resolved electron spectra of the 4d 3/2 and 4d 5/2 atomic and molecular levels that are disentangled by this method provide a key step towards studying structural and chemical changes from a specific spectator site.

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

Multi-resolution partial differential equations preserved learning framework for spatiotemporal dynamics

Traditional data-driven deep learning models often struggle with high training costs, error accumulation, and poor generalizability in complex physical processes. Physics-informed deep learning (PiDL) addresses these challenges by incorporating physical principles into the model. Most PiDL approaches regularize training by embedding governing equations into the loss function, yet this depends heavily on extensive hyperparameter tuning to weigh each loss term. To this end, we propose to leverage physics prior knowledge by “baking” the discretized governing equations into the neural network architecture via the connection between the partial differential equations (PDE) operators and network structures, resulting in a PDE-preserved neural network (PPNN). This method, embedding discretized PDEs through convolutional residual networks in a multi-resolution setting, largely improves the generalizability and long-term prediction accuracy, outperforming conventional black-box models. The effectiveness and merit of the proposed methods have been demonstrated across various spatiotemporal dynamical systems governed by spatiotemporal PDEs, including reaction-diffusion, Burgers’, and Navier-Stokes equations.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2026

Ozone pollution reduction partially offsets the negative impact of climate change mitigation efforts on global hunger

Studies warning of the potential negative effects of climate mitigation on food security through the competing use of land for bioenergy and afforestation have overlooked the impact of reduced ozone and its potential enhancement of crop yields. Here we use six global agro-economic models to compare the impacts of climate change with climate mitigation policy and ozone reduction on agriculture. We find that ozone reduction could reduce the negative impact of a 1.5 °C-consistent climate change mitigation policy on global hunger by 15% in 2050. Sub-Saharan Africa and India, where hunger is most severe, account for 56% of this global reduction. Our findings indicate that the negative effects of climate mitigation on global hunger could be partially offset by the ozone reduction impact.

54 ENVIRONMENTAL SCIENCES↗