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Search indexed NASA NTRS and DOE OSTI research on propulsion, heat transfer, battery materials and energy systems. Follow report and document links to the original sources.

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At least 1,153 records · Page 64
All sourcesNASA NTRSDOE OSTI
DOE OSTI2021

The Dutch–Belgian Registry of Stereotactic Body Radiation Therapy for Liver Metastases: Clinical Outcomes of 515 Patients and 668 Metastases

Although various studies have reported that stereotactic body radiation therapy (SBRT) for liver metastases has high local control rates and relatively low toxicity, most series included a small number of patients. We aimed to validate these outcomes in a large multi-institution patient cohort treated in accordance with a common protocol.

62 RADIOLOGY AND NUCLEAR MEDICINE↗
DOE OSTI2022

Gantry-Based 5-Fraction Elective Nodal Irradiation in Unfavorable-Risk Prostate Cancer: Outcomes From 2 Prospective Studies Comparing SABR Boost With MR Dose-Painted HDR Brachytherapy Boost

Guidelines from the American Society of Clinical Oncology and Cancer Care Ontario recommend brachytherapy boost for patients with intermediate-risk or high-risk prostate cancer. SABR is an emerging technique for prostate cancer, but its use in high-risk disease is limited. Efficacy, toxic effects, and quality of life (QoL) were compared in patients treated on 2 prospective protocols that used SABR boost or magnetic resonance–guided high-dose-rate brachytherapy (HDR-BT) boost with 6 to 18 months of androgen deprivation therapy (ADT).

62 RADIOLOGY AND NUCLEAR MEDICINE↗
DOE OSTI2022

Patterns of Initial Relapse from a Phase 3 Study of Response-Based Therapy for High-Risk Hodgkin Lymphoma (AHOD0831): A Report from the Children's Oncology Group

The Children's Oncology Group protocol AHOD0831, for pediatric patients with high-risk classical Hodgkin lymphoma (cHL), used response-adapted radiation fields, rather than larger involved-field radiation therapy (IFRT) that were historically used. This retrospective analysis of patterns of relapse among patients enrolled in the study was conducted to study the potential effect of a reduction in RT exposure.

62 RADIOLOGY AND NUCLEAR MEDICINE↗
DOE OSTI2022

Machine learning magnetism classifiers from atomic coordinates

The determination of magnetic structure poses a long-standing challenge in condensed matter physics and materials science. Experimental techniques such as neutron diffraction are resource-limited and require complex structure refinement protocols, while computational approaches such as first-principles density functional theory (DFT) need additional semi-empirical correction, and reliable prediction is still largely limited to collinear magnetism. Here, we present a machine learning model that aims to classify the magnetic structure by inputting atomic coordinates containing transition metal and rare earth elements. By building a Euclidean equivariant neural network that preserves the crystallographic symmetry, the magnetic structure (ferromagnetic, antiferromagnetic, and nonmagnetic) and magnetic propagation vector (zero or non-zero) can be predicted with an average accuracy of 77.8% and 73.6%. In particular, a 91% accuracy is reached when predicting no magnetic ordering even if the structure contains magneticelement(s). Ourworkrepresents onestepforwardtosolvingthegrand challenge of full magnetic structure determination.

75 CONDENSED MATTER PHYSICS, SUPERCONDUCTIVITY AND↗
DOE OSTI2026

Complex magnetic ground state driving a large rotating magnetocaloric effect in Tb 3 Ni at low temperature

The rotating magnetocaloric effect (RMCE) offers a promising alternative to conventional magnetocaloric configurations by taking advantage of magnetic anisotropy to simplify device architecture and enhance refrigeration efficiency. In this study, the RMCE in a high-quality single crystal of Tb 3 Ni is investigated, a compound previously shown to exhibit significant magnetocaloric behavior along its easy axis of magnetization. By measuring the magnetization and corresponding entropy change along the three principal crystallographic axes using a discontinuous measurement protocol, we verify the anisotropic magnetic properties and derive the RMCE from rotations between hard ( a, b ) and easy ( c ) axes of magnetization. Our results show a maximum value for the rotating entropy change of 19.5 J kg −1 K −1 for µ 0 H = 7 T around 60 K, within the critical temperature window for industrial gas liquefaction applications. Neutron diffraction and magnetic Pair-Distribution Function (mPDF) analysis reveal that the origin of this large anisotropic response lies in a partially ordered incommensurate spin-density wave phase and persistent short-range ferromagnetic (FM) correlations. These complex magnetic states enable the release of a substantial amount of magnetic entropy when the field is applied along the easy c-axis, effectively driving the large RMCE. Comparison with other RMCE materials confirms Tb 3 Ni as one of the most promising candidates in this temperature regime, offering both a large magnetic entropy change and a wide operating window.

Gas liquefaction↗
DOE OSTI2021

Biophysical analysis of the plant-specific GIPC sphingolipids reveals multiple modes of membrane regulation

The plant plasma membrane (PM) is an essential barrier between the cell and the external environment, controlling signal perception and transmission. It consists of an asymmetrical lipid bilayer made up of three different lipid classes: sphingolipids, sterols, and phospholipids. The glycosyl inositol phosphoryl ceramides (GIPCs), representing up to 40% of total sphingolipids, are assumed to be almost exclusively in the outer leaflet of the PM. However, their biological role and properties are poorly defined. In this study, we investigated the role of GIPCs in membrane organization. Because GIPCs are not commercially available, we developed a protocol to extract and isolate GIPC-enriched fractions from eudicots (cauliflower and tobacco) and monocots (leek and rice). Lipidomic analysis confirmed the presence of trihydroxylated long chain bases and 2-hydroxylated very long-chain fatty acids up to 26 carbon atoms. The glycan head groups of the GIPCs from monocots and dicots were analyzed by gas chromatograph-mass spectrometry, revealing different sugar moieties. Multiple biophysics tools, namely Langmuir monolayer, ζ-Potential, light scattering, neutron reflectivity, solid state 2H-NMR, and molecular modeling, were used to investigate the physical properties of the GIPCs, as well as their interaction with free and conjugated phytosterols. We showed that GIPCs increase the thickness and electronegativity of model membranes, interact differentially with the different phytosterols species, and regulate the gel-to-fluid phase transition during temperature variations. These results unveil the multiple roles played by GIPCs in the plant PM.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2021

Recombinant expression of computationally designed peptide-bundlemers in Escherichia coli

Computational design of fully artificial peptides is extensively researched by material scientists and engineers for the construction of novel nanostructures and biomaterials. Such design has yielded a peptide-based building block or bundlemer, a coiled coil peptide assembly that undergoes further physical-covalent interactions to form 1D, 2D and, potentially, 3D hierarchical assemblies and displays targeted and biomimetic material properties. Recombinant expression is a convenient, flexible tool to synthesize such artificial and modified peptides in large quantities while also enabling economical synthesis of isotopically labeled peptides and longer protein-like artificial peptides. This report describes the protocol for recombinant expression of a 31-amino acid, computationally designed bundlemer-forming peptide in Escherichia coli. Peptide yields of 10 mgs per liter of media were achieved which highlights complementary advantages of recombinant expression technique relative to conventional laboratory-scale synthesis, such as solid-phase peptide synthesis.

36 MATERIALS SCIENCE↗
DOE OSTI2021

Identification and quantification of distinct active sites in Hf-Beta zeolites for transfer hydrogenation catalysis

Despite the significant progress made in characterizing different framework heteroatom sites that exist in Lewis acidic zeolites with probe molecule adsorption and spectroscopy, methods to reliably quantify site counts remain indefinite and have been primarily limited to Sn and Ti Lewis acid sites. Here, methods to quantify framework Lewis acidic Hf 4+ sites in zeolite Beta (Hf-Beta) with two Lewis base titrants (pyridine, deuterated acetonitrile) were developed using infrared (IR) spectroscopy. Lewis acid site counts for Hf-Beta zeolites were validated by measuring integrated molar extinction coefficients (IMECs; ε, cm μmol –1 ) on Sn-Beta zeolites using identical Lewis base titrants to benchmark site counts with established literature procedures to quantify Lewis acid sites in Beta zeolites from IR spectra. Highlighting the importance of benchmarking active site counts against well-established experimental protocols, IMECs of CD 3 CN bound to open (ε(Sn; 2316 cm –1 ): 1.80 ± 0.25) and closed (ε(Sn; 2308 cm –1 ): 3.76 ± 0.33) Sn sites were ~1.8x larger than those previously reported while total Lewis acid site counts agreed with those measured by pyridine (ε(Sn; 1451 cm –1 ): 1.58 ± 0.16) on six different Sn-Beta zeolites. IMECs measured for IR peaks reflecting pyridine bound to Lewis acidic Hf sites (ε(Hf; 1448 cm –1 ): 1.54 ± 0.21) and CD 3 CN bound to open (ε(Hf; 2313 cm –1 ): 2.40 ± 0.22) and closed (ε(Hf; 2307 cm –1 ): 3.55 ± 0.41) Hf sites, gave similar counts for the total number of Lewis acidic sites across six Hf-Beta zeolites (Si/Hf = 100–413). Consistent with previous reports with Sn-Beta catalysts where open Sn sites are responsible for catalytic turnover, apparent first and zero-order MPVO rate constants (0.01–1 M cyclohexanone in 2-butanol; per total Hf, 373 K) correlated with the total number of open Hf sites, per total Hf, but not with the total number of closed Hf sites or total Lewis acid site counts. Measured initial MPVO rates (0.1 M cyclohexanone in 2-butanol, per open Hf, 373 K) were ~25x higher on hydrophobic Hf-Beta-F than on hydrophilic Hf-Beta-OH zeolites. Overall, the apparent first-order MPVO rate constants (2-butanol solvent, per open Hf, 373 K) were ~6x higher on Hf-Beta-F than on Hf-Beta-OH zeolites. The characterization methods reported here enable normalization of MPVO turnover rates on Sn- and Hf-Beta zeolites by their number of open sites. Finally, this enables performing quantitative rate comparisons across Lewis acid zeolites of varying active site identity, solvation, and pore topology used in liquid-phase catalysis.

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

Mean field model parameterization to recover coverage-dependent kinetics

Lateral interactions between adsorbates introduce coverage dependence into adsorption energies and activation barriers of surface reactions. Lattice-based kinetic Monte Carlo (kMC) simulations can capture these interactions quantitatively but are laborious to parameterize and solve. Mean field models are more tractable, but protocols to construct and parameterize them are unclear. Here we explore the ability of a coverage-aware mean-field model to map to a lattice-kMC model of a generic two-step reaction network, including quasi-equilibrated adsorption and rate-limiting dissociation steps. We derive expressions for mean-field and coverage-dependent adsorption energies and dissociation barriers and parameterize against lattice-kMC predictions. We show that the parameterized mean-field rates correlate with ground truth lattice-kMC results across a wide range of reaction conditions and identify regions where the mean field fails. The mean field model similarly captures kMC-derived rate-order, Arrhenius and Sabatier plots at a greatly reduced computational cost. Further, the results provide guidance for parameterizing mean-field models, benchmarked against explicit lattice-based approaches for incorporating the influence of coverage effects.

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

Metal-facilitated, sustainable nitroarene hydrogenation under ambient conditions

Hydrogenation is a critical reaction in the chemical industry, yielding a range of important compounds such as fine chemicals, pharmachemicals and agrochemicals. However, conventional hydrogenation typically requires pressurized hydrogen, high temperatures and involves noble metal catalysts. Here, we proposed a two-step hydrogenation process, utilizing water as the hydrogen source for the industrially important reduction of nitroarenes to anilines. A metal or reduced metal oxide, which can be obtained from solar thermal or electrochemical reduction, acts as the active site for nitrobenzene adsorption, H 2 O dissociation and in-situ hydrogen generation. Among the 15 metal and reduced metal oxides investigated, Zn and Sn emerged as highly efficient catalysts for the reduction of a broad range of organic nitro compounds under mild conditions, with H 2 utilization efficiency 1-2 orders of magnitude above the state-of-the-art. The presented protocol provides extra dimensions for designing and optimizing conventional hydrogenation process with an alternative pathway. The reactive hydrogen atoms generated in-situ effectively overcome the barriers associated with hydrogen gas dissolution and its subsequent dissociation on the catalyst surface, thereby greatly enhancing the overall effectiveness for the hydrogenation reaction. This research potentially establishes a sustainable, generally applicable alternative to conventional hydrogenation methods, simultaneously presenting a viable solution for renewable energy storage.

25 ENERGY STORAGE↗
DOE OSTI2024

SDYN-GANs: Adversarial learning methods for multistep generative models for general order stochastic dynamics

We introduce adversarial learning methods for data-driven generative modeling of dynamics of nth-order stochastic systems. Our approach builds on Generative Adversarial Networks (GANs) with generative model classes based on stable m-step stochastic numerical integrators. From observations of trajectory samples, we introduce methods for learning long-time predictors and stable representations of the dynamics. Our approaches use discriminators based on Maximum Mean Discrepancy (MMD), training protocols using both conditional and marginal distributions, and methods for learning dynamic responses over different time-scales. We show how our approaches can be used for modeling physical systems to learn force-laws, damping coefficients, and noise-related parameters. Our adversarial learning approaches provide methods for obtaining stable generative models for dynamic tasks including long-time prediction and developing simulations for stochastic systems.

• Artificial intelligence (AI) / machine learning ↗
DOE OSTI2024

Democratizing uncertainty quantification

Uncertainty Quantification (UQ) is vital to safety-critical model-based analyses, but the widespread adoption of sophisticated UQ methods is limited by technical complexity. In this paper, we introduce UM-Bridge (the UQ and Modeling Bridge), a high-level abstraction and software protocol that facilitates universal interoperability of UQ software with simulation codes. It breaks down the technical complexity of advanced UQ applications and enables separation of concerns between experts. UM-Bridge democratizes UQ by allowing effective interdisciplinary collaboration, accelerating the development of advanced UQ methods, and making it easy to perform UQ analyses from prototype to High Performance Computing (HPC) scale. In addition, we present a library of ready-to-run UQ benchmark problems, all easily accessible through UM-Bridge. These benchmarks support UQ methodology research, enabling reproducible performance comparisons. We demonstrate UM-Bridge with several scientific applications, harnessing HPC resources even using UQ codes not designed with HPC support.

Benchmarks↗
DOE OSTI2023

A critical review of operational strategies for the management of harmful algal blooms (HABs) in inland reservoirs

Occurrences of freshwater harmful algal blooms (HABs) are increasing on a global scale, largely in part due to increased nutrient input and changing climate patterns. While reservoir management strategies that can influence phytoplankton are known, there is no published guideline or protocol for the management of harmful algal blooms. There is a need to establish what factors are the predominant drivers of blooms, and how common reservoir management strategies specifically influence each factor. The following literature review seeks to establish the benefits and drawbacks of operational management strategies that currently exist. The main focus is altering hydrodynamic conditions (hypolimnetic withdrawals, surface flushing, pulsed inflow, artificial mixing), in order to induce environmental changes within the reservoir itself. Since excess nutrients are one of the biggest contributors to worsening bloom conditions, internal nutrient dynamics and reduction are also discussed. Additionally, we review the predominant seasonal factors (stratification, light, temperature, and wind) that affect likelihood of bloom occurrence and duration. In conclusion, the ultimate objective of this review is to increase understanding of the relationships between HAB drivers and reservoir operations in order to inform the development of data, modeling, and management strategies for the prevention and mitigation of blooms.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2020

Metamagnetism and kinetic arrest in a long-range ferromagnetically ordered multicaloric double perovskite Y 2 CoMnO 6

A systematic magnetic study of the double perovskite oxide Y 2 CoMnO 6 (YCMO) has been performed. A monoclinic P21/n phase of YCMO was synthesized using a sol-gel method. Neutron diffraction (ND) measurements evidence the onset of long-range ferromagnetic (FM) ordering at TC ~ 76 K, which persists down to 5 K. The presence of 25% antisite disorder, estimated from the ND data, leads to the appearance of short-range antiferromagnetic (AFM) interactions. The existence of thermal hysteresis due to competing interactions between FM and AFM phases is observed in the M vs. T measurements. The pinning of magnetic domain walls at the Co/Mn antiphase boundaries results in a metamagnetic-like behavior. The field dependence of thermomagnetic irreversibility and the nature of virgin curves indicate the occurrence of a kinetic arrest phenomenon, which is further verified via cooling and heating of the system in an unequal fields (CHUF) protocol. In full agreement with the ND data, a detailed analysis of critical exponents near the paramagnetic (PM)-FM phase transition also establishes YCMO as a long-range interacting mean-field system. A close examination of the temperature- and field-dependent magnetic entropy change yields an in-depth understanding of coexisting magnetically ordered and disordered phases in YCMO, leading to a comprehensive magnetic phase diagram of this multifunctional double perovskite system.

36 MATERIALS SCIENCE↗
DOE OSTI2021

Proton-detected solid-state NMR spectroscopy of spin-1/2 nuclei with large chemical shift anisotropy

Constant-time (CT) dipolar heteronuclear multiple quantum coherence (D-HMQC) has previously been demonstrated as a method for proton detection of high-resolution wideline NMR spectra of spin-1/2 nuclei with large chemical shift anisotropy (CSA). However, 1 H transverse relaxation and t 1 -noise often reduce the sensitivity of D-HMQC experiments, preventing the theoretical gains in sensitivity provided by 1 H detection from being realized. In this paper, we demonstrate a series of improved pulse sequences for 1 H detection of spin-1/2 nuclei under fast MAS, with 195 Pt SSNMR experiments on cisplatin as an example. First, a t 1 -incrementation protocol for D-HMQC dubbed Arbitrary Indirect Dwell (AID) is demonstrated. AID allows the use of arbitrary, rotor asynchronous t 1 -increments, but removes the constant time period from CT D-HMQC, resulting in improved sensitivity by reducing transverse relaxation losses. Next, we show that short high-power adiabatic pulses (SHAPs), which efficiently invert broad MAS sideband manifolds, can be effectively incorporated into 1 H detected symmetry-based resonance echo double resonance (S-REDOR) and t 1 -noise eliminated (TONE) D-HMQC experiments. The S-REDOR experiments with SHAPs provide approximately double the dipolar dephasing, as compared to experiments with rectangular inversion pulses. We lastly show that sensitivity and resolution can be further enhanced with the use of swept excitation pulses as well as adiabatic magic angle turning (aMAT).

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2022

Current limitations of solid-state NMR in carbohydrate and cell wall research

High-resolution investigation of cell wall materials has emerged as an important application of biomolecular solid-state NMR (ssNMR). Multidimensional correlation experiments have become a standard method for obtaining sufficient spectral resolution to determine the polymorphic structure of carbohydrates and address biochemical questions regarding the supramolecular organization of cell walls. Here, using plant cellulose and matrix polysaccharides as examples, we will review how the multifaceted complexity of polysaccharide structure is impeding the resonance assignment process and assess the available biochemical and spectroscopic approaches that could circumvent this barrier. We will emphasize the ineffectiveness of the current methods in reconciling the ever-growing dataset and deriving structural information. We will evaluate the protocols for achieving efficient and homogeneous hyperpolarization across the cell wall material using magic-angle spinning dynamic nuclear polarization (MAS-DNP). Critical questions regarding the line-broadening effects of cell wall molecules at cryogenic temperature and by paramagnetic biradicals will be considered. Finally, the MAS-DNP method will be placed into a broader context with other structural characterization techniques, such as cryo-electron microscopy, to advance ssNMR research in carbohydrate and cell wall biomaterials.

09 BIOMASS FUELS↗
DOE OSTI2023

Diamond rotors

The resolution of magic angle spinning (MAS) nuclear magnetic resonance (NMR) spectra remains bounded by the spinning frequency, which is limited by the material strength of MAS rotors. Since diamond is capable of withstanding 1.5–2.5x greater MAS frequencies, compared to state-of-the art zirconia, we fabricated rotors from single crystal diamond. When combined with bearings optimized for spinning with helium gas, diamond rotors could achieve the highest MAS frequencies to date. Furthermore, the excellent microwave transmission properties and thermal conductivity of diamond could improve sensitivity enhancements in dynamic nuclear polarization (DNP) experiments. The fabrication protocol we report involves novel laser micromachining and produced rotors that presently spin at ω r = 111.000 ± 0.004 kHz, with stable spinning up to 124 kHz, using N 2 gas as the driving fluid. Here, we present the first proton-detected 13 C/ 15 N MAS spectra recorded using diamond rotors, a critical step towards studying currently inaccessible ex-vivo protein samples with MAS NMR. Previously, the high aspect ratio of MAS rotors (~10:1) precluded fabrication of MAS rotors from diamond.

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

A laboratory-scale process for producing dilithium beryllium tetrafluoride (FLiBe) with dissolved uranium tetrafluoride

Flibe Energy, Incorporated (FEI)'s conceptual Lithium Fluoride Thorium Reactor (LFTR) incorporates a chemical processing facility aimed at recovering uranium and other valuable volatile radionuclides while managing harmful radionuclides from the used fuel. The fuel utilized in this reactor is a combination of dilithium beryllium tetrafluoride (Li 2 BeF 4 or FLiBe) and uranium tetrafluoride (UF 4 ), (FLiBe/U). FEI's plan involves extracting the uranium and other valuable volatile fluoride-forming radionuclides using nitrogen trifluoride (NF 3 ). To facilitate laboratory-scale testing of uranium extraction using NF 3 and address the toxicity and physical hazards associated with beryllium and beryllium fluoride (BeF 2 ), we used a two-step process to prepare the simulated fuel salt. The first step entailed thermally decomposing ammonium beryllium tetrafluoride [(NH 4 ) 2 BeF 4 ] (ABeF) through a nominal 3-step process, combined with appropriate amounts of lithium fluoride (LiF) and UF 4 , resulting in the formation of beryllium fluoride (BeF 2 ). In the second step, the mixture was repeatedly melted and frozen at the melting point of FLiBe to prepare the eutectic FLiBe with dissolved UF 4 . Although the concept appears straightforward, the production of FLiBe/U involved various challenges. These challenges included transporting the gaseous decomposition products of ABeF, hydrogen fluoride (HF) and ammonia (NH 3 ), while preventing the formation of ammonium fluoride (NH 4 F). Additionally, it was necessary to control the reaction between the higher-than-anticipated water content in the commercial ABeF with NH 3 , HF, and the condensed NH 4 F, protect UF 4 from forming an unknown black compound, select suitable structural materials to mitigate fluoride corrosion, address the risks associated with beryllium toxicity through equipment design and operational protocols, and monitor process conditions. This article provides an account of the thermal decomposition chemistry observed in the commercial ABeF, describes the FLiBe/U production apparatus, describes the experiences and process refinements developed to prepare FLiBe/U, and presents our characterizations of prepared FLiBe/U.

Ammonium beryllium fluoride thermal decomposition↗