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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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All sourcesNASA NTRSDOE OSTI
NASA NTRS1989

Multi-spacecraft testing of time-dependent interplanetary MHD models for operational forecasting of geomagnetic storms

An MHD 2-1/2D, time-dependent model is used, together with observations of six solar flares during February 3-7, 1986, to demonstrate global, large-scale, compound disturbances in the solar wind over a wide range of heliolongitudes. This scenario is one that is likely to occur many times during the cruise, possibly even encounter, phases of the Multi-Comet Mission. It is suggested that a model such as this one should be tested with multi-spacecraft data (such as the MCM and earth-based probes) with several goals in view: (1) utility of the model for operational real-time forecasting of geomagnetic storms, and (2) scientific interpretation of certain forms of cometary activities and their possible association with solar-generated activity.

Dryer, M.↗
DOE OSTI2022

Climate change increases risk of extreme rainfall following wildfire in the western United States

Post-wildfire extreme rainfall events can have destructive impacts in the western United States. Using two climate model large ensembles, we assess the future risk of extreme fire weather events being followed by extreme rainfall in this region. By mid-21st century, in a high warming scenario (RCP8.5), we report large increases in the number of extreme fire weather events followed within 1 year by at least one extreme rainfall event. By 2100, the frequency of these compound events increases by 100% in California and 700% in the Pacific Northwest in the Community Earth System Model v1 Large Ensemble. We further project that more than 90% of extreme fire weather events in California, Colorado, and the Pacific Northwest will be followed by at least three spatially colocated extreme rainfall events within five years. Our results point to a future with substantially increased post-fire hydrologic risks across much of the western United States.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2022

Magnetic excitation linking quasi-one-dimensional Chevrel-type selenide and arsenide superconductors

The quasi-one-dimensional Chevrel phases, A 2 M o6 Se 6 (A=Tl, In, K, Rb, Cs), are of interest due to their atypical electronic properties. The Tl and In analogs undergo a superconducting transition whereas the alkali metal analogs show charge gapping of another, not well understood type. Here we report the results of inelastic neutron scattering on polycrystalline In 2 Mo 6 Se 6 (T c =2.85 K) and Rb 2 Mo 6 Se 6 (nonsuperconducting) samples, which reveal a column of intensity with linear dispersion from [0 0 1/2] to [0 0 1] in both compounds. The observed temperature and |Q| independence together suggest the presence of unconventional carriers with a spin contribution to the excitation. This is contrary to the prevailing model for these materials, which is that they are nonmagnetic. The excitation has similar dispersion and S(Q,E,T) behavior as one observed in the structurally related superconducting compounds A 2 Cr 3 As 3 and A 2 Mo 3 As 3 (A=K, Rb, Cs), which has been interpreted as magnetic in origin and related to Fermi surface nesting. The connection is unexpected because the calculated Fermi surface of the arsenides differs substantially from the A 2 Mo 6 Se 6 compounds, and many consider them distinct classes of materials. This observation suggests a hidden link in the physics between both classes of superconductors, perhaps originating from their quasi-low-dimensional character.

1-dimensional systems↗
DOE OSTI2021

Prospects for Surrogate Neutron Capture Measurements with Radioactive Ion Beams and GODDESS

Neutron capture reactions are responsible for the synthesis of almost all of the elements heavier than iron through the slow s-process, that proceeds close to the line of stability, and the rapid r-process, with very neutron-rich waiting points. Uncertainties in (n,γ) rates in neutron rich nuclei, especially near closed neu- tron shells, can have significant impact [1] on the predictions of final abundances for different astrophysical scenarios for the r process. Understanding (n,γ) rates on neutron-rich fission fragments is also important for nuclear forensics and stockpile stewardship science. Ratkiewicz et al. [2 and references therein] has recently demonstrated that the (d,pγ) reaction is a valid surrogate for (n,γ), where the formation of the compound nucleus from the breakup of the deuteron has been calculated in a reaction model and the subsequent measured gamma-decay probabilities are reproduced with standard level density and strength functions in a Bayesian approach. In parallel to the surrogate validation efforts, we have demonstrated that the (d,pγ) reaction can be measured in inverse kinematics with Gammasphere ORRUBA: Dual Detectors for Experimental Structure Studies (GODDESS) [3] where the Gammasphere array of Compton-suppressed HPGe detectors is coupled to the Oak Ridge Rutgers University Barrel Array of position-sensitive silicon strip detectors. During the commissioning campaign we measured the (d,pγ) reaction with 134 Xe and 95 Mo beams, the latter to demonstrate the surrogate method in inverse kinematics. The present talk will present preliminary results from this campaign including γ-decay probabilities and prospects for surrogate (n,γ) measurements with 143 Ba fission-fragment beams.

73 NUCLEAR PHYSICS AND RADIATION PHYSICS↗
DOE OSTI2023

Integrated data-driven and experimental approaches to accelerate lead optimization targeting SARS-CoV- 2 main protease

Identification of potential therapeutic candidates can be expedited by integrating computational modeling with domain aware machine learning (ML) approaches followed by experimental validation. Generative deep learning models have been recently developed that can generate thousands of new candidates, but their physiochemical properties are typically not optimized. Using our deep learning models and a scaffold as a starting point, we generated tens of thousands of compounds for SARS-CoV-2 M pro that preserve the core scaffold. Here we utilized and implemented several computational tools such as structural alert and toxicity analysis, high throughput virtual screening, ML-based 3D quantitative structure–activity relationships, multi-parameter optimization, and graph neural networks on libraries of generated candidates to predict biological activity and binding affinity a priori. From these collective computational results, eight promising candidates were identified and tested experimentally using Native Mass Spectrometry (MS) and FRET-based functional assays. Two compounds, with quinazoline-2-thiol and acetylpiperidine core moiety showed IC 50 values in the low micromolar range: 2.95±0.0017 µM and 3.41±0.0015 µM, respectively. The molecular dynamics simulations further highlight that binding of these compounds results in allosteric modulations in the chain B and the interface domains of the M pro . The key fragments from these top hits can be used as input for closed loop lead optimization in the integrated pipeline.

60 APPLIED LIFE SCIENCES↗
DOE OSTI2022

13 C-Isotope-Assisted Assessment of Metabolic Quenching During Sample Collection from Suspension Cell Cultures

Metabolomics and fluxomics are core approaches to directly profile and interrogate cellular metabolism in response to various genetic or environmental perturbations. In order to accurately measure the abundance and isotope enrichment of intracellular metabolites, cell culture samples must be rapidly harvested and cold-quenched to preserve the in vivo metabolic state of the cells at the time of sample collection. When dealing with suspension cultures, this process is complicated by the need to separate the liquid culture media from cellular biomass prior to metabolite extraction. Here, we examine the efficacy of several commonly used metabolic quenching methods, using the model cyanobacterium Synechocystis sp. PCC 6803 as an example. Multiple 13 C-labeled compounds, including 13 C-bicarbonate, 13 C-glucose and 13 C-glutamine, were used as tracers during the sample collection and cold-quenching process to assess the extent of metabolic turnover after cells were harvested from culture flasks. We show that the combination of rapid filtration followed by 100% cold (–80°C) methanol quenching exhibits the highest quenching efficiency, while mixing cell samples with a partially frozen 30% methanol slurry (–24°C) followed by centrifugation is slightly less effective at quenching metabolism but enables less laborious sample processing. By contrast, rapidly mixing the cells with a saline ice slurry (~0°C) is less effective as indicated by high isotope-labeling rates after sample harvest, while mixing the cells with 60% cold methanol (–65°C) prior to centrifugation causes significant metabolite loss. Furthermore, this study demonstrates a rigorous, quantitative, and broadly applicable method for assessing the metabolic quenching efficacy of protocols used for sample collection in metabolomics and fluxomics studies.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2025

Prospects of Nanoscience with Nanocrystals: 2025 Edition

Abstract Nanocrystals (NCs) of various compositions have made important contributions to science and technology, with their impact recognized by the 2023 Nobel Prize in Chemistry for the discovery and synthesis of semiconductor quantum dots (QDs). Over four decades of research into NCs has led to numerous advancements in diverse fields, such as optoelectronics, catalysis, energy, medicine, and recently, quantum information and computing. The last 10 years since the predecessor perspective “Prospect of Nanoscience with Nanocrystals” was published in ACS Nano have seen NC research continuously evolve, yielding critical advances in fundamental understanding and practical applications. Mechanistic insights into NC formation have translated into precision control over NC size, shape, and composition. Emerging synthesis techniques have broadened the landscape of compounds obtainable in colloidal NC form. Sophistication in surface chemistry, jointly bolstered by theoretical models and experimental findings, has facilitated refined control over NC properties and represents a trusted gateway to enhanced NC stability and processability. The assembly of NCs into superlattices, along with two-dimensional (2D) photolithography and three-dimensional (3D) printing, has expanded their utility in creating materials with tailored properties. Applications of NCs are also flourishing, consolidating progress in fields targeted early on, such as optoelectronics and catalysis, and extending into areas ranging from quantum technology to phase-change memories. In this perspective, we review the extensive progress in research on NCs over the past decade and highlight key areas where future research may bring further breakthroughs.

Chemistry↗
DOE OSTI2026

High-pressure neutron powder diffraction study of an arsenolite deuterium inclusion compound: structure and formation kinetics

High-pressure variable-temperature neutron powder diffraction was employed to investigate the synthesis and structural properties of arsenolite (As 4 O 6 ), a cubic arsenic( III ) oxide polymorph, and its inclusion compound with deuterium. The compound forms with the stoichiometry As 4 O 6 ·2D 2 , consistent with earlier findings. At 295 K and 1.96(2) GPa, D 2 molecules occupy the 16c site (0, 0, 0) and are aligned along the <111> direction. The diffraction data suggest that the D 2 molecules at this site become rotationally disordered upon decompression to 0.78(2) GPa at 120 K, while no occupancy is observed at the 8a position (⅛, ⅛, ⅛) under any of the studied conditions. The kinetic data of the high-pressure inclusion compound synthesis at 1.56(2) and 1.96(2) GPa were analyzed using the Avrami model. The Avrami exponent, 0.135(16), remains invariant with pressure, demonstrating that the reaction topochemistry is unaffected by compression. Similarly, the reaction rates, 0.29(3) and 0.23(3) min −0.135 at 1.56(2) and 1.96(2) GPa, respectively, exhibit negligible pressure dependence and suggest a surprisingly low activation volume of 1.6 cm 3 mol −1 for the reaction. These results provide detailed insight into the structural dynamics and kinetics of deuterium inclusion in arsenolite under high pressure.

Guńka, Piotr A. [Warsaw University of Technology (↗
DOE OSTI2020

Augmenting machine learning of energy landscapes with local structural information

We present a machine learning approach for accurately predicting formation energies of binary compounds in the context of crystal structure predictions. The success of any machine learning model depends significantly on the choice of representation used to encode the relevant physical information into machine-learnable data. We test different representation schemes based on partial radial and angular distribution functions (RDF+ADF) on Al–Ni and Cd–Te structures generated using our genetic algorithm for structure prediction. We observe a remarkable improvement in predictive accuracy upon transitioning from global to atom-centered representations, resulting in a threefold decrease in prediction errors. We show that a support vector regression model using a combination of atomic radial and angular distribution functions performs best at the formation energy prediction task, providing small root mean squared errors of 3.9 meV/atom and 10.9 meV/atom for Al–Ni and Cd–Te, respectively. We test the performance of our models against common traditional descriptors and find that RDF- and ADF-based representations significantly outperform many of those in the prediction of formation energies. The high accuracy of predictions makes our machine learning models great candidates for the exploration of energy landscapes.

Honrao, Shreyas J. (ORCID:0000000166155257)↗
DOE OSTI2021

Four-decade follow-up of a plutonium-contaminated puncture wound treated with Ca-DTPA

Contaminated wounds are a common route of internal deposition of radionuclides for nuclear and radiation workers. They may result in significant doses to radiosensitive organs and tissues in an exposed individual's body. The United States Transuranium and Uranium Registries' whole-body donor (Case 0303) accidentally punctured his finger on equipment contaminated with plutonium nitrate. The wound was surgically excised and medically treated with intravenous injections of Ca-DTPA. A total of 16 g Ca-DTPA was administered in 18 treatments during the 2 months following the accident. Ninety-three urine samples were collected and analysed over 14 years following the accident. An estimated 239 Pu activity of 73.7 Bq was excreted during Ca-DTPA treatment. Post-mortem radiochemical analysis of autopsy tissues indicated that 40 years post-accident 21.6 ± 0.2 Bq of 239 Pu was retained in the skeleton, 12.2 ± 0.3 Bq in the liver, and 3.7 ± 0.1 Bq in other soft tissues; 1.35 ± 0.02 Bq of 239 Pu was measured in tissue samples from the wound site. To estimate the plutonium intake, late urine measurements, which were unaffected by chelation, and post-mortem radiochemical analysis results were evaluated using the IMBA Professional Plus software. The application of the National Council on Radiation Protection and Measurements wound model with an assumption of intake material as a predominantly strongly retained soluble plutonium compound with a small insoluble fraction adequately described the data (p = 0.46). The effective intake was estimated to be 50.2 Bq of plutonium nitrate and 1.5 Bq of the fragment. Here, the prompt medical intervention with contaminated tissue excision and subsequent Ca-DTPA decorporation therapy reduced 239 Pu activity available for uptake and long-term retention in this individual's systemic organs by a factor of 38.

239Pu↗
DOE OSTI2024

Inhibition of atomic layer deposition of TiO 2 by functionalizing silicon surface with 4-fluorophenylboronic acid

As the size of the components in electronic devices decreases, new approaches and chemical modification schemes are needed to produce nanometer-size features with bottom-up manufacturing. Organic monolayers can be used as effective resists to block the growth of materials on non-growth substrates in area-selective deposition methods. However, choosing the appropriate surface modification requires knowledge of the corresponding chemistry and also a detailed investigation of the behavior of the functionalized surface in realistic deposition schemes. This study aims to investigate the chemistry of boronic acids that can be used to prepare such non-growth areas on elemental semiconductors. 4-Fluorophenylboronic acid is used as a model to investigate the possibility to utilize the Si(100) surface functionalized with this compound as a non-growth substrate in a titanium dioxide (TiO 2 ) deposition scheme based on sequential doses of tetrakis(dimethylamido)titanium and water. Here, a combination of X-ray photoelectron spectroscopy and time-of-flight secondary ion mass spectrometry allows for a better understanding of the process. The resulting surface is shown to be an effective non-growth area to TiO 2 deposition when compared to currently used H-terminated silicon surfaces but to exhibit much higher stability in ambient conditions.

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

When does global attention help: a unified empirical study on atomistic graph learning

Graph neural networks (GNNs) are widely used as surrogates for costly experiments and first-principles simulations to study the behavior of compounds at atomistic scale, and their architectural complexity is constantly increasing to enable the modeling of complex physics. While most recent GNNs combine more traditional message passing neural networks (MPNNs) layers to model short-range interactions with more advanced graph transformers (GTs) with global attention mechanisms to model long-range interactions, it is still unclear when global attention mechanisms provide real benefits over well-tuned MPNN layers due to inconsistent implementations, features, or hyperparameter tuning. We introduce the first unified, reproducible benchmarking framework–built on HydraGNN–that enables seamless switching among four controlled model classes: MPNN, MPNN with chemistry/topology encoders, GPS-style hybrids of MPNN with global attention, and fully fused localglobal models with encoders. Using seven diverse open-source datasets for benchmarking across regression and classification tasks, we systematically isolate the contributions of message passing, global attention, and encoder-based feature augmentation. Our study shows that encoder-augmented MPNNs form a robust baseline, while fused localglobal models yield the clearest benefits for properties governed by long-range interaction effects. We further quantify the accuracycompute trade-offs of attention, reporting its overhead in memory. Together, these results establish the first controlled evaluation of global attention in atomistic graph learning and provide a reproducible testbed for future model development.

Equivariant graph neural networks↗
DOE OSTI2023

Global seamless tidal simulation using a 3D unstructured-grid model (SCHISM v5.10.0)

We present a new 3D unstructured-grid global ocean model to study both tidal and nontidal processes, with a focus on the total water elevation. Unlike existing global ocean models, the new model resolves estuaries and rivers down to ~8 m without the need for grid nesting. The model is validated with both satellite and in situ observations for elevation, temperature, and salinity. Tidal elevation solutions have a mean complex root-mean-square error (RMSE) of 4.2 cm for M2 and 5.4 cm for all five major constituents in the deep ocean. The RMSEs for the other four constituents, S2, N2, K1, and O1, are, respectively, 2.05, 0.93, 2.08, and 1.34 cm). The nontidal residual assessed by a tide gauge dataset (GESLA) has a mean RMSE of 7 cm. For the first time ever, we demonstrate the potential for seamless simulation on a single mesh from the global ocean into several estuaries along the US West Coast. The model is able to accurately capture the total elevation, even at some upstream stations. The model can therefore potentially serve as the backbone of a global tide surge and compound flooding forecasting framework.

54 ENVIRONMENTAL SCIENCES↗
NASA NTRS1981

Vertical transport and photochemistry in the terrestrial mesosphere and lower thermosphere /50-120 km/

A study is conducted of the coupled effects of kinetics, solar cycle flux variations, and vertical transport on the distribution of long-lived hydrogen-carbon-oxygen compounds in the terrestrial mesosphere and lower thermosphere, using a one-dimensional aeronomy model. The calculations account for the important chemical reactions and use rocket measurements of the solar flux at solar minimum and maximum. Photodissociation rates appropriate for the mesosphere are determined with a spherical shell atmosphere formalism. Detailed corrections for the O2 Schumann-Runge bands and the temperature dependence of the CO2 cross sections are used. An eddy diffusion profile is derived which is in agreement with the Aladdin 74 mass spectral measurements of atomic O, O2, CO2, and Ar in the lower thermosphere and observations of the O3 minimum at about 80 km.

Allen, M.↗
NASA NTRS1985

High atmospheric NO(x) levels and multiple photochemical steady states

The rate of removal of atmospheric NO(x) compounds at different NO(x) levels is estimated using a one-dimensional photochemical model. NO(x) removal by wet deposition, surface deposition, and thermochemical processes is examined. NO(x) removal rates at different surface NO mixing ratios are calculated and the data are analyzed. It is revealed that at low NO(x) levels NO(x) is photochemically converted to HNO3 by either wet or dry deposition; however, at high NO(x) levels formation of HNO3 is inhibited due to the disappearance of tropospheric ozone and OH, and the NO(x) is removed by rainout of N2O4 and N2O5, surface deposition of NO and NO2, and direct dissolution of NO and NO2 in rainwater. The effects of NO(x) mixing ratios greater than 10 to the -7th on the ozone and climate are investigated.

Kasting, J. F.↗
NASA NTRS1995

The control of purity and stoichiometry of compound semiconductors by high vapor pressure transport

In this report we summarize the results of a three year research program on high pressure vapor transport (HPVT) of compound semiconductors. Most of our work focused onto pnictides, in particular ZnGeP2, as a model system. Access to single crystals of well controlled composition of this material is desired for advancing the understanding and control of its point defect chemistry in the contest of remote, real-time sensing of trace impurities, e.g., greenhouse gases, in the atmosphere by ZnGeP2 optical parametric oscillators (OPO's).

Bachmann, Klaus J.↗
NASA NTRS1988

A molecular dynamics study of chloride binding by the cryptand SC24

The capture of chloride from water by the tetraprotonated form of the spherical macrotricyclic molecule SC24 was studied using molecular dynamics simulation methods. This model ionophore represents a broad class of molecules which remove ions from water. Two binding sites for the chloride were found, one inside and one outside the ligand. These sites are separated by a potential energy barrier of approximately 20 kcal mol-1. The major contribution to this barrier comes from dehydration of the chloride. The large, unfavorable dehydration effect is compensated for by an increase in electrostatic attraction between the oppositely charged chloride and cryptand, and by energetically favorable rearrangements of water structure. Additional assistance in crossing the barrier and completing the dehydration of the ion is provided by the shift of three positively charged hydrogen atoms of the cryptand towards the chloride. This structural rigidity is partially responsible for its selectivity.

NASA Discipline Exobiology↗
NASA NTRS1994

The origin of inner planet atmospheres

A comet-impact model for Mars uses the current atmosphere with argon as the index volatile and assumes a surface pressure of about 40 mb. The model also allows for changes in surface pressure. The model is based on analysis of gases trapped in Shergottite and Nakhlite meteorites. Tests of the model include the identification of noble gases in comets and the presence of nitrogen compounds in Jupiter identified by the Galileo probe.

Non-NASA Center↗