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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

Solar Energetic Proton Access to the Inner Magnetosphere During the September 7–8, 2017 Event

Here, the access of solar energetic protons into the inner magnetosphere on September 7–8, 2017 is investigated by following reversed proton trajectories to compute the proton cutoff energy using the Dartmouth geomagnetic cutoff code (Kress et al., 2010, https://doi.org/10.1029/2009sw000488). The cutoff energies for protons coming from the west and east direction, the minimum and maximum cutoff energy respectively, are calculated every 5 min along the orbit of Van Allen Probes using TS07 and the Lyon-Fedder-Mobarry (LFM) MHD magnetic field model. The result shows that the cutoff energy increases significantly as the radial distance decreases, and that the cutoff energy decreases with the building up of the ring current during magnetic storms. Solar wind dynamic pressure also affects cutoff suppression (Kress et al., 2004, https://doi.org/10.1029/2003gl018599). The LFM-RCM model shows stronger suppression of cutoff energy than TS07 during strong solar wind driving conditions. The simulation result is compared with proton flux measurements, showing consistent variation of the cutoff location during the September 7–8, 2017 geomagnetic storm.

79 ASTRONOMY AND ASTROPHYSICS↗
DOE OSTI2025

Nature of quantum criticality in the Ising ferromagnet TbV 6 Sn 6

TbV 6 Sn 6 is a topological metal where ferromagnetic Tb ions with strong uniaxial magnetic anisotropy interact with V kagome layers. Inelastic neutron scattering (INS) measurements show that the Tb ions adopt an Ising doublet ground state. Here, we consider whether a transverse magnetic field can drive TbV 6 Sn 6 toward a quantum critical point, providing a rare example of transverse-field Ising criticality in a metallic compound. High-field magnetization measurements reveal a first-order-like spin-reorientation transition at 25.6 T. Our INS-based magnetic model finds that this is caused by an avoided crossing of an excited-state singlet with the ground-state doublet. Surprisingly, our model predicts that quantum critical and tricritical points are accessible within the range of experimentally determined model parameters and may be reached by varying the direction of an applied magnetic field.

36 MATERIALS SCIENCE↗
DOE OSTI2021

bnl/pub-Maffettone_2020_08

The application of the XCA package as first demonstrated in aXiv:2008.00283. ABSTRACT: The discovery of new structural and functional materials is driven by phase identification, often using X-ray diffraction (XRD). Automation has accelerated the rate of XRD measurements, greatly outpacing XRD analysis techniques that remain manual, time consuming, error prone, and impossible to scale. With the advent of autonomous robotic scientists or self-driving labs, contemporary techniques prohibit the integration of XRD. Here, we describe a computer program for the autonomous characterization of XRD data, driven by artificial intelligence (AI), for the discovery of new materials. Starting from structural databases, we train an ensemble model using a physically accurate synthetic dataset, which output probabilistic classifications --- rather than absolutes --- to overcome the overconfidence in traditional neural networks. This AI agent behaves as a companion to the researcher, improving accuracy and offering unprecedented time savings, and is demonstrated on a diverse set of organic and inorganic materials challenges. This innovation is directly applicable to inverse design approaches, robotic discovery systems, and can be immediately considered for other forms of characterization such as spectroscopy and the pair distribution function.

Maffettone, PhillipM [Brookhaven National Lab. (BN↗
DOE OSTI2022

Proteomic and phosphoproteomic measurements enhance ability to predict ex vivo drug response in AML

Acute Myeloid Leukemia (AML) affects 20,000 patients in the US annually with a five-year survival rate of approximately 25%. One reason for the low survival rate is the high prevalence of clonal evolution that gives rise to heterogeneous sub-populations of leukemic cells with diverse mutation spectra, which eventually leads to disease relapse. This genetic heterogeneity drives the activation of complex signaling pathways that is reflected at the protein level. This diversity makes it difficult to treat AML with targeted therapy, requiring custom patient treatment protocols tailored to each individual’s leukemia. Toward this end, the Beat AML research program prospectively collected genomic and transcriptomic data from over 1000 AML patients and carried out ex vivo drug sensitivity assays to identify genomic signatures that could predict patient-specific drug responses. However, there are inherent weaknesses in using only genetic and transcriptomic measurements as surrogates of drug response, particularly the absence of direct information about phosphorylation-mediated signal transduction. As a member of the Clinical Proteomic Tumor Analysis Consortium, we have extended the molecular characterization of this cohort by collecting proteomic and phosphoproteomic measurements from a subset of these patient samples (38 in total) to evaluate the hypothesis that proteomic signatures can improve the ability to predict response to 26 drugs in AML ex vivo samples. In this work we describe our systematic, multi-omic approach to evaluate proteomic signatures of drug response and compare protein levels to other markers of drug response such as mutational patterns. We explore the nuances of this approach using two drugs that target key pathways activated in AML: quizartinib (FLT3) and trametinib (Ras/MEK), and show how patient-derived signatures can be interpreted biologically and validated in cell lines. In conclusion, this pilot study demonstrates strong promise for proteomics-based patient stratification to assess drug sensitivity in AML.

60 APPLIED LIFE SCIENCES↗
DOE OSTI2025

Extreme Heating of Minor Ions in Imbalanced Solar-wind Turbulence

Minor ions in the solar corona are heated to extreme temperatures, far in excess of those of the electrons and protons that comprise the bulk of the plasma. These highly nonthermal distributions make minor ions sensitive probes of the collisionless processes that heat the corona and power the solar wind. The recent discovery of the "helicity barrier" offers a mechanism in which imbalanced Alfvénic turbulence in low-β plasmas preferentially heats protons over electrons, generating high-frequency, proton-cyclotron-resonant fluctuations. We use the hybrid-kinetic particle-in-cell code Pegasus++ to drive imbalanced Alfvénic turbulence in a 3D low-β plasma with additional passive ion species, He 2+ and O 5+ . A helicity barrier naturally develops, followed by clear phase-space signatures of oblique proton-cyclotron-wave heating and Landau-resonant heating from the imbalanced Alfvénic fluctuations. The former results in characteristically arced ion velocity distribution functions, whose non-bi-Maxwellian features are shown by linear ALPS calculations to be critical to the heating process. Additional features include a steep transition-range electromagnetic spectrum, proton-cyclotron waves propagating in the direction of the imbalance, significantly enhanced proton-to-electron heating ratios, ion temperatures that are considerably more perpendicular with respect to magnetic field, and extreme heating of heavier species in a manner consistent with mass scalings inferred from spacecraft measurements. None of these features are realized in an otherwise equivalent simulation of balanced turbulence. If seen simultaneously in the fast solar wind, these signatures of the helicity barrier would testify to the necessity of incorporating turbulence imbalance in a complete theory for the evolution of the solar wind.

79 ASTRONOMY AND ASTROPHYSICS↗
DOE OSTI2020

Energy and environmental aspects in recycling lithium-ion batteries: Concept of Battery Identity Global Passport

The emergence and dominance of lithium-ion batteries in expanding markets such as consumer electronics, electric vehicles, and renewable energy storage are driving enormous interests and investments in the battery sector. The explosively growing demand is generating a huge number of spent lithium-ion batteries, thereby urging the development of cost-effective and environmentally sustainable recycling technologies to manage end-of-life batteries. Currently, the recycling of end-of-life batteries is still in its infancy, with many fundamental and technological hurdles to overcome. Here in this paper, the authors provide an overview of the current state of battery recycling by outlining and evaluating the incentives, key issues, and recycling strategies. The authors highlight a direct recycling strategy through discussion of its benefits, processes, and challenges. Perspectives on the future energy and environmental science of this important field is also discussed with respect to a new concept introduced as the Battery Identity Global Passport (BIGP).

25 ENERGY STORAGE↗
DOE OSTI2025

Photolytic activation of Ni (II) X 2 L explains how Ni-mediated cross coupling begins

Nickel photocatalysis has recently become vital to organic synthesis, but how the Ni (II) X 2 L pre-catalyst (X = Cl, Br; L = bidentate ligand) becomes activated to Ni (I) XL has remained puzzling and is typically addressed on a case-by-case basis. Here, we reveal a general mechanism where light induces photolysis of the Ni (II) -X bond, either via direct excitation or triplet energy transfer. Photolysis produces Ni (I) XL and a halogen radical, X*. Subsequent hydrogen atom abstraction, often from the solvent, produces a C(sp 3 ) radical, R*, that recombines with Ni (I) to form organonickel(II) complexes, Ni (II) XRL. Rather than acting as a loss pathway, Ni (II) XRL behaves as a light-activated reservoir of Ni (I) via photolysis of the Ni (II) -C bond. These results explain the role of the solvent in protecting the catalyst from off-cycle dimerization, demonstrate that two photons are often required to drive the reaction, and show how tuning the ligand can control the concentration of active Ni (I) species.

08 HYDROGEN↗
DOE OSTI2021

Crystallography companion agent for high-throughput materials discovery

The discovery of new structural and functional materials is driven by phase identification, often using X-ray diffraction (XRD). Automation has accelerated the rate of XRD measurements, greatly outpacing XRD analysis techniques that remain manual, time-consuming, error-prone and impossible to scale. With the advent of autonomous robotic scientists or self-driving laboratories, contemporary techniques prohibit the integration of XRD. Here, we describe a computer program for the autonomous characterization of XRD data, driven by artificial intelligence (AI), for the discovery of new materials. Starting from structural databases, we train an ensemble model using a physically accurate synthetic dataset, which outputs probabilistic classifications—rather than absolutes—to overcome the overconfidence in traditional neural networks. This AI agent behaves as a companion to the researcher, improving accuracy and offering substantial time savings. It is demonstrated on a diverse set of organic and inorganic materials characterization challenges. This method is directly applicable to inverse design approaches and robotic discovery systems, and can be immediately considered for other forms of characterization such as spectroscopy and the pair distribution function.

36 MATERIALS SCIENCE↗
DOE OSTI2022

Relative permeability as a stationary process: Energy fluctuations in immiscible displacement

Relative permeability is commonly used to model immiscible fluid flow through porous materials. In this work, we derive the relative permeability relationship from conservation of energy, assuming that the system to be non-ergodic at large length scales and relying on averaging in both space and time to homogenize the behavior. Explicit criteria are obtained to define stationary conditions: (1) there can be no net change for extensive measures of the system state over the time averaging interval; (2) the net energy inputs into the system are zero, meaning that the net rate of work done on the system must balance with the heat removed; and (3) there is no net work performed due to the contribution of internal energy fluctuations. Results are then evaluated based on direct numerical simulation. Dynamic connectivity is observed during steady-state flow, which is quantitatively assessed based the Euler characteristic. We show that even during steady-state flow at low capillary number ([Formula: see text]), typical flow processes will explore multiple connectivity states. The residence time for each connectivity state is captured based on the time-and-space average. The distribution for energy fluctuations is shown to be multi-modal and non-Gaussian when terms are considered independently. However, we demonstrate that their sum is zero. Given an appropriate choice of the thermodynamic driving force, we show that the conventional relative permeability relationship is sufficient to model the energy dissipation in systems with complex pore-scale dynamics that routinely alter the structure of fluid connected pathways.

71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗
DOE OSTI2020

Dendrite Growth Morphology Modeling in Liquid and Solid Electrolytes

The main goal of this project is to develop a multi-scale modeling approach that connects micron-scale phase-field models and atomic-scale density functional theory (DFT)-based simulations via parameter- and relationship-passing in order to predict Li-metal dendrite morphology evolution, in both liquid and solid electrolytes. The key hypothesis of the DFT-informed phase-field multiscale modeling approach is that it can capture the electrochemical-mechanical driving forces and incorporate the roles of nano-meter-thin solid electrolyte interphase (SEI) in liquid electrolytes as well as of the microstructures of micro-meter-thick solid electrolytes (SEs) for all-solid-state batteries. In this project, we have formulated and implemented phase-field models to incorporate the electrochemical driving forces in liquid electrolytes and then incorporate mechanical driving forces to simulate dendrite growth in solid electrolytes with resolved microstructures. We have implemented two treatments for the SEI: an explicit model to include the microstructure of the SE or SEI in the phase field model and an implicit model to simulate the impact of nano-meter thick SEI in liquid electrolytes by varying the electrode/electrolyte interfacial properties. The key interfacial properties, including the electronic and ionic transport properties, the charge transfer reaction kinetics, and mechanical properties, were computed by DFT-based calculations. At the DFT-based model, one key advancement is to directly predict the charge transfer reaction kinetics at a complex Li/SEI/electrolyte interface by linking DFT with density functional tight binding (DFTB) calculations. As the main accomplishments, we have demonstrated two successful predictions in both solid electrolyte and liquid electrolyte based on this multiscale approach. The predicted intergranular Li dendrite growth in LLZO revealed the importance of trapped electrons at internal interfaces in the microstructure of LLZO. The predicted electroplating morphology of mossy Li and faceted Mg agreed well with experiments. The insights provided by the multiscale model and the model enabled electrolyte and SEI design will accelerate the development of Li-metal electrode for high energy density batteries, that meet DOE’s target on cell density (>350 Wh/kg) and cost below $100/kWhuse for EV applications.

25 ENERGY STORAGE↗
DOE OSTI2025

Harnessing Ultra-Intense Long-Wave Infrared Lasers: New Frontiers in Fundamental and Applied Research

This review explores two main topics: the state-of-the-art and emerging capabilities of high-peak-power, ultrafast (picosecond and femtosecond) long-wave infrared (LWIR) laser technology based on CO2 gas laser amplifiers, and the current and advanced scientific applications of this laser class. The discussion is grounded in expertise gained at the Accelerator Test Facility (ATF) of Brookhaven National Laboratory (BNL), a leading center for ultrafast, high-power CO2 laser development and a National User Facility with a strong track record in high-intensity physics experiments. We begin by reviewing the status of 9–10 μm CO2 laser technology and its applications, before exploring potential breakthroughs, including the realization of 100 terawatt femtosecond pulses. These advancements will drive ongoing research in electron and ion acceleration in plasma, along with applications in secondary radiation sources and atmospheric energy transport. Throughout the review, we highlight how wavelength scaling of physical effects enhances the capabilities of ultra-intense lasers in the LWIR spectrum, expanding the frontiers of both fundamental and applied science.

43 PARTICLE ACCELERATORS↗
DOE OSTI2024

The crucial role of diagnostics in achieving ignition on the National Ignition Facility (NIF)

Well over 100 diagnostics can operate on the National Ignition Facility (NIF) as a result of several decades of development on NIF, and before that on Nova, OMEGA, and earlier LLNL lasers. A subset of these have guided the approach to achieving ignition on the NIF in 2022 [H. Abu-Shawareb et al. (Indirect Drive ICF Collaboration), Phys. Rev. Lett. 129(7), 075001 (2022)]. Achieving ignition on NIF has required many types of experiments with this core set of diagnostics, some constraining known unknowns and some revealing surprises—arguably unknown unknowns. Early design work realized that the extreme precision required for ignition on NIF would require fine-tuning by experiment, that is, measuring and adjusting known unknowns. Many examples are given where the use of the core set of ignition diagnostics in experimental arrangements called platforms demonstrated control of the key theoretical parameters defined as shape, adiabat, velocity, and mix. The direction of the adjustments to input conditions is found either by trend analysis or, in many cases, by observing from the diagnostic data the direction to make an adjustment. In addition, diagnostics have revealed some unexpected or neglected known issues, which degrade performance, or unexpected issues, unknown unknowns. Some of these factors had been previously considered, but underestimated or difficult to calculate at the time. The overall methodology can be described as a variant of Popper's falsifiability philosophy [K. Popper, The Logic of Scientific Discovery (Hutchinson, 1974)]. This paper summarizes the role of ignition diagnostics in terms of falsification or validation of theory or experimental setup as well as uncovering unexpected issues. The journey to ignition started in the seventies with a 1-µm wavelength laser producing disastrous results. Diagnostics have guided us to the recent multi-decadal goal of demonstrating ignition and burn in the laboratory.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗
DOE OSTI2023

Data for Glucose Assimilation Rate Determines the Partition of Flux at Pyruvate Between Lactic Acid and Ethanol in Saccharomyces cerevisiae

Engineered Saccharomyces cerevisiae expressing a lactic acid dehydrogenase can metabolize pyruvate into lactic acid. However, three pyruvate decarboxylase (PDC) isozymes drive most carbon flux toward ethanol rather than lactic acid. Deletion of endogenous PDCs will eliminate ethanol production, but the resulting strain suffers from C2 auxotrophy and struggles to complete a fermentation. Engineered yeast assimilating xylose or cellobiose produce lactic acid rather than ethanol as a major product without the deletion of any PDC genes. We report here that sugar flux, but not sensing, contributes to the partition of flux at the pyruvate branch point in S. cerevisiae expressing the Rhizopus oryzae lactic acid dehydrogenase (LdhA). While the membrane glucose sensors Snf3 and Rgt2 did not play any direct role in the option of predominant product, the sugar assimilation rate was strongly correlated to the partition of flux at pyruvate: fast sugar assimilation favors ethanol production while slow sugar assimilation favors lactic acid. Applying this knowledge, we created an engineered yeast capable of simultaneously converting glucose and xylose into lactic acid, increasing lactic acid production to approximately 17 g L−1 from the 12 g L−1 observed during sequential consumption of sugars. This work elucidates the carbon source-dependent effects on product selection in engineered yeast.

Conversion↗
DOE OSTI2022

Low-GWP Refrigerants Status and Outlook

Refrigeration - including air conditioning (AC) – contributes substantially to the modern life of the 21st century and its economy. The food cold chain, air conditioning, healthcare and energy are examples of sectors for which refrigeration is indispensable. About 5 billion refrigeration systems – of different types and sizes– operate worldwide in different applications [1]. The dominant share of equipment providing refrigeration operate on the vapor-compression-cycle principle and use fluorocarbon refrigerants. Concerns about the environmental safety have become the driving force for refrigerant changes within the last 35 years. The phased-out schedule of stratospheric-ozone-depleting fluids was first formulated by the Montreal Protocol (MP) in 1987 and was made more stringent during the follow-up international meetings [2]. The affected chlorofluorocarbon (CFC) and hydrochlorofluorocarbon (HCFC) refrigerants were largely replaced by hydrofluorocarbons (HFCs).The 2016 Kigali Amendment to the MP [3] responses to the concerns about the Earth climate change. The refrigeration and AC sectors are attributed with about 7.8 % of global greenhouse gas emissions [4]. This contribution comes in the form of direct effect, which is related to refrigerant emissions from refrigeration systems (37 %), and in the form of indirect effect, which is related to CO2 emissions from fossil fuel power plants producing electricity to power refrigeration systems (63 %) [4]. The Kigali Amendment aims at reducing the direct effect. The effect a given molecule has on the climate change is quantified in a simplified manner by its Global Warming Potential (GWP), a relative index referencing the effect produced to that of the same mass of carbon dioxide released to the atmosphere. By definition, GWP of carbon dioxide is equal to one.While HFC refrigerants have on average a lower GWP than the CFCs and HCFCs they replaced, they are still potent greenhouse gases (GHGs). The Kigali Amendment phases down the use of HFCs by imposing a schedule for reducing a weighted GWP value to be implemented by a country through the year 2047 (Figure 1). It provides four paths depending on the country location and category assigned in the MP, and also prescribes a method for establishing the baseline consumption used for calculating GWP reductions. For developing countries, it is expected to bring the weighed GWP across all refrigeration applications down to about 300 from the baseline value of about 2000. The implementation of Kigali Amendment aims at reducing the future warming due to HFCs from the range of 0.3 °C to 0.5 °C to less than 0.1 °C [5]. While this reduction may seem to be small, it must be viewed in the context of the 2015 Paris Agreement [6], which calls for holding global warming to well below 2 °C and pursuing to limit global warming to 1.5 °C relative to pre-industrial levels [6]. Considering that average global temperatures reached 1 °C above pre-industrial levels for the first time in 2015 [7], the Earth is already within 1 °C of the “2 °C limit”.The low-GWP requirement narrows the pool of fluids that can be considered for application as a refrigerant [8]. This Informatory Note discusses low-GWP refrigerant options for major applications and presents their selection merits.

Yana Motta, Samuel↗
DOE OSTI2026

Large language models for transportation research: Methodologies, state of the art, and future opportunities

The rapid rise of large language models (LLMs) is transforming transportation research, with significant advancements emerging between 2023 and 2025, a period marked by the inception and swift growth of adopting and adapting LLMs for various transportation applications. Despite these significant advancements, however, a systematic review and synthesis of the existing literature remains lacking. This paper aims to fill this gap by providing a comprehensive review of the methodologies and applications of LLMs in transportation. We explore key applications, including autonomous driving, travel behavior prediction, and general transportation-related queries, alongside LLM methodologies such as zero- or few-shot learning, prompt engineering, and fine-tuning. From the review, critical research gaps are identified. From the methodological perspective, many of the research limitations can be addressed by integrating LLMs with existing tools and refining LLM architectures. From the application perspective, research opportunities for LLMs to address various transportation challenges are also explored. By synthesizing these findings, this review not only presents the state-of-the-art LLM adoption and adaptation in transportation, but also proposes future research directions as well as insights and recommendations for policymakers and practitioners, paving the way for greater LLM-driven research innovations in transportation in the future.

42 ENGINEERING↗
DOE OSTI2021

Layer Hall effect in a 2D topological axion antiferromagnet

While ferromagnets have been known and exploited for millennia, antiferromagnets (AFMs) were only discovered in the 1930s. The elusive nature indicates AFMs' unique properties: At large scale, due to the absence of global magnetization, AFMs may appear to behave like any non-magnetic material; However, such a seemingly mundane macroscopic magnetic property is highly nontrivial at microscopic level, where opposite spin alignment within the AFM unit cell forms a rich internal structure. In topological AFMs, such an internal structure leads to a new possibility, where topology and Berry phase can acquire distinct spatial textures. Here, we study this exciting possibility in an AFM Axion insulator, even-layered MnBi 2 Te 4 flakes, where spatial degrees of freedom correspond to different layers. Remarkably, we report the observation of a new type of Hall effect, the layer Hall effect, where electrons from the top and bottom layers spontaneously deflect in opposite directions. Specifically, under no net electric field, even-layered MnBi 2 Te 4 shows no anomalous Hall effect (AHE); However, applying an electric field isolates the response from one layer and leads to the surprising emergence of a large layer-polarized AHE (~50e 2 /h). Such a layer Hall effect uncovers a highly rare layer-locked Berry curvature, which serves as a unique character of the space-time PT-symmetric AFM topological insulator state. Moreover, we found that the layer-locked Berry curvature can be manipulated by the Axion field, E∙B, which drives the system between the opposite AFM states. Our results achieve previously unavailable pathways to detect and manipulate the rich internal spatial structure of fully-compensated topological AFMs. The layer-locked Berry curvature represents a first step towards spatial engineering of Berry phase, such as through layer-specific moiré potential.

36 MATERIALS SCIENCE↗
DOE OSTI2024

Control of a twisted domain wall motion supported by topology

We report the topology-mediated modulation of a twisted domain wall speed in a thick perpendicularly magnetized system. By exploiting the topological robustness of the direction of the Bloch wall component in the twisted domain wall, we show that the domain wall speed either increases or decreases depending on whether the transverse magnetic field is parallel or antiparallel to the Bloch wall component. The decrease in the speed is maintained until the antiparallel transverse reaches ~0.3 T, indicating that the twisted domain wall can offer wide controllability supported by the topological robustness which involves an injection of a Bloch point. We also demonstrate that the transverse magnetic field suppresses the Walker breakdown, allowing high mobility domain wall motion for a wide range of perpendicular driving fields.

71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗