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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 199 records · Page 11
All sourcesNASA NTRSDOE OSTI
DOE OSTI2025

Revealing the electronic structure of the current-induced metastable state in 1T-TaS 2

Among the key features for next-generation memory devices is the need for high-contrast switching between metallic and insulating states with fast switching speed and long lifetime. However, materials exhibiting such properties are rare, and their electronic structure is often poorly understood. Here, by combining state-of-the-art devices with angle-resolved photoemission spectroscopy, we study the emergence of a metastable metallic state from the insulating ground state in the charge-density wave (CDW) material 1T-TaS 2 after applying short current pulses. Analysis of the electronic structure suggests a picture in which 1T-TaS 2 transforms from a band insulator in the commensurate CDW ground state to a correlated metal in the metastable state. Moreover, the optically induced metastable state reveals a strong similarity to the current-induced one. This work provides an extensive characterization of metastable order in 1T-TaS 2 and proves how studying electronic properties under in-operando conditions is a critical step for next-generation devices.

Huber, Maximilian [Lawrence Berkeley National Labo↗
DOE OSTI2024

Nitrogen management during decarbonization

Decarbonization is crucial to combat climate change. However, some decarbonization strategies could profoundly impact the nitrogen cycle. Here, in this Review, we explore the nitrogen requirements of five major decarbonization strategies to reveal the complex interconnections between the carbon and nitrogen cycles and identify opportunities to enhance their mutually sustainable management. Some decarbonization strategies require substantial new nitrogen production, potentially leading to increased nutrient pollution and exacerbation of eutrophication in aquatic systems. For example, the strategy of substituting 44% of fossil fuels used in marine shipping with ammonia-based fuels could reduce CO 2 emissions by up to 0.38 Gt CO 2 -eq yr -1 but would require a corresponding increase in new nitrogen synthesis of 212 Tg N yr -1 . Similarly, using biofuels to achieve 0.7 ± 0.3 Gt CO 2 -eq yr -1 mitigation would require new nitrogen inputs to croplands of 21–42 Tg N yr -1 . To avoid increasing nitrogen losses and exacerbating eutrophication, decarbonization efforts should be designed to provide carbon–nitrogen co-benefits. Reducing the use of carbon-intensive synthetic nitrogen fertilizer is one example that can simultaneously reduce both nitrogen inputs by 14 Tg N yr -1 and CO 2 emissions by 0.04 (0.03–0.06) Gt CO 2 -eq yr -1 . Future research should guide decarbonization efforts to mitigate eutrophication and enhance nitrogen use efficiency in agriculture, food and energy systems.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2022

Single thermodynamic transition at 2 K in superconducting UTe 2 single crystals

UTe 2 is a newly-discovered unconventional superconductor wherein multicomponent topological superconductivity is anticipated based on the presence of two superconducting transitions and time-reversal symmetry breaking in the superconducting state. The observation of two superconducting transitions, however, remains controversial. Here we demonstrate that UTe 2 single crystals displaying an optimal superconducting transition temperature at 2 K exhibit a single transition and remarkably high quality supported by their large residual resistance ratio and small residual heat capacity in the superconducting state. Our results shed light on the intrinsic superconducting properties of UTe 2 and bring into question whether UTe 2 is a multicomponent superconductor at ambient pressure.

75 CONDENSED MATTER PHYSICS, SUPERCONDUCTIVITY AND↗
DOE OSTI2024

Thermodynamic evidence for polaron stabilization inside the antiferromagnetic order of Eu5In2Sb6

Abstract Materials exhibiting electronic inhomogeneities at the nanometer scale have enormous potential for applications. Magnetic polarons are one such type of inhomogeneity which link the electronic, magnetic and lattice degrees of freedom in correlated matter and often give rise to colossal magnetoresistance. Here, we investigate single crystals of Eu 5 In 2 Sb 6 by thermal expansion and magnetostriction along different crystallographic directions. These data provide compelling evidence for the formation of magnetic polarons in Eu 5 In 2 Sb 6 well above the magnetic ordering temperature. More specifically, our results are consistent with anisotropic polarons with varying extent along the different crystallographic directions. A crossover revealed within the magnetically ordered phase can be associated with a surprising stabilization of ferromagnetic polarons within the global antiferromagnetic order upon decreasing temperature. These findings make Eu 5 In 2 Sb 6 a rare example of such coexisting and competing magnetic orders and, importantly, shed new light on colossal magnetoresistive behavior beyond manganites.

Dawczak-Dębicki, Hubert↗
DOE OSTI2024

A machine learning estimator trained on synthetic data for real-time earthquake ground-shaking predictions in Southern California

Abstract After large-magnitude earthquakes, a crucial task for impact assessment is to rapidly and accurately estimate the ground shaking in the affected region. To satisfy real-time constraints, intensity measures are traditionally evaluated with empirical Ground Motion Models that can drastically limit the accuracy of the estimated values. As an alternative, here we present Machine Learning strategies trained on physics-based simulations that require similar evaluation times. We trained and validated the proposed Machine Learning-based Estimator for ground shaking maps with one of the largest existing datasets (<100M simulated seismograms) from CyberShake developed by the Southern California Earthquake Center covering the Los Angeles basin. For a well-tailored synthetic database, our predictions outperform empirical Ground Motion Models provided that the events considered are compatible with the training data. Using the proposed strategy we show significant error reductions not only for synthetic, but also for five real historical earthquakes, relative to empirical Ground Motion Models.

Environmental Sciences & Ecology↗
DOE OSTI2024

Diagnosis of Alzheimer’s disease using plasma biomarkers adjusted to clinical probability

Abstract Recently approved anti-amyloid immunotherapies for Alzheimer’s disease (AD) require evidence of amyloid-β pathology from positron emission tomography (PET) or cerebrospinal fluid (CSF) before initiating treatment. Blood-based biomarkers promise to reduce the need for PET or CSF testing; however, their interpretation at the individual level and the circumstances requiring confirmatory testing are poorly understood. Individual-level interpretation of diagnostic test results requires knowledge of disease prevalence in relation to clinical presentation (clinical pretest probability). Here, in a study of 6,896 individuals evaluated from 11 cohort studies from six countries, we determined the positive and negative predictive value of five plasma biomarkers for amyloid-β pathology in cognitively impaired individuals in relation to clinical pretest probability. We observed that p-tau217 could rule in amyloid-β pathology in individuals with probable AD dementia (positive predictive value above 95%). In mild cognitive impairment, p-tau217 interpretation depended on patient age. Negative p-tau217 results could rule out amyloid-β pathology in individuals with non-AD dementia syndromes (negative predictive value between 90% and 99%). Our findings provide a framework for the individual-level interpretation of plasma biomarkers, suggesting that p-tau217 combined with clinical phenotyping can identify patients where amyloid-β pathology can be ruled in or out without the need for PET or CSF confirmatory testing.

Cell Biology↗
DOE OSTI2025

Scientific frontiers of agrivoltaic cropping systems

Agrivoltaic (AV) systems integrate agriculture with electricity conversion through photovoltaic (PV) modules. Compared with conventional ground-mounted PV systems, AV systems can reduce land-use competition and offer agronomic and economic advantages, such as more stable crop production and additional farm income. However, AV systems can decrease agricultural performance and are typically 20-90% costlier to install than conventional PV systems. Here, in this Review, we analyse the implementation of AV cropping systems to preserve agricultural activities and highlight challenges and barriers. The global electricity potential of AV systems is ~66-385 PWh annually, depending on PV technology and installation density, if deployed in the most suitable areas, without accounting for grid availability. Scaling up has been hindered by crop selection for shading conditions, decreased energy conversion per unit of land area and issues with social acceptance, landscape impact and environmental sustainability. These issues can be addressed by developments such as wavelength-selective PV; system configurations, such as optimizing module spacing to reduce shading; and operational methods, such as optimizing tracking strategies and integrating agricultural infrastructure. Cross-sector policies can support AV systems by addressing the needs of diverse stakeholders over shared land resources. Further development will require collaboration among the design, performance, deployment and systems research communities.

14 SOLAR ENERGY↗
DOE OSTI2020

Vacancies in graphene: an application of adiabatic quantum optimization

Quantum annealers have grown in complexity to the point that quantum computations involving a few thousand qubits are now possible. In this paper, with the intentions to show the feasibility of quantum annealing to tackle problems of physical relevance, we used a simple model, compatible with the capability of current quantum annealers, to study the relative stability of graphene vacancy defects. By mapping the crucial interactions that dominate carbon-vacancy interchange onto a quadratic unconstrained binary optimization problem, our approach exploits the ground state as well as the excited states found by the quantum annealer to extract all the possible arrangements of multiple defects on the graphene sheet together with their relative formation energies. Furthermore, this approach reproduces known results and provides a stepping stone towards applications of quantum annealing to problems of physical–chemical interest.

36 MATERIALS SCIENCE↗
DOE OSTI2022

A ferric guest inside a spin crossover ferrous helicate

A designed dimetallic Fe(II) helicate made with biphenylene-bridged bispyrazolylpyridine ligands and exhibiting a process of spin crossover at temperatures above ambient is shown to encapsulate an S = 5/2 tris-oxalato Fe(III) ion. The spin relaxation dynamics of this guest are strongly reduced upon encapsulation.

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

The impact of G-quadruplex dynamics on inter-tetrad electronic couplings: a hybrid computational study

The G-quadruplex is a fascinating nucleic acid motif with implications in biology, medicine, and nanotechnologies. G-quadruplexes can form in the telomeres at the edges of chromosomes and in other guanine-rich regions of the genome. They can also be engineered for exploitation as biological materials for nanodevices. Their higher stiffness and higher charge transfer rates make them better candidates in nanodevices than duplex DNA. For the development of molecular nanowires, it is important to optimize electron transport along the wire axis. One powerful basis to do so is by manipulating the structure, based on known effects that structural changes have on electron transport. Here, for this work, we investigate such effects, by a combination of classical simulations of the structure and dynamics and quantum calculations of electronic couplings. We find that this structure–function relationship is complex. A single helix shape parameter alone does not embody such complexity, but rather a combination of distances and angles between stacked bases influences charge transfer efficiency. By analyzing linear combinations of shape descriptors for different topologies, we identify the structural features that most affect charge transfer efficiency. We discuss the transferability of the proposed model and the limiting effects of inherent flexibility.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2025

Linking structural and rheological memory in disordered soft materials

Linking the macroscopic flow properties and nanoscopic structure is a fundamental challenge to understanding, predicting, and designing disordered soft materials. Under small stresses, these materials are soft solids, while larger loads can lead to yielding and the acquisition of plastic strain, which adds complexity to the task. In this work, we connect the transient structure and rheological memory of a colloidal gel under cyclic shearing across a range of amplitudes via a generalized memory function using rheo-X-ray photon correlation spectroscopy (rheo-XPCS). Our rheo-XPCS data show that the nanometer scale aggregate-level structure recorrelates whenever the change in recoverable strain over some interval is zero. The macroscopic recoverable strain is therefore a measure of the nano-scale structural memory. We further show that yielding in disordered colloidal materials is strongly heterogeneous and that memories of prior deformation can exist even after the material has been subjected to flow.

Kamani, Krutarth M. [Univ. of Illinois at Urbana-C↗
DOE OSTI2020

Planck 2018 results: III. High frequency instrument data processing and frequency maps

This paper presents the High Frequency Instrument (HFI) data processing procedures for the Planck 2018 release. Major improvements in mapmaking have been achieved since the previous Planck 2015 release, many of which were used and described already in an intermediate paper dedicated to the Planck polarized data at low multipoles. These improvements enabled the first significant measurement of the reionization optical depth parameter using Planck-HFI data. This paper presents an extensive analysis of systematic effects, including the use of end-to-end simulations to facilitate their removal and characterize the residuals. The polarized data, which presented a number of known problems in the 2015 Planck release, are very significantly improved, especially the leakage from intensity to polarization. Calibration, based on the cosmic microwave background (CMB) dipole, is now extremely accurate and in the frequency range 100-353 GHz reduces intensity-to-polarization leakage caused by calibration mismatch. The Solar dipole direction has been determined in the three lowest HFI frequency channels to within one arc minute, and its amplitude has an absolute uncertainty smaller than 0.35 μK, an accuracy of order 10 -4 . This is a major legacy from the Planck HFI for future CMB experiments. The removal of bandpass leakage has been improved for the main high-frequency foregrounds by extracting the bandpass-mismatch coefficients for each detector as part of the mapmaking process; these values in turn improve the intensity maps. This is a major change in the philosophy of "frequency maps", which are now computed from single detector data, all adjusted to the same average bandpass response for the main foregrounds. End-to-end simulations have been shown to reproduce very well the relative gain calibration of detectors, as well as drifts within a frequency induced by the residuals of the main systematic effect (analogue-to-digital convertor non-linearity residuals). Using these simulations, we have been able to measure and correct the small frequency calibration bias induced by this systematic effect at the 10 -4 level. There is no detectable sign of a residual calibration bias between the first and second acoustic peaks in the CMB channels, at the 10 -3 level.

79 ASTRONOMY AND ASTROPHYSICS↗