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At least 1,099 records · Page 61
All sourcesNASA NTRSDOE OSTI
DOE OSTI2025

High average-flux laser-driven neutron source

Laser-driven neutron generation is an attractive alternative to more established methods for compact, short-pulse-duration neutron sources with applications in medical science, material science and imaging. Despite extensive investigation of various techniques, achieving performance comparable to nuclear reactors or conventional accelerators remains challenging. In this work, we generate a stable, high-repetition-rate laser-driven neutron source reaching a record average flux of 7.8 × 10 7 n/sr/s, improving on other existing laser-based sources by more than one order of magnitude. Our approach is based on a two-step process where electrons are accelerated to relativistic energies via laser wakefield acceleration (LWFA), and subsequently generate neutrons through Bremsstrahlung emission followed by photonuclear reactions in a tungsten converter. Experimental results, supported by Monte Carlo simulations, show a neutron flux of 3.0 × 10 7 n/cm 2 /s near the target, on par with some compact accelerator-based neutron sources. Additionally, a direct comparison with the target-normal sheath acceleration (TNSA) pitcher-catcher scheme, performed on the same laser system, reveals a significantly higher total neutron yield of 3.9 × 10 8 neutrons per shot, outperforming the TNSA scheme by several orders of magnitude. These findings represent a significant advancement towards the development of practical laser-driven neutron sources and highlight the advantages of LWFA-based neutron generation for future applications.

Vallières, Simon [Institut National de la Recherch↗
DOE OSTI2025

Vegetation biogeography is a main source of uncertainty in modelling the land carbon cycle

The terrestrial biosphere exchanges a large amount of CO 2 with the atmosphere through photosynthesis and respiration, determining the magnitude of land carbon sink and consequently influencing the rate of global warming. The magnitudes of global photosynthesis and respiration, however, vary widely across models (100-200 PgC/year), constituting a key and persistent source of uncertainty in carbon cycle and climate modelling. Here, we argue that the uncertainty in the land carbon cycle modelling is largely attributable to the uncertainty in biogeography – the distribution of plant functional types (PFTs). Using an ensemble of dynamic global vegetation models (DGVMs), we find a strong dependence of total photosynthesis on total area for each PFT. The dependence allows us to reduce the spread of land carbon cycle estimates by ~75% using remote sensing-based PFT maps. We further find that 56 ± 21% of climate-driven changes in global photosynthesis modelled by DGVMs are caused by changes in PFT distribution in the last two decades. Our study identifies vegetation biogeography as a main controlling factor of uncertainty in land carbon cycle modelling and highlights the importance of biogeography-climate interactions in carbon cycle and climate studies.

Zhao, Ruiying [National Univ. of Singapore (Singap↗
DOE OSTI2026

Learning earthquake ground motions via conditional generative modeling

Predicting high-fidelity ground motions for future earthquakes is crucial for seismic hazard assessment and infrastructure resilience. Conventional empirical simulations suffer from sparse sensor distribution and geographically localized earthquake locations, while physics-based methods are computationally intensive and require accurate representations of Earth structures and earthquake sources. We propose an artificial intelligence (AI) spectrogram generator, Conditional Generative Modeling for Ground Motion (CGM-GM). CGM-GM leverages earthquake magnitudes and geographic coordinates of earthquakes and sensors as inputs, when postprocessed with phase information, capturing spatially continuous Fourier amplitude spectra (FAS) as well as properties such as P and S arrivals, and waveform durations, without explicit physics constraints. This is achieved through a probabilistic autoencoder that extracts latent distributions in the time-frequency domain and variational sequential models for prior and posterior distributions. We evaluate the performance of CGM-GM using small-magnitude earthquake records from the San Francisco Bay Area, a region with high seismic risks. Here, we report that CGM-GM demonstrates potential for complementing physics-based simulations and non-ergodic empirical ground motion models, as well as shows promise in seismology and beyond.

geophysics↗
DOE OSTI2022

Nanoscale studies of electric field effects on monolayer 1T′-WTe2

Abstract Monolayer 1 T′-WTe 2 is a quantum spin Hall insulator with a gapped 2D-bulk and gapless helical edge states persisting to temperatures ~100 K. Despite the far-ranging interest, the magnitude of the bulk gap, the effect of gating on the 2D-band structure, as well the role interactions are not established. In this work we use STM spectroscopy to measure the intrinsic bulk gap of monolayer 1 T′-WTe 2 and show that gate induced electric fields cause large changes of the gap magnitude. Our first-principles DFT-derived tight-binding model reveal that a combination of spatial localization of the conduction and valance bands and Rashba-like spin-orbit coupling leads to a gating induced spin-splitting of the 2D-bulk bands in the tens of meV, thereby reducing the band gap. Our work explains the large sensitivity of the band structure to electric fields and suggests a new avenue for realizing proximity induced non-trivial superconductivity in monolayer 1 T′-WTe 2 .

36 MATERIALS SCIENCE↗
DOE OSTI2022

A two-directional vibrational probe reveals different electric field orientations in solution and an enzyme active site

We report the catalytic power of an electric field depends on its magnitude and orientation with respect to the reactive chemical species. Understanding and designing new catalysts for electrostatic catalysis thus requires methods to measure the electric field orientation and magnitude at the molecular scale. We demonstrate that electric field orientations can be extracted using a two-directional vibrational probe by exploiting the vibrational Stark effect of both the C=O and C–D stretches of a deuterated aldehyde. Combining spectroscopy with molecular dynamics and electronic structure partitioning methods, we demonstrate that, despite distinct polarities, solvents act similarly in their preference for electrostatically stabilizing large bond dipoles at the expense of destabilizing small ones. In contrast, we find that for an active-site aldehyde inhibitor of liver alcohol dehydrogenase, the electric field orientation deviates markedly from that found in solvents, which provides direct evidence for the fundamental difference between the electrostatic environment of solvents and that of a preorganized enzyme active site.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2019

Increasing impacts of extreme droughts on vegetation productivity under climate change

Terrestrial gross primary production (GPP) is the basis of food production and vegetation growth globally1 and plays a critical role in regulating atmospheric CO2 through its impact on ecosystem carbon balance. Even though higher CO2 concentrations in future decades can increase GPP2, low soil water availability, heat stress and disturbances associated with droughts could reduce the benefits of such CO2 fertilization. Here we analysed outputs of 13 Earth system models to show an increasingly stronger impact on GPP by extreme droughts than by mild and moderate droughts over the twenty-first century. Due to a dramatic increase in the frequency of extreme droughts, the magnitude of globally averaged reductions in GPP associated with extreme droughts was projected to be nearly tripled by the last quarter of this century (2075–2099) relative to that of the historical period (1850–1999) under both high and intermediate GHG emission scenarios. By contrast, the magnitude of GPP reduction associated with mild and moderate droughts was not projected to increase substantially. Our analysis indicates a high risk of extreme droughts to the global carbon cycle with atmospheric warming; however, this risk can be potentially mitigated by positive anomalies of GPP associated with favourable environmental conditions.

Xu, Chonggang↗
DOE OSTI2021

Greater committed warming after accounting for the pattern effect

Our planet’s energy balance is sensitive to spatial inhomogeneities in sea surface temperature and sea ice changes, but this is typically ignored in climate projections. Here, we show the energy budget during recent decades can be closed by combining changes in effective radiative forcing, linear radiative damping and this pattern effect. The pattern effect is of comparable magnitude but opposite sign to Earth’s net energy imbalance in the 2000s, indicating its importance when predicting the future climate on the basis of observations. Additionally, after the pattern effect is accounted for, the best-estimate value of committed global warming at present-day forcing rises from 1.31 K (0.99–2.33 K, 5th–95th percentile) to over 2 K, and committed warming in 2100 with constant long-lived forcing increases from 1.32 K (0.94–2.03 K) to over 1.5 K, although the magnitude is sensitive to sea surface temperature dataset. Further constraints on the pattern effect are needed to reduce climate projection uncertainty.

58 GEOSCIENCES↗
DOE OSTI2023

A constraint on historic growth in global photosynthesis due to rising CO 2

Theory predicts that rising CO 2 increases global photosynthesis, a process known as CO 2 fertilization, and that this is responsible for much of the current terrestrial carbon sink. The estimated magnitude of the historic CO 2 fertilization, however, differs by an order of magnitude between long-term proxies, remote sensing-based estimates and terrestrial biosphere models. Here we constrain the likely historic effect of CO 2 on global photosynthesis by combining terrestrial biosphere models, ecological optimality theory, remote sensing approaches and an emergent constraint based on global carbon budget estimates. Our analysis suggests that CO 2 fertilization increased global annual terrestrial photosynthesis by 13.5 ± 3.5% or 15.9 ± 2.9 PgC (mean ± s.d.) between 1981 and 2020. Our results help resolve conflicting estimates of the historic sensitivity of global terrestrial photosynthesis to CO 2 and highlight the large impact anthropogenic emissions have had on ecosystems worldwide.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2024

Formation of secondary organic aerosol from wildfire emissions enhanced by long-time ageing

Wildfire smoke, consisting primarily of organic aerosols, has profound impacts on air quality, climate and human health. Wildfire organic aerosol evolves over long-time photochemical oxidation due to the formation and ageing of secondary organic aerosol, which substantially changes its magnitude and properties. However, there are large uncertainties in the long-time ageing of wildfire organic aerosol because of the distinct ageing behaviours of the complex organic emissions. Here we developed an oxidation model that simulates the ageing of wildfire organic emissions in the full volatility range on a precursor level and integrated insights from single-species ageing and wildfire emissions ageing experiments and field plume observations to constrain the long-time ageing of wildfire organic aerosol. The model captured the enhancement of organic aerosol mass (2–8 times) and oxygen-to-carbon ratio (1–4 times) in the wildfire ageing experiments. It also reconciled a long-standing discrepancy between field and laboratory observations of the magnitude of secondary organic aerosol formation. The model indicated large emissions-driven variations in precursor contributions to secondary organic aerosol, which further evolve with long-time ageing. In conclusion, the estimated global wildfire secondary organic aerosol production (139 ± 34 Tg per year) was much higher than previous studies omitting or under-constraining long-time ageing.

58 GEOSCIENCES↗
DOE OSTI2025

Direct observations of transient weakening during phase transformations in quartz and olivine

Phase transformations are widely invoked as a source of rheological weakening during subduction, continental collision, mantle convection and various other geodynamic phenomena. However, despite more than half a century of research, the likelihood and magnitude of such weakening in nature remain poorly constrained. Here we use experiments performed on a synchrotron beamline to reveal transient weakening of up to three orders of magnitude during the polymorphic quartz to coesite (SiO 2 ) and olivine to ringwoodite (Fe 2 SiO 4 ) phase transitions. Weakening becomes increasingly prominent as the transformation outpaces deformation. We suggest that this behaviour is broadly applicable among silicate minerals undergoing first-order phase transitions and examine the likelihood of weakening due to the olivine-spinel, (Mg,Fe) 2 SiO 4 , transformation during subduction. Modelling suggests that cold, wet slabs are most susceptible to transformational weakening, consistent with geophysical observations of slab stagnation in the mantle transition zone beneath the western Pacific. In conclusion, our study highlights the importance of incorporating transformational weakening into geodynamic simulations and provides a quantitative basis for doing so.

Cross, Andrew J. [Woods Hole Oceanographic Institu↗
DOE OSTI2020

Variability and origins of grain boundary electric potential detected by electron holography and atom-probe tomography

A number of grain boundary phenomena in ionic materials, in particular, anomalous (either depressed or enhanced) charge transport, have been attributed to space charge effects. Developing effective strategies to manipulate transport behaviour requires deep knowledge of the origins of the interfacial charge, as well as its variability within a polycrystalline sample with millions of unique grain boundaries. Electron holography is a powerful technique uniquely suited for studying the electric potential profile at individual grain boundaries, whereas atom-probe tomography provides access to the chemical identify of essentially every atom at individual grain boundaries. Using these two techniques, we show in this paper that the space charge potential at grain boundaries in lightly doped, high-purity ceria can vary by almost an order of magnitude. We further find that trace impurities (<25 ppm), rather than inherent thermodynamic factors, may be the ultimate source of grain boundary charge. These insights suggest chemical tunability of grain boundary transport properties. A number of grain boundary phenomena in ionic materials, such as anomalous charge transport, have been attributed to space charge effects. Space charge potential at grain boundaries in lightly doped, high-purity ceria is now shown to vary by almost an order of magnitude.

36 MATERIALS SCIENCE↗
DOE OSTI2022

Non-volatile electric-field control of inversion symmetry

Competition between ground states at phase boundaries can lead to significant changes in properties under stimuli, particularly when these ground states have different crystal symmetries. A key challenge is to stabilize and control the coexistence of symmetry-distinct phases. Using BiFeO 3 layers confined between layers of dielectric TbScO 3 as a model system, we stabilize the mixed-phase coexistence of centrosymmetric and non-centrosymmetric BiFeO 3 phases at room temperature with antipolar, insulating and polar semiconducting behaviour, respectively. Application of orthogonal in-plane electric (polar) fields results in reversible non-volatile interconversion between the two phases, hence removing and introducing centrosymmetry. Counterintuitively, we find that an electric field 'erases' polarization, resulting from the anisotropy in octahedral tilts introduced by the interweaving TbScO 3 layers. Consequently, this interconversion between centrosymmetric and non-centrosymmetric phases generates changes in the non-linear optical response of over three orders of magnitude, resistivity of over five orders of magnitude and control of microscopic polar order. Here our work establishes a platform for cross-functional devices that take advantage of changes in optical, electrical and ferroic responses, and demonstrates octahedral tilts as an important order parameter in materials interface design.

36 MATERIALS SCIENCE↗
DOE OSTI2023

Li iontronics in single-crystalline T-Nb2O5 thin films with vertical ionic transport channels

Abstract The niobium oxide polymorph T -Nb 2 O 5 has been extensively investigated in its bulk form especially for applications in fast-charging batteries and electrochemical (pseudo)capacitors. Its crystal structure, which has two-dimensional (2D) layers with very low steric hindrance, allows for fast Li-ion migration. However, since its discovery in 1941, the growth of single-crystalline thin films and its electronic applications have not yet been realized, probably due to its large orthorhombic unit cell along with the existence of many polymorphs. Here we demonstrate the epitaxial growth of single-crystalline T -Nb 2 O 5 thin films, critically with the ionic transport channels oriented perpendicular to the film’s surface. These vertical 2D channels enable fast Li-ion migration, which we show gives rise to a colossal insulator–metal transition, where the resistivity drops by 11 orders of magnitude due to the population of the initially empty Nb 4 d 0 states by electrons. Moreover, we reveal multiple unexplored phase transitions with distinct crystal and electronic structures over a wide range of Li-ion concentrations by comprehensive in situ experiments and theoretical calculations, which allow for the reversible and repeatable manipulation of these phases and their distinct electronic properties. This work paves the way for the exploration of novel thin films with ionic channels and their potential applications.

Chemistry↗
DOE OSTI2024

Anomalous localization in a kicked quasicrystal

Abstract Quantum transport can distinguish between dynamical phases of matter. For instance, ballistic propagation characterizes the absence of disorder, whereas in many-body localized phases, particles do not propagate for exponentially long times. Additional possibilities include states of matter exhibiting anomalous transport in which particles propagate with a non-trivial exponent. Here we report the experimental observation of anomalous transport across a broad range of the phase diagram of a kicked quasicrystal. The Hamiltonian of our system has been predicted to exhibit a rich phase diagram, including not only fully localized and fully delocalized phases but also an extended region comprising a nested pattern of localized, delocalized and multifractal states, which gives rise to anomalous transport. Our cold-atom realization is enabled by new Floquet engineering techniques, which expand the accessible phase diagram by five orders of magnitude. Mapping transport properties throughout the phase diagram, we observe disorder-driven re-entrant delocalization and sub-ballistic transport, and we present a theoretical explanation of these phenomena based on eigenstate multifractality.

Physics↗
DOE OSTI2022

Instantaneous tracking of earthquake growth with elastogravity signals

Rapid and reliable estimation of large earthquake magnitude (above 8) is key to mitigating the risks associated with strong shaking and tsunamis. Standard early warning systems based on seismic waves fail to rapidly estimate the size of such large earthquakes. Geodesy-based approaches provide better estimations, but are also subject to large uncertainties and latency associated with the slowness of seismic waves. Recently discovered speed-of-light prompt elastogravity signals (PEGS) have raised hopes that these limitations may be overcome, but have not been tested for operational early warning. Here we show that PEGS can be used in real time to track earthquake growth instantaneously after the event reaches a certain magnitude. We develop a deep learning model that leverages the information carried by PEGS recorded by regional broadband seismometers in Japan before the arrival of seismic waves. After training on a database of synthetic waveforms augmented with empirical noise, we show that the algorithm can instantaneously track an earthquake source time function on real data. Our model unlocks ‘true real-time’ access to the rupture evolution of large earthquakes using a portion of seismograms that is routinely treated as noise, and can be immediately transformative for tsunami early warning.

58 GEOSCIENCES↗
DOE OSTI2023

Pattern of global spin alignment of ϕ and K*0 mesons in heavy-ion collisions

The strong force, as one of the four fundamental forces at work in the universe, governs interactions of quarks and gluons, and binds together the atomic nucleus. Notwithstanding decades of progress since Yukawa first developed a description of the force between nucleons in terms of meson exchange 1 , a full understanding of the strong interaction remains a major challenge in modern science. One remaining difficulty arises from the non-perturbative nature of the strong force, which leads to the phenomenon of quark confinement at distance scales on the order of the size of the proton. Here we show that in relativistic heavy-ion collisions, where quarks and gluons are set free over an extended volume, two species of produced vector (spin-1) mesons, namely φ and K∗0 , emerge with a surprising pattern of global spin alignment. In particular, the global spin alignment for φ is unexpectedly large, while that for K∗0 is consistent with zero. The observed spin-alignment pattern and magnitude for the φ cannot be explained by conventional mechanisms, while a model with strong force fields2, 3 accommodates the current data. This is the first time that the strong force field is experimentally supported as a key mechanism that leads to global spin alignment. We extract a quantity proportional to the intensity of the field of the strong force. Within the framework of the Standard Model, where the strong force is typically described in the quark and gluon language of Quantum Chromodynamics, the field being considered here is an effective proxy description. This is a qualitatively new class of measurement, which opens a new avenue for studying the behaviour of strong force fields via their imprint on spin alignment.

Abdallah, M. S.↗
DOE OSTI2024

Environmental drivers of increased ecosystem respiration in a warming tundra

Abstract Arctic and alpine tundra ecosystems are large reservoirs of organic carbon 1,2 . Climate warming may stimulate ecosystem respiration and release carbon into the atmosphere 3,4 . The magnitude and persistency of this stimulation and the environmental mechanisms that drive its variation remain uncertain 5–7 . This hampers the accuracy of global land carbon–climate feedback projections 7,8 . Here we synthesize 136 datasets from 56 open-top chamber in situ warming experiments located at 28 arctic and alpine tundra sites which have been running for less than 1 year up to 25 years. We show that a mean rise of 1.4 °C [confidence interval (CI) 0.9–2.0 °C] in air and 0.4 °C [CI 0.2–0.7 °C] in soil temperature results in an increase in growing season ecosystem respiration by 30% [CI 22–38%] (n = 136). Our findings indicate that the stimulation of ecosystem respiration was due to increases in both plant-related and microbial respiration (n = 9) and continued for at least 25 years (n = 136). The magnitude of the warming effects on respiration was driven by variation in warming-induced changes in local soil conditions, that is, changes in total nitrogen concentration and pH and by context-dependent spatial variation in these conditions, in particular total nitrogen concentration and the carbon:nitrogen ratio. Tundra sites with stronger nitrogen limitations and sites in which warming had stimulated plant and microbial nutrient turnover seemed particularly sensitive in their respiration response to warming. The results highlight the importance of local soil conditions and warming-induced changes therein for future climatic impacts on respiration.

Science & Technology - Other Topics↗
DOE OSTI2021

Regularized machine learning on molecular graph model explains systematic error in DFT enthalpies

Abstract A major goal of materials research is the discovery of novel and efficient heterogeneous catalysts for various chemical processes. In such studies, the candidate catalyst material is modeled using tens to thousands of chemical species and elementary reactions. Density Functional Theory (DFT) is widely used to calculate the thermochemistry of these species which might be surface species or gas-phase molecules. The use of an approximate exchange correlation functional in the DFT framework introduces an important source of error in such models. This is especially true in the calculation of gas phase molecules whose thermochemistry is calculated using the same planewave basis set as the rest of the surface mechanism. Unfortunately, the nature and magnitude of these errors is unknown for most practical molecules. Here, we investigate the error in the enthalpy of formation for 1676 gaseous species using two different DFT levels of theory and the ‘ground truth values’ obtained from the NIST database. We featurize molecules using graph theory. We use a regularized algorithm to discover a sparse model of the error and identify important molecular fragments that drive this error. The model is robust to rigorous statistical tests and is used to correct DFT thermochemistry, achieving more than an order of magnitude improvement.

36 MATERIALS SCIENCE↗