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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 739 records · Page 41
All sourcesNASA NTRSDOE OSTI
DOE OSTI2026

Soil Moisture Buffers the Impact of Precipitation Variability on Ecosystem Productivity

Water availability governs ecosystem productivity, yet estimates of vegetation sensitivity to water can differ greatly depending on whether the sensitivity is examined spatially or temporally. In particular, the spatial sensitivity is often reported to be much stronger than temporal sensitivities, leading to highly uncertain projections of ecosystem responses to future climate change when using space-for-time substitution. The large difference between spatial and temporal sensitivities remains unexplained. Prior research, however, primarily relied on precipitation as the water availability proxy, whereas vegetation responds to soil moisture. Here, we combined satellite estimates of vegetation productivity with soil moisture data across water-limited ecosystems of the continental United States (CONUS) to identify a convergent sensitivity of productivity to water availability. Using precipitation, we show that temporal sensitivity is 66% lower than spatial sensitivity overall. Our analysis identified the cause of the difference to be primarily driven by the seasonal variability of water availability, rooting depth, and soil properties. When using soil moisture instead of precipitation, we observed widespread convergence in the spatial and temporal sensitivities—that is, the two sensitivities became much more similar in magnitude across all water-limited ecosystems within CONUS. These results show that overlooking soil hydrology can inflate perceived discrepancies between spatial and temporal vegetation sensitivities, leading to biased projections of ecosystem dynamics under future hydro-climatic change.

Wang, Huiqi [University of California, Berkeley, C↗
DOE OSTI2021

Changing expression patterns of TonB-dependent transporters suggest shifts in polysaccharide consumption over the course of a spring phytoplankton bloom

Algal blooms produce large quantities of organic matter that is subsequently remineralised by bacterial heterotrophs. Polysaccharide is a primary component of algal biomass. It has been hypothesised that individual bacterial heterotrophic niches during algal blooms are in part determined by the available polysaccharide substrates present. Measurement of the expression of TonB-dependent transporters, often specific for polysaccharide uptake, might serve as a proxy for assessing bacterial polysaccharide consumption over time. To investigate this, we present here high-resolution metaproteomic and metagenomic datasets from bacterioplankton of the 2016 spring phytoplankton bloom at Helgoland island in the southern North Sea, and expression profiles of TonB-dependent transporters during the bloom, which demonstrate the importance of both the Gammaproteobacteria and the Bacteroidetes as degraders of algal polysaccharide. TonB-dependent transporters were the most highly expressed protein class, split approximately evenly between the Gammaproteobacteria and Bacteroidetes , and totalling on average 16.7% of all detected proteins during the bloom. About 93% of these were predicted to take up organic matter, and for about 12% of the TonB-dependent transporters, we predicted a specific target polysaccharide class. Most significantly, we observed a change in substrate specificities of the expressed transporters over time, which was not reflected in the corresponding metagenomic data. From this, we conclude that algal cell wall-related compounds containing fucose, mannose, and xylose were mostly utilised in later bloom stages, whereas glucose-based algal and bacterial storage molecules including laminarin, glycogen, and starch were used throughout. Quantification of transporters could therefore be key for understanding marine carbon cycling.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2020

Machine-learning-revealed statistics of the particle-carbon/binder detachment in lithium-ion battery cathodes

The microstructure of a composite electrode determines how individual battery particles are charged and discharged in a lithium-ion battery. It is a frontier challenge to experimentally visualize and, subsequently, to understand the electrochemical consequences of battery particles’ evolving (de)attachment with the conductive matrix. Herein, we tackle this issue with a unique combination of multiscale experimental approaches, machine-learning-assisted statistical analysis, and experiment-informed mathematical modeling. Our results suggest that the degree of particle detachment is positively correlated with the charging rate and that smaller particles exhibit a higher degree of uncertainty in their detachment from the carbon/binder matrix. We further explore the feasibility and limitation of utilizing the reconstructed electron density as a proxy for the state-of-charge. Our findings highlight the importance of precisely quantifying the evolving nature of the battery electrode’s microstructure with statistical confidence, which is a key to maximize the utility of active particles towards higher battery capacity.

25 ENERGY STORAGE↗
DOE OSTI2020

Hormonal contraception alters vaginal microbiota and cytokines in South African adolescents in a randomized trial

Young women in sub-Saharan Africa are disproportionally affected by HIV infection and unintended pregnancies. However, hormonal contraceptive (HC) use may influence HIV risk through changes in genital tract microbiota and inflammatory cytokines. To investigate this, 130 HIV negative adolescent females aged 15–19 years were enrolled into a substudy of UChoose, an open-label randomized crossover study (NCT02404038), comparing acceptability and contraceptive product preference as a proxy for HIV prevention delivery methods. Participants were randomized to injectable norethisterone enanthate (Net-En), combined oral contraceptives (COC) or etonorgesterol/ethinyl estradiol combined contraceptive vaginal ring (CCVR) for 16 weeks, then crossed over to another HC for 16 weeks. Cervicovaginal samples were collected at baseline, crossover and exit for characterization of the microbiota and measurement of cytokine levels; primary endpoints were cervical T cell activation, vaginal microbial diversity and cytokine concentrations. Adolescents randomized to COCs had lower vaginal microbial diversity and relative abundance of HIV risk-associated taxa compared to Net-En or CCVR. Cervicovaginal inflammatory cytokine concentrations were significantly higher in adolescents randomized to CCVR compared to COC and Net-En. This suggests that COC use may induce an optimal vaginal ecosystem by decreasing bacterial diversity and inflammatory taxa, while CCVR use is associated with genital inflammation.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2021

Constraining maximum event magnitude during injection-triggered seismicity

Abstract Understanding mechanisms controlling fluid injection-triggered seismicity is key in defining strategies to ameliorate it. Recent triggered events (e.g. Pohang, Mw 5.5) have exceeded predictions of average energy release by a factor of >1000x, necessitating robust methodologies to both define critical antecedent conditions and to thereby constrain anticipated event size. We define maximum event magnitudes resulting from triggering as a function of pre-existing critical stresses and fluid injection volume. Fluid injection experiments on prestressed laboratory faults confirm these estimates of triggered moment magnitudes for varied boundary conditions and injection rates. In addition, observed ratios of shear slip to dilation rates on individual faults signal triggering and may serve as a measurable proxy for impending rupture. This new framework provides a robust method of constraining maximum event size for preloaded faults and unifies prior laboratory and field observations that span sixteen decades in injection volume and four decades in length scale.

58 GEOSCIENCES↗
DOE OSTI2021

Multiple fermion scattering in the weakly coupled spin-chain compound YbAlO 3

The Heisenberg antiferromagnetic spin-1/2 chain, originally introduced almost a century ago, is one of the best studied models in quantum mechanics due to its exact solution, but nevertheless it continues to present new discoveries. Its low-energy physics is described by the Tomonaga-Luttinger liquid of spinless fermions, similar to the conduction electrons in one-dimensional metals. In this work we investigate the Heisenberg spin-chain compound YbAlO3 and show that the weak interchain coupling causes Umklapp scattering between the left- and right-moving fermions and stabilizes an incommensurate spin-density wave order at q = 2k F under finite magnetic fields. These Umklapp processes open a route to multiple coherent scattering of fermions, which results in the formation of satellites at integer multiples of the incommensurate fundamental wavevector Q = nq. Our work provides surprising and profound insight into bandstructure control for emergent fermions in quantum materials, and shows how neutron diffraction can be applied to investigate the phenomenon of coherent multiple scattering in metals through the proxy of quantum magnetic systems.

36 MATERIALS SCIENCE↗
DOE OSTI2023

Learning perturbation-inducible cell states from observability analysis of transcriptome dynamics

Abstract A major challenge in biotechnology and biomanufacturing is the identification of a set of biomarkers for perturbations and metabolites of interest. Here, we develop a data-driven, transcriptome-wide approach to rank perturbation-inducible genes from time-series RNA sequencing data for the discovery of analyte-responsive promoters. This provides a set of biomarkers that act as a proxy for the transcriptional state referred to as cell state. We construct low-dimensional models of gene expression dynamics and rank genes by their ability to capture the perturbation-specific cell state using a novel observability analysis. Using this ranking, we extract 15 analyte-responsive promoters for the organophosphate malathion in the underutilized host organism Pseudomonas fluorescens SBW25. We develop synthetic genetic reporters from each analyte-responsive promoter and characterize their response to malathion. Furthermore, we enhance malathion reporting through the aggregation of the response of individual reporters with a synthetic consortium approach, and we exemplify the library’s ability to be useful outside the lab by detecting malathion in the environment. The engineered host cell, a living malathion sensor, can be optimized for use in environmental diagnostics while the developed machine learning tool can be applied to discover perturbation-inducible gene expression systems in the compendium of host organisms.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2024

Ocean cavity regime shift reversed West Antarctic grounding line retreat in the late Holocene

Recent geologic and modeled evidence suggests that the grounding line of the Siple Coast of the West Antarctic Ice Sheet (WAIS) retreated hundreds of kilometers beyond its present position in the middle to late Holocene and readvanced within the past 1.7 ka. This grounding line reversal has been attributed to both changing rates of isostatic rebound and regional climate change. Here, we test these two hypotheses using a proxy-informed ensemble of ice sheet model simulations with varying ocean thermal forcing, global glacioisostatic adjustment (GIA) model simulations, and coupled ice sheet-GIA simulations that consider the interactions between these processes. Our results indicate that a warm to cold ocean cavity regime shift is the most likely cause of this grounding line reversal, but that GIA influences the rate of ice sheet response to oceanic changes. This implies that the grounding line here is sensitive to future changes in sub-ice shelf ocean circulation.

58 GEOSCIENCES↗
DOE OSTI2024

Probing the evolution of fault properties during the seismic cycle with deep learning

We use seismic waves that pass through the hypocentral region of the 2016 M6.5 Norcia earthquake together with Deep Learning (DL) to distinguish between foreshocks, aftershocks and time-to-failure (TTF). Binary and N-class models defined by TTF correctly identify seismograms in test with > 90% accuracy. We use raw seismic records as input to a 7 layer CNN model to perform the classification. Here we show that DL models successfully distinguish seismic waves pre/post mainshock in accord with lab and theoretical expectations of progressive changes in crack density prior to abrupt change at failure and gradual postseismic recovery. Performance is lower for band-pass filtered seismograms (below 10 Hz) suggesting that DL models learn from the evolution of subtle changes in elastic wave attenuation. Tests to verify that our results indeed provide a proxy for fault properties included DL models trained with the wrong mainshock time and those using seismic waves far from the Norcia mainshock; both show degraded performance. Our results demonstrate that DL models have the potential to track the evolution of fault zone properties during the seismic cycle. If this result is generalizable it could improve earthquake early warning and seismic hazard analysis.

58 GEOSCIENCES↗
DOE OSTI2025

Automatic speech recognition predicts contemporaneous earthquake fault displacement

Abstract Significant progress has been made in probing the state of an earthquake fault by applying machine learning to continuous seismic waveforms. The breakthroughs were originally obtained from laboratory shear experiments and numerical simulations of fault shear, then successfully extended to slow-slipping faults. Here we apply the Wav2Vec-2.0 self-supervised framework for automatic speech recognition to continuous seismic signals emanating from a sequence of moderate magnitude earthquakes during the 2018 caldera collapse at the Kīlauea volcano on the island of Hawai’i. We pre-train the Wav2Vec-2.0 model using caldera seismic waveforms and augment the model architecture to predict contemporaneous surface displacement during the caldera collapse sequence, a proxy for fault displacement. We find the model displacement predictions to be excellent. The model is adapted for near-future prediction information and found hints of prediction capability, but the results are not robust. The results demonstrate that earthquake faults emit seismic signatures in a similar manner to laboratory and numerical simulation faults, and artificial intelligence models developed for encoding audio of speech may have important applications in studying active fault zones.

58 GEOSCIENCES↗
DOE OSTI2019

The effect of irradiation on the atomic structure and chemical durability of calcite and dolomite

When exposed to irradiation—e.g., in nuclear power plant environments—minerals may experience alterations in their atomic structure which, in turn, result in changes in their physical and chemical properties. Herein, we mimic via Ar + implantation the effects of neutron irradiation on calcite (CaCO 3 ) and dolomite (CaMg(CO 3 ) 2 ) – two carbonate minerals that often find use as aggregates in concrete: a material that is extensively used in the construction of critical structural and safety components in nuclear power plants. By a pioneering combination of nanoscale quantifications of mineral dissolution rates (i.e., a proxy for chemical durability) in alkaline solutions, vibrational (infrared and Raman) spectroscopy, and molecular simulations, we find that irradiation minimally affects the atomic structure and properties of these carbonate minerals. This insensitivity to radiation arises from the predominantly ionic nature of the interatomic bonds in these minerals which can relax and recover their initial configuration, thus ensuring minimal damage and permanent alterations to these minerals following radiation exposure. The outcomes have significant implications on the selection, use, and specification of mineral aggregates for use in nuclear concrete construction.

63 RADIATION, THERMAL, AND OTHER ENVIRON. POLLUTAN↗
DOE OSTI2022

Declining tropical cyclone frequency under global warming

Assessing the role of anthropogenic warming from temporally inhomogeneous historical data in the presence of large natural variability is difficult and has caused conflicting conclusions on detection and attribution of tropical cyclone (TC) trends. Here, using a reconstructed long-term proxy of annual TC numbers together with high-resolution climate model experiments, we show robust declining trends in the annual number of TCs at global and regional scales during the twentieth century. The Twentieth Century Reanalysis (20CR) dataset is used for reconstruction because, compared with other reanalyses, it assimilates only sea-level pressure fields rather than utilize all available observations in the troposphere, making it less sensitive to temporal inhomogeneities in the observations. It can also capture TC signatures from the pre-satellite era reasonably well. The declining trends found are consistent with the twentieth century weakening of the Hadley and Walker circulations, which make conditions for TC formation less favourable.

54 ENVIRONMENTAL SCIENCES↗
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 OSTI2019

Air temperature optima of vegetation productivity across global biomes

The global distribution of the optimum air temperature for ecosystem-level gross primary productivity ( T $^{eco}_{opt}$) is poorly understood, despite its importance for ecosystem carbon uptake under future warming. In this paper, we provide empirical evidence for the existence of such an optimum, using measurements of in situ eddy covariance and satellite-derived proxies, and report its global distribution. T $^{eco}_{opt}$ is consistently lower than the physiological optimum temperature of leaf-level photosynthetic capacity, which typically exceeds 30 °C. The global average T $^{eco}_{opt}$ is estimated to be 23 ± 6 °C, with warmer regions having higher T $^{eco}_{opt}$ values than colder regions. In tropical forests in particular, T $^{eco}_{opt}$ is close to growing-season air temperature and is projected to fall below it under all scenarios of future climate, suggesting a limited safe operating space for these ecosystems under future warming.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2025

Machine learning-accelerated discovery of heat-resistant polysulfates for electrostatic energy storage

The development of heat-resistant dielectric polymers that withstand intense electric fields at high temperatures is critical for electrification. Balancing thermal stability and electrical insulation, however, is exceptionally challenging as these properties are often inversely correlated. A traditional intuition-driven polymer design approach results in a slow discovery loop that limits breakthroughs. Here we present a machine learning-driven strategy to rapidly identify high-performance, heat-resistant polymers. A trustworthy feed-forward neural network is trained to predict key proxy parameters and down select polymer candidates from a library of nearly 50,000 polysulfates. The highly efficient and modular sulfur fluoride exchange click chemistry enables successful synthesis and validation of selected candidates. A polysulfate featuring a 9,9-di(naphthalene)-fluorene repeat unit exhibits excellent thermal resilience and achieves ultrahigh discharged energy density with over 90% efficiency at 200 °C. Its exceptional cycling stability underscores its promise for applications in demanding electrified environments.

Li, He↗
DOE OSTI2019

Glacially sourced dust as a potentially significant source of ice nucleating particles

Aeolian dusts serve as ice nucleating particles in mixed-phase clouds, and thereby alter the cloud properties and lifetime. Glacial outwash plains are thought to be a major dust source in cold, high latitudes. Due to the recent rapid and widespread retreat of glaciers, high-latitude dust emissions are projected to increase, especially in the Arctic region, which is highly sensitive to climate change. However, the potential contribution of high-latitude dusts to ice nucleation in Arctic low-level clouds is not well acknowledged. Here we show that glacial outwash sediments in Svalbard (a proxy for glacially sourced dusts) have a remarkably high ice nucleating ability under conditions relevant for mixed-phase cloud formation, as compared with typical mineral dusts. The high ice nucleating ability of the sediments is probably governed by the presence of small amounts of organic matter (<1 wt% organic carbon) rather than mineral components. In addition, our results from intensive field measurements and model simulations indicate that the concentrations of atmospheric ice nucleating particles over the Svalbard region are expected to be enhanced in the summertime under the influence of dust emissions from Svalbard and its surroundings. In conclusion, we suggest that high-latitude dust sources have the potential to significantly influence glaciation of Arctic low-level clouds.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2022

Confronting the water potential information gap

Water potential directly controls the function of leaves, roots and microbes, and gradients in water potential drive water flows throughout the soil–plant–atmosphere continuum. Notwithstanding its clear relevance for many ecosystem processes, soil water potential is rarely measured in situ, and plant water potential observations are generally discrete, sparse, and not yet aggregated into accessible databases. These gaps limit our conceptual understanding of biophysical responses to moisture stress and inject large uncertainty into hydrologic and land-surface models. Here, we outline the conceptual and predictive gains that could be made with more continuous and discoverable observations of water potential in soils and plants. We discuss improvements to sensor technologies that facilitate in situ characterization of water potential, as well as strategies for building new networks that aggregate water potential data across sites. Here, we end by highlighting novel opportunities for linking more representative site-level observations of water potential to remotely sensed proxies. Together, these considerations offer a road map for clearer links between ecohydrological processes and the water potential gradients that have the ‘potential’ to substantially reduce conceptual and modelling uncertainties.

58 GEOSCIENCES↗
DOE OSTI2025

Daytime urban heat stress in North America reduced by irrigation

There is considerable uncertainty regarding the impact of irrigation on heat stress, partly stemming from the choice of heat stress index. Moreover, existing simulations are at scales that cannot appropriately resolve population centres or clouds and thus the potential for human impacts. Using multi-year convection-permitting and urban-resolving regional climate simulations, we demonstrate that irrigation alleviates summertime heat stress across more than 1,600 urban clusters in North America. This holds true for most physiologically relevant heat stress indices. The impact of irrigation varies by climate zone, with more notable irrigation signals seen for arid urban clusters that are situated near heavily irrigated fields. Through a component attribution framework, we show that irrigation-induced changes in wet-bulb temperature, often used as a moist heat stress proxy in the geosciences, exhibit an opposite sign to the corresponding changes in wet bulb globe temperature—a more complete index for assessing both indoor and outdoor heat risk—across climate zones. In contrast, the local changes in both wet-bulb and wet bulb globe temperature due to urbanization have the same sign. Here, our results demonstrate a complex relationship between irrigation and heat stress, highlighting the importance of using appropriate heat stress indices when assessing the potential for population-scale human impacts.

54 ENVIRONMENTAL SCIENCES↗