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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 415 records · Page 23
All sourcesNASA NTRSDOE OSTI
NASA NTRS2017

Limits to Creation of Oxygen-Rich Atmospheres on Planets in the Outer Reaches of the Conventional Habitable Zone

Abundant free oxygen appears to be a requirement for macroflora and macrofauna. To the best of our knowledge, a general discussion of which habitable planets are conducive to oxygen has not taken place. Theories for the rise of oxygen fall into 4 categories: (i) It is governed by an intrinsic rate of biological innovation, independent of environmental factors. (ii) It is caused by mantle evolution, probably consequent to secular cooling. (iii) It is caused by hydrogen escape, which irreversibly oxidizes the Earth. (iv) It is Gaia's response to the brightening Sun, its rise prevented until reduced greenhouse gases were no longer needed to maintain a clement climate. All but the first of these make implicit astronomical predictions that can be quantified and made explicit. Here we address the third hypothesis. In this hypothesis hydrogen escape acts like an hourglass that continues until all relevant reduced mineral buffers have been oxidized (titrated, as it were) and the surface made safe for O2. The hypothesis predicts that abundant free O2 will be absent from habitable planets that have not experienced significant hydrogen escape. Where hydrogen escape is modest or insignificant, the atmosphere can be approximated as hydrostatic, which makes assessing radiative cooling by embedded molecules, atoms, and ions such as CO2 and H3+ straightforward. In particular, H2 is efficient at exciting non-LTE CO2 15 micron emission, which makes radiative cooling very effective when H2 is abundant. We can therefore map out the region of phase space in which habitable planets do not lose hydrogen, and therefore do not develop O2 atmospheres. A related matter is the power of radiative cooling by embedded molecules to enforce the diffusion limit to hydrogen escape. This matter in particular is relevant to addressing the empirical observation that rocky planets with thin or negligible atmospheres are rarely or never bigger than approx.1.6 Earth radii.

Zahnle, Kevin↗
NASA NTRS2018

Stem Cell-Based Regenerative Health in Microgravity

The research of Dr. Almeida's Lab at NASA Ames focuses on the effects of microgravity mechanical unloading on stem-cell-based tissue regeneration. The research focuses on testing the broad hypothesis that mechanical load from gravity at 1 g is required for normal adult stem cell proliferation and differentiation during tissue regeneration. Research from the lab has provides evidence supporting the hypothesis in various biological models, including newt tail regeneration, mouse bone and bone marrow in whole animals, and mouse embryonic stem cells all exposed to microgravity during spaceflight. Using these models, the lab has identified overexpression of the cell cycle inhibitor p21/CDKN1a as a candidate molecular mediator mechanism of bone marrow mesenchymal and hematopoietic lineage tissue regenerative arrest in microgravity. The labis currently focused on using p21/CDKN1a null mouse and cell culture approaches in microgravity to test the gravity tissue regeneration hypothesis.

stem cells microgravity regeneration↗
NASA NTRSDate not supplied

CDKN1A/P21’S Role in Osteoprogenitor Fate Regulation in Response to Mechanical Loading: A Single Cell Resolution Investigation

Forces generated by gravity in load-bearing tissues such as bone marrow promote stem cell-based tissue-regenerative processes by increasing proliferation and differentiation of tissue progenitors. Conversely, in microgravity, mouse bone marrow mesenchymal and hematopoietic precursors down-regulate differentiation markers and up-regulate stemness maintenance genes. During microgravity, these transcriptomic changes are associated with Cdkn1a overexpression in osteoprogenitors, and further the homozygous deletion of the CDKN1a gene in the mouse model results in elevated stem-cell based regeneration of severed digits and ear-hole punches. In this work we sought to test the hypothesis that gravity mechanotransduction regulates mesenchymal stem cell derived osteoprogenitor based osteogenesis by modulating proliferation and differentiation fates at specific cell cycle stages via a p21/CDKN1a-regulated mechanism.. To test our hypothesis, we isolated primary mouse bone marrow osteoprogenitors from Cdkn1a-/- (null) or wildtype mice, cultured the cells for 7-days unloaded in osteogenic differentiation media, to allow commitment of the adherent cell population, and subsequently, cultured an additional 48-hours under cyclic stretch or static control loading conditions. After 48-hours of dynamic mechanical loading, we used a 10X Genomics Chromium/Single Cell controller to generate bar-coded single cell Illumina libraries and sequenced expressomes for 6,000 static control and 6,000 cyclic stretch cells for each genotype. Stage-specific single cell analyses show Cdkn1a-/- osteogenic cultures are more differentiated with fewer progenitors, and that cyclic stretch further promotes the conversion of progenitors to osteoblasts in both wildtype and Cdkn1a-/- backgrounds. The proportion of late mineralizing osteoblasts doubled in Cdkn1a-/- cultures, but is not affected by load. Finally, single cell expression of Cdkn1a, in the wildtype cells, is most strongly suppressed by cyclic stretch both in early and late osteoblasts, and minimally in the progenitor population. Collectively, our results support the hypothesis that Cdkn1a constitutively plays a mechano-reversible anti-proliferative role during stem cell-based bone tissue regeneration, and suggests a new molecular target to counter regenerative deficits caused by disuse.

Eduardo Almeida↗
NASA NTRSDate not supplied

LSKnowledge: Nexus for Transformative Scientific Discoveries and Enhanced Information Retrieval in NASA Life Sciences Portal

We stand at the brink of an extraordinary transformation in the field of AI, driven by the convergence of generative AI and semantic technologies (e.g., knowledge graphs). This fusion holds immense potential and could redefine the future of scientific exploration, particularly in the realm of life sciences research. In this context, we shed light on the pivotal roles that Large Language Models (LLMs) and semantic technologies will play in advancing research, unearthing and comprehending life sciences information through innovative approaches, and empowering researchers to extract insights from NASA's extensive Life Sciences Data Archive. Within the NASA Life Sciences Portal (NLSP), the integration of LLMs and semantic technologies unlocks several advanced capabilities. First and foremost, it equips scientists with sophisticated tools to manage the ever-expanding wealth of scientific literature and data. Furthermore, it facilitates the creation of knowledge graphs that visually represent intricate relationships among biological entities, enabling comprehensive systems-level analysis. Additionally, the fusion of generative AI (including LLMs) and semantic technology can significantly benefit NASA's life sciences research by enhancing information retrieval and hypothesis generation. These tools enhance natural language understanding, facilitating knowledge discovery within NLSP. The overarching vision is to establish a cohesive knowledge ecosystem within NLSP, harnessing the power of LLMs and semantic technologies to synthesize and cross-reference data from diverse missions, disciplines, and research domains. This holistic approach ultimately deepens our understanding of how space environments impact life sciences data. To advance this initiative, we have launched LSKnowledge, aimed at enhancing the information retrieval capabilities of NLSP. In the short term, our primary goal is to develop a robust semantic search system. This system will empower HRP (Human Research Program) researchers to navigate NLSP data repositories more efficiently and precisely, catalyzing the process of hypothesis formation and scientific breakthroughs. To achieve this, we have employed pre-trained LLMs as part of a semantic search tool that can rank and highlight the most relevant records for user queries. To assess the tool's performance, we have curated a set of approximately 200 queries from subject matter experts (SMEs) and manually ranked the top records retrieved by both the current search system and the new semantic search, using SME judgments as the gold standard for relevancy. Herein, we present the results of our comparative analysis and illustrate how these findings have informed the fine-tuning of the system for enhanced performance. In the long term, our objectives include 1) retrieving publicly available information and integrating it with NLSP data to provide more precise answers to user queries, and 2) incorporating non-textual information from the NLSP database into our approach. In conclusion, the fusion of LLMs and semantic technologies within NLSP represents a pioneering stride towards reshaping the landscape of scientific discovery. This synergy not only equips researchers with powerful tools to navigate the burgeoning sea of information but also facilitates a deeper understanding of complex biological relationships, all while accelerating hypothesis generation and knowledge discovery. Through our initiative, LSKnowledge, we are committed to continually refining and expanding these capabilities, with the aim of not only enhancing information retrieval but also integrating diverse data sources to provide more precise insights. In the grand vision, NLSP strives to become the cornerstone of a comprehensive knowledge ecosystem, unraveling the enigmatic intricacies of life sciences phenomena in the context of space environments.

Life Sciences↗
NASA NTRS2024

Summary and Annotated Bibliography of Measurement Error Corrections with Potential Application in Future Quesst Mission Community Noise Studies

This document is motivated by likely needs of the Quesst mission community response tests, which will culminate in data collection and estimation of dose-response regression relationships for consideration by domestic and international aviation regulators. Furthermore, basic research questions evaluating interactions between rates of community annoyance, dose levels, and indicators of the presence of rattle, vibration, and startle hinge on hypothesis testing in the context of regression models. For a variety of reasons, noise doses may be known only imprecisely and may not reflect the actual level experienced by responding subjects. These differences between true dose and estimated dose, be they systematic or random, constitute covariate measurement error. Available statistics literature speaks to the impacts of measurement error on regression models, both in terms of bias in estimated coefficients and predicted values, and in terms of the loss of statistical power for hypothesis testing. Given the particulars of a categorical annoyance response variable and a continuous noise dose predictor variable subject to measurement error during testing, the emphasis of this report is on findings and methods pertinent to generalized linear (and mixed) models likely to be employed during the Quesst mission community tests. We reach the following conclusions: 1. Of four reviewed methods, structural Bayesian measurement error models and simulation extrapolation (SIMEX) may be the most readily applicable to Quesst mission community noise study objectives. 2. If warranted, a linear measurement model can help model systematic sources of measurement error that the classical measurement error does not. 3. For its ready implementation and small additional input requirements, simulation extrapolation may be ideally suited for addressing secondary research questions involving interactions between annoyance, noise dose, and other factors through hypothesis testing. 4. For their flexibility and ability to propagate uncertainty, structural Bayesian hierarchical models have great appeal for mission purposes; some care may be needed in developing appropriate probability models describing actual noise exposure during testing. An annotated bibliography logs additional papers and resources that may be of value to analysts in other projects and disciplines.

Dose-Response Model↗
DOE OSTI2023

Logarithmic scaling of higher-order temperature moments in the atmospheric surface layer

A generalized logarithmic law for high-order moments of homogeneous passive scalars is proposed for turbulent boundary layers. This law is analogous to the generalized log law that has been proposed for high-order moments of the turbulent longitudinal velocity and is derived by combining the random sweeping decorrelation hypothesis with a spectral model informed by the attached eddy hypothesis. The proposed theory predicts that the high-order moments of passive scalar fluctuations within the inertial sublayer will vary logarithmically with wall-normal distance (), and is evaluated using high frequency time-series measurements of temperature and streamwise velocity fluctuations obtained in the first meter of the atmospheric surface layer (ASL) under near-neutral thermal stratification. The logarithmic dependence with within the inertial sublayer is observed in both the air temperature and velocity moments, with good agreement to the predictions from the proposed theory. Surprisingly, the proposed theory appears to be as, if not more, valid for transported passive scalars than for the longitudinal velocity.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2024

Disturbance and diversity: Lichen species richness decreases with increasing anthropogenic disturbance

Anthropogenic disturbance is rapidly increasing through habitat degradation, development, and deforestation. Gaps remain in understanding the effects of this disturbance on diverse and ecologically important organisms such as lichens. In North America, studies have focused on epiphytic macrolichens and catastrophic disturbance, largely ignoring microlichens and less severe disturbances. The Intermediate Disturbance Hypothesis predicts these moderate disturbances will lead to higher species richness. Here we examine the effects of anthropogenic disturbance in the form of land management on overall lichen richness, including microlichens, and on the species richness of eight lichen functional groups. The study draws on a comprehensive data set of 872 species, in 208 one-hectare plots throughout the Southern Appalachian Mountains, a global biodiversity hotspot in eastern North America. A habitat quality index based on an established forestry metric was used as a proxy for anthropogenic disturbance and was quantified using a 10-part score including categories such as percent native tree canopy cover and degree of fragmentation. Linear models were used to compare habitat quality scores to overall species richness and to species richness of functional groups. Rather than following the Intermediate Disturbance Hypothesis, all groups uniformly follow a negative linear relationship: as disturbance increases, species richness decreases. This pattern held even for widely variable functional groups such as morphotype. Effective conservation of lichen richness should prioritize the maintenance of existing older, less-disturbed stands within large, contiguously forested areas.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2025

Computational investigation of water glasses using machine-learning potentials

The molecular origins of water’s anomalous properties have long been a subject of scientific inquiry. The liquid–liquid phase transition hypothesis, which posits the existence of distinct low-density and high-density liquid states separated by a first-order phase transition terminating at a critical point, has gained increasing experimental and computational support and offers a thermodynamically consistent framework for many of water’s anomalies. However, experimental challenges in avoiding crystallization near the postulated liquid–liquid critical point have focused attention to water’s canonical glassy states: low-density and high-density amorphous ice. Here, we use two Deep Potential machine-learning models, trained on the Strongly Constrained and Appropriately Normed density functional and the highly accurate Many-Body Polarizable potential, to conduct an investigation of water’s glassy phenomenology based on quantum mechanical calculations. Despite not being explicitly trained on amorphous ices, both models accurately capture the structure and transformation of the water glasses, including their interconversion along different thermodynamic paths. Isobaric quenching of liquid water at various pressures generates a continuum of intermediate amorphous ices and density fluctuations increase near the liquid–liquid critical pressure. The glass transition temperatures of the amorphous ices produced at different pressures exhibit two distinct branches, corresponding to low-density and high-density amorphous ice behaviors, consistent with experiment and the liquid–liquid transition hypothesis. Extrapolating transformation pressures from isothermal compressions to experimental compression rates brings our simulations into excellent agreement with data. Our findings demonstrate that machine-learning potentials trained on equilibrium phases can effectively model nonequilibrium glassy behavior and pave the way for studying long-timescale, out-of-equilibrium processes with quantum mechanical accuracy.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2024

Eigenstate thermalization in ( 2 + 1 )-dimensional SU(2) lattice gauge theory

We present preliminary numerical evidence for the hypothesis that the Hamiltonian SU(2) gauge theory discretized on a lattice obeys the eigenstate thermalization hypothesis (ETH). To do so we study three approximations: (a) a linear plaquette chain in a reduced Hilbert space limiting the electric field basis to j = 0 , 1 2 , (b) a two-dimensional honeycomb lattice with periodic or closed boundary condition and the same Hilbert space constraint, and (c) a chain of only three plaquettes but such a sufficiently large electric field Hilbert space ( j ≤ 7 2 ) that convergence of all energy eigenvalues in the analyzed energy window is observed. While an unconstrained Hilbert space is required to reach the continuum limit of SU(2) gauge theory, numerical resource constraints do not permit us to realize this requirement for all values of the coupling constant and large lattices. In each of the three studied cases we check first for random matrix theory (RMT) behavior in the eigenenergy spectrum and then analyze the diagonal as well as the off-diagonal matrix elements between energy eigenstates for a few operators. Within current uncertainties all results for (a), (b) and (c) agree with ETH predictions. Furthermore, we find the off-diagonal matrix elements of the electric energy operator exhibit RMT behavior in frequency windows that are small enough in (b) and (c). To unambiguously establish ETH behavior and determine for which class of operators it applies, an extension of our investigations is necessary. Published by the American Physical Society 2024

73 NUCLEAR PHYSICS AND RADIATION PHYSICS↗
DOE OSTI2022

Statistical Significance Testing for Mixed Priors: A Combined Bayesian and Frequentist Analysis

In many hypothesis testing applications, we have mixed priors, with well-motivated informative priors for some parameters but not for others. The Bayesian methodology uses the Bayes factor and is helpful for the informative priors, as it incorporates Occam’s razor via the multiplicity or trials factor in the look-elsewhere effect. However, if the prior is not known completely, the frequentist hypothesis test via the false-positive rate is a better approach, as it is less sensitive to the prior choice. We argue that when only partial prior information is available, it is best to combine the two methodologies by using the Bayes factor as a test statistic in the frequentist analysis. We show that the standard frequentist maximum likelihood-ratio test statistic corresponds to the Bayes factor with a non-informative Jeffrey’s prior. We also show that mixed priors increase the statistical power in frequentist analyses over the maximum likelihood test statistic. We develop an analytic formalism that does not require expensive simulations and generalize Wilks’ theorem beyond its usual regime of validity. In specific limits, the formalism reproduces existing expressions, such as the p-value of linear models and periodograms. We apply the formalism to an example of exoplanet transits, where multiplicity can be more than 10 7 . We show that our analytic expressions reproduce the $p$-values derived from numerical simulations. We offer an interpretation of our formalism based on the statistical mechanics. We introduce the counting of states in a continuous parameter space using the uncertainty volume as the quantum of the state. We show that both the $p$-value and Bayes factor can be expressed as an energy versus entropy competition.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2025

Abnormal Slow Phonon Dynamics Toward Prolonging Excited States Dynamics Enabled by Crystalline‐Assembling Donor–Acceptor Molecules

Phonon dynamics are a critical factor to control the optical properties of excited states in light-emitting materials. Here, we report an extremely slow relaxation of photoexcited lattice vibrations enabled by assembling the donor-acceptor (D–A) molecules [2-(9,9-dimethylacridin-10(9H)-yl)-9,9-dimethyl-9H-thioxanthene 10,10-dioxide], namely AC molecules, into dipolar crystal. By using photoexcitation-modulated Raman spectroscopy, we find that the crystalline-lattice vibrations monitored by Raman-scattering laser beam of 785 nm demonstrate an un-usual slow relaxation in the time scale of seconds after ceasing photoexcitation beam of 343 nm in such dipolar crystal. This presents extremely slow phonon dynamics enabled by crystalline-assembling the D–A molecules into a dipolar crystal. Simultaneously, the photoluminescence (PL) exhibits a prolonged behavior, lasting 10 ms after ceasing photoexcitation in dipolar AC crystal. This phenomenon provides an experimental hypothesis that the slow phonon dynamics function as an important mechanism to unusually prolong excited states dynamics upon crystalline-assembling the D–A molecules into dipolar crystal. Here, this hypothesis can be verified by directly suppressing the phonon dynamics through freezing D–A molecular liquid into dipolar crystalline solid at 77 K to largely prolong the PL to 1 s- after removing photoexcitation. Clearly, crystalline-assembling D–A molecules provide the necessary conditions to enable slow phonon dynamics toward prolonging excited states dynamics.

36 MATERIALS SCIENCE↗
DOE OSTI2025

Self‐Healable Poly(ionic liquid) Copolymers Driven by Polar and Dipolar Forces

Abstract Commodity aliphatic and aromatic acrylic‐based copolymers self‐heal due to ubiquitouskey‐and‐lock,ring‐and‐lock, andfluorophilic‐σ‐lockvan der Waals (vdW) interactions. However, the role of these interactions in the presence of covalently copolymerized ionic liquid (IL) is not known. This study is driven by the hypothesis that covalently incorporated cation–anion pairs to form poly(ionic liquid) copolymers (PILCs) can perturb inter‐ or intra‐chain vdW interactions reflected in mechanical and electrical responses. To test this hypothesis, we synthesized a series of PILCs comprising of pentafluorostyrene (PFS) and imidazolium‐based IL monomers with variable‐length aliphatic tails (methyl and butyl). Using a combination of 2D 1 H‐ 1 H and 19 F ‐ 19 F NOESY NMR and FTIR measurements supplemented by molecular dynamic (MD) simulations, these studies demonstrate that preferentially alternating/random PILCs topologies facilitate self‐healing. The introduction of cation–anion moieties modifies thefluorophilic‐σ‐lockinteractions and, along with longer aliphatic tails ─(CH 2 ) 3 CH 3 covalently attached to the imidazolium cation, enhances cation‐anion mobility, thus faster recovery from mechanical damage occurs. These findings underline how precise control over dipolar and ionic interactions through copolymer composition enables self‐healing in PILCs. These insights may open pathways for designing sustainable, mechanically resilient materials for applications in energy storage and energy harvesting.

Chemistry↗
DOE OSTI2023

Tailoring Chemical Absorption-Precipitation to Lower the Regeneration Energy of a CO 2 Capture Solvent

Solvent-based CO 2 capture consumes significant amounts of energy for solvent regeneration. To improve energy efficiency, this study investigates CO 2 fixation in a solid form through solvation, followed by ionic self-assembly-aided precipitation. Based on the hypothesis that CO 3 2- ions may bind with monovalent metal ions, we introduced Na + into an aqueous hexane-1,6-diamine solution where CO 2 forms carbamate and bicarbonate. Then, Na + ions in the solvent act as a seed for ionic self-assembly with diamine carbamate to form an intermediate ionic complex. The recurring chemical reactions lead to the formation of an ionic solid from a mixture of organic carbamate/carbonate and inorganic sodium bicarbonate (NaHCO 3 ), which can be easily removed from the aqueous solvent through sedimentation or centrifugation and heated to release the captured CO 2 . Mild-temperature heating of the solids at 80–150 °C causes decomposition of the solid CO 2 -diamine-Na molecular aggregates and discharge of CO 2 . This sorbent regeneration process requires 6.5–8.6 GJ/t CO 2 . It was also found that the organic carbamate/carbonate solid, without NaHCO 3 , contains a significant amount of CO 2 , up to 6.2 mmol CO 2 /g-sorbent, requiring as low as 2.9–5.8 GJ/t CO 2 . In conclusion, molecular dynamic simulations support the hypothesis of using Na + to form relatively less stable, yet sufficiently solid, complexes for the least energy-intensive recovery of diamine solvents compared to bivalent carbonate–forming ions.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2021

Disturbance-accelerated succession increases the production of a temperate forest

Many secondary deciduous forests of eastern North America are approaching a transition in which maturing early successional tree species are declining, resulting in an uncertain future for these forests’ century-long carbon (C) sink. We initiated the Forest Accelerated Succession Experiment (FASET) at the University of Michigan Biological Station to examine the patterns and mechanisms underlying forest C cycling following the stem-girdling induced mortality of >6,700 early successional Populus spp. (aspen) and Betula papyrifera (paper birch). Since 2008, meteorological flux tower-based C cycling observations from the 33-ha treatment forest have been paired with those from a nearby unmanipulated forest. Following over a decade of observations, herein we revisit our core hypothesis: that net ecosystem production (NEP) would increase following the transition to mid-late successional species dominance due to increased canopy structural complexity. Supporting our hypothesis, NEP was stable, briefly declined, and then increased relative to the control in the decade following disturbance; however, increasing NEP was not associated with rising structural complexity but rather the rapid 1-year recovery of total LAI as mid-late successional Acer, Quercus, and Pinus assumed canopy dominance. The transition to mid-late successional species dominance improved carbon-use efficiency (CUE = NEP/gross primary production) as ecosystem respiration declined. Similar soil respiration rates in control and treatment forests, along with species differences in leaf physiology and the rising relative growth rates of mid-late successional species in the treatment forest, suggest changes in aboveground plant respiration and growth, respectively, were primarily responsible for increases in NEP. We conclude that deciduous forests transitioning from early to middle succession are capable of sustained or increased NEP, even when experiencing extensive tree mortality. This adds to mounting evidence that aging deciduous forests in the region will function as C sinks for decades to come.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2020

Lignin lags, leads, or limits the decomposition of litter and soil organic carbon

Lignin’s role in litter and soil organic carbon (SOC) decomposition remains contentious. Lignin decomposition was traditionally thought to increase during midstage litter decomposition, when cellulose occlusion by lignin began to limit mass loss. Alternatively, lignin decomposition could be greatest in fresh litter as a consequence of co-metabolism, and lignin might decompose faster than bulk SOC. To test these competing hypotheses, we incubated 10 forest soils with C 4 grass litter (amended with 13 C-labeled or unlabeled lignin) over 2 yr and measured soil respiration and its isotope composition. Early lignin decomposition was greatest in 5 of 10 soils, consistent with the co-metabolism hypothesis. However, lignin decomposition peaked 6–24 months later in the other five soils, consistent with the substrate-limitation hypothesis; these soils were highly acidic. Rates of lignin, litter, and SOC decomposition tended to converge over time. Cumulative lignin decomposition was never greater than SOC decomposition; lignin decomposition was significantly lower than SOC decomposition in six soils. Net nitrogen mineralization predicted lignin decomposition ratios relative to litter and SOC. Although the onset of lignin decomposition can indeed be rapid, lignin still presents a likely bottleneck in litter and SOC decomposition, meriting a reconsideration of lignin’s role in modern decomposition paradigms.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2024

Search for a new resonance decaying into two spin-0 bosons in a final state with two photons and two bottom quarks in proton-proton collisions at $\sqrt{s}$ = 13 TeV

A search for a new boson X is presented using CERN LHC proton-proton collision data collected by the CMS experiment at $\sqrt{s}$ = 13 TeV in 2016–2018, and corresponding to an integrated luminosity of 138 fb -1 . The resonance X decays into either a pair of Higgs bosons HH of mass 125 GeV or an H and a new spin-0 boson Y. One H subsequently decays to a pair of photons, and the second H or Y, to a pair of bottom quarks. The explored mass ranges of X are 260–1000 GeV and 300–1000 GeV, for decays to HH and to HY, respectively, with the Y mass range being 90–800 GeV. For a spin-0 X hypothesis, the 95% confidence level upper limit on the product of its production cross section and decay branching fraction is observed to be within 0.90–0.04 fb, depending on the masses of X and Y. The largest deviation from the background-only hypothesis with a local (global) significance of 3.8 (below 2.8) standard deviations is observed for X and Y masses of 650 and 90 GeV, respectively. The limits are interpreted using several models of new physics.

72 PHYSICS OF ELEMENTARY PARTICLES AND FIELDS↗
DOE OSTI2022

A framework for detection and attribution of regional precipitation change: Application to the United States historical record

Abstract Despite the emerging influence of anthropogenic climate change on the global water cycle, at regional scales the combination of observational uncertainty, large internal variability, and modeling uncertainty undermine robust statements regarding the human influence on precipitation. Here, we use output from global climate models in a perfect-data sense to develop a framework for conducting regional detection and attribution (D&A) for precipitation, starting with the contiguous United States (CONUS) where observational uncertainty is lower than in other regions. Our unified approach can simultaneously detect systematic trends in mean and extreme precipitation, attribute trends to anthropogenic forcings, compute the effects of forcings as a function of time, and map the effects of individual forcings. Model output is used to conduct a set of tests that yield a parsimonious representation for characterizing seasonal precipitation over the CONUS for the historical record (1900 to present day), which ensures our D&A is insensitive to structural uncertainty. Our framework is developed using synthetic data in a Pearl-causal perspective wherein causality can be identified using intervention-based simulations. While the hypothesis-based framework and accompanying generalized D&A formula we develop should be widely applicable, we include a strong caution that the hypothesis-guided simplification of the formula for the historical climatic record of CONUS as described in this paper will likely fail to hold in other geographic regions and under future warming.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2021

A proposed criteria to identify wind turbine drivetrain bearing loads that induce roller slip based white-etching cracks

In this article, the type of roller slip behavior that may result in the formation of white-etching cracks (WECs) in wind turbine gearbox bearings is identified. A new hypothesis based on the inner raceway normal contact load magnitude at the time of roller slip is proposed as the probable cause of WECs. For this purpose, the maximum normal contact loads are identified when roller slip occurs in high-speed shaft bearings at different mean wind speeds. Subsequently, the annual probability of occurrence of the maximum normal loads are obtained. The probability of maximum load under slip exceeding a limit probability is hypothesized as a probable cause for WEC. In order to apply the proposed hypothesis, two different wind turbines high-speed shaft bearings are used: the cylindrical roller bearing of the General Electric 1.5 SLE turbine and the tapered roller bearing of Vestas V52 turbine. Both the chosen bearings are on the generator side of the high-speed shaft. For both turbines, measurement data together with analytical models are used for identifying the slip and the maximum normal contact loads. We propose forecasting the probability of exceedance of a threshold maximum normal contact load level during slip to identify the possibility for inducing WECs.

17 WIND ENERGY↗