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At least 343 records · Page 19

Miscanthus × giganteus increases soil maximum water holding capacity compared to maize

Soil ecosystem services, like the ability to store water, have been depleted after a century of conventional, annual cropping, and perennial crops offer a solution to this and other agricultural environmental issues. We assessed the impact of Miscanthus × giganteus (miscanthus), a perennial biomass crop, on soil water holding capacity and structure compared to continuous maize (Zea mays L.) at two sites in Iowa. After three growing seasons, we measured the following: (1) maximum water holding capacity (MWHC) with and without soil structure, and (2) total porosity and pore size distribution (PSD) via micro-computed tomography (microCT). Miscanthus increased MWHC by 14.7% across both sites relative to maize (p = 0.002), and we attributed this to structural changes due to the lack of a crop effect when measured on structureless soils. No significant changes were detected in soil organic matter, texture, total porosity, or PSD that could explain the increase in MWHC under miscanthus. Our findings suggest that the increases in MWHC are primarily due to structural changes rather than increases in soil organic matter or porosity (at least porosity detectable by microCT). This study highlights miscanthus' potential to enhance soil water storage and underscores the need for further investigation to clarify the mechanisms through which this biomass crop influences soil structural properties.

60 APPLIED LIFE SCIENCES↗

Maximum Impact of Ionic Strength on Acid‐Catalyzed Reaction Rates Induced by a Zeolite Microporous Environment

Abstract The intracrystalline ionic environment in microporous zeolite can remarkably modify the excess chemical potential of adsorbed reactants and transition states, thereby influencing the catalytic turnover rates. However, a limit of the rate enhancement for aqueous‐phase dehydration of alcohols appears to exist for zeolites with high ionic strength. The origin of such limitation has been hypothesized to be caused by the spatial constraints in the pores via, e.g., size exclusion effects. It is demonstrated here that the increase in turnover rate as well as the formation of a maximum and the rate drop are intrinsic consequences of the increasingly dense ionic environment in zeolite. The molecularly sized confines of zeolite create a unique ionic environment that monotonically favors the formation of alcohol‐hydronium ion complexes in the micropores. The zeolite microporous environment determines the kinetics of catalytic steps and tailors the impact of ionic strength on catalytic rates.

Liu, Qiang↗

Maximum Impact of Ionic Strength on Acid‐Catalyzed Reaction Rates Induced by a Zeolite Microporous Environment

Abstract The intracrystalline ionic environment in microporous zeolite can remarkably modify the excess chemical potential of adsorbed reactants and transition states, thereby influencing the catalytic turnover rates. However, a limit of the rate enhancement for aqueous‐phase dehydration of alcohols appears to exist for zeolites with high ionic strength. The origin of such limitation has been hypothesized to be caused by the spatial constraints in the pores via, e.g., size exclusion effects. It is demonstrated here that the increase in turnover rate as well as the formation of a maximum and the rate drop are intrinsic consequences of the increasingly dense ionic environment in zeolite. The molecularly sized confines of zeolite create a unique ionic environment that monotonically favors the formation of alcohol‐hydronium ion complexes in the micropores. The zeolite microporous environment determines the kinetics of catalytic steps and tailors the impact of ionic strength on catalytic rates.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

A principle of maximum ignorance for semiclassical gravity

The principle of maximum ignorance posits that the coarse-grained description of a system is maximally agnostic about its underlying microscopic structure. We briefly review this principle for random matrix theory and for the eigenstate thermalization hypothesis. We then apply this principle in holography to construct ensembles of random mixed states. This leads to an ensemble of microstates which models our microscopic ignorance, and which on average reproduces the effective semiclassical physics of a given bulk state. We call this ensemble the state-averaging ansatz. The output of our model is a prediction for semiclassical contributions to variances and higher statistical moments over the ensemble of microstates. The statistical moments provide coarse-grained — yet gravitationally non-perturbative — information about the microstructure of the individual states of the ensemble. We show that these contributions exactly match the on-shell action of known wormhole configurations of the gravitational path integral. These results strengthen the view that wormholes simply parametrize the ignorance of the microstructure of a fundamental state, given a fixed semiclassical bulk description.

71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗

Robust and optimal alignment of high-dimensional data using maximum likelihood estimation through a random sample consensus framework

Abstract Correcting spatial orientations of groups of high-dimensional data sets such that they are all in a consistent coordinate system is often a time-consuming and error-prone process. Automation of this process can be accomplished by using Generalized Procrustes Analysis to estimate the relative orientations among a population of high-dimensional data sets. A least squares Procrustes solution is applied through a maximum likelihood estimation and random sample consensus framework for robustness. The likelihood model is comprised of a mixture distribution where inliers are modeled using t -distribution and outliers from a uniform distribution. Applications will focus on a synthetic data set that emulates triaxial acceleration data and also real shock data from a population of triaxial accelerometers. Outliers represent either non-rigid body responses, environmental noise, and/or sensor and data acquisition issues. The intended application for the methodology is to robustly automate the rotation of populations of experimentally collected triaxial accelerometer data sets to a single global coordinate system.

LOSAC↗

SIF-based GPP modeling for evergreen forests considering the seasonal variation in maximum photochemical efficiency

Solar-induced chlorophyll fluorescence (SIF) has shown great potential in estimating gross primary production (GPP). However, their quantitative relationship is not invariant, which undermines the reliability of empirical SIF-based GPP estimation at fine spatiotemporal scales, especially under extreme conditions. In this study, we developed a parsimonious mechanistic model for SIF-based GPP estimation in evergreen needle forests (ENF) by employing the Mechanistic Light Response framework and Eco-Evolutionary theory to describe the light and dark reactions during photosynthesis, respectively. Specifically, we found that considering the seasonal variation in a key parameter of the MLR framework, the maximum photochemical efficiency of photosystem II (Φ PSIImax ), can avoid the GPP overestimation in winter and early spring due to the relatively low environmental sensitivity of SIF. Compared to the estimates from other benchmark models, our GPP estimates were closer to the 1: 1 line and had higher accuracy (average R 2 = 0.86, RMSE=1.99 μmol m -2 s -1 ) across sites. Furthermore, the changes in the relationship between SIF and J (refers to the electron transport rate) contribute a lot to the dynamic SIF–GPP relationship in this study, while the J–GPP relationship is less variant when the temperature drops. Further, the seasonal variation in the SIF–J relationship, especially the reduction in its slope at low temperatures, is found largely explained by the Φ PSIImax . These results indicate the importance of the uncertainty caused by the variation in the SIF–J relationship for SIF-based GPP estimation, and the consideration of changes in Φ PSIImax under extreme conditions (such as severe winter in this study) is crucial for the improvement of GPP estimation via SIF.

59 BASIC BIOLOGICAL SCIENCES↗

Compression of tokamak boundary plasma simulation data using a maximum volume algorithm for matrix skeleton decomposition

This report demonstrates satisfactory data compression of SOLPS-ITER simulation output ranging from 2D fields, 1D profiles, and 0D scalar variables with a novel matrix decomposition approach. The singular value decomposition (SVD) scales poorly for large matrix sizes and is unsuited to the application on high dimensional data common to fusion plasma physics simulation. In this work, we employ the columns-submatrix-rows (CUR) matrix factorization technique in order to compute a low-rank approximation up to two orders of magnitude faster than the SVD, but within a nominal L2-norm relative error of ε = 10 –2 . In addition, the CUR approach maintains the original format of the data, in its extracted columns and rows, allowing for interpretable data storage at the original resolution of the simulation. We utilize an iterative algorithm to compute the CUR decomposition of simulation output by maximizing the volume, or linearly independent information content, of a low-rank submatrix contained within the data. Experiments over $\textit{n} × \textit{n}$ randomized test matrices with embedded rank-deficient features show that this maximum volume implementation of CUR matrix approximation has reduced asymptotic computational complexity on the order of n compared to the SVD, which scales approximately as $n^3$. These results show that the CUR technique can be used to effectively select time step snapshots (columns) of over 140 SOLPS-ITER output variables and the associated discretized coordinate timeseries (rows) allowing for reconstruction of the complete simulation dynamics.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗

Detailed comparison of renormalization scale-setting procedures based on the principle of maximum conformality

The Principle of Maximum Conformality (PMC), which generalizes the conventional Gell-Mann-Low method for scale-setting in perturbative QED to non-Abelian QCD, provides a rigorous method for achieving unambiguous scheme-independent, fixed-order predictions for physical observables consistent with the principles of the renormalization group. In addition to the original multi-scale-setting approach (PMCm), two variations of the PMC have been proposed to deal with ambiguities associated with the uncalculated higher order terms in the pQCD series, i.e. the single-scale-setting approach (PMCs) and the procedures based on ``intrinsic conformality" (PMC ∞ ). In this paper, we will give a detailed comparison of these PMC approaches by comparing their predictions for three important quantities R e+e– , R τ , and $Γ(H→b\bar{b}$) up to four-loop pQCD corrections. The PMCs approach determines an overall effective running coupling α s (Q) by the recursive use of the renormalization group equation, whose argument Q represents the actual momentum flow of the process. Our numerical results show that the PMCs method, which involves a somewhat simpler analysis, can serve as a reliable substitute for the full multi-scale PMCm method, and that it leads to more precise pQCD predictions with small residual scale dependence.

73 NUCLEAR PHYSICS AND RADIATION PHYSICS↗

The maximum carboxylation rate of Rubisco affects CO2 refixation in temperate broadleaved forest trees

Mesophyll resistance to CO 2 diffusion (rm) and the maximum carboxylation rate of Rubisco (Vcmax) affect photosynthetic rates, and can potentially also influence the percentage of respiratory and photorespiratory CO 2 being refixated (Pr) by mesophyll cells. Here we investigated how various leaf anatomical traits (e.g. leaf mass per area [LMA] and leaf dry matter content [LDMC]) influenced rm in leaves of mature forest trees. We further explored how rm and Vcmax in turn affected Pr, and if these traits varied among species and leaves along a light gradient. Photosynthetic CO 2 response of leaves grown in high-, medium-, and low-light environments was measured, from Pinus sylvestris [Scots pine], Picea abies [Norway spruce], Quercus robur [English oak], and Betula pendula [Silver birch] in southern Sweden. A modified version of the Farquhar-von Caemmerer-Berry model was fitted to the leaf gas exchange data to estimate Vcmax, rm and Pr. We found that of all leaf traits measured, only LMA for Q. robur was significantly higher in leaves from high-light environments. When comparing species, both rm and LMA were significantly higher in the conifers, and rm had a negative correlation with Vcmax. We found that Pr was similar between different species and functional groups, with an average of 73.2% (and SD of ±10.4) across all species. There was a strong, positive correlation between Pr and Vcmax in broadleaves, and we hypothesise that this effect might derive from a higher CO 2 drawdown near Rubisco in leaves with high Vcmax.

59 BASIC BIOLOGICAL SCIENCES↗

A mechanistic understanding of oxygen isotopic changes in the Western United States at the Last Glacial Maximum

At the Last Glacial Maximum (LGM), records suggest drier conditions in the northwest United States and wetter conditions in the southwest United States relative to present-day as well as widespread changes in the isotopic composition of water. However, the mechanisms responsible for these changes remain ambiguous. Here, we explore differences in western United States hydroclimate between the LGM and preindustrial with a water isotope tracer enabled Earth System Model. We then use proxy forward models to compare simulated and recorded δ 18 O in speleothems. We find that the pattern of hydroclimate response in the western United States at the LGM relates to a combination of 1) increased frequency and southward shifted wintertime extratropical cyclones in the North Pacific, 2) greater rainout of moisture as it moves over the continent, and 3) reduced evaporation in the cooler LGM climate. The simulated lower δ 18 O of precipitation at the LGM relates predominantly to an increase in cool season moisture removal efficiency, with a secondary contribution from relatively more cool season precipitation. Both surface temperatures and North American ice sheets contribute to these hydroclimate changes at the LGM. Comparisons between δ 18 O from proxy forward models and speleothem records in the western United States show general agreement at the LGM, with increasing depletion moving towards the continental interior. Finally, this study highlights the similarities and differences between hydrologic and δ 18 O changes at the LGM and emphasizes the utility of model-proxy comparison for interpretation.

54 ENVIRONMENTAL SCIENCES↗

Climate reconstructions for the Last Glacial Maximum from a simple cirque glacier in Fiordland, New Zealand

Mountain glacier records offer important constraints on the timing and magnitude of climate variability during the last glacial cycle. Existing moraine chronologies from the central Southern Alps indicate maximum ice extent was achieved during marine isotope stages 3–4, followed by repeated advances of similar, but gradually declining extent during marine isotope stage 2, until onset of the glacial termination. Questions remain over the precise role of climate in driving these changes, as most existing moraine chronologies come from large, complex former valley glacier systems, where non-climatic influences such as changing bed topography and proglacial lake formation may have influenced glacier length changes. In this work, we address this problem via a new cosmogenic 10Be chronology and equilibrium line altitude reconstruction from a cirque glacier situated in Fiordland, New Zealand. Our chronology shows moraine deposition at 32 ± 11 ka, 18.7 ± 0.2 ka, 18.1 ± 0.1 ka, and c. 17.2 ± 0.3 ka. The simple geometry of the former glacier supports the role of climate in driving a net decline of regional ice volume during marine isotope stages 3–2. Close spacing and good preservation of the 19–17 ka moraines permits 2D glacier reconstruction which suggests the equilibrium line altitude remained depressed by c.1130 m (equivalent to 5.8 ± 0.6 °C colder than present) during this interval. Onset of warming after 17.2 ± 0.2 ka is consistent with climate proxy evidence for a sustained southward shift in the southern westerly winds, which may have promoted deglaciation via shifting ocean currents and promoting increases in atmospheric carbon dioxide.

54 ENVIRONMENTAL SCIENCES↗

Complex Structural Disorder in a Polar Orthorhombic Perovskite Observed through the Maximum Entropy Method/Rietveld Technique

Ambient pressure stable perovskite oxides with all Bi3+ on the A-site are rare, with only four examples known. Due to the lone pair on Bi 3+ , these materials are seen as the best alternative to Pb-based piezoelectrics, which are used widely in society. The industry standard piezoelectric, Pb (Zr 1 – x Ti x )O 3 , relies on the [001] polarization of PbTiO 3 , but there are currently no ambient pressure stable Bi-based perovskites with this polarization vector, preventing the creation of an analogous system. We present the full structural analysis of the orthorhombic phase of (1 – x)Bi (Ti 3/8 Fe 2/8 Mg 3/8 )O 3 – x CaTiO 3 , which crystallizes in Pna2 1 symmetry with [001] polarization. This symmetry is rare and has only been reported twice for perovskites at ambient conditions. Analysis of maximum entropy method (MEM) models using synchrotron radiation powder X-ray diffraction reveals a disordered A-site configuration, and the MEM/Rietveld technique generates a structural model of this extreme disorder. Combined Rietveld analysis of X-ray and neutron diffraction data yields an accurate description of the local A-site configuration, which we use to understand our dielectric, ferroelectric, and piezoelectric measurements. These results give insight into how to stabilize this unique symmetry and inspire new design principles for Bi-based piezoelectrics.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

Maximum Entropy Theory of Multiscale Coarse-Graining via Matching Thermodynamic Forces: Application to a Molecular Crystal (TATB)

The MSCG/FM (multiscale coarse-graining via force-matching) approach is an efficient supervised machine learning method to develop microscopically informed coarse-grained (CG) models. Here we present a theory based on the principle of maximum entropy (PME) enveloping the existing MSCG/FM approaches. This theory views the MSCG/FM method as a special case of matching the thermodynamic forces from the extended ensemble described by the set of thermodynamic (relevant) system coordinates. This set may include CG coordinates, the stress tensor, applied external fields, and so forth, and may be characterized by nonequilibrium conditions. Following the presentation of the theory, we discuss the consistent matching of both bonded and nonbonded interactions. The proposed PME formulation is used as a starting point to extend the MSCG/FM method to the constant strain ensemble, which together with the explicit matching of the bonded forces is better suited for coarse-graining anisotropic media at a submolecular resolution. The theory is demonstrated by performing the fine coarse-graining of crystalline 1,3,5-triamino-2,4,6-trinitrobenzene (TATB), a well-known insensitive molecular energetic material, which exhibits highly anisotropic mechanical properties.

1,3,5-triamino-2,4,6-trinitrobenzene↗

Equipartition and the Temperature of Maximum Density of TIP4P/2005 Water

Here, we simulate TIP4P/2005 water in the temperature range of 257 to 318 K with time-steps δ = 0.25, 0.50, 1.00, 2.00, and 4.00 fs. The density–temperature behavior obtained using 0.25 or 0.50 fs is in excellent agreement with each other but differs from those obtained using time steps that have been shown earlier to lead to a breakdown of equipartition. For δt = 0.25 or 0.50 fs, the temperature of maximum density (TMD) is 277.15 K and the density value is in close agreement with experiments. For δt = 1.00 fs, the TMD is 277.15 K, but the density value is shifted higher. For the other time steps considered here, the TMD is shifted to progressively lower values for longer time steps, a trend that holds for different thermostat/barostat combinations. Enhancing the water–water dispersion interaction, as has been recommended for simulating disordered proteins in TIP4P/2005, degrades the description of the liquid–vapor phase envelope. We present a simple physically transparent explanation that highlights the separation of the time scales between translational and rotational motion. We also develop a metric, χ, that we term the equipartition anomaly, to detect equipartition violations in simulations that include molecules that are treated as rigid objects. Calculating χ is shown to be straightforward and sensitive to equipartition violations. A key takeaway from this study is that using sufficiently short time steps (≤0.5 fs) to preserve equipartition is essential for obtaining meaningful liquid water properties and for producing reliable simulation data, as correct ensemble sampling is fundamental to ensure reproducibility across codes and simulation algorithms.

Asthagiri, Dilipkumar N. [Oak Ridge National Labor↗

Understanding the Surprising Ionic Conductivity Maximum in Zn(TFSI) 2 Water/Acetonitrile Mixture Electrolytes

Aqueous electrolytes composed of 0.1 M zinc bis-(trifluoromethyl-sulfonyl)-imide (Zn-(TFSI) 2 ) and acetonitrile (ACN) were studied using combined experimental and simulation techniques. The electrolyte was found to be electrochemically stable when the ACN V% is higher than 74.4. In addition, it was found that the ionic conductivity of the mixed solvent electrolytes changes as a function of ACN composition, and a maximum was observed at 91.7 V% of ACN although the salt concentration is the same. This behavior was qualitatively reproduced by molecular dynamics (MD) simulations. Detailed analyses based on experiments and MD simulations show that at high ACN composition the water network existing in the high water composition solutions breaks. As a result, the screening effect of the solvent weakens and the correlation among ions increases, which causes a decrease in ionic conductivity at high ACN V%. Furthermore, this study provides a fundamental understanding of this complex mixed solvent electrolyte system.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

The Evolving Distribution of Relative Humidity Conditional Upon Daily Maximum Temperature in a Warming Climate

Abstract The impacts of heat waves in a warming climate depend not only on changing temperatures but also on changing humidity. Using 35 simulations from the Community Earth System Model Large Ensemble (CESM LENS), we investigate the long‐term evolution of the joint distribution of summer relative humidity (RH) and daily maximum temperature ( Tmax ) near four U.S. cities (New York City, Chicago, Phoenix, and New Orleans) under the high‐emissions Representative Concentration Pathway (RCP) 8.5. We estimate the conditional quantiles of RH given Tmax with quantile regression models, using functions of temperature for each city in July for three time periods (1990–2005, 2026–2035, and 2071–2080). Quality‐of‐fit diagnostics indicate that these models accurately estimate conditional quantiles for each city. As expected, each quantile of Tmax increases from 1990–2005 to 2071–2080, while mean RH decreases modestly. Conditional upon a fixed quantile of Tmax , the median and high quantiles of RH decrease, while those of the Heat Index (HI) and dew point both increase. This result suggests that, despite a modest decrease in median relative humidity, heat stress measured by metrics considering both humidity and temperature in a warming climate will increase faster than that measured by temperatures alone would indicate. For a fixed Tmax , the high quantiles of RH (and thus of HI and dew point) increase from 1990–2005 to 2071–2080 in all four cities. This result suggests that the heat stress of a day at a given Tmax will increase in a warming climate due to the increase of RH.

Yuan, Jiacan↗

Bayesian Poroelastic Aquifer Characterization From InSAR Surface Deformation Data. Part I: Maximum A Posteriori Estimate

Characterizing the properties of groundwater aquifers is essential for predicting aquifer response and managing groundwater resources. In this work, we develop a high-dimensional scalable Bayesian inversion framework governed by a three-dimensional quasi-static linear poroelastic model to characterize lateral permeability variations in groundwater aquifers. In this work, we determine the maximum a posteriori (MAP) point of the posterior permeability distribution from centimeter-level surface deformation measurements obtained from Interferometric Synthetic Aperture Radar (InSAR). The scalability of our method to high parameter dimension is achieved through the use of adjoint-based derivatives, inexact Newton methods to determine the MAP point, and a Mat´ern class sparse prior precision operator. Together, these guarantee that the MAP point is found at a cost, measured in number of forward/adjoint poroelasticity solves, that is independent of the parameter dimension. We apply our methodology to a test case for a municipal well in Mesquite, Nevada, in which InSAR and GPS surface deformation data are available. We solve problems with up to 320,824 state variable degrees of freedom (DOFs) and 16,896 parameter DOFs. A consistent treatment of noise level is employed so that the aquifer characterization result does not depend on the pixel spacing of surface deformation data. Our results show that the use of InSAR data significantly improves characterization of lateral aquifer heterogeneity, and the InSAR-based aquifer characterization recovers complex lateral displacement trends observed by independent daily GPS measurements.

54 ENVIRONMENTAL SCIENCES↗

Isopycnal Submesoscale Stirring Crucially Sustaining Subsurface Chlorophyll Maximum in Ocean Cyclonic Eddies

Abstract Mesoscale and submesoscale processes have crucial impacts on ocean biogeochemistry, importantly enhancing the primary production in nutrient‐deficient ocean regions. Yet, the intricate biophysical interplay still holds mysteries. Using targeted high‐resolution in situ observations in the South China Sea, we reveal that isopycnal submesoscale stirring serves as the primary driver of vertical nutrient transport to sustain the dome‐shaped subsurface chlorophyll maximum (SCM) within a long‐lived cyclonic mesoscale eddy. Density surface doming at the eddy core increased light exposure for phytoplankton production, while along‐isopycnal submesoscale stirring disrupted the mesoscale coherence and drove significant vertical exchange of tracers. These physical processes play a crucial role in maintaining the elevated phytoplankton biomass in the eddy core. Our findings shed light on the universal mechanism of how mesoscale and submesoscale coupling enhances primary production in ocean cyclonic eddies, highlighting the pivotal role of submesoscale stirring in structuring marine ecosystems.

Cao, Haijin↗