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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 19 records
All sourcesNASA NTRSDOE OSTI
DOE OSTI2023

A new method for detecting abrupt changes in the dependence among multivariate hydrological series based on moving cut total correlation

Knowledge of how to define and estimate the dependence among multivariate hydrological series is essential for detecting abrupt changes in the dependence. Here, in this paper, a new method (BMCTC) is proposed to detect all possible abrupt change points in the dependence among multivariate hydrological series. The total correlation estimated by the matrix-based Renyi's alpha-order entropy functional is firstly introduced to define and measure the dependence strength among multivariate hydrological series. Then, the moving cut total correlation (MCTC) sequence is built by the moving window technique, which is used to measure changes in the dependence strength among multivariate hydrological series. Finally, the Bernaola-Galvan algorithm is used to detect all change points of the MCTC sequence. Simulations are performed to compare the effectiveness of BMCTC with Pearson correlation (BMCPC) and Spearman correlation (BMCSC), Cramer-von Mises (CvM) and copula-based likelihood-ratio (CLR). The results show that all change points are detected by BMCTC regardless of the samples size, but wrong change points or no change points are detected by other methods in most cases. BMCTC is applied to detect change points in the dependence among annual runoff, precipitation and sediment discharge series in the Xiliugou and the Kuyehe River, China. It is found that the dependence among runoff, precipitation and sediment discharge changed abruptly in 1980 and 1996 in the Kuyehe River and in 1999 in the Xiliugou River. These changes are mainly caused by human activities such as construction of water conservancy projects and coal mining.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2020

Accurate Atomic Correlation and Total Energies for Correlation Consistent Effective Core Potentials

Very recently, we introduced a set of correlation consistent effective core potentials (ccECPs) constructed within full many-body approaches. By employing significantly more accurate correlated approaches, we were able to reach a new level of accuracy for the resulting effective core Hamiltonians. We also strived for simplicity of use and easy transferability into a variety of electronic structure methods in quantum chemistry and condensed matter physics. Here, as a reference for future use, we present exact or nearly exact total energy calculations for these ccECPs. The calculations cover H–Kr elements and are based on the state-of-the-art configuration interaction (CI), coupled-cluster (CC), and quantum Monte Carlo (QMC) calculations with systematically eliminated/improved errors. In particular, we carry out full CI/CCSD(T)/CCSDT(Q) calculations with cc-pVnZ with up to n = 6 basis sets and we estimate the complete basis set limits. Using combinations of these approaches, we achieved an accuracy of ≈1–10 mHa for K–Zn atoms and ≈0.1–0.3 mHa for all other elements—within about 1% or better of the ccECP total correlation energies. We also estimate the corresponding kinetic energies within the feasible limit of full CI calculations. In order to provide data for QMC calculations, we include fixed-node diffusion Monte Carlo energies for each element that give quantitative insights into the fixed-node biases for single-reference trial wave functions. The results offer a clear benchmark for future high-accuracy calculations in a broad variety of correlated wave function methods such as CI and CC as well is in stochastic approaches such as real space sampling QMC.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2020

The nature of the chemical bond and the role of non-dynamical and dynamical correlation in Be2

In the spin-coupled generalized valence bond (SCGVB) description of Be2, there is a pair of electrons in highly overlapping “inner” orbitals corresponding to a traditional σ bond, but this bond is compromised by Pauli repulsion arising from its overlap with a second “outer” pair. The presence of this outer pair of electrons leads to a repulsive potential energy curve at long range and a bound, but metastable molecule at short range. To obtain further insights into the nature of the bond in Be2, we determined the non-dynamical and dynamical correlation contributions to the potential energy curve of Be2 using four different choices for the zero-order wave function: Restricted Hartree–Fock (RHF), SCGVB, valence-CASSCF(4,4), and valence-CASSCF(4,8). The SCGVB and valence-CASSCF(4,4) wave functions yield similar breakdowns of the total correlation energy, with non-dynamical correlation being the more important contribution. For the RHF and valence-CASSCF(4,8) wave functions, dynamical correlation is critical, without which the potential energy curve is purely repulsive. High accuracy calculations on the HBen−1Be–BeBen−1H molecule as a function of n (n = 1–6) suggest that the intrinsic strength of a Be–Be σ bond uncompromised by Pauli repulsion is on the order of 62–63 kcal/mol, and its length is 2.13–2.14 Å, ∼60 kcal/mol stronger and ∼0.35 Å shorter than in Be2.

Xu, Lu. T. (ORCID:0000000182064902)↗
DOE OSTI2019

Exploring the Random Phase Approximation for Materials and Chemical Physics

In this work we test the performance of the fully nonlocal random phase approximation (RPA) for challenging problems in materials chemistry and physics. In this work we assessed the fully nonlocal random phase approximation (RPA) for the delicate energy differences of interest in materials chemistry and physics. The applications in this proposal are challenges for the simpler approximations of Kohn-Sham density functional theory, which are part of the current “standard model” for quantum chemistry and condensed matter physics. Direct RPA includes the full exact exchange energy and a nonlocal correlation energy from the occupied and unoccupied Kohn-Sham orbitals and orbital energies, with an approximate but universal description of long-range van der Waals attraction. RPA still cannot be a benchmark electronic structure method without a correction for its short-range correlation energy which is too deep. The short-range error of RPA can be corrected by a spatially nonlocal, exchange-only kernel. Such kernels could be a more reliable and “intrinsic” approximation to capture accurate ground-state energy differences than the expensive SOSEX and other beyond-RPA corrections. In this project we revealed the strengths and limitations of some model kernels through some materials problems focusing on structural phase transitions and transition metal chemistry. In addition we demonstrated the accuracy of the Renormalized RPA for total correlation energies of simple solids, and the pressure-induced phase transitions.

36 MATERIALS SCIENCE↗
DOE OSTI2020

A comparative study of the effectiveness of empirical potentials for molecular dynamics simulations of borosilicate glasses

Despite their practical importance, atomistic modeling of B 2 O 3 containing glasses have been challenging due to the lack of reliable empirical potentials. Fortunately, a few recent developments have shown promises to simulate these glasses where the boron coordination has complex and non-linear dependence on glass composition. This work aims to provide an evaluation of the effectiveness of three recently developed potentials by a systematic study of a series (~20) of sodium borosilicate glasses with constant K (ratio of [SiO 2 ]/[B 2 O 3 ]) =2 and varying R (ratio of [Na 2 O]/[B 2 O 3 ] ranging from 0.1 to 4) values and several sodium boroaluminosilicate glasses. A comparative assessment was established on the basis of the short- and medium-range structure features, such as boron N 4 values, total correlation functions, bond angle distribution, oxygen speciation, and mechanical properties using experimental or well-established models as criteria. Furthermore, this work provides insights on the choices of empirical potentials for MD simulations of borosilicate glasses and gives directions of future potential development and refining.

12 MANAGEMENT OF RADIOACTIVE AND NON-RADIOACTIVE W↗
DOE OSTI2019

The Impact of Coordination Environment on the Thermodynamic Stability of Uranium Oxides

Amorphous uranium oxides are acknowledged to arise via industrial processes relevant to the nuclear fuel cycle yet evade rigorous structural characterization. An encouraging approach is to develop statistical relationships between uranium–oxygen coordination environments and thermodynamic stability from which general statements about the likelihood of observing particular U–O arrangements can be made. The number of known crystalline uranium oxides is insufficient to build statistical relationships. We have developed a database of theoretical compounds using genetic algorithms with the density functional theory as a foundation to analyze coordination geometries in the uranium–oxygen phase space. We draw fundamental insights into the nature of uranium–oxygen interactions by correlating total energy with the coordination environment. The most stable configuration of U cations with O anions is in an environment with coordination numbers 5–8 in a cubic configuration. Higher and lower coordination numbers are observed only in metastable phases. General trends are observable in the relationships between the coordination number, density, and uranium fraction in each structure. The new insight into uranium coordination enabled by these analyses is foundational for further studies into the characteristic properties of individual uranium oxide materials and for elucidation of potential oxidation pathways for uranium metal.

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

Molecular-orbital-based machine learning for open-shell and multi-reference systems with kernel addition Gaussian process regression

We introduce a novel machine learning strategy, kernel addition Gaussian process regression (KA-GPR), in molecular-orbital-based machine learning (MOB-ML) to learn the total correlation energies of general electronic structure theories for closed- and open-shell systems by introducing a machine learning strategy. The learning efficiency of MOB-ML(KA-GPR) is the same as the original MOB-ML method for the smallest criegee molecule, which is a closed-shell molecule with multi-reference characters. In addition, the prediction accuracies of different small free radicals could reach the chemical accuracy of 1 kcal/mol by training on one example structure. Accurate potential energy surfaces for the H10 chain (closed-shell) and water OH bond dissociation (open-shell) could also be generated by MOB-ML(KA-GPR). To explore the breadth of chemical systems that KA-GPR can describe, we further apply MOB-ML to accurately predict the large benchmark datasets for closed- (QM9, QM7b-T, and GDB-13-T) and open-shell (QMSpin) molecules.

Chemistry↗
DOE OSTI2025

A Variational Autoencoder Model Toward Molecular Structure Representation Learning of Fuels

Here, in this work, a Variational Autoencoder (VAE)-based data-driven modeling framework is developed with the overarching goal of enabling fuel design. The VAE model is trained on a large dataset with several chemical species to learn a compressed latent space molecular representation. Chemical structure in the form of Simplified Molecular Input Line Entry System (SMILES) string is fed as input, encoded into the VAE latent space, and decoded back to the SMILES string using Long Short-Term Memory (LSTM) networks. Complexities of the VAE training loss function are thoroughly examined by varying the weightage (beta (𝜷) parameter) of the latent space regularization term, thereby assessing the balance between reconstruction accuracy and validity, and focusing on both accurate molecular structure reconstruction and latent space consistency. Two different strategies for 𝜷 variation are evaluated: linear annealing and cyclic annealing. In addition, the impact of total correlation adjustment and hierarchical priors is also studied with regard to the balance between reconstruction fidelity and latent space regularization, and potential issues such as posterior collapse, over-regularization, and poor disentanglement of latent variables. Overall, the best performance of the model is achieved with hierarchical priors and incrementally increasing 𝜷 from 0 to a threshold value of 0.25 over 75 epochs. The generative VAE model can be readily coupled with Quantitative Structure–Property Relationship (QSPR) analysis to develop an integrated end-to-end framework for fuel-property prediction and molecular design of novel promising fuels.

fuel design↗
DOE OSTI2022

Impact of Tree Age and Anatomical Fraction on Forest Residue Pyrolysis and Hydrotreating

Utilization of cost-advantaged biomass and waste resources to produce clean, domestic biofuels will be a key factor in decarbonizing transportation in the United States. This study investigates how the distribution of anatomical fractions (stem wood, bark, needles, branches) from pine forest residues of different ages impacts pyrolysis and hydrotreating processes, including product composition, carbon efficiency, economics, and overall sustainability. Commercially sourced 13- and 23-year-old loblolly pine residues were chosen to represent available resources; whole tree thinnings, and tops and branches from merchantable timber, respectively. Detailed characterization of the residue samples, product distributions, bio-oil, char, and gas characterization data are presented for 13 experiments, including the individual fractions, blends, and air-classified samples to reduce ash content. Pyrolysis mass balances averaged 97 +/- 3%. As expected, bio-oil yields were lower for the bark, needles, and blends with high proportions of these (53-56% dry basis), and highest for the debarked stem wood (67-71% dry basis). Lower yields were attributed to the high ash content of the needles, but also to the high lignin content in the bark (>50%), which is hypothesized to have led to increased char formation during pyrolysis. Higher-oil yield was generally correlated with total volatiles, hydrogen, oxygen, glucan, and mannan; somewhat correlated with xylan and acetyl content; and negatively correlated with total carbon, fixed carbon, nitrogen, sulfur, and extractives. Air classification of the residues was effective in reducing ash content (1.5% to 0.64%), extractives (~7% to 2%), and sulfur (0.04% to 0.02%), resulting in a small increase in yield, a significant increase in the GC-detectable proportion of oil (27% to 34%) and a net economic benefit. These experimental results were used to conduct technoeconomic and life cycle analyses, which are also summarized here.

biofuels↗
DOE OSTI2025

Mobilization of mercury from contaminated creekbank soils

The industrial use of mercury (Hg) led to the contamination of numerous watersheds worldwide, including the East Fork Poplar Creek (EFPC) in Tennessee, USA. Mercury can accumulate in creek banks and floodplain soils and is mobilized into downstream environments due to erosion from precipitation and flooding. Here, this study aimed to evaluate the geochemical conditions contributing to the release of Hg from contaminated soils in this watershed. Bank soil samples from the EFPC watershed with total Hg concentrations ranging from 27.2 to 1,425 mg·kg −1 were used in a series of batch experiments with artificial creek water at a solid-to-solution ratio of 1:30 to assess Hg release. Additional experiments examined Hg release across different soil size fractions and solid-to-solution ratios, as well as the effect of dissolved organic matter and time on Hg mobilization. Mercury release ranged from 0.011 to 0.17% of the total soil Hg and is correlated with total Hg concentrations. Variations in release among size fractions suggested heterogeneous distribution of labile Hg species. Results indicated two distinct solubility regimes depending on solid-to-solution ratios. Dissolved organic matter enhanced Hg release, and time-dependent experiments showed that changes in mercury speciation could decrease dissolved Hg concentrations over time. Identifying conditions that promote Hg mobilization from contaminated soils improves our understanding of Hg fluxes into downstream environments. Key factors influencing mercury release include soil characteristics, water chemistry, and temporal changes in mercury speciation.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2023

Local lattice distortions and electronic orders in strongly correlated systems by resonant total x-ray scattering: A case study of A Pt 2 X 2 intermetallics ( A = U , Ce, or La and X = Si or Ge)

Revealing local lattice distortions in physical systems is nontrivial, largely because such structural features often are not necessarily amenable to traditional crystallographic investigations. This poses limits to our understanding of the underlying physic, particularly in the case of strongly correlated systems where structural, electronic and magnetic degrees of freedom are intertwined. Using resonant total x-ray scattering coupled to differential pair distribution function analysis, we reveal the presence of pronounced local lattice distortions in the square net Pt planes in the prototypical strongly correlated APt 2 X 2 intermetallics (A = U, Ce or La and X = Si or Ge). The distortions are present before charge density wave, magnetic, Kondo lattice coherence and/or superconducting orders emerge in these materials and, as density functional calculations suggest, are likely to affect them. Finally, our study sheds light on the poorly known interactions between electronic orders and structural disorder in strongly correlated systems and also demonstrates an advanced experimental approach to determine it that is relevant to any physical system showing deviations from perfect crystallinity.

75 CONDENSED MATTER PHYSICS, SUPERCONDUCTIVITY AND↗
DOE OSTI2019

Multivariate Pointwise Information-Driven Data Sampling and Visualization

With increasing computing capabilities of modern supercomputers, the size of the data generated from the scientific simulations is growing rapidly. As a result, application scientists need effective data summarization techniques that can reduce large-scale multivariate spatiotemporal data sets while preserving the important data properties so that the reduced data can answer domain-specific queries involving multiple variables with sufficient accuracy. While analyzing complex scientific events, domain experts often analyze and visualize two or more variables together to obtain a better understanding of the characteristics of the data features. Therefore, data summarization techniques are required to analyze multi-variable relationships in detail and then perform data reduction such that the important features involving multiple variables are preserved in the reduced data. To achieve this, in this work, we propose a data sub-sampling algorithm for performing statistical data summarization that leverages pointwise information theoretic measures to quantify the statistical association of data points considering multiple variables and generates a sub-sampled data that preserves the statistical association among multi-variables. Using such reduced sampled data, we show that multivariate feature query and analysis can be done effectively. The efficacy of the proposed multivariate association driven sampling algorithm is presented by applying it on several scientific data sets.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2022

Implications of the correlation between bulge-to-total baryonic mass ratio and the number of satellites for SAGA galaxies

We searched for correlations between the number of satellites and fundamental galactic properties for the Milky Way-like host galaxies in order to better understand their diverse satellite populations. We specifically aim to understand why galaxies that are very similar in stellar mass content, star formation rate, and local environment have very different numbers of satellites. Deep and extensive spectroscopic observations are needed to characterize the complete satellite luminosity function beyond the Local Group. One such endeavor is an ongoing Satellites of Galactic Analogs (SAGA) spectroscopic survey that has completed spectroscopic observations of 36 Milky Way-like galaxies within their virial radii down to the luminosity of Leo I dwarf galaxy. We correlated the number of satellites of SAGA galaxies with several fundamental properties of their hosts – including total specific angular momentum, which is considered to be well preserved throughout galaxy lifetime – in an attempt to identify the main driver of their diverse satellite populations. We aim to reveal some intrinsic galactic property decisive in making more or less satellites irrespective of baryonic mass or the environment in which galaxies reside. We modeled Spitzer Heritage Archive images of SAGA host galaxies at 3.6 and 4.5 microns with GALFIT code to obtain their stellar masses. We also searched the Extragalactic Database for information on their gas content and rotation velocities. Empirical correlations, like the baryonic Tully–Fisher relation and the stellar mass–size relation were used to exclude outliers. All the available galactic properties from the literature along with measured stellar masses were correlated with the number of satellites and no significant correlation was found. However, when we considered the “expected” number of satellites based on the correlation between the baryonic bulge-to-total ratio and the number of satellites confirmed for several nearby galaxies then strong correlations emerge between this number and (1) the mass of the bulge, and (2) the total specific angular momentum. The first correlation is positive, implying that galaxies with more massive bulges have more satellites, as already confirmed. Furthermore, the second correlation with the angular momentum is negative, meaning that, the smaller the angular momentum, the greater the number of expected satellites. This would imply that either satellites cannot form if galaxy angular momentum is too high, or that satellites form inside-out, so that angular momentum is being transferred to the outer parts of the galaxies. However, deeper spectroscopic observations are needed to confirm these findings, because they rely on the expected rather than detected number of satellites. There was a luminosity limit to the SAGA survey equivalent to the luminosity of Leo I dwarf satellite of the Milky Way galaxy (the SAGA limit). In particular, correlations found in this work are very susceptible to the total number of satellites of the NGC 4158 galaxy. This galaxy is predicted to have many more satellites than detected up to the SAGA limit.

79 ASTRONOMY AND ASTROPHYSICS↗
DOE OSTI2020

Taxon-specific microbial growth and mortality patterns reveal distinct temporal population responses to rewetting in a California grassland soil

Abstract Microbial activity increases after rewetting dry soil, resulting in a pulse of carbon mineralization and nutrient availability. The biogeochemical responses to wet-up are reasonably well understood and known to be microbially mediated. Yet, the population level dynamics, and the resulting changes in microbial community patterns, are not well understood as ecological phenomena. Here, we used sequencing of 16S rRNA genes coupled with heavy water (H218O) DNA quantitative stable isotope probing to estimate population-specific rates of growth and mortality in response to a simulated wet-up event in a California annual grassland soil. Bacterial growth and mortality responded rapidly to wet-up, within 3 h, and continued throughout the 168 h incubation, with patterns of sequential growth observed at the phylum level. Of the 37 phyla detected in the prewet community, growth was found in 18 phyla while mortality was measured in 26 phyla. Rapid growth and mortality rates were measurable within 3 h of wet-up but had contrasting characteristics; growth at 3 h was dominated by select taxa within the Proteobacteria and Firmicutes, whereas mortality was taxonomically widespread. Furthermore, across the community, mortality exhibited density-independence, consistent with the indiscriminate shock resulting from dry-down and wet-up, whereas growth was density-dependent, consistent with control by competition or predation. Total aggregated growth across the community was highly correlated with total soil CO2 production. Together, these results illustrate how previously “invisible” population responses can translate quantitatively to emergent observations of ecosystem-scale biogeochemistry.

58 GEOSCIENCES↗
DOE OSTI2025

Structural decomposition of merger-free galaxies hosting luminous AGNs

ABSTRACT Active galactic nucleus (AGN) growth in disc-dominated, merger-free galaxies is poorly understood, largely due to the difficulty in disentangling the AGN emission from that of the host galaxy. By carefully separating this emission, we examine the differences between AGNs in galaxies hosting a (possibly) merger-grown, classical bulge, and AGNs in secularly grown, truly bulgeless disc galaxies. We use galfit to obtain robust, accurate morphologies of 100 disc-dominated galaxies imaged with the Hubble Space Telescope. Adopting an inclusive definition of classical bulges, we detect a classical bulge component in $53.3 \pm 0.5$ per cent of the galaxies. These bulges were not visible in Sloan Digital Sky Survey photometry, however these galaxies are still unambiguously disc-dominated, with an average bulge-to-total luminosity ratio of $0.1 \pm 0.1$. We find some correlation between bulge mass and black hole mass for disc-dominated galaxies, though this correlation is significantly weaker in comparison to the relation for bulge-dominated or elliptical galaxies. Furthermore, a significant fraction ($\gtrsim 90$ per cent) of our black holes are overly massive when compared to the relationship for elliptical galaxies. We find a weak correlation between total stellar mass and black hole mass for the disc-dominated galaxies, hinting that the stochasticity of black hole–galaxy co-evolution may be higher in disc-dominated than bulge-dominated systems.

Fahey, Matthew J.↗
DOE OSTI2023

Molecular Nature of Mineral-Organic Associations within Redox-Active Mountainous Floodplain Sediments

Floodplains are critical terrestrial-aquatic interfaces that act as hotspots of organic carbon (OC) cycling, regulating ecosystem carbon storage as well as export to riverine systems. Within floodplain sediments, regular flooding and textural gradients interact to create dynamic redox conditions. While anaerobic protection of OC upon burial is a well-recognized carbon storage mechanism in redox-active floodplain sediments, the impact of protective mineral-organic associations is relatively unknown. Here we determined the quantitative importance and chemical composition of mineral-organic associations along well-defined redox gradients emerging from textural variations and depth within meander sediments of the subalpine East River watershed (Gothic, CO). Here we characterized mineral-organic associations using a combination of sequential extractions, physical fractionation, and high-resolution mass spectrometry. Across the meander, we found that mineral-associated OC constitutes a significant fraction of total OC, and that extractable iron (Fe) and aluminum (Al) phases as well as high-density isolates were strongly correlated with total OC content, suggesting that mineral-organic associations are quantitatively important for floodplain sediment OC protection. Our mass spectrometry results showed OC associated with increasingly ordered Fe and Al phases are relatively enriched in low-molecular weight, oxidized, aromatic compounds. Surprisingly, however, total OC content showed weak or no correlation with indicators of anaerobic protection, such as relatively bioavailable OC pools (water-extractable and particulate OC) or the molecular weight and oxidation state of OC. Overall, this work highlights that protection of OC bound to reactive mineral phases-in addition to anaerobic protection-can play a quantitatively important role in controlling soil carbon storage in redox-active floodplain sediments.

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

Identification and quantification of distinct active sites in Hf-Beta zeolites for transfer hydrogenation catalysis

Despite the significant progress made in characterizing different framework heteroatom sites that exist in Lewis acidic zeolites with probe molecule adsorption and spectroscopy, methods to reliably quantify site counts remain indefinite and have been primarily limited to Sn and Ti Lewis acid sites. Here, methods to quantify framework Lewis acidic Hf 4+ sites in zeolite Beta (Hf-Beta) with two Lewis base titrants (pyridine, deuterated acetonitrile) were developed using infrared (IR) spectroscopy. Lewis acid site counts for Hf-Beta zeolites were validated by measuring integrated molar extinction coefficients (IMECs; ε, cm μmol –1 ) on Sn-Beta zeolites using identical Lewis base titrants to benchmark site counts with established literature procedures to quantify Lewis acid sites in Beta zeolites from IR spectra. Highlighting the importance of benchmarking active site counts against well-established experimental protocols, IMECs of CD 3 CN bound to open (ε(Sn; 2316 cm –1 ): 1.80 ± 0.25) and closed (ε(Sn; 2308 cm –1 ): 3.76 ± 0.33) Sn sites were ~1.8x larger than those previously reported while total Lewis acid site counts agreed with those measured by pyridine (ε(Sn; 1451 cm –1 ): 1.58 ± 0.16) on six different Sn-Beta zeolites. IMECs measured for IR peaks reflecting pyridine bound to Lewis acidic Hf sites (ε(Hf; 1448 cm –1 ): 1.54 ± 0.21) and CD 3 CN bound to open (ε(Hf; 2313 cm –1 ): 2.40 ± 0.22) and closed (ε(Hf; 2307 cm –1 ): 3.55 ± 0.41) Hf sites, gave similar counts for the total number of Lewis acidic sites across six Hf-Beta zeolites (Si/Hf = 100–413). Consistent with previous reports with Sn-Beta catalysts where open Sn sites are responsible for catalytic turnover, apparent first and zero-order MPVO rate constants (0.01–1 M cyclohexanone in 2-butanol; per total Hf, 373 K) correlated with the total number of open Hf sites, per total Hf, but not with the total number of closed Hf sites or total Lewis acid site counts. Measured initial MPVO rates (0.1 M cyclohexanone in 2-butanol, per open Hf, 373 K) were ~25x higher on hydrophobic Hf-Beta-F than on hydrophilic Hf-Beta-OH zeolites. Overall, the apparent first-order MPVO rate constants (2-butanol solvent, per open Hf, 373 K) were ~6x higher on Hf-Beta-F than on Hf-Beta-OH zeolites. The characterization methods reported here enable normalization of MPVO turnover rates on Sn- and Hf-Beta zeolites by their number of open sites. Finally, this enables performing quantitative rate comparisons across Lewis acid zeolites of varying active site identity, solvation, and pore topology used in liquid-phase catalysis.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2023

Performance of Fire Danger Indices and Their Utility in Predicting Future Wildfire Danger Over the Conterminous United States

Abstract Predicting current and future wildfire frequency and size is central to wildfire control and management. Multiple fire danger indices (FDIs) that incorporate weather and fuel conditions have been developed and utilized to support wildfire predictions and risk assessment. However, the scale‐dependent performance of individual FDIs remains poorly understood, which leads to large uncertainty in the estimated fire sizes under climate change. Here, we calculate four commonly used FDIs over the conterminous United States using high‐resolution (4 km) climate and fuel data sets for the 1984–2019 period. The relationships of these four FDIs to the observed wildfire sizes show that higher values of FDIs correlate to larger total fire sizes; this correlation is more robust at larger spatial scales. Sensitivity analysis indicates that the daily minimum relative humidity and precipitation are the most important drivers of the annual mean fire danger. In the instances of extreme fire danger, wind speed becomes a critical factor and should be considered in the calculation of the FDI. To assess the impact of climate change on future fire size, we calculate the present‐day and end‐of‐century FDIs using the 12 km regional climate model simulations. The four FDIs generally predict consistent changes in future fire potential, suggesting an overall higher fire potential in conjunction with a prolonged wildfire season in future climate. Regionally, the four FDIs also reveal similar seasonal patterns as the enhancement arises mostly in spring and summer over the southwest US while in summer and fall over the northern and eastern US.

54 ENVIRONMENTAL SCIENCES↗