Engineering Papers⌕ Search

SEARCH · Engineering Papers

Results for “Model assignment”

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.

Quote a phrase for an exact phrase match. Source license links do not imply unrestricted reuse.

At least 235 records · Page 13
All sourcesNASA NTRSDOE OSTI
DOE OSTI2024

Improving gas adsorption modeling for MOFs by local calibration of Hubbard U parameters

While computational screening with density functional theory (DFT) is frequently employed for the screening of metal–organic frameworks (MOFs) for gas separation and storage, commonly applied generalized gradient approximations (GGAs) exhibit self-interaction errors, which hinder the predictions of adsorption energies. We investigate the Hubbard U parameter to augment DFT calculations for full periodic MOFs, targeting a more precise modeling of gas molecule–MOF interactions, specifically for N2, CO2, and O2. We introduce a calibration scheme for the U parameter, which is tailored for each MOF, by leveraging higher-level calculations on the secondary building unit (SBU) of the MOF. When applied to the full periodic MOF, the U parameter calibrated against hybrid HSE06 calculations of SBUs successfully reproduces hybrid-quality calculations of the adsorption energy of the periodic MOF. The mean absolute deviation of adsorption energies reduces from 0.13 eV for a standard GGA treatment to 0.06 eV with the calibrated U, demonstrating the utility of the calibration procedure when applied to the full MOF structure. Furthermore, attempting to use coupled cluster singles and doubles with perturbative triples calculations of isolated SBUs for this calibration procedure shows varying degrees of success in predicting the experimental heat of adsorption. It improves accuracy for N2 adsorption for cases of overbinding, whereas its impact on CO2 is minimal, and ambiguities in spin state assignment hinder consistent improvements of O2 adsorption. Our findings emphasize the limitations of cluster models and advocate the use of full periodic MOF systems with a calibrated U parameter, providing a more comprehensive understanding of gas adsorption in MOFs.

Chemistry↗
DOE OSTI2026

Influence of Numerical Modeling Approaches on Damped Behavior of Flexible Beams: Preprint

Composites structures are widely used in aerospace and wind energy applications for their excellent stiffness and strength-to-weight properties. In these structures, structural damping is critical to predict vibration amplitudes, performance, and reliability. Structural damping is of particular interest for slender wings, rotorcraft blades, and wind turbine blades that can exhibit complex vibration phenomena and are frequently modeled with geometrically exact beam theory (GEBT). Standard approaches of stiffness proportional or modal damping merely assign user defined values and cannot predict damping behavior. This work compares stiffness proportional damping to two more advanced damping approaches: modal strain energy and Prony series. The modal strain energy approach uses a sectional analysis tool to calculate the beam stiffness and postprocess internal stresses from GEBT simulations. The internal stresses are then used to calculate modal damping factors. The Prony series is implemented within GEBT to directly model viscoelastic behavior of the composites. These approaches are compared by modeling the evolution of the damping factors of a realistic flexible wind turbine blade with varying rotational speed. Discrepancies between the approaches suggest areas for future modeling development, but differences in nonlinear damping values are less than current uncertainties about the magnitude of structural damping.

17 WIND ENERGY↗
DOE OSTI2024

Stock-specific spatial overlap among seabird predators and Columbia River juvenile Chinook Salmon suggests a mechanism for predation during early marine residence

Abstract Objective Because predation is thought to be the primary source of natural mortality for juvenile salmon first entering the ocean, we sought to identify regions where, on average, stock-specific spatial overlap between the distribution of threatened and endangered juvenile Chinook Salmon Oncorhynchus tshawytscha and abundant fish-eating seabirds (common murres Uria aalge and sooty shearwaters Ardenna grisea) suggests the greatest potential for ocean predation risk to juvenile Chinook Salmon. Methods The relative abundance and spatial distribution of seabird predators and juvenile Chinook Salmon were quantified as part of long-term ecosystem surveys during May 2003–2012 and June 2003–2022. Genetic stock identification methods were used to assign individual fish to their respective stock groups. Stock-specific species distribution models then generated maps and indices of average annual spatial overlap between predators and prey within the survey area. Result There is unequivocal evidence for spatial overlap between common murres, sooty shearwaters, and five genetic groups of interior and lower Columbia River juvenile Chinook Salmon. We found strongly positive (≥0.70) spatial correlations between predator and prey densities in both May and June, although spatial overlap was, in general, greater during May. The region of highest spatial overlap occurred on the inner continental shelf between the Columbia River mouth (46.2°N) and Grays Harbor (47.0°N), a region at the beginning of the juvenile salmon migratory pathway that is strongly affected by freshwater outflow from the river. Conclusion Our findings support the idea that ocean avian predation during early marine residence has the potential to affect marine survival of juvenile Chinook Salmon and should be further investigated to better inform and implement ecological models and possible recovery actions for Chinook Salmon populations of the Columbia River basin.

Zamon, Jeannette E.↗
DOE OSTI2026

Deciphering the excited-state landscape of Cr(iii) tris(diimines) using [Cr(phen) 3 ] 3+

Earth-abundant Cr(III) polypyridines chromophores feature long-lived doublet ligand-field excited states. The thermally equilibrated 2 T 1 / 2 E ligand-field excited state manifold produces broad, structured UV-Vis-NIR absorption bands. Although ubiquitous across pseudo-octahedral Cr(III) diimine complexes, the dynamics and individual electronic transitions underlying these spectra have remained elusive. Here, we combine time-resolved spectroscopy and multiconfigurational calculations to assign ground- and excited-state absorption spectra of Cr(III) tris(1,10-phenanthroline), [Cr(phen) 3 ] 3+ , as a prototypical example for this class of complexes. Excited-state kinetics reveal a rapid biexponential decay of the initially prepared intraligand/ligand-to-metal charge transfer [ 4 ( 1 IL)/ 4 LMCT] excited state into the lowest 2 T 1 / 2 E state within 10 picoseconds, assigned to intersystem crossing and vibrational relaxation. Calculations identify broad excited-state absorption features associated with metal-centered ligand-field states ( 2 MC) mixed with intraligand ( 2 IL) transitions within the doublet manifold. These results provide detailed spectral assignments and highlight the need to include multiconfigurational ligand-based orbitals when modeling the spectral properties of Cr(III) coordination complexes.

Barth, Alexandra T. [North Carolina State Universi↗
DOE OSTI2021

Cross-shell excitations in Ca 46 studied with fusion reactions induced by a reaccelerated rare isotope beam

Discovering unexplored high-spin states in neutron-rich nuclei can open up a new direction to study band structure and the associated shell structure in isospin-asymmetric many-body systems. However, experimental reach has so far been limited to neutron-deficient or stable nuclei which are preferentially produced in fusion reactions used in such studies. Here in this paper, we report the first γ-ray spectroscopy with fusion reactions using a reaccelerated rare-isotope beam of 45 K performed at the ReA3 facility of the National Superconducting Cyclotron Laboratory. Using particle and γ-ray coincidence techniques, three new higher-lying states around 6 MeV and five new γ-ray transitions were identified for 46 Ca, suggesting three independent band structures formed from different particle-hole configurations. The rotational-like band built on the 0$^+_2$ state is established up to the tentatively assigned 6$^+_2$ state. New results are compared to large-scale shell model calculations, confirming the validity of the effective interaction describing particle-hole excitations across the Z=20 and N=28 shell gaps in the vicinity of doubly-magic 48 Ca.

73 NUCLEAR PHYSICS AND RADIATION PHYSICS↗
DOE OSTI2022

β decay of neutron-rich 76 Cu and the structure of 76 Zn

In this work, the β decay of 76 Cu to the levels of 76 Zn was studied at the Holifield Radioactive Ion Beam Facility (HRIBF) at Oak Ridge National Lab (ORNL). A purified 76 Cu beam was developed and data were recorded for the decay of the A=76 decay chain using four high-purity germanium (HPGe) clover detectors at the Low-energy Radioactive Ion Beam Spectroscopy Station (LeRIBSS). In this measurement, data on γ-ray emission following β decay, including βγ and γγ coincidences, were collected and γγ spectra were analyzed to identify the statistically significant coincidences. From this analysis, we propose a level scheme for 76 Zn which contains a total of 59 energy levels up to 6.0 MeV containing 105 γ rays. We have identified an additional 53 γ rays associated with this decay which could not be place in the decay scheme due to insufficient coincidence information or no energy match to identified levels. No γ rays from states in 75 Zn fed in the delayed-neutron branch were observed even though other γ rays in the A=75 decay chain were observed. Spin and parity assignments are proposed for some levels based on comparison to systematics and shell model calculations.

73 NUCLEAR PHYSICS AND RADIATION PHYSICS↗
DOE OSTI2022

The Pantheon+ Analysis: Evaluating Peculiar Velocity Corrections in Cosmological Analyses with Nearby Type Ia Supernovae

Separating the components of redshift due to expansion and peculiar motion in the nearby universe (z < 0.1) is critical for using Type Ia Supernovae (SNe Ia) to measure the Hubble constant (H 0 ) and the equation-of-state parameter of dark energy (w). Here, we study the two dominant "motions" contributing to nearby peculiar velocities: large-scale, coherent-flow (CF) motions and small-scale motions due to gravitationally associated galaxies deemed to be in a galaxy group. We use a set of 584 low-z SNe from the Pantheon+ sample, and evaluate the efficacy of corrections to these motions by measuring the improvement of SN distance residuals. We study multiple methods for modeling the large and small-scale motions and show that, while group assignments and CF corrections individually contribute to small improvements in Hubble residual scatter, the greatest improvement comes from the combination of the two (relative standard deviation of the Hubble residuals, Rel. SD, improves from 0.167 to 0.157 mag). We find the optimal flow corrections derived from various local density maps significantly reduce Hubble residuals while raising H 0 by ~0.4 km s -1 Mpc -1 as compared to using CMB redshifts, disfavoring the hypothesis that unrecognized local structure could resolve the Hubble tension. We estimate that the systematic uncertainties in cosmological parameters after optimally correcting redshifts are 0.06–0.11 km s -1 Mpc -1 in H 0 and 0.02–0.03 in w which are smaller than the statistical uncertainties for these measurements: 1.5 km s -1 Mpc -1 for H 0 and 0.04 for w.

79 ASTRONOMY AND ASTROPHYSICS↗
DOE OSTI2022

Muonic force behind flavor anomalies

We develop an economical theoretical framework for combined explanations of the flavor physics anomalies involving muons: (g - 2) μ , R K(*), and b → sμ + μ - angular distributions and branching ratios, that was first initiated by some of us in ref. [1]. The Standard Model (SM) is supplemented with a lepton-flavored U(1) X gauge group. The U(1) X gauge boson with the mass of O(0.1) GeV resolves the (g - 2) μ tension. A TeV-scale leptoquark, charged under the U(1) X , carries a muon number and mediates B-decays without prompting charged lepton flavor violation or inducing proton decay. We explore the theory space of the chiral, anomaly-free U(1) X gauge extensions featuring the above scenario, and identify many suitable charge assignments for the SM+3ν R fermion content with the integer charges in the range X F i $\in$ [-10, 10]. We then carry out a comprehensive phenomenological study of the muonic force in representative benchmark models. Interestingly, we found models which can resolve the tension without conflicting the complementary constraints, and all of the viable parameter space will be tested in future muonic resonance searches. Finally, the catalog of the anomaly-free lepton-non-universal charge assignments motivated us to explore different directions in model building. We present a model in which the muon mass and the (g - 2) μ are generated radiatively from a common short-distance dynamics after the U(1) X breaking. We also show how to charge a vector leptoquark under U(1) μ-τ in a complete gauge model.

72 PHYSICS OF ELEMENTARY PARTICLES AND FIELDS↗
DOE OSTI2023

Evaluating U.S. Natural Gas Environmental Performance

This work summarizes the U.S. Department of Energy National Energy Technology Laboratory's (NETL) modeling and analysis of natural gas environmental performance. Over the past year, NETL updated its U.S. natural gas supply chain life cycle baseline model to incorporate 2020 data, regionalize the transmission and distribution network into six regions, incorporate improved gathering and boosting stage and distribution stage emissions factors, and assign environmental burdens among the various co-products (i.e., crude oil, natural gas liquids, natural gas) of the natural gas supply chain. The updated natural gas model helps generate more comprehensive and regionalized natural gas profiles, mapping production basins to the relevant transmission and distribution regions downstream. The work incorporates data from multiple peer reviewed measurement-based studies to achieve the objective of providing a comprehensive understanding of emissions from the U.S. natural gas supply chain. This presentation also explores future work by NETL to develop a platform that enables stakeholders to customize key parameters within the natural gas LCA model and observe the corresponding effects on the carbon intensity of the overall supply chain. The platform aims to offer a convenient method for stakeholders to obtain relevant insights from the updated model, without diving deep into the intricacies of the NETL natural gas model with hundreds of parameters and linkages.

Khutal, Harshvardhan↗
DOE OSTI2020

Optimizing workplace charging facility deployment and smart charging strategies

This study introduces a workplace charging (WPC) optimization model that maximizes the total satisfied electric miles of employees’ plug-in electric vehicles, subject to a given annual budget. The model optimizes both planning decisions of charger number and power levels and operation decisions of charging spot assignment and charging schedule for the given temporal distribution of charging demands and varied electricity prices. Results of experiments based on national average travel data indicate that the actual WPC strategy varies by budget level. Through optimization, the strategy could reduce impacts of the varied electricity price by shifting charging schedules to periods when electricity prices are low. Also, the model is expanded to study the trade-off between providing WPC and addressing consequence of degraded charging service by including the per-mile shadow cost of unsatisfied charging demand. Finally, we observe that their relative competitiveness mainly depends on the actual shadow cost of WPC.

33 ADVANCED PROPULSION SYSTEMS↗
DOE OSTI2026

An improved dataset for predicting mammal infecting viruses from genetic sequence information

There have been several attempts to develop machine learning (ML) models to identify human infecting viruses from their genomic sequences, with varying degrees of success. Direct comparison between models is problematic, because these models are typically trained and evaluated on different datasets with alternative data splitting schemes, features, and model performance metrics. In this paper we present a standardized dataset of mammal infecting and non-infecting viral pathogens, refined from the previous work of Mollentze et al. to include the latest literature evidence, roughly doubling the number of curated host-virus records available to the community, and new host target labels, primate and mammal. The new host labels were included for several reasons, including previous reports that classification performance is better at broader taxonomic ranks and the idea that there may be more data for primate infection that might serve as a suitable proxy for zoonotic potential and avoidance of false positives for human infection due to absence of evidence. On this dataset, we report the performance of eight machine learning models for predicting mammal-infecting viruses from their genomic sequences. We find that randomly assigning cases in our improved dataset to training/testing sets, when compared to the original assignments into training/testing in Mollentze et al., increases the overall average ROC AUC of prediction of human infection from 0.663 ± 0.070 to 0.784 ± 0.013, consistent with the reduction in phylogenetic distance between train and test sets (relative entropy change from 3.00 to 0.08). The broadest host category of mammal infection can be predicted most reliably at 0.850 ± 0.020. We share our improved dataset and code to enable standardized comparisons of machine learning methods to predict human host infections. Overall, we have presented preliminary evidence that classification of virus host infection is more tractable at higher taxonomic ranks, that unsurprisingly reducing the phylogenetic distance between training and test sets can improve predictive performance, that peptide kmer features appear to be harmful to out of sample model performance, and we are left with the question of whether models for virus host prediction can reasonably be expected to perform well in out of sample scenarios given the likelihood that viruses do not share a common ancestor. Consistent with this concern, when the data is resampled such that there is no overlap between viral families in training and test sets (relative entropy > 24), models perform no better than random chance at prediction of human infection regardless of whether kmers are included (ROC AUC 0.50 ± 0.08) or not (ROC AUC 0.50 ± 0.04).

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2024

Probabilistic projections of the Amery Ice Shelf catchment, Antarctica, under conditions of high ice-shelf basal melt

Abstract. Antarctica's Lambert Glacier drains about one-sixth of the ice from the East Antarctic Ice Sheet and is considered stable due to the strong buttressing provided by the Amery Ice Shelf. While previous projections of the sea-level contribution from this sector of the ice sheet have predicted significant mass loss only with near-complete removal of the ice shelf, the ocean warming necessary for this was deemed unlikely. Recent climate projections through 2300 indicate that sufficient ocean warming is a distinct possibility after 2100. This work explores the impact of parametric uncertainty on projections of the response of the Lambert–Amery system (hereafter “the Amery sector”) to abrupt ocean warming through Bayesian calibration of a perturbed-parameter ice-sheet model ensemble. We address the computational cost of uncertainty quantification for ice-sheet model projections via statistical emulation, which employs surrogate models for fast and inexpensive parameter space exploration while retaining critical features of the high-fidelity simulations. To this end, we build Gaussian process (GP) emulators from simulations of the Amery sector at a medium resolution (4–20 km mesh) using the Model for Prediction Across Scales (MPAS)-Albany Land Ice (MALI) model. We consider six input parameters that control basal friction, ice stiffness, calving, and ice-shelf basal melting. From these, we generate 200 perturbed input parameter initializations using space filling Sobol sampling. For our end-to-end probabilistic modeling workflow, we first train emulators on the simulation ensemble and then calibrate the input parameters using observations of the mass balance, grounding line movement, and calving front movement with priors assigned via expert knowledge. Next, we use MALI to project a subset of simulations to 2300 using ocean and atmosphere forcings from a climate model for both low- and high-greenhouse-gas-emission scenarios. From these simulation outputs, we build multivariate emulators by combining GP regression with principal component dimension reduction to emulate multivariate sea-level contribution time series data from the MALI simulations. We then use these emulators to propagate uncertainty from model input parameters to predictions of glacier mass loss through 2300, demonstrating that the calibrated posterior distributions have both greater mass loss and reduced variance compared to the uncalibrated prior distributions. Parametric uncertainty is large enough through about 2130 that the two projections under different emission scenarios are indistinguishable from one another. However, after rapid ocean warming in the first half of the 22nd century, the projections become statistically distinct within decades. Overall, this study demonstrates an efficient Bayesian calibration and uncertainty propagation workflow for ice-sheet model projections and identifies the potential for large sea-level rise contributions from the Amery sector of the Antarctic Ice Sheet after 2100 under high-greenhouse-gas-emission scenarios.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2026

Genomic Language model for Annotation of Repetitive Elements (GLARE) v1.0

GLARE (Genomic Language model for Annotation of Repetitive Elements) is a tool that classifies transposable elements (TEs)—the mobile, repetitive DNA sequences that make up large fractions of eukaryotic genomes. GLARE fine-tunes the NTv3-650M genomic language model on a harmonized collection of curated TE sequences from the PanTEon and Repbase reference databases, assigning each input sequence to one of 11 orders and 32 superfamilies in a Wicker-compatible taxonomy. Features. From nucleotide FASTA input, GLARE outputs per-sequence predictions, class summaries, composition figures, and an annotated FASTA. It provides calibrated confidence scores with optional abstention and runs on CPU or GPU. Uses. GLARE serves as a classification component in genome-annotation pipelines, downstream of TE discovery, supporting genome annotation and comparative and evolutionary genomics. Advantages. GLARE is the first repeat-element classifier to leverage a pretrained genomic language model. Combined with multi-database training, this approach outperformed all nine classifiers in the PanTEon benchmark, generalized better to unseen taxonomic clades, and remained robust to sequence orientation—a common failure mode of existing tools.

Bruna, Tomas [Lawrence Berkeley National Laborator↗
DOE OSTI2021

MACAW v1.0

The ability to embed molecules in a numeric space is essential in order to build mathematical and machine-learning models describing molecular properties or other processes affected by molecules. MACAW is a cheminformatic tool that allows embedding small molecules into a multidimensional numeric space. In the embedding, each molecule is assigned a numeric vector that captures information of the molecule in relation to other molecules, and that vector can be used as input to mathematical models. Molecules that are more similar to each other are embedded closer in this numeric space, whereas molecules that are more different are embedded further away. One advantage of the MACAW embedding technology compared to established alterantives is that it is fast and does not require extensive computational resources or expertise. In particular, MACAW embeddings can be used as input to mathematical models without the need for variable cleaning or feature selection, saving time and simplifying their use. On the other hand, MACAW also contains methods to generate new molecules and to recommend new molecules satisfying a desired molecular property. The generation of new molecules can be biased based on an input set of molecules, effectively generating molecular diversity around it. In its turn, MACAW's molecular recommendation tool is a novel method for evolving molecules in silico towards a desired molecular specification. In this method, the biased molecular generator tool is applied iteratively in combination with a molecular selection step. As a result, in each iteration the molecules selected by the software are increasingly closer to the desired specification. Both the molecular generation and the molecular recommendation tools are very fast, efficient, and intuitive to use.

Roger, VincentBlay↗
DOE OSTI2026

Optimizing Porous Transport Layer Porosity for Proton Exchange Membrane Water Electrolysis

An empirical model is presented that describes anode-side losses related to porous transport layer (PTL) morphology in proton exchange membrane water electrolysis (PEMWE). The model is based on an advanced voltage breakdown analysis that links various overpotentials to PTL morphology. Custom Ti PTLs, spanning uncommonly low porosities (22 - 31%), were fabricated and analyzed with X-ray CT to obtain pore and particle size distributions. Particle size distributions were consistent across samples with an average particle diameter of 12.0?..mu..m, whereas average pore diameters ranged from 6.0 to 7.0?..mu..m. The PTLs were tested in standard PEMWE cell assemblies with anode catalyst loadings of 0.1 mgIr cm-2 to obtain polarization curves, electrochemical impedance spectra, and augmented Tafel analysis. The PTL-dependent anode side losses were deconvoluted and assigned to excess utilization, concentration, ion transport resistance, and electrical contact resistance overpotentials. The data and model reveal an optimal 20 - 28% PTL porosity region where utilization and contact resistance overpotentials are minimized without triggering concentration and ion transport losses related to water deprivation. The optimal PTL porosity depends on the operating current density and is demonstrated at realistic PEMWE water flow rates to establish PTL design guidance for operation at scale.

08 HYDROGEN↗
DOE OSTI2022

Inverse Calculation of Burden Distribution Matrix Using B-spline Model Based PDF control in Blast Furnace Burden Charging Process

The inverse calculation of burden distribution matrix (BDM) is one of the most important challenges in the blast furnace operation in iron-making processes. In general, blast furnace consumes 65% of the total energy for the whole steel-making. Focusing on this practical challenge, this article proposes a new burden distribution spatial model in calculating burden charging process, and develops a B-spline approximation-based probability density function (PDF) control algorithm to assign the expected thickness distribution of burden layer and, thus, develops a new method for the required inverse calculation of BDM. First, a novel method for the thickness distribution of burden layer is given using B-spline model to produce an expected distribution shape subjected to a desired tracking within a specific spatial constraint. Then, according to the coexistence of continuous and bounded discrete variables in BDM, a novel hybrid optimization control method by combining integer programming and PDF tracking is further established for the effective inverse calculation of BDM. Finally, the proposed PDF-based iterative inverse calculation of BDM using B-spline models are tested using various data from industrial examples. Furthermore, the simulation results show that the proposed method is well suited to solve the BDM inverse calculation problem in practice.

42 ENGINEERING↗
DOE OSTI2022

Existence of tidal tails for the globular cluster NGC 5824

Context: Several dynamically cold streams have been associated with certain globular clusters (GCs) based on orbital energies and angular momenta. Some of these streams are surprisingly far apart from their progenitors and one such pair is Triangulum and NGC 5824. Triangulum can be considered as a piece of the leading tail of NGC 5824 since the cluster’s future orbit matches well with the stream’s track. The existence of the leading tail of NGC 5824 is the motivation behind the search for its trailing tail. Aims: Our goal is to confirm the connection between Triangulum and NGC 5824. We also search for the trailing tail of the cluster. Methods: The selection of member stars of Triangulum is made through various cuts in metallicity, proper motions (PMs), radial velocity and a color–magnitude diagram (CMD). The selected members are compared in phase space to a mock stream that models the disruption of NGC 5824. We then try to detect the trailing tail of the cluster based on a modified matched-filter technique. Stars are assigned weights using their color differences from the cluster’s locus in the CMD. These weights are further scaled, based on the stars’ departures from expected PMs of the model stream. Results: A total of 26 member stars for Triangulum are obtained, 16 of which are newly identified. These members are consistent with the mock stream in the phase space, and their metalicity and position on the CMD are in good agreement with NGC 5824. By applying the matched filter, a tenuous trailing tail of the cluster is detected, spanning ~50° long on sky. The signature matches well with the mock stream’s trajectory. Conclusions: Our results support that the Triangulum stream acts as a part of the leading tail for NGC 5824. On the trailing side, we detected a 50° tail extending from the cluster. The existence of both leading and trailing tails for the GC NGC 5824 is verified.

79 ASTRONOMY AND ASTROPHYSICS↗
DOE OSTI2021

Compositional analysis of organosolv poplar lignin by using high-performance liquid chromatography/high-resolution multi-stage tandem mass spectrometry

Organosolv treatment is an efficient and environmentally friendly process to degrade lignin into small compounds. The capability of characterizing the individual compounds in the complex mixtures formed upon organosolv treatment is essential for the optimization of the further lignin conversion processes and for the rational genetic engineering of plants used to produce lignin in order to improve lignin properties. In this study, an organosolv poplar lignin sample was initially analyzed by high-resolution mass spectrometry coupled with negative-ion mode electrospray ionization ((-)ESI HRMS). Lignin monomers and dimers were found to constitute the majority of the compounds in the organosolv lignin sample. Larger lignin oligomers, such as trimers and tetramers, and some not lignin-related compounds, were also detected. A high-performance liquid chromatograph/linear quadrupole ion trap/orbitrap mass spectrometer capable of multi-stage high-resolution tandem mass spectrometry experiments (HRMS n ), equipped with an (-)ESI source (HPLC/(-)ESI HRMS n ), was employed to separate the unknown compounds in the organosolv mixture and to obtain structural information for the deprotonated compounds via collision-activated dissociation (CAD) HRMS n experiments. To improve the understanding of the CAD behavior of deprotonated lignin-related compounds, 16 deprotonated model compounds with different functionalities and linkage types were examined. This approach enabled the assignment of likely structures for several lignin monomers, dimers, trimers, and tetramers, and some not lignin-related compounds, most likely fatty acids. Based on the proposed structures, compounds in the organosolv lignin sample contain β-O-4, 5–5, β-5, and possibly also 4-O-5 linkages. Most compounds contain G- and S-monomeric units although a small amount of H-units were also detected.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗