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DOE OSTI2021

Investigations of water/oxide interfaces by molecular dynamics simulations

Water/oxide interfaces are ubiquitous on earth and show significant influence on many chemical processes. For example, understanding water and solute adsorption as well as catalytic water splitting can help build better fuel cells and solar cells to overcome our looming energy crisis; the interaction between biomolecules and water/oxide interfaces is one hypothesis to explain the origin of life. However, knowledge in this area is still limited due to the difficulty of studying water/solid interfaces. As a result, research using increasingly sophisticated experimental techniques and computational simulations has been carried out in recent years. Although it is difficult for experimental techniques to provide detailed microscopic structural information, molecular dynamics (MD) simulations have satisfactory performance. In this report, we discuss classical and ab initio MD simulations of water/oxide interfaces. Generally, we are interested in the following questions: How do solid surfaces perturb interfacial water structure? How do interfacial water molecules and adsorbed solutes affect solid surfaces and how do interfacial environments affect solvent and solute behavior? Finally, we discuss progress in the application of neural network potential based MD simulations, which offer a promising future because this approach has already enabled ab initio level accuracy for very large systems and long trajectories.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

DOE OSTI2023

HPLC-Parallel accelerator and molecular mass spectrometry analysis of 14 C-labeled amino acids

Accelerator mass spectrometry (AMS) is the method of choice for quantitation of low amounts of 14 C-labeled biomolecules. Despite exquisite sensitivity, an important limitation of AMS is its inability to provide structural information about the analyte. This limitation is not critical when the labeled compounds are well-characterized prior to AMS analysis. However, analyte identity is important in other experiments where, for example, a compound is metabolized and the structures of its metabolites are not known. We previously described a moving wire interface that enables direct AMS measurement of liquid sample in the form of discrete drops or HPLC eluent without the need for individual fraction collection, termed liquid sample-AMS (LS-AMS). Here, we now report the coupling of LS-AMS with a molecular mass spectrometer, providing parallel accelerator and molecular mass spectrometry (PAMMS) detection of analytes separated by liquid chromatography. The repeatability of the method was examined by performing repeated injections of 14 C-labeled tryptophan, and relative standard deviations of the 14 C peak areas were ≤10.57% after applying a normalization factor based on a standard. Five 14 C-labeled amino acids were separated and detected to provide simultaneous quantitative AMS and structural MS data, and AMS results were compared with solid sample-AMS (SS-AMS) data using Bland-Altman plots. To demonstrate the utility of the workflow, yeast cells were grown in a medium with 14 C-labeled tryptophan. The cell extracts were analyzed by PAMMS, and 14 C was detected in tryptophan and its metabolite kynurenine.

38 RADIATION CHEMISTRY, RADIOCHEMISTRY, AND NUCLEA↗

DOE OSTI2022

Improved Distributed-memory Triangle Counting by Exploiting the Graph Structure

Graphs are ubiquitous in modeling complex systems and representing interactions between entities to uncover structural information of the domain. Traditionally, graph analytics workloads are challenging to efficiently scale (both strong and weak cases) on distributed memory due to the irregular memory-access driven nature (with little or no computations) of the methods. The structure of graphs and their relative distribution over the processing elements poses another level of complexity, making it difficult to attain sustainable scalability across platforms. In this paper, we discuss enhancements to TriC, a distributed-memory implementation of graph triangle counting using Message Passing Interface (MPI), which was featured in the 2020 Graph Challenge competition. We have made some incremental enhancements to TriC, primarily adopting a user-defined buffering strategy to overcome the startup problem for large graphs (by fixing the memory for intermediate data), and experimenting with probabilistic data structures such as bloom filter to improve the query response time for assessing edge existence, at the expense of increasing the overall false positive rate. These adjustments have led to a modest improvements in most cases, as compared to the previous version.

Graph Analytics, HPC↗

DOE OSTI2024

Cyclable Variable Path Length Multilevel Structures for Lossless Ion Manipulations (SLIM) Platform for Enhanced Ion Mobility Separations

Ion mobility-mass spectrometry (IMS-MS) is increasingly used to analyze complex samples and provide structural information of unknown compounds. As the complexity of samples increases, there is a need to improve the resolution of IMS-MS instruments to increase the rate of molecular identification. In this work, we evaluated a cyclable and variable-pathlength multilevel Structures for Lossless Ion Manipulations (SLIM) platform to achieve a higher resolving power than previously possible. This new multilevel SLIM platform has eight separation levels connected by ion escalators and a path length of ~88 meters (~11 meters per level). Our new multilevel SLIM can also be operated in an ‘ion cycling’ mode where a set of return ion escalators transport ions from the eighth back to the first level, allowing even longer path lengths (and higher IMS resolution). The platform has been improved to enhance the ion transmission and IMS separation quality by reducing the spacing between SLIM boards as well as board thickness, reducing the ions’ escalator residence time. Compared to the previous generation, the new multilevel SLIM demonstrated a better transmission for a set of phosphazene ions, especially for the low-mobility ions. The new multilevel SLIM achieved better resolving powers than our previous 4-level SLIM. The collision cross-section-based resolving power of the SLIM platform was tested using a pair of singly-charged reverse sequence peptides (SDGRG 1+ , GRGDS 1+ ). We achieved 1100 resolving power using 88 meters of path length (i.e., 8 levels) and 1400 following an additional pass through the eight levels (i.e., 16 levels or 173.5 m). The multilevel SLIM was further evaluated to demonstrate the enhanced separation for a positively and negatively charged brain total lipid extract sample. Finally, the new multilevel SLIM enables much higher resolving powers for a wide range of ion mobilities, improved transmission for low-mobility ions, and the ability to perform even higher resolving power for ions of interest.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

DOE OSTI2021

Ultra-Structural Imaging Provides 3D Organization of 46 Chromosomes of a Human Lymphocyte Prophase Nucleus

Three dimensional (3D) ultra-structural imaging is an important tool for unraveling the organizational structure of individual chromosomes at various stages of the cell cycle. Performing hitherto uninvestigated ultra-structural analysis of the human genome at prophase, we used serial block-face scanning electron microscopy (SBFSEM) to understand chromosomal architectural organization within 3D nuclear space. Acquired images allowed us to segment, reconstruct, and extract quantitative 3D structural information about the prophase nucleus and the preserved, intact individual chromosomes within it. Our data demonstrate that each chromosome can be identified with its homolog and classified into respective cytogenetic groups. Thereby, we present the first 3D karyotype built from the compact axial structure seen on the core of all prophase chromosomes. The chromosomes display parallel-aligned sister chromatids with familiar chromosome morphologies with no crossovers. Furthermore, the spatial positions of all 46 chromosomes revealed a pattern showing a gene density-based correlation and a neighborhood map of individual chromosomes based on their relative spatial positioning. A comprehensive picture of 3D chromosomal organization at the nanometer level in a single human lymphocyte cell is presented.

75 CONDENSED MATTER PHYSICS, SUPERCONDUCTIVITY AND↗

DOE OSTI2022

Resolving Lipid Structures for Threat-Agnostic Signatures

Development of threat-agnostic biosignatures is critical for the detection of and response to biological threats that go beyond the historical list-based approach. Lipids are a class of structurally diverse biomolecules that hold great promise as relevant threat-agnostic biosignatures, yet the fundamental challenge of resolving and decoding structural differences among lipids remains an obstacle in the pursuit of signature development. Structural analysis of complex lipids remains stymied due to spectral complexity and the inability to resolve low abundance lipids. To address these challenges, we integrated ozonolysis with ion mobility mass spectrometry (IMS-MS) analysis to determine the structural information for complex lipid species and (2) reduced lipid sample complexity prior to introduction into the IMS-MS using normal phase high pressure liquid chromatography (HPLC) to enable the ozonolysis of low abundance lipids. We applied these new capabilities to define the lipid structures in antimicrobial resistant (AMR) and antimicrobial susceptible (AMS) biothreat organism Yersinia pestis and cells infected with Severe Acute Respiratory Syndrome coronavirus 2 (SARS-CoV-2) variants.

59 BASIC BIOLOGICAL SCIENCES↗

DOE OSTI2025

Coupling of Charge Regulation and Geometry in Soft Ionizable Molecular Assemblies

The size, shape, and charge of structures, such as proteins and amphiphile assemblies, respond in an interconnected manner to solution ionic conditions. Here, we analyze assemblies of an amphiphile (C 16 K 2 ), with two ionizable amino acids [lysine (K)] coupled to a 16-carbon alkyl tail, via small-angle X-ray scattering (SAXS), nonlinear Poisson–Boltzmann theory (nl-PB), and hybrid Monte Carlo-molecular dynamics (MC-MD) simulations. SAXS revealed structural transitions from spherical micelles to cylindrical micelles to bilayers with increasing pH. By combining SAXS-determined structural information and nl-PB, we derived the molecular degree of ionization as a function of pH. The back-calculated titration curves matched the experimental data over an extended pH range, without adjustable parameters. Similarly, the SAXS data on the evolution of spherical micelle structure with ionic strength were combined with nl-PB and MC-MD to derive the bare and effective charges. MC-MD, which considered finite ion sizes, showed that bare and effective charges saturate quickly with increasing salt concentration. Furthermore, the calculated effective charges closely matched results from Zeta-potential measurements. The presented approach has advantages over customary methods for charge regulation, such as the Henderson–Hasselbalch (HH) or Hill models, where molecular ionization/deionization in assemblies is described by effective pKs that are distinct from the pK for isolated molecules. However, these models lack a physical explanation for these pK shifts. By contrast, our approach of combining structural details with an electrostatic model and simulations provides a more intuitive understanding of structure-charge coupling and a framework for understanding charge regulation in many synthetic and biological systems.

ionization↗

DOE OSTI2020

Refining internal bilayer structure of bicelles resolved by extended-q small angle X-ray scattering

The internal profile across the bilayer reveals important structural information regarding the crystallinity of acyl chains or the positions of encapsulated species. Here, we demonstrate that a simple five-layer-core-shell discoidal model can be employed tobest fit the extended-qsmall angle X-ray scattering (SAXS) data and resolvethe bilayer internal structure (with sub-nanometer resolution) of a nanoscale discoidal system comprised of a mixture of long-and short-chain lipids(known as “bicelles”). In contrast to the traditional core-shell discoidal model, the detailed structure in the hydrophobic core such as the methylene and methyl groups can be distinguished via this model. The refined model is validated by the SAXS data of bicelles whose electron scattering length density of the hydrophobic core is adjusted by the addition of a long-chain lipid with a fluorine-end group.The higher resolution of the bilayer internal structure can be employed to advance our understanding of the interaction and conformation of the membrane and associated molecules, such as membrane-associated proteins and locations of entrapped species in the lipid nanoparticles.

36 MATERIALS SCIENCE↗

DOE OSTI2026

UCB-GLOBES: An open-access mass spectral database of identified and unidentified atmospheric organic compounds

Chemical characterization of atmospheric organic aerosols using gas chromatography with 70 eV electron ionization mass spectrometry (GC/EI-MS) has been used for decades in advancing molecular marker detection and identification, though primarily through suspect screening and/or targeted analyses. To advance non-targeted analyses of environmental samples, we have catalogued approximately 27 000 mass spectra (MS) of the trimethylsilyl derivatives of semi-volatile organic aerosol (OA) analytes in the open-access University of California Berkeley Goldstein Library of Organic Biogenic Environmental Spectra (UCB-GLOBES). Analytes were observed in ambient samples from the U.S. and the Central Amazon and/or laboratory simulations of secondary OA (SOA) formation. These samples are representative of OA under urban and biomass burning influences as well as SOA derived from biogenic precursors (e.g., isoprene, monoterpenes, sesquiterpenes) and biomass burning intermediates. MS are documented in UCB-GLOBES without regard to known chemical identity, annotated with extensive metadata such as sample source/experimental conditions, any structural information gained from MS analyses, and predicted chemical properties such as average carbon oxidation state and carbon number. UCB-GLOBES MS are compatible for importing into the NIST MS Search program, and we have also provided a Jupyter Notebook for MS visualization and comparisons. We demonstrate the utility of UCB-GLOBES through MS reanalyses of prior analytes observed in ambient data, finding a 20 % reduction in the number of analytes assigned to OA source categories reliant solely on time series correlation and an overall 11 % increase in new MS-based OA source categorization for the Southeast U.S. For 1513 analytes observed previously in the Central Amazon, we found 375 MS matches using UCB-GLOBES vs. 136 MS matches during prior analyses, representing a 14 % gain in newly confirmed or newly categorized OA species. While OA from laboratory oxidation experiments in UCB-GLOBES are highly diverse chemically, on average only 29 % of UCB-GLOBES MS have a mass spectral match to another MS entry in UCB-GLOBES and/or in databases of known compounds (i.e. NIST MS Database, Adams Essential Oil, MANE Flavor and Fragrance Company). This indicates that roughly 70 % of UCB-GLOBES MS are unique thus far, not observed more than once among the laboratory oxidation samples and ambient data in UCB-GLOBES MS. Further, only 18 % can be positively identified using these databases or known authentic standards. This points to a large gap between these laboratory simulations and ambient OA. Overall, the UCB-GLOBES database can be utilized for improving confidence in OA source categorization and/or identification, novel chemical marker discovery, tracking chemical diversity, de novo structure and properties prediction, and improving MS search and matching algorithms. This can ultimately inform future research priorities for the chemical characterization of atmospheric organic samples.

Mass spectrometry↗

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↗

DOE OSTI2023

Prediction of impact sensitivity, heat of formation and heat of explosion using atomic connectivity

In these proceedings we revisit a large collection of explosives and explosive descriptors with the goal of predicting impact sensitivity using only local atomic environments that can be deciphered from molecular SMILES strings as descriptors without utilizing empirically measured values or computationally expensive electronic structure calculations. From the original database of nearly 500 descriptors, removing empirically measured and electronic structure values decreased the number of descriptors to 135, which we reduced to 18 the most important descriptors using Random Forests. The condensed model predicted impact sensitivity with essentially the same accuracy as the existing, more complex model (R 2 = 0.788 and RSME = 0.312), while remaining applicable to all types of explosives (Peroxides, azides, C-Nitros, Nitroamines, Nitrate Esters, etc.). In addition to impact sensitivity, we proposed similar models to accurately predict values heat of formation (ΔH f ) and heat of explosion (Q), with R 2 = 0.966 and 0.916, respectively. In conclusion, the work in these proceedings allows for prediction of explosive performance and sensitivity with only chemical structure information and an estimate of density.

75 CONDENSED MATTER PHYSICS, SUPERCONDUCTIVITY AND↗

DOE OSTI2020

Impacts of Degradation on Water, Energy, and Carbon Cycling of the Amazon Tropical Forests

Selective logging, fragmentation, and understory fires directly degrade forest structure and composition. However, studies addressing the effects of forest degradation on carbon, water, and energy cycles are scarce. Here, we integrate field observations and high-resolution remote sensing from airborne lidar to provide realistic initial conditions to the Ecosystem Demography Model (ED-2.2) and investigate how disturbances from forest degradation affect gross primary production (GPP), evapotranspiration (ET), and sensible heat flux (H). We used forest structural information retrieved from airborne lidar samples (13,500 ha) and calibrated with 817 inventory plots (0.25 ha) across precipitation and degradation gradients in the eastern Amazon as initial conditions to ED-2.2 model. Our results show that the magnitude and seasonality of fluxes were modulated by changes in forest structure caused by degradation. During the dry season and under typical conditions, severely degraded forests (biomass loss ≥66%) experienced water stress with declines in ET (up to 34%) and GPP (up to 35%) and increases of H (up to 43%) and daily mean ground temperatures (up to 6.5°C) relative to intact forests. In contrast, the relative impact of forest degradation on energy, water, and carbon cycles markedly diminishes under extreme, multiyear droughts, as a consequence of severe stress experienced by intact forests. Our results highlight that the water and energy cycles in the Amazon are driven by not only climate and deforestation but also the past disturbance and changes of forest structure from degradation, suggesting a much broader influence of human land use activities on the tropical ecosystems.

54 ENVIRONMENTAL SCIENCES↗

DOE OSTI2021

The pH-dependent orientation of N3 dye on a gold substrate is revealed using heterodyne-detected vibrational sum frequency generation spectroscopy

We report on systematic changes to the adsorption geometry of the dye N3 {[cis-bis(isothiocyanato)bis(2,2' -bipyridyl-4,4' -dicarboxylato ruthenium(II)]} on a gold substrate as the pH of the deposition environment is altered. The protonation states of the four --COOH groups of the N3 dye change according to the modified pH conditions, thus affecting the number of --COOH and --NCS functional groups that participate in the adsorption to gold. Here, we use heterodyne detected vibrational sum frequency generation (HD-VSFG) spectroscopy to obtain surface specific vibrational information on both --COOH and --NCS groups as a function of pH of the deposition conditions. Polarization-dependent HD-VSFG yields sets of complex χ (2) spectra, enabling us to perform a simultaneous fitting procedure to the polarization-dependent real and imaginary components and thus extract detailed structural information of the N3/gold interface. Overall, our results show that N3 preferentially adsorbs to gold either with two --COOH groups and one --NCS group in more acidic conditions or with one --COOH group and two --NCS groups in more basic conditions.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

DOE OSTI2022

Synthetic aromatic kerosene property prediction improvements with isomer specific characterization via GCxGC and vacuum ultraviolet spectroscopy

This research explores an advanced method of fuel composition determination and builds upon typical hydrocarbon group type analyses performed with two-dimensional gas chromatography (GCxGC). In this study, structural information of individual species within Virent’s Synthetic Aromatic Kerosene (SAK) is identified by vacuum ultraviolet (VUV) spectroscopy. By mass, 71.3% of the components elute within six peaks of the chromatogram, from which 12 unique species are identified through a novel deconvolution method. Overall, the identification of 93.6%m across 26 structural isomers is made by the methods described in this work. With 93.6%m ascribed to specific isomers, the precision of fuel property predictions improves dramatically. For example, the absolute error of the viscosity prediction is reduced by 90% because of this advancement in diagnostic capability, and its 95-percentile confidence interval (precision only) is reduced by 93%. Additionally, the properties of SAK, blended with hydro processed esters fatty acids (HEFA), are demonstrated to have blended properties consistent with conventional jet fuel.

10 SYNTHETIC FUELS↗

DOE OSTI2025

Enhancing the accuracy of XPS calculations: Exploring hybrid basis set schemes for CVS-EOMIP-CCSD calculations

Reliable computational methodologies and basis sets for modeling x-ray spectra are essential for extracting and interpreting electronic and structural information from experimental x-ray spectra. In particular, the trade-off between numerical accuracy and computational cost due to the size of the basis set is a major challenge, since molecular orbitals undergo extreme relaxation in the core-hole state. To gain clarity on the changes in electronic structure induced by the formation of a core-hole, the use of sufficiently flexible basis for expanding the orbitals, particularly for the core region, has been shown to be essential. This work focuses on the refinement of core-hole ionized state calculations using the equation-of-motion coupled cluster family of methods through an extensive analysis on the effectiveness of “hybrid” and mixed basis sets. In this investigation, we utilize the CVS-EOMIP-CCSD method in combination and construct hybrid basis sets piecewise from readily available Dunning’s correlation consistent basis sets in order to calculate x-ray ionization energies (IEs) for a set of small gas phase molecules. Our results provide insights into the impact of basis sets on the CVS-EOMIP-CCSD calculations of K-edge IEs of first-row p-block elements. Furthermore, these insights enable us to understand more about the basis set dependence of the core IEs computed and allow us to establish a protocol for deriving reliable and cost-effective theoretical estimates for computing IEs of small molecules containing such elements.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

DOE OSTI2025

Scattering-based structural inversion of soft materials via Kolmogorov–Arnold networks

Small-angle scattering techniques are indispensable tools for probing the structure of soft materials. However, traditional analytical models often face limitations in structural inversion for complex systems, primarily due to the absence of closed-form expressions of scattering functions. To address these challenges, we present a machine learning framework based on the Kolmogorov–Arnold Network (KAN) for directly extracting real-space structural information from scattering spectra in reciprocal space. This model-independent, data-driven approach provides a versatile solution for analyzing intricate configurations in soft matter. By applying the KAN to lyotropic lamellar phases and colloidal suspensions—two representative soft matter systems—we demonstrate its ability to accurately and efficiently resolve structural collectivity and complexity. Here, our findings highlight the transformative potential of machine learning in enhancing the quantitative analysis of soft materials, paving the way for robust structural inversion across diverse systems.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

DOE OSTI2021

Insights into the Structure–Activity Relationship in Aerobic Alcohol Oxidation over a Metal–Organic-Framework-Supported Molybdenum(VI) Catalyst

The understanding of structure–activity relationships at the atomic level has played a profound role in heterogeneous catalysis, providing valuable insights into designing suitable heterogeneous catalysts. However, uncovering the detailed roles of how such active species’ structures affect their catalytic performance remains a challenge owing to the lack of direct structural information on a specific active species. Herein, we deposited molybdenum(VI), an active species in oxidation reactions, on the Zr 6 node of a mesoporous zirconium-based metal–organic framework (MOF) NU-1200, using solvothermal deposition in MOFs (SIM). Due to the high crystallinity of the NU-1200 support, the precise structure of the resulting molybdenum catalyst, Mo-NU-1200, was characterized through single-crystal X-ray diffraction (SCXRD). Two distinct anchoring modes of the molybdenum species were observed: one mode (Mo1), displaying an octahedral geometry, coordinated to the node through one terminal oxygen atom and the other mode (Mo2) coordinated to two adjacent Zr 6 node oxygen atoms in a tetrahedral geometry. To investigate the role of base in the catalytic activity of these Mo centers, we assessed the activity of Mo-NU-1200 for the aerobic oxidation of 4-methoxybenzyl alcohol as a model reaction. The results revealed that Mo-NU-1200 exhibited remarkably higher catalytic reactivity under base-free conditions, while the presence of base inhibited the catalytic reactivity of this species. SCXRD studies revealed that the molybdenum binding motifs (structures of the supported metal on the Zr 6 node in the MOF) changed over the course of the reactions. Following the oxidation without base, both pristine coordination modes (Mo1 and Mo2) evolved into a new coordination mode (Mo3), in which the molybdenum atom coordinated to two adjacent oxygen atoms from the Zr 6 node in an octahedral geometry, while in the presence of base, the pristine Mo1 coordination mode evolved entirely into the pristine Mo2. Here, this study demonstrates the direct observation of an active species’ structural evolution from metal installation to subsequent catalytic reaction. As a result, these subtle structural changes in catalyst binding motifs led to distinct differences in catalytic activities, providing a compelling strategy for elucidating structure–activity relationships.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

DOE OSTI2021

Measurement of U 238 ( n , n ' γ ) cross section data and their impact on reaction models

A better knowledge of (n,xn) reaction cross sections is important for both reaction modeling and energy applications. This article focuses on inelastic scattering of neutrons off 238 U for which improvements are needed to better constrain evaluations and solve inconsistencies in nuclear power reactor calculations. A new precise measurement of (n,xnγ) reaction cross sections on 238 U has been performed at the GELINA (Geel Electron LINear Accelerator) neutron facility operated by EC-JRC-Geel (Belgium) with the GRAPhEME (GeRmanium array for Actinides PrEcise MEasurements) setup. The prompt γ-ray spectroscopy method coupled to time-of-flight measurements is used to extract (n,xnγ) cross section values which can be further combined to infer the total neutron inelastic scattering cross section. Cross section data for 18 γ transitions (five never measured before) are presented and compared to the data in the literature. Here, emphasis is especially given to the uncertainty determination to produce partial cross section data as accurate as possible. Due to intrinsic limitations of the experimental method, the use of additional nuclear structure information coupled with theoretical modeling is required to determine the total (n, n') cross section over the whole neutron energy range. We have investigated modeling aspects of the 238 U(n,n'γ) cross sections related to the description of compound nucleus and preequilibirum mechanisms as well as the discrete part of nuclear structure. Through comparison between experimental and calculated (n,n'γ) cross sections, we pinpoint inaccuracies in the description of specific reaction mechanisms and challenge recently implemented models. This helps improving the whole modeling of the (n, n') reaction.

73 NUCLEAR PHYSICS AND RADIATION PHYSICS↗