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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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DOE OSTI2026

Structure prediction of porous organic crystals

In this work, we explore the possibility of applying automated crystal structure prediction to reproduce the experimentally identified metastable porous polymorphs. Using our recently developed High-Throughput Organic Crystal Structure Prediction ( HTOCSP ) framework, we conducted a systematic study on five representative organic crystalline systems including hydrogen-bonded frameworks (HOFs), featured by the presence of significant porosity, in conjunction with different choices of energy models from classical, machine learning force fields, tight binding to density functional theory. Our results suggest that the current structure generation framework, with careful selection of symmetry conditions, is likely to generate rather complex and abundant metastable crystal candidates for porous crystals. In conjunction with the recent advance in universal machine learning force fields, it becomes possible to identify experimental structures as the energetically favorable candidates from a simple energy versus density analysis, thus paving the way for computational design of complex porous materials with the target systems prior to the experimental synthesis and characterization.

36 MATERIALS SCIENCE↗
DOE OSTI2020

Gas–Phase Synthesis of 3–Vinylcyclopropene via the Crossed Beam Reaction of the Methylidyne Radical (CH; X 2 Π) with 1,3–Butadiene (CH 2 CHCHCH 2 ; X 1 Ag)

The crossed molecular beam reactions of the methylidyne radical (CH; X 2 Π) with 1,3-butadiene (CH 2 CHCHCH 2 ; X 1 Ag) along with their (partially) deuterated counterparts were performed at collision energies of 20.8 kJ mol -1 under single collision conditions. Combining our laboratory data with ab initio calculations, we reveal that the methylidyne radical may add barrierlessly to the terminal carbon atom and/or carbon-carbon double bond of 1,3-butadiene, leading to doublet C 5 H 7 intermediates with life times longer than the rotation periods. Furthermore, these collision complexes undergo non-statistical unimolecular decomposition through hydrogen atom emission yielding the cyclic cis- and trans-3-vinyl-cyclopropene products with reaction exoergicities of 119±42 kJ mol -1 . Since this reaction is barrierless, exoergic, and all transition states are located below the energy of the separated reactants, these cyclic C 5 H 6 products are predicted to be accessed even in low-temperature environments, such as in hydrocarbon-rich atmospheres of planets and cold molecular clouds such as TMC-1.

3-vinylcyclopropene↗
DOE OSTI2024

Carbon- and Oxygen-rich stars in MaStar: identification and classification

ABSTRACT Carbon- and Oxygen-rich stars populating the Thermally Pulsing Asymptotic Giant Branch (TP-AGB) phase of stellar evolution are relevant contributors to the spectra of ∼1 Gyr old populations. Atmosphere models for these types are uncertain, due to complex molecules and mass-loss effects. Empirical spectra are then crucial, but samples are small due to the short (∼3 Myr) TP-AGB lifetime. Here we exploit the vastness of the MaNGA Stellar library MaStar (∼60 000 spectra) to identify C and O-rich type stars. We define an optical colour selection with cuts of (g − r) > 2 and (g − i) < 1.55(g − r) − 0.07, calibrated with known C- and O-rich spectra. This identifies C- and O-rich stars along clean, separated sequences. An analogue selection is found in V, R, I bands. Our equation identifies C-rich and O-rich spectra with predictive performance metric F1-scores of 0.72 and 0.74 (over 1), respectively. We finally identify 41 C- and 87 O-rich type AGB stars in MaStar, 5 and 49 of which do not have a SIMBAD counterpart. We also detect a sample of non-AGB, dwarf C-stars. We further design a fitting procedure to classify the spectra into broad spectral types, by using as fitting templates empirical C- and O-rich spectra. We find remarkably good fits for the majority of candidates and categorize them into C- and O-rich bins following existing classifications, which correlate to effective temperature. Our selection models can be applied to large photometric surveys (e.g. Euclid, Rubin). The classified spectra will facilitate future evolutionary population synthesis models.

Hill, Lewis (ORCID:0000000180528080)↗
DOE OSTI2025

Enhancing stability, magnetic anisotropy, and coercivity of manganese aluminum: Machine learning, ab initio , and micromagnetic modeling

The binary manganese aluminum (MnAl) alloy with L⁢1 0 crystal structure is a promising rare earth (RE) element-free permanent magnetic material because of its exceptional magnetic properties. However, experimentally synthesizing it in a stable bulk form is extremely challenging. Here, in this study, an alternative method of stabilizing the material, a pathway for experimental synthesis and validation, is proposed and theoretically verified. This is done by partially substituting Mn and Al sites with Fe and Ni and identifying its enhanced phase stability, saturation magnetization density, magnetic anisotropy, and coercivity from density functional theory (DFT), machine learning (ML) crystal graph convolution neural network (CGCNN), and micro-magnetic modeling. When considering a fixed 50% Ni, the magnetic anisotropy increases with the increasing Fe content but decreases the formation energy. The calculated formation energies, elastic constants, and phonon frequencies demonstrate that the binary and quaternary compositions are stable. Most importantly, in 50% Fe and Ni-substituted-equiatomic phase, magnetic anisotropy constants and saturation magnetization density increase by 56% and 23% as compared to the MnAl. Further, the coercivity of the equiatomic phase predicted with micro-magnetic modeling is higher by 17% than the parent compound.

Bhandari, Churna [Ames National Laboratory, and Io↗
DOE OSTI2021

Unbalancing Symbiotic Nitrogen Fixation: Can We Make Effectiveness More Effective?

One of the most critical uses of carbon fuels is in generating nitrogen fertilizer. Atmospheric dinitrogen is too stable to be used directly by plants, so plants need other chemical forms of nitrogen. Nitrogen fertilizer production uses ~4% of the world’s natural gas. Making N fertilizers leverages methane’s energy content by enabling additional energy to be captured into food and fiber through increased photosynthesis. Manufacturing fertilizer is essential—without it there would only be enough combined nitrogen to feed ~3 billion of the world’s ~7 billion people. How to alter this addiction is not obvious, but the best chance to secure substantial and sustainable amounts of future N might be through symbiotic nitrogen fixation (SNF). SNF describes mutualistic interactions where nitrogen-fixing bacteria provide fixed nitrogen to their plant hosts, freeing them from the need for nitrogen fertilizers. SNF already occurs on a large scale; "biological nitrogen” contributes about 5 Tg N/yr to American agriculture, a quarter of the nitrogen needed. Improving SNF and replacing inorganic fertilizers are both important goals in establishing sustainable and more energy-efficient farming. SNF has been used in agriculture for millennia, largely by using legumes like beans or alfalfa in mixed cropping systems. Legume SNF occurs in root nodules, organs that develop after a growing root is infected by bacteria called rhizobia. In the plant cells of a legume nodule, specialized forms of rhizobia fix nitrogen and can produce enough ammonia to supply the growing plant. The exchange of photosynthetically derived plant carbon compounds for nitrogen reduced by the bacteria is the engine that drives the symbiosis. Important details about the organization of development and metabolism in SNF remain to be determined, such as how plant and bacterial metabolism are coordinated as nitrogen is being fixed and what governs the overall level of nitrogen fixation. Most bacterial mutations that affect SNF completely block fixation (e.g. are Fix – ), providing a limited window into the feedback interactions that must be part of the process. We have investigated an unusual mutant of Sinorhizobium meliloti, a symbiotic partner of alfalfa, that fixes dinitrogen at a normal rate (i.e., it is Fix + ) but is not effective in supporting plant growth (i.e., it is ineffective or Eff – ). We have shown that the mutant has a specific mutation in the glnD gene, which codes for a protein that regulates the bacterial response to nitrogen stress, among other key pathways. A Fix + Eff – phenotype contains an unavoidable puzzle—how is it possible for the bacteria to fix nitrogen at a normal rate and without benefiting the nitrogen starved plant host? After eliminating other possibilities, we proposed that the bacteria synthesize a nitrogen-containing compound that the plant can’t use so that acquiring this compound does not relieve plant nitrogen stress. Extracts of nodules made by glnD mutant strains have high concentrations of pyruvate canaline oxime (PCO), a derivative of the plant defensive compound canaline, a toxic analog of ornithine, an amino acid. Many legumes produce canaline and the related arginine mimic canavanine. For reasons we do not yet understand, the mutation in glnD appears to trigger significant overproduction of canaline in a defense response that leads to substantial synthesis of PCO. We expected the bacteria to be able to use PCO, but we have not been able to grow S. meliloti on PCO under several conditions. PCO thus appears to be a metabolic dead end for both the plant and bacteria. We also examined bacterial catabolic pathways that degrade arginine and canavanine and showed that mutation of these did not alter the symbiosis in an obvious way. In related experiments to examine the metabolic development of root nodules, we carried out an ambitious experiment to simultaneously measure metabolites and protein changes during nodule maturation. For these experiments we used a related symbiotic interaction between S. medicae and Medicago truncatula. M. truncatula has a simpler genome than alfalfa so we could identify plant proteins based on predictions from the DNA sequence. Nodules formed on Medicago grow linearly, with the least mature tissues at the tip. Because development of nitrogen fixation is accompanied by the production of the pigmented plant oxygen carrier protein leghemoglobin, we were able to locate and manually separate the tip, transitional, and mature nitrogen-fixing regions from each other. Advances in proteomic and metabolomic techniques allowed us to analyze these tissues from a pool of as few as 10 nodules. We observed correlated transitions of various enzymes in the plant and bacterial proteomes from those characteristic of free-living metabolism to the microaerobic metabolism of the nitrogen-fixing tissues. The metabolome could not be separated into plant and bacterial domains but was consistent with this overall transition. A subsequent paper examined proteolysis in nodule bacteria. Protein turnover in mature regions of the nodule is significant. We were able to show complexes between various proteins and important proteases, using precipitation capture techniques to isolate the proteases and sensitive proteomic analysis to reveal the associated proteins.

09 BIOMASS FUELS↗
DOE OSTI2025

Empirical evidence that glucan-interacting amino acid side chains within the transmembrane channel collectively facilitate cellulose synthase function

The fundamental mechanism of cellulose synthesis is widely conserved across Kingdoms and depends on cellulose synthases, which are processive, dual-function, family 2 glycosyltransferases (GT-2). These enzymes polymerize glucose on the cytoplasmic side of the plasma membrane and export the glucan chain to the cell surface through an integral transmembrane (TM) channel. Structural studies of active plant cellulose synthases (CESAs) have revealed interactions between the nascent glucan chain and the side chains of polar, charged, and aromatic amino acid residues that line the TM channel. However, the functional consequences of modifying these side chains have not been tested in vivo in CESAs or other processive GT-2s. To test this, we used an established in vivo assay based on genetic complementation of CESA5 in the moss, Physcomitrium patens. For accurate prediction of glucan-interacting amino acid residues, we generated a complete homotrimeric molecular model of PpCESA5 using a combination of homology and de novo modeling. All-atom molecular dynamics-based analyses of contact metrics and interaction energy identified 23 amino acid residues with high propensity to interact with the nascent glucan chain within the TM channel or on the apoplastic surface of PpCESA5. Mutating any one of 18 of these amino acid residues to alanine, thereby removing their side chains, abolished or impaired CESA function, with the strongest effects observed upon the loss of charged amino acid side chains. This provides direct evidence to support the hypothesis that multiple amino acid residues collectively maintain a smooth energy landscape within the TM channel to facilitate glucan translocation.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2025

Compositionally Complex Spinel Oxides as Conversion Anodes for Lithium-Ion Batteries

Four different compositionally complex multicomponent M 3 O 4 spinels containing 5–8 distinct metals were prepared by a rapid combustion synthesis method or solvothermal synthesis. High resolution synchrotron X-ray diffraction patterns show that the materials consist primarily of spinel phases with small amounts of rock salt impurities, and, in several samples, a minor amount of contracted spinel phase. Materials were investigated as conversion anodes in lithium half-cells and delivered significantly higher capacities than two-component MgFe 2 O 4 made by combustion synthesis. X-ray absorption near-edge structure (XANES) was used to estimate the oxidation states of the metals in the pristine, lithiated (discharged) and delithiated (charged) materials to better understand the redox processes in half cells that led to the improvement. Co, Ni, and Zn are reduced to low oxidation states during lithiation (cell discharge) but are only partially oxidized. The presence of a conductive metallic network that forms after lithiation is thought to account for the improved electrochemical characteristics. Interestingly, in most of the samples, iron is not fully reduced during initial lithiation unlike what happens with a set of related high entropy spinel ferrites studied previously. Finally, the improved electrochemical properties of these materials illustrates both the advantages of complexity and the difficulties in predicting their behavior.

25 ENERGY STORAGE↗
DOE OSTI2025

Smart culture medium optimization for recombinant protein production: Experimental, modeling, and AI/ML-driven strategies

Recombinant protein production (RPP) is central to biotechnology, where recombinant proteins are used as either end products or catalysts in the synthesis of chemicals, fuels, and materials. Among the major cost drivers, culture medium plays a pivotal role in determining protein yield and quality. This review presents a comprehensive perspective on the critical stages of “smart” culture medium optimization: planning, screening, modeling, optimization, and validation. In the planning stage, we examine the nutritional and energetic roles of medium components, including carbon, nitrogen, amino acids, salts, and trace metals, and their impacts on culture parameters such as pH, oxidative state, and osmolality. We highlight the variability in trace metal content due to water sources, culture vessels, and raw materials, which can substantially influence RPP. The screening stage covers Design of Experiments (DoE) approaches, assessing their theoretical basis, implementation, and limitations. For modeling, we describe methods that integrate experimental data to develop predictive models for smart medium formulation. Model-based optimization strategies can then be employed to select optimal media compositions for a given application. The validation stage aims to evaluate model predictions and provide feedback for model training and refinement. Finally, we survey mechanistic and artificial intelligence/machine learning (AI/ML)-driven models as integrated, transformational tools for predictive modeling of bioprocess conditions, nutrient availability, cellular metabolism, and protein quality, with the goal of optimizing culture media to enhance protein yields while reducing costs and environmental impact. We conclude by addressing the challenges of translating laboratory-scale medium optimization to industrial-scale settings and exploring future AI/ML-driven approaches that may overcome current bottlenecks and accelerate medium design for RPP. Overall, this review provides a unified framework for advancing smart medium design in RPP.

Artificial Intelligence/Machine Learning (AI/ML)↗
DOE OSTI2024

Influence of substituents on the vectorial difference static dipole upon excitation in synthetic bacteriochlorins

Organic dye aggregates have been shown to exhibit exciton delocalization in natural and synthetic systems. Such dye aggregates show promise in the emerging area of quantum information science (QIS). We believe that the difference static dipole (Δd) is an essential dye parameter in the development of molecular QIS systems. However, a foundational understanding of the structural factors influencing Δd remains elusive. Bacteriochlorins play a vital role in photosynthesis due to their exceptional photophysical properties. Therefore, bacteriochlorins are particularly suitable dyes for the construction of aggregate systems for QIS. Synthetic bacteriochlorins further offer stability and tunability via chemical modifications. Here, the influence of substituents on the Δd of monomeric (non-aggregated) dyes was investigated via density functional theory (DFT) and time-dependent (TD-)DFT in a set of 5-methoxybacteriochlorins progressively substituted with ethynyl, phenyl, and phenylethynyl substituents at the 3,13- and 3,13,15-positions of the macrocycle. Symmetrically substituted 5-methoxybacteriochlorins were shown to have the largest Δd. The increase in Δd in the series of dyes was largely due to changes in orientation of the static dipole upon excitation rather than large changes in magnitude. In addition, the transition dipole (μ) and the angle between Δd and μ (ζ) were calculated. Three 5-methoxybacteriochlorins with high predicted Δd and μ were synthesized and characterized spectroscopically. The trend in Δd values empirically determined using the solvatochromic Stokes shift method was comparable with the DFT calculations.

36 MATERIALS SCIENCE↗
DOE OSTI2021

Spin splitting of dopant edge state in magnetic zigzag graphene nanoribbons

Spin-ordered electronic states in hydrogen-terminated zigzag nanographene give rise to magnetic quantum phenomena that have sparked renewed interest in carbon-based spintronics. Zigzag graphene nanoribbons (ZGNRs)-quasi one-dimensional semiconducting strips of graphene bounded by parallel zigzag edges-host intrinsic electronic edge states that are ferromagnetically ordered along the edges of the ribbon and antiferromagnetically coupled across its width. Despite recent advances in the bottom-up synthesis of GNRs featuring symmetry protected topological phases and even metallic zero mode bands, the unique magnetic edge structure of ZGNRs has long been obscured from direct observation by a strong hybridization of the zigzag edge states with the surface states of the underlying support. Here, we present a general technique to thermodynamically stabilize and electronically decouple the highly reactive spin-polarized edge states by introducing a superlattice of substitutional N-atom dopants along the edges of a ZGNR. First-principles GW calculations and scanning tunnelling spectroscopy reveal a giant spin splitting of low-lying nitrogen lone-pair flat bands by an exchange field (~850 tesla) induced by the ferromagnetically ordered edge states of ZGNRs. Finally, our findings directly corroborate the nature of the predicted emergent magnetic order in ZGNRs and provide a robust platform for their exploration and functional integration into nanoscale sensing and logic devices.

36 MATERIALS SCIENCE↗
DOE OSTI2022

3D simulations of spinlike flames in Co/Al multilayers with enhanced conduction losses

Reactive Co/Al multilayers are uniformly structured materials that may be ignited to produce rapid and localized heating. Prior studies varying the bilayer thickness (i.e., sum of two individual layers of Co and Al) have revealed different types of flame morphologies, including: (a) steady/planar, (b) wavy/periodic, and (c) transverse bands, originating in the flame front. These instabilities resemble the “spin waves” first observed in the early studies of solid combustion (i.e., Ti cylinder in a N 2 atmosphere), and are likewise thought to be due to the balance of heat released by reaction and heat conduction forward into the unreacted multilayer. However, the multilayer geometry and three-dimensional (3D) edge effects are relatively unexplored. In this work, a new diffusion-limited reaction model for Co/Al multilayers was implemented in large, novel 3D finite element analysis (FEA) simulations, in order to study the origins of these spinlike flames. This reaction model builds upon previous work by introducing three new phase-dependent property models for: (1) the diffusion coefficient, (2) anisotropic thermal conductivity tensor, and (3) bulk heat capacity, as well as one additional model for the bilayer-dependent heat of reaction. These novel 3D simulations are the first to predict both steady and unsteady flames in Co/Al multilayers. Moreover, two unsteady modes of flame propagation are identified, which depend on the enhanced conduction losses with slower flames, as well as flame propagation around notched edges. Finally, future work will consider the generality of the current modeling approach and also seek to define a more generalized set of stability criteria for additional multilayer systems.

42 ENGINEERING↗
DOE OSTI2025

Charge Disproportionation at Twisted SrTiO 3 Bilayer Interface Driven by Local Atomic Registry

The interplay of lattice, orbital, and charge degrees of freedom in complex oxide materials has hosted a plethora of exotic quantum phases and physical properties. Recent advances in the synthesis of freestanding complex oxide membranes and twisted heterostructures assembled from membranes provide diverse opportunities for discovery using moiré design with local lattice control. To this end, we designed moiré crystals at the coincidence site lattice condition, providing commensurate structure within the moiré supercell arising from the multiatom complex oxide unit cell. We fabricated such twisted bilayers from freestanding SrTiO 3 membranes and used depth-sectioning-based electron microscopic methods to investigate ordered charge states at the moiré interface. By selectively imaging SrTiO 3 atomic planes at different depths through the bilayer, we clearly resolved the moiré periodic structure at the twisted interface and found that it exhibits lattice-dependent charge disproportionation in the local atomic registry within the moiré supercell. Density functional modeling of the twisted oxide interface predicts that these moiré phenomena are accompanied by a two-dimensional flat band that can drive exceptional electronic phases. Our work provides a robust strategy for controlling moiré periodicity in twisted oxides and paves pathways to exploit the extraordinary functionalities via moiré lattice-driven charge-orbital correlation.

charge disproportionation↗
DOE OSTI2024

Phase Field Modeling of Pressure Induced Densification in Solid Electrolytes

Adoption of dense and homogeneous solid electrolytes can possibly mitigate the propagation of lithium dendrites and enable lithium metal anodes. Application of external pressure helps to minimize the sintering temperature in oxide ceramics and can potentially densify softer sulfide electrolytes even under room temperature conditions. Here, a previously developed phase field-based computational scheme for predicting the high-temperature sintering-induced densification of oxide ceramic solid electrolytes is extended in the present context to capture the influence of external pressure for densifying solid electrolytes. Two different bulk deformation mechanisms, namely, "reorganization" and "creep deformation," are dominant under external pressure, which is different from the surface and grain-boundary diffusion-induced densification of solid electrolytes that occurs during high temperature sintering. External pressure also increases the points of contact between the particles, which further enhances the propensity of diffusion-induced sintering process. Results obtained from simulations indicate that densification under external pressure is independent of the solid electrolyte particle morphology. Finally, a phase map is generated between applied pressure and temperature for achieving complete densification of oxide ceramics, which can possibly guide the synthesis of thin and dense solid electrolyte separators.

25 ENERGY STORAGE↗
DOE OSTI2020

Collaborative Research: Advancing Arctic Climate Projection Capability at Seasonal to Decadal Scales (Final Technical Report)

The Regional Arctic System Model (RASM) at process resolving configurations has been used to (i) advance understanding of physical processes and feedbacks involved in Arctic amplification and (ii) understand and potentially reduce uncertainty in prediction of arctic climate change at seasonal to decadal scales. RASM consists the atmosphere (Weather and Research Forecasting model, WRF), ocean (Parallel Ocean Program, POP), sea ice (CICE), land hydrology (Variable Infiltration Capacity model, VIC), river routing scheme (RVIC), marine biogeochemistry components and the coupling framework (CPL7). Its domain is pan-Arctic, with the atmosphere and land components configured on a 50-km or 25-km grid and four configurations of the ocean and sea ice components: 1/12°(~9.3km) or 1/48°(~2.4km) and 45 or 60 vertical layers. These RASM configurations have been motivated by the emerging exascale capability for high performance computing to improve model fidelity. The dynamical downscaling of reanalysis allows comparison of RASM results with observations in place and time to: (i) advance system level understanding of physical processes and coupling involved in an event, (ii) optimize model parameter space, (iii) diagnose and reduce model biases and (iv) produce realistic and consistent across all the components initial conditions for predictions and predictability studies, which are all unique capabilities not available in global Earth System Models (ESMs). An evaluation of RASM 1.0 (Cassano et al. 2017) revealed that it had a cold bias over the oceans and a warm bias over land areas due largely to cloud and radiation biases in the model, with too little cloud cover simulated over land and too much cloud cover simulated over sub-polar oceans. This study has motivated an upgrade to WRF version 3.7.1 in RASM and allowed for the inclusion of the radiative impact of convective clouds. A variety of atmospheric physics parameterizations were evaluated against observations (e.g. data from the Arctic Clouds in Summer Experiment (ACSE); Sedlar et al. 2020) to identify an optimal suite of WRF physics options in RASM. The RASM with the optimized WRF physics were used to study the impact of strong mesoscale winds over the ocean around the southern tip of Greenland (DuVivier and Cassano 2016) and their impact on oceanic convection (DuVivier et al. 2017a). Data from the PolarWinds field campaign were used to evaluate WRF boundary layer physics and resolution impacts on the simulation of a Greenland barrier wind event (DuVivier et al. 2017b). The RVIC streamflow routing model has been implemented in RASM to realistically represent high-resolution streamflow processes (Hamman et al. 2017) and to couple the land buoyancy fluxes to the ocean. The RASM-RVIC high-resolution data set of all coastal freshwater fluxes for the Arctic drainage basin and surrounding areas for 1979-2014 was published as a separate product (https://doi.org/10.5281/zenodo.293037). The fidelity of atmospheric momentum transfer to and the response of polar marine Ekman layer in RASM and Community Earth System Model (CESM) was investigated by Roberts et al. (2015). The increased frequency of oceanic flux exchange in CESM, following the RASM guidance, caused a considerable increase in the median inertial ice speed across the Southern Ocean and parts of the Arctic. A comprehensive evaluation of the RASM1.0 atmosphere-ocean-sea ice-land interface was completed by Brunke et al. (2018). RASM was also demonstrated for its capability to simulate extreme events in agreement with observations in space and time (Lee et al. submitted). In particular, the development of three open water events, known as polynyas, have been simulated north of Greenland in February of 2011, 2017 and 2018, in agreement with satellite observations for the past four decades. The optimized RASM sea ice results have been favorably evaluated against satellite observations and a subset of eleven CMIP6 models (Watts et al. submitted). In a complementary project, Jin et al. (2018) have shown that RASM with higher-resolution and new sea-ice processes contributed to lower model errors in sea-ice conditions, concentrations of nutrients and ice algae, in comparison to results from the coarse-resolution (1°) CESM. In two other complementary studies, RASM results were used (i) to explain areas of concentrated use by bowhead whales, the seasonal progression in the use, and the physical environment within those areas (Citta et al. 2015) and (ii) for a synthesis of fall bowhead whales distribution and migration in the Bering-Chukchi-Beaufort (BCB) Sea to investigate whale movements and feeding to the local ocean hydrography and currents (Citta et al. 2018). However, the multi-decadal output from the CESM Large Ensemble yielded unrealistic forcing. Instead, the shorter NCEP CFSv2 9-month forecasts were successfully tested and afforded an increased ensemble size (~30) to demonstrate gains of dynamical downscaling at sub-seasonal to intra-annual time scales. The improved model physics and coupling among RASM model components have yielded more realistic representation of the sea ice cover and consistent across all model components initial conditions. Consequently, RASM demonstrates significant gains compared to simulation of sea ice in the NCEP reanalysis. In addition, RASM 6-month ensemble forecasts yield very realistic sea ice distribution, which demonstrates both significant gains of dynamical downscaling and the continued impact of the initial conditions on forecasts out to 6 months (https://nps.edu/web/rasm/predictions). A follow up study using RASM for dynamical downscaling of the more realistic CESM initialized Decadal Prediction Large Ensemble output is currently ongoing as part of the DOE RGMA HiLAT-RASM project.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2021

Self-Assembly of Flexible Linear–Semiflexible Bottlebrush–Flexible Linear Triblock Copolymers

Block copolymer (BCP) self-assembly is a fundamental process in which incompatible blocks spontaneously form organized microstructures with broad practical applications. Classical understanding is that the domain spacing is limited by the contour length of the polymer backbone. Here, using a combination of molecular design, chemical synthesis, small-/wide-angle X-ray scattering, transmission electron microscopy, and electron tomography, we discover that this molecular picture does not hold for architecturally semiflexible BCPs. For strongly segregated linear–semiflexible bottlebrush–linear triblock copolymers, the size of the bottlebrush domain can be twice the bottlebrush backbone contour length. The mechanism of such anomalous self-assembly is likely that the interfacial repulsion between the incompatible blocks is large enough to pull a part of the linear end blocks into the bottlebrush domain. This effectively increases the bottlebrush domain size. Moreover, the semiflexible bottlebrush widens the regime for the cylinder morphology that is associated with the volume fraction of the end blocks fC SFB &isin; (0.10, >0.41). This window is much wider than that for flexible linear BCPs, fC F &isin; (0.14, 0.35), and that predicted by the recent self-consistent field theory for linear-bottlebrush BCPs of the same chemistry and molecular architecture. Finally, our experimental findings reveal previously unrecognized mechanisms for the self-assembly of architecturally complex BCPs.

36 MATERIALS SCIENCE↗
DOE OSTI2022

Structural Characterization of Uranium Tetrafluoride Hydrate (UF 4 ·2.5H 2 O)

Uranium tetrafluoride is an important intermediate in the nuclear fuel cycle. Facile synthesis of its hydrate, uranium tetrafluoride hydrate (UF 4 ·2.5H 2 O), has recently been reported. The hydrate forms by contacting anhydrous UF 4 with neat H 2 O at room temperature for 24 h or by exposing anhydrous UF 4 to high relative humidity (>90%) conditions for several weeks. These pathways are of clear environmental relevance. Further understanding of the structure and optical spectra of UF 4 ·2.5H 2 O, especially of the water molecules, is therefore necessary. Herein, the structure of UF 4 ·2.5H 2 O was probed using time-of-flight neutron powder diffraction to improve understanding of the crystalline water environments in the structure. The complete structure was elucidated and compared to a previously reported partial structure for UF 4 ·2.5H 2 O and a predicted complete structure from density functional theory. The crystalline structure exhibits three distinct water environments: two of the three water sites are bound to uranium, and the third water is unbound or “free”. Furthermore, the completed structure reveals an extensive hydrogen bonding network involving water–fluorine and water–water interactions. One bound water site participates in hydrogen bonding with nearby fluoride ligands (O–H···F–U), and the second bound water site participates in hydrogen bonding with the unbound water (O–H···O) and a nearby fluoride ligand (O–H···F–U); the unbound water participates in hydrogen bonding with bound water (O–H···O–U). Low-temperature experiments and thermal analysis indicate UF 4 ·2.5H 2 O is thermally stable from 10 to 358 K, undergoes dehydration at higher temperatures, and is nearly dehydrated at 473 K. Structural measurements provide foundational understanding and will inform future investigations of the thermal and environmental stability of UF 4 ·2.5H 2 O.

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

Domain architecture and catalysis of the Staphylococcus aureus fatty acid kinase

Fatty acid kinase (Fak) is a two-component enzyme that generates acyl-phosphate for phospholipid synthesis. Fak consists of a kinase domain protein (FakA) that phosphorylates a fatty acid enveloped by a fatty acid binding protein (FakB). The structural basis for FakB function has been established, but little is known about FakA. Here, we used limited proteolysis to define three separate FakA domains: the amino terminal FakA_N, the central FakA_L, and the carboxy terminal FakA_C. The isolated domains lack kinase activity, but activity is restored when FakA_N and FakA_L are present individually or connected as FakA_NL. The X-ray structure of the monomeric FakA_N captures the product complex with ADP and two Mg 2+ ions bound at the nucleotide site. The FakA_L domain encodes the dimerization interface along with conserved catalytic residues Cys240, His282, and His284. AlphaFold analysis of FakA_L predicts the catalytic residues are spatially clustered and pointing away from the dimerization surface. Furthermore, the X-ray structure of FakA_C shows that it consists of two subdomains that are structurally related to FakB. Analytical ultracentrifugation demonstrates that FakA_C binds FakB, and site-directed mutagenesis confirms that a positively charged wedge on FakB meshes with a negatively charged groove on FakA_C. Finally, small angle X-ray scattering analysis is consistent with freely rotating FakA_N and FakA_C domains tethered by flexible linkers to FakA_L. These data reveal specific roles for the three independently folded FakA protein domains in substrate binding and catalysis.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2025

Out-of-distribution detection with non-parametric density estimation for models predicting processing history of uranium ore concentrates

The rapid advancement in machine learning (ML) and computer vision (CV) coincides with the growth of interest in deploying these ML/CV models in numerous fields from medicine to social science. Similar to those areas, we have witnessed a great number of works in materials science employing ML/CV models – neural networks in particular – in their studies in recent years. These models have proven to obtain accurate performance in various tasks. However, these models struggle to attain a similar performance when encountering test samples coming from a distribution that is different from the training set. More importantly, they fail without providing any warning to the users. Therefore, we propose a framework for detecting out-of-distribution (OOD) samples to alert users when a human intervention might be necessary in this work. Specifically, we explore the use of a non-parametric density estimation method to detect OOD samples. Here, we assess OOD detection capability of the proposed framework on ML models developed for categorizing precipitation routes of U 3 O 8 when encountering OOD datasets that contain samples (1) undergone different imaging acquisition process, (2) undergone different material synthesis process, and (3) different materials than ID set. Through those experiments, we achieve an average area under the receiver operating characteristic (AUROC) of at least 91% on average in detecting OOD samples. With minimal overhead cost and superior performance, the proposed framework enables a reliable and safe system when deploying in real-world scenarios.

Convolutional neural networks↗