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All sourcesNASA NTRSDOE OSTI
DOE OSTI2021

Screening two-dimensional materials with topological flat bands

The topological flat band (TFB) has been proposed theoretically in various lattice models, to exhibit a rich spectrum of intriguing physical behaviors. However, the experimental demonstration of flat band (FB) properties has been severely hindered by the lack of materials realization. In this study, by screening materials from a first-principles materials database, we identify a group of two-dimensional materials with TFBs near the Fermi level, covering some simple line-graph and generalized line-graph FB lattice models. These include the kagome sublattice of O in Ti O 2 yielding a spin-unpolarized TFB, and that of V in ferromagnetic V 3 F 8 yielding a spin-polarized TFB. The monolayer Nb 3 Te Cl 7 and its counterparts from element substitution are found to be breathing-kagome-lattice crystals. The family of monolayer II I 2 V I 3 compounds exhibit a TFB representing the coloring-triangle lattice model. Re F 3 , Mn F 3 , and Mn Br 3 are all predicted to be diatomic-kagome-lattice crystals, with TFB transitions induced by atomic substitution. Finally, Hg F 2 , Cd F 2 , and Zn F 2 are discovered to host dual TFBs in the diamond-octagon lattice. Our findings pave the way to further experimental exploration of eluding FB materials and properties.

36 MATERIALS SCIENCE↗
DOE OSTI2024

Raman Sideband Cooling of Molecules in an Optical Tweezer Array to the 3D Motional Ground State

Ultracold polar molecules are promising for quantum information processing and searches for physics beyond the standard model. Laser cooling to ultracold temperatures is an established technique for trapped diatomic and triatomic molecules. Further cooling of the molecules to near the motional ground state is crucial for reducing various dephasings in quantum and precision applications. In this work, we demonstrate Raman sideband cooling (RSC) of CaF molecules in optical tweezers to near their motional ground state, with average motional occupation quantum numbers of n ¯ x = 0.16 ( 12 ) , n ¯ y = 0.17 ( 17 ) (radial directions), and n ¯ z = 0.22 ( 16 ) (axial direction), and a 3-D motional-ground-state probability of 54 ± 18 % of the molecules that survive the RSC. This process paves the way to increase molecular coherence times in optical tweezers for robust quantum computation and simulation applications. Published by the American Physical Society 2024

Physics↗
DOE OSTI2020

Temperature drives local contributions to beta diversity in mountain streams: stochastic and deterministic processes

Community variation (i.e. beta diversity) in geographical coenoclines is of substantial interest in ecology, yet the elevational patterns in beta diversity are still understudied, and no general conclusions have been reached. Here, we explored local contributions to beta diversity (LCBD) of stream bacteria, diatoms and macroinvertebrates on mountainsides. Across all taxa, we revealed a general U-shaped LCBD-elevation relationships (LCBDer), suggesting higher uniqueness of community composition at the two ends of the elevational gradients. This pattern was confirmed by coenocline simulations based on observed communities, and supported by the dominance of species replacement in total beta diversity. Across mountains and taxonomic groups, temperature was the main environmental factor underlying elevational patterns in LCBD and its metric relatives, which were also mediated by local environmental variables. The observed magnitudes of U-shaped LCBDer across mountains and taxonomic groups were specifically related to the heterogeneity of stream morphology, and the mean annual temperature on each mountain. U-shaped LCBDer were strengthened by the occurrence of generalist species with large elevational ranges, while rare species had a lesser effect on the patterns. Raup-Crick beta diversity indicated that both stochastic and deterministic processes drove the community assembly, and the latter one was positively related to the magnitudes of LCBDer. Our synthesis across mountains and taxonomic groups clearly shows that there are consistent elevational patterns in LCBD among taxonomic groups, and that these patterns are explained by similar ecological mechanisms, producing a more complete picture in understanding and bridging the spatial variation in biodiversity under changing climate.

Wang, Jianjun↗
DOE OSTI2021

The Influence of Bacteria on the Growth, Lipid Production, and Extracellular Metabolite Accumulation by Phaeodactylum tricornutum (Bacillariophyceae)

Here, to examine the impact of heterotrophic bacteria on microalgal physiology, we co-cultured the diatom Phaeodactylum tricornutum with six bacterial strains to quantify bacteria-mediated differences in algal biomass, total intracellular lipids, and for a subset, extracellular metabolite accumulation. A Marinobacter isolate significantly increased algal cell concentrations, dry biomass, and lipid content compared to axenic algal cultures. Two other bacterial strains from the Bacteroidetes order, of the genera Algoriphagus and Muricauda, significantly lowered P. tricornutum biomass, leading to overall decreased lipid accumulation. These three bacterial co-cultures (one mutualistic, two competitive) were analyzed for extracellular metabolites via untargeted liquid chromatography mass spectrometry to compare against bacteria-free cultures. Over 80% of the extracellular metabolites differentially abundant in at least one treatment were in higher concentrations in the axenic cultures, in agreement with the hypothesis that the co-cultured bacteria incorporated algal-derived organic compounds for growth. Furthermore, the extracellular metabolite profiles of the two growth-inhibiting cultures were more similar to one another than the growth-promoting co-culture, linking metabolite patterns to ecological role. Our results show that algal–bacterial interactions can influence the accumulation of intracellular lipids and extracellular metabolites, and suggest that utilization and accumulation of compounds outside the cell play a role in regulating microbial interactions.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2023

Dynamic Phaeodactylum tricornutum exometabolites shape surrounding bacterial communities

Summary Roles of different ecological classes of algal exometabolites in regulating microbial community composition are not well understood. Here, we identify exometabolites from the model diatom Phaeodactylum tricornutum and demonstrate their potential to influence bacterial abundances. We profiled exometabolites across a time course of axenic algal growth using liquid chromatography–tandem mass spectrometry. We then investigated growth of 12 bacterial isolates on individual‐identified exometabolites. Lastly, we compared responses of a P. tricornutum ‐adapted enrichment community to additions of two contrasting metabolites: selective growth substrate 4‐hydroxybenzoic acid and putative signaling/facilitator molecule lumichrome. We identified 50 P. tricornutum metabolites and found distinct temporal accumulation patterns. Two exometabolites (of 12 tested) supported growth of distinct subsets of bacterial isolates. While algal exudates and algal presence drove similar changes in community composition compared with controls, exogenous 4‐hydroxybenzoic acid addition promoted increased abundances of taxa that utilized it in isolation, and also revealed the importance of factors relating to algal presence in regulating community composition. This work demonstrates that secretion of selective bacterial growth substrates represents one mechanism by which algal exometabolites can influence bacterial community composition and illustrates how the algal exometabolome has the potential to modulate bacterial communities as a function of algal growth.

4-hydroxybenzoic acid↗
DOE OSTI2024

Identifying the gene responsible for non‐photochemical quenching reversal in Phaeodactylum tricornutum

SUMMARY Algae such as diatoms and haptophytes have distinct photosynthetic pigments from plants, including a novel set of carotenoids. This includes a primary xanthophyll cycle comprised of diadinoxanthin and its de‐epoxidation product diatoxanthin that enables the switch between light harvesting and non‐photochemical quenching (NPQ)‐mediated dissipation of light energy. The enzyme responsible for the reversal of this cycle was previously unknown. Here, we identified zeaxanthin epoxidase 3 (ZEP3) from Phaeodactylum tricornutum as the candidate diatoxanthin epoxidase. Knocking out the ZEP3 gene caused a loss of rapidly reversible NPQ following saturating light exposure. This correlated with the maintenance of high concentrations of diatoxanthin during recovery in low light. Xanthophyll cycling and NPQ relaxation were restored via complementation of the wild‐type ZEP3 gene. The zep3 knockout strains showed reduced photosynthetic rates at higher light fluxes and reduced specific growth rate in variable light regimes, likely due to the mutant strains becoming locked in a light energy dissipation state. We were able to toggle the level of NPQ capacity in a time and dose dependent manner by placing the ZEP3 gene under the control of a β‐estradiol inducible promoter. Identification of this gene provides a deeper understanding of the diversification of photosynthetic control in algae compared to plants and suggests a potential target to improve the productivity of industrial‐scale cultures.

Ware, Maxwell A.↗
DOE OSTI2022

Metatranscriptomic Sequencing of Winter and Spring Planktonic Communities from Lake Erie, a Laurentian Great Lake

Previous reports suggest planktonic and under-ice winter microbial communities in Lake Erie are dominated by diatoms. Here, we report the assembled metatranscriptomes of 79 Lake Erie surface water microbial communities spanning both the winter (28 samples) and spring (51 samples) months over spatial, temporal, and climatic gradients in 2019 through 2020.

Zepernick, Brittany N.↗
DOE OSTI2023

ORNL_AISD-Ex: Quantum chemical prediction of UV/Vis absorption spectra for over 10 million organic molecules

We performed calculations of electronic excitation energies and associated oscillator strengths based on the time-dependent density-functional tight-binding (TD-DFTB) method [1]. The SMILES (Simplified molecular-input line-entry system) strings of the molecules from the AISD HOMO-LUMO database [2] were converted to a 3D atomistic structure and stored in a PDB file after preliminary geometry optimization using the Merck Molecular Force Field (MMFF94) in RDKit [3,4]. The primary information stored in the PDB file archive consists of Cartesian coordinates for each atom of the molecule in their 3D location in space, along with summary information about the structure, sequence, and experiment. We then performed molecular geometry optimization using the density-functional tight-binding (DFTB) method [5] in the electronic ground state, followed by single-point excited states calculations, as described below. We note that, since RDKit employs a random choice for the generation of molecular conformers, the molecular geometries obtained in this dataset could be different from the ones that were generated when the AISD HOMO-LUMO dataset was generated. The computed excitation energies and associated oscillator strengths can be converted to predict UV/Vis absorption spectra, where excitation energies correspond to absorption peak positions, and oscillator strengths are a good measure of the probability of absorption of visible or UV light in transitions between electronic ground and excited states. The conversion of SMILES strings to 3D Cartesian coordinates of fully DFTB-optimized molecules was successful for 10,502,904 out of 10,502,917 molecules. For these molecules, both geometry optimizations and excited states calculations were successful. The DFTB calculations did not complete for 13 molecules of the original AISD HOMO-LUMO dataset. We still provide information about the geometry of these molecules. The molecules are diverse for chemical compositions (which span 5 non-hydrogen elements: oxygen, carbon, nitrogen, fluorine, sulfur) and molecular size (the smallest molecule contains 5 non-hydrogen atoms, and the largest molecule contains 71 non-hydrogen atoms). The DFTB method [5] is an approximation to density functional theory (DFT), utilizing a minimal basis set in conjunction with a two-center approximation to the electronic Hamiltonian and overlap matrix elements. The DFTB total energy is the sum of an electronic and a repulsive energy contribution, and their calculation requires optimized electronic parameters and diatomic repulsive potential energy functions. All DFTB calculations were performed using the DFTB+ code [6] (version 21.2) and the wrapper for DFTB+ in the Atomic Simulation Environment (ASE) (version 3.22.1) [7], which performed an internal conversion of Cartesian coordinates from PDB to the .gen file format. For the geometry optimizations on the electronic ground state potential energy surface of the molecules, we have chosen the third-order DFTB (DFTB3) method [5c] and employed the matching 3ob set of electronic parameters and repulsive potentials [8]. The empirical γ-damping for hydrogen bond correction, and Grimme's D3 empirical dispersion correction with Becke-Johnson damping (D3(BJ)) [9] dispersion correction was included to improve the description of non-covalent interactions. For excited states single-point energy calculations, we employed the TD-DFTB method in conjunction with the DFTB2 method [5b] and the matching mio [5b,10] and halorg [11] parameter sets. We opted to request the simultaneous calculation of 50 excited states for singlet transition to investigate sufficient number of excited states, based on linear response theory using the Casida equation [Ref: T. A. Niehaus, S. Suhai, F. Della Sala, P Lugli, M. Elstner, G. Seifert, and Th. Frauenheim. Tight-binding approach to time-dependent density-functional response theory. Phys. Rev. B, 63:085108, 2001] and the ARPACK diagonalizer [R. B. Lehoucq, D. C. Sorensen, and C. Yang. Arpack users guide: Solution of large-scale eigenvalue problems by implicitly restarted arnoldi methods, 1997. 46, 51]. The dataset contains 1001 tar.gz files. Tar files are named as “ornl_aisd_ex_1.tar.gz†through “ornl_aisd_ex_1000.tar.gzâ€. Additionally, the 13 failed molecules are in “ornl_aisd_ex_unprocessed.tar.gzâ€. Except for the tar files listed below, each tar file contains 10,500 molecules. Tar files numbered 34, 121, 128, 352, 360, 429, 495, 509, 518, 627, 676, 668, and 862 contain 10,499 molecules each. The last tar file numbered 1000 contains 13,417 molecules. The total size of the uncompressed dataset is over 283 Gigabytes. The code for calculating the electronic excitation energies and statistical analysis of the dataset is provided at the following GitLab repository: https://github.com/ORNL/Analysis-of-Large-Scale-Molecular-Datasets-with-Python Calculating the UV spectrum of a molecule requires performing 3 main operations: 1. Converting the smiles string representation of a molecule into a geometric structure where each atom is assigned XYZ coordinates. The geometric structure is written to the file smiles.pdb. 2. Using smiles.pdb to compute the relaxed geometry of the molecule, which corresponds with the position of the atoms at the position of equilibrium at the ground state. This generates the files band.out, detailed.out, and geo_end.gen. 3. Using geo_end.gen to calculate the UV spectrum of the molecule which is written into the file EXC.DAT. Every molecule in the dataset has its own directory. The files contained in each molecule directory are as follows: 1. geo_end.gen 2. detailed.out 3. band.out 4. EXC.DAT 5. smiles.pdb REFERENCES [1] Niehaus, T. A.; Suhai, S.; Della Salla, F.; Lugli, P.; Elstner, M.; Seifert, G.; Frauenheim, Th. Tight-binding approach to time-dependent density-functional response theory. Phys. Rev. B, 2001, 63, 085108/1-9. [2] Blanchard, A.; Gounley, J.; Metha, K.; Yoo, P.; Irle, S. AISD HOMO-LUMO. DOI: 10.13139/ORNLNCCS/1869409 [3] RDKit: Cheminformatics and Machine Learning Software. 2013, [http://www.rdkit.org] [4] Tosco, P.; Stiefl, N. and Landrum, G. Bringing the MMFF force field to the RDKit: implementation and validation. J Cheminform. 2014, 6, 1–4. [5] a) Porezag, D.; Frauenheim, T.; Kohler, T.; Seifert, G.; Kaschner, Construction of tight-binding-like potentials on the basis of density-functional theory: Application to carbon, R. Phys. Rev. B 1995, 51, 12947-12957; b) Elstner, M.; Porezag, D.; Jungnickel, G.; Elsner, J.; Haugk, M.; Frauenheim, Th.; Suhai, S.; Seifert, G.; Phys. Rev. B 1998, 58, 7260-7268; c) Gaus, M.; Cui, Q.; Elstner, M. DFTB3: Extension of the Self-Consistent-Charge Density-Functional Tight-Binding Method (SCC-DFTB), J. Chem. Theory Comput. 2011, 7, 931-948; d) Cui, Q.; Elstner, M. Density functional tight binding: values of semi-empirical methods in an ab initio era, Phys. Chem. Chem. Phys. 2014, 16, 14368-14377. [6] Hourahine, B. et al. DFTB+, a software package for efficient approximate density functional theory based atomistic simulations, J. Chem. Phys. 2020, 152, 124101/1-19. [7] Larsen, A. H. et al. The atomic simulation environment—a Python library for working with atoms. J. Phys.: Cond. Matter 2017, 29, 273002. [8] Kubillus, M.; Kubar, T.; Gaus, M.; Rezac, J.; Elstner, M. Parameterization of the DFTB3 Method for Br, Ca, Cl, F, I, K, and Na in Organic and Biological Systems, J. Chem. Theory Comput. 2015, 11, 332-342. [9] Brandenburg, J. G.; Grimme, S. Accurate Modeling of Organic Molecular Crystals by Dispersion-Corrected Density Functional Tight Binding (DFTB), J. Phys. Chem. Lett. 2014, 5, 1785−1789. [10] a) Niehaus, T. A.; Elstner, M.; Frauenheim, Th.; Suhai, S. Application of an approximate density-functional method to sulfur containing compounds. J. Mol. Struct.: THEOCHEM 2001, 541, 185-94; b) Elstner, M.; Hobza, P.; Frauenheim, Th.; Suhai, S.; Kaxiras, E. Hydrogen bonding and stacking interactions of nucleic acid base pairs: A density-functional-theory based treatment. J. Chem. Phys. 2001, 114, 5149-55. [11] Kubar, T.; Bodrog, Z.; Gaus, M.; Köhler, C.; Aradi, B.; Frauenheim, Th.; Elstner, M. Parametrization of the SCC-DFTB Method for Halogens. J. Chem. Theory Comput. 2013, 9, 2939-49.

36 MATERIALS SCIENCE↗
DOE OSTI2023

Four-dimensional dynamics of multirotational transition stimulated rotational Raman scattering in air

Stimulated rotational Raman scattering in air is a powerful parasitic process that degrades high intensity laser beams and pulses propagated over significant distances. Conversely, it is used beneficially in the context of Raman lasers. Through this inelastic scattering process, laser photons are converted to higher (anti-Stokes) or lower (Stokes) energies, according to rotational mode transitions in nitrogen and oxygen diatomic molecules. The full wave-mixing problem involves numerous frequencies, and it is consistently assumed that only one rotational mode contributes to the conversion process. We instead present a dynamic 4D multirotational model that is implemented in a parallelized manner within the Virtual Beamline++ optical modeling package allowing high-resolution 4D studies. We highlight the effect that spontaneous emission plays in large and small beam-width setups, even in the highly saturating regime. The weaker transition modes play a large role in the persistent dynamics and can lead to complex spatiotemporal coupling through nonlinear competition of the modes. We highlight how and why these weaker modes persist, how the size and shape of speckle patterns depends highly on the initial beam profile, and how weaker modes can transiently become stronger as a result of such competition.

47 OTHER INSTRUMENTATION↗
DOE OSTI2022

Simultaneous single-shot rotation–vibration non-equilibrium thermometry using pure rotational fs/ps CARS coherence beating

Here, we report the development of a simple and sensitive two-beam hybrid femtosecond/picosecond pure rotational coherent anti-Stokes Raman scattering (fs/ps CARS) method to simultaneously measure the rotational and vibrational temperatures of diatomic molecules. Rotation–vibration non-equilibrium plays a key role in the chemistry and thermalization in low-temperature plasmas as well as thermal loading of hypersonic vehicles. This approach uses time-domain interferences between ground state and vibrationally excited N 2 molecules to intentionally induce coherence beating that leads to apparent non-Boltzmann distributions in the pure rotational spectra. These distortions enable simultaneous inference of both the rotational and vibrational temperatures. Coherence beating effects were observed in single-shot fs/ps CARS measurements of a 75 Torr N 2 DC glow discharge and were successfully modeled for rotational and vibrational temperature extraction. We show that this method can be more sensitive than a pure rotational fs/ps CARS approach using a spectrally narrow probe pulse. Lastly, we experimentally measured the beat frequencies via Fourier transform of the time-domain response and obtained excellent agreement with the model.

42 ENGINEERING↗
DOE OSTI2024

One-dimensional temperature measurement of supersonic jet flow by resonantly ionized photoemission thermometry of molecular nitrogen

As the field of fluid dynamics progresses, the demand for sophisticated diagnostic methods to accurately assess flow conditions rises. In this work, resonantly ionized photoemission thermometry (RIPT) has been used to directly target and ionize diatomic nitrogen (N 2 ) to measure one-dimensional (1D) temperature profiles in a supersonic jet flow. This technique can be considered non-intrusive as the premise uses resonantly enhanced multiphoton ionization (REMPI) to target molecular nitrogen. This resonance excites N 2 into absorption bands of the P, Q, and R rotational branches of N 2 ( b 1 Π u ). The ideal (3 + 1) REMPI scheme excites from the ground state and ionizes N 2 ( b 1 Π u ← X 1 Σ g + ) where de-excitation results in photoemission from the first negative band of ionized N 2 + ( B 2 Σ u + → X 2 Σ g + ) as nitrogen returns to the ground state. The resulting emission can be observed using an intensified camera, thus permitting inference of the rotational temperature of ground-state molecular nitrogen. A linearly regressive Boltzmann distribution is applied based on previous calibration data for this technique to quantify the temperature along the ionized line. This work applies this technique to a pure N 2 supersonic jet in cross-flow and counter-flow orientations to demonstrate N 2 RIPT’s applications in a supersonic flow. Temperature variations are observed at different locations downstream of the exit in cross-flow, and axisymmetric in counter-flow, to generate profiles characterizing the flow dynamics. Due to the collisional effects resulting from the number density of N 2 at higher pressures, a (3 + 2) REMPI scheme is observed throughout this text.

Clark, Aleksander (ORCID:0009000855600042)↗
DOE OSTI2021

Elucidation of trophic interactions in an unusual single-cell nitrogen-fixing symbiosis using metabolic modeling

Marine nitrogen-fixing microorganisms are an important source of fixed nitrogen in oceanic ecosystems. The colonial cyanobacterium Trichodesmium and diatom symbionts were thought to be the primary contributors to oceanic N 2 fixation until the discovery of the unusual uncultivated symbiotic cyanobacterium UCYN-A ( Candidatus Atelocyanobacterium thalassa ). UCYN-A has atypical metabolic characteristics lacking the oxygen-evolving photosystem II, the tricarboxylic acid cycle, the carbon-fixation enzyme RuBisCo and de novo biosynthetic pathways for a number of amino acids and nucleotides. Therefore, it is obligately symbiotic with its single-celled haptophyte algal host. UCYN-A receives fixed carbon from its host and returns fixed nitrogen, but further insights into this symbiosis are precluded by both UCYN-A and its host being uncultured. In order to investigate how this syntrophy is coordinated, we reconstructed bottom-up genome-scale metabolic models of UCYN-A and its algal partner to explore possible trophic scenarios, focusing on nitrogen fixation and biomass synthesis. Since both partners are uncultivated and only the genome sequence of UCYN-A is available, we used the phylogenetically related Chrysochromulina tobin as a proxy for the host. Through the use of flux balance analysis (FBA), we determined the minimal set of metabolites and biochemical functions that must be shared between the two organisms to ensure viability and growth. We quantitatively investigated the metabolic characteristics that facilitate daytime N 2 fixation in UCYN-A and possible oxygen-scavenging mechanisms needed to create an anaerobic environment to allow nitrogenase to function. This is the first application of an FBA framework to examine the tight metabolic coupling between uncultivated microbes in marine symbiotic communities and provides a roadmap for future efforts focusing on such specialized systems.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2026

Multidimensional scaling informed by F -statistic: Visualizing grouped microbiome data with inference

Multidimensional scaling (MDS) is a widely used dimensionality reduction technique in microbial ecology data analysis that captures the multivariate structure of the data while preserving pairwise distances between samples. While improvements in MDS have enhanced the ability to reveal group-specific data patterns, these MDS-based methods require prior assumptions for inference, limiting their application in general microbiome analysis. Here, in this study, we introduce a new MDS-based ordination method, “F-informed MDS,” which configures the data distribution based on the F-statistic, the ratio of dispersion between groups sharing common and different characteristics. Using semisynthetic datasets, we demonstrate that the proposed method is robust to hyperparameter selection while maintaining statistical significance throughout the ordination process. Various quality metrics for evaluating dimensionality reduction confirm that F-informed MDS is comparable to state-of-the-art methods in preserving both local and global data structures. Its application to a diatom-associated bacterial community suggests the role of this new method in interpreting the community’s response to the host. Our approach offers a well-founded refinement of MDS that aligns with statistical test results, which can be beneficial for broader multidimensional data analyses in microbiology and ecology. This new visualization tool can be incorporated into standard microbiome data analyses.

Biological and medical sciences↗
DOE OSTI2024

Characteristics and sources of fluorescent aerosols in the central Arctic Ocean

The Arctic is sensitive to cloud radiative forcing. Due to the limited number of aerosols present throughout much of the year, cloud formation is susceptible to the presence of cloud condensation nuclei and ice nucleating particles (INPs). Primary biological aerosol particles (PBAP) contribute to INPs and can impact cloud phase, lifetime, and radiative properties. We present yearlong observations of hyperfluorescent aerosols (HFA), tracers for PBAP, conducted with a Wideband Integrated Bioaerosol Sensor, New Electronics Option during the Multidisciplinary drifting Observatory for the Study of Arctic Climate (MOSAiC) expedition (October 2019–September 2020) in the central Arctic. We investigate the influence of potential anthropogenic and natural sources on the characteristics of the HFA and relate our measurements to INP observations during MOSAiC. Anthropogenic sources influenced HFA during the Arctic haze period. But surprisingly, we also found sporadic “bursts” of HFA with the characteristics of PBAP during this time, albeit with unclear origin. The characteristics of HFA between May and August 2020 and in October 2019 indicate a strong contribution of PBAP to HFA. Notably from May to August, PBAP coincided with the presence of INPs nucleating at elevated temperatures, that is, >–9°C, suggesting that HFA contributed to the “warm INP” concentration. The air mass residence time and area between May and August and in October were dominated by the open ocean and sea ice, pointing toward PBAP sources from within the Arctic Ocean. As the central Arctic changes drastically due to climate warming with expected implications on aerosol–cloud interactions, we recommend targeted observations of PBAP that reveal their nature (e.g., bacteria, diatoms, fungal spores) in the atmosphere and in relevant surface sources, such as the sea ice, snow on sea ice, melt ponds, leads, and open water, to gain further insights into the relevant source processes and how they might change in the future.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2021

Development of Algal Biomass Yield Improvements in an Integrated Process (Final Report)

This project built on the success of Global Algae Innovations Algae Biomass Yield Phase 1 project to accelerate the commercialization of algal biofuels through development of an integrated, economical, photosynthetic, open raceway system to produce algal oil. Two parallel pathways to a biofuel were investigated. In the algal crude oil pathway, highlighted in blue, the dewatered algal biomass slurry is used as a feed to hydrothermal liquefaction to produce an algae crude oil and recycle aqueous stream. In the algal lipid oil pathway, highlighted in green, the algal biomass slurry is dried, and the oil is extracted to produce an algal lipid oil biofuel intermediate and a high protein algae meal co-product. Upgrading to drop-in fuels has been demonstrated for the biofuel intermediates in both pathways. Since the algal lipid oil pathway requires lipid accumulation, the productivity is generally lower than the algal crude oil pathway, but the required productivity for economical algal biofuel production is also lower because the coproduct value is greater. The outdoor cultivation was performed at the Kauai Algae Farm. The project team has expertise across the full breadth strain development, advanced algal cultivation, open raceway contamination control, CO 2 supply, harvesting, dewatering, extraction, hydrothermal liquefaction, technoeconomic analysis and life cycle analysis: Hildebrand laboratory at Scripps Institution of Oceanography – diatom strain development. Mayfield laboratory at UCSD - green algae strain development. TSD Management Associates- CO 2 supply, algal harvesting and dewatering, and algal drying and extraction. Qualitas - large-scale test site for algal harvesting technology. Texas A&M University - algal drying and extraction technology. Pacific Northwest National Laboratory - hydrothermal liquefaction technology. GE Water and Power - membrane technology. National Renewable Energy Laboratory - algal techno-economic analysis. Phase 1 of the project resulted in tremendous productivity and pre-processing improvements in an integrated, large-scale, low-cost cultivation and pre-processing process that moved algal technology closer to economic viability for biofuels than ever before. Phase 2 accomplishments further facilitate development of a commercial algal biofuel industry by adding: several top performing strains and strain development tools including breeding; open-pond cultivation innovations that achieved a 30% improvement in overall productivity, an 83% reduction in cost, and a 95% reduction in energy use relative to conventional technology; further improvements in harvesting that led to the Zobi harvester ® as a universal, economical, low energy, commercially available microalgae harvesting solution; breakthroughs in drying and extraction including a new low energy drying process and several new low energy extraction unit operations that together with the Zobi harvester ® achieve a 90% reduction in cost and 97% reduction in energy use relative to conventional technology. These improvements are sufficient to enable economical production of algae biofuel and protein meal co-product if the process were scaled up to a commercial-scale 5,000-acre algae farm.

09 BIOMASS FUELS↗
DOE OSTI2024

Biomanufacturing and bioprocessing of lunar regolith

Microbial biomanufacturing is important to accelerate lunar construction because it can leverage lunar material and waste streams as feedstocks to create a circular production system. In-space bio-mining and biomanufacturing using moon and asteroidal source material will enable the creation of infrastructure, produce industrial fuels and lubricants, and enable recovery of actinides and rare-earth elements (REEs) present in trace concentrations. Moreover, biomanufacturing in closed-loop systems (recycling and reuse of resources toward the establishment of a circular economy) will enable long-term lunar activities by recycling waste (CO 2 , gray water) and producing oxygen and biomaterials. Our response focuses on the use of lunar regolith and waste streams as feedstocks for protein and microbial-enabled biomining and bioprocessing to extract actinides and REEs, and to create biocomposites for lunar infrastructure. We envision an enclosed process that initiates with (1a) extracting actinides and REEs from lunar regolith using immobilized proteins, followed by (1b) creating biocomposites from the post-extracted lunar regolith for infrastructure, and (1c) cultivating diatoms and other microalgae on waste streams to harvest silica shells for incorporating into biocomposites and to generate O 2 for human respiration and/or producing refinable feedstocks. LLNL has significant expertise in all three processes and provides facilities, personnel, and expertise at the intersection of metal (lanthanide, actinide, transition) separations, purifications, biohydrometallurgy, radiobiochemistry, synthetic and systems biology, and materials science and engineering. Importantly, all three processes are relatively well-studied for Earth-based workflows and can be derisked for demonstration on the lunar surface by 2029.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2024

Bottom-up design of actinide materials from molecular clusters: Demonstration of a general-purpose simulation capability leveraging machine-learned atomic potentials

Actinide thin-film coatings such as uranium dioxide (UO 2 ) play an important role in nuclear reactors and other mission-relevant applications, but realization of their potential requires a deep fundamental understanding of the chemical vapor deposition (CVD) processes used for their growth. The slow experimental progress can be attributed, in part, to the standard safety guidelines associated with handling uranium byproducts, which are often corrosive, toxic, and radioactive. Accurate simulation techniques, when used in concert with experiment, can improve laboratory safety, material durability, and deliverable timeframes. However, state-of-the-art computational methods are either insufficiently accurate or intractably expensive. To remedy this situation, in this project we suggested a machine-learning (ML) accelerated workflow for simulating molecular clustering toward deposition. As a benchmark test case, we considered molecular clustering in steam and assessed independent components of our workflow by comparing with measured thermodynamic properties of water. After analyzing each component individually and finding no fundamental barrier to realization of the workflow, we attempted to integrate the ML component, a Sandia-developed tool called FitSNAP. As this was the first application of FitSNAP to atoms and molecules in the gas phase at Sandia, the method required more fitting data than was originally anticipated. Systematic improvements were made by including in the fit data diatomic potentials, molecular single-bond-breaking curves, and symmetry-constrained intermolecular potentials. We concluded that our strategy provides a feasible pathway toward modeling CVD and related processes, but that extensive training data must be generated before it can be of practical use.

36 MATERIALS SCIENCE↗
DOE OSTI2021

Iodine Sorption on AgZ-PAN

The Department of Energy (DOE) Nuclear Fuel Cycle and Supply Chain Program Material Recovery and Waste Form Development (MRWFD) Campaign Off-gas Sigma Team has performed research and development on iodine control and iodine waste forms for the past several years. This research and development has included iodine adsorption tests using a laboratory-scale test system containing multiple-segmented fixed beds of iodine adsorbents. Iodine capture performance has been tested using (a) non-radioactive synthetic gas mixtures blended from air, nitrogen, NO, NO 2 , water, to simulate dissolver off-gas (DOG) and vessel off-gas (VOG) streams from used nuclear fuel aqueous reprocessing, (b) inorganic and organic iodine species, and (c) different sorbents. An initial test of silver-functionalized mordenite in polyacrylonitrile matrix (AgZ-PAN) was conducted to assess if this sorbent, initially designed for selective sorption of Xe that evolves into used fuel reprocessing off-gas streams, could also be a candidate for iodine sorption. This test was conducted using the same deep-bed test system and methodologies used in many prior iodine sorption tests using other sorbents. Diatomic iodine (I2) was used as the target iodide in a gas stream containing air, NO, NO 2 , and moisture designed to simulate an aqueous reprocessing dissolver off-gas (DOG) stream.

12 MANAGEMENT OF RADIOACTIVE AND NON-RADIOACTIVE W↗