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All sourcesNASA NTRSDOE OSTI
DOE OSTI2024

Redshift evolution and covariances for joint lensing and clustering studies with DESI Y1

ABSTRACT Galaxy–galaxy lensing (GGL) and clustering measurements from the Dark Energy Spectroscopic Instrument Year 1 (DESI Y1) data set promise to yield unprecedented combined-probe tests of cosmology and the galaxy–halo connection. In such analyses, it is essential to identify and characterize all relevant statistical and systematic errors. We forecast the covariances of DESI Y1 GGL + clustering measurements and the systematic bias due to redshift evolution in the lens samples. Focusing on the projected clustering and GGL correlations, we compute a Gaussian analytical covariance, using a suite of N-body and lognormal simulations to characterize the effect of the survey footprint. Using the DESI one percent survey data, we measure the evolution of galaxy bias parameters for the DESI luminous red galaxy (LRG) and bright galaxy survey (BGS) samples. We find mild evolution in the LRGs in $0.4 < z < 0.8$, subdominant to the expected statistical errors. For BGS, we find less evolution for brighter absolute magnitude cuts, at the cost of reduced sample size. We find that for a redshift bin width $\Delta z = 0.1$, evolution effects on DESI Y1 GGL is negligible across all scales, all fiducial selection cuts, all fiducial redshift bins. Galaxy clustering is more sensitive to evolution due to the bias squared scaling. Nevertheless the redshift evolution effect is insignificant for clustering above the 1-halo scale of $0.1h^{-1}$ Mpc. For studies that wish to reliably access smaller scales, additional treatment of redshift evolution is likely needed. This study serves as a reference for GGL and clustering studies using the DESI Y1 sample.

79 ASTRONOMY AND ASTROPHYSICS↗
DOE OSTI2024

Measuring M31 globular cluster ages and metallicities using both photometry and spectroscopy

ABSTRACT The ages and metallicities of globular clusters play an important role not just in testing models for their formation and evolution but also in understanding the assembly history of their host galaxies. Here, we use a combination of imaging and spectroscopy to measure the ages and metallicities of globular clusters in M31, the closest massive galaxy to our own. We use the strength of the near-infrared calcium triplet spectral feature to provide a relatively age-insensitive prior on the metallicity when fitting stellar population models to the observed photometry. While the age–extinction degeneracy is an issue for globular clusters projected on to the disc of M31, we find generally old ages for globular clusters in the halo of M31 and in its satellite galaxy NGC 205 in line with previous studies. We measure ages for a number of outer halo globular clusters for the first time, finding that globular clusters associated with halo substructure extend to younger ages and higher metallicities than those associated with the smooth halo. This is in line with the expectation that the smooth halo was accreted earlier than the substructured halo.

Usher, Christopher (ORCID:0000000273837106)↗
DOE OSTI2024

Impact of property covariance on cluster weak lensing scaling relations

ABSTRACT We present an investigation into a hitherto unexplored systematic that affects the accuracy of galaxy cluster mass estimates with weak gravitational lensing. Specifically, we study the covariance between the weak lensing signal, ΔΣ, and the ‘true’ cluster galaxy number count, Ngal, as measured within a spherical volume that is void of projection effects. By quantifying the impact of this covariance on mass calibration, this work reveals a significant source of systematic uncertainty. Using the MDPL2 simulation with galaxies traced by the SAGE semi-analytic model, we measure the intrinsic property covariance between these observables within the three-dimensional vicinity of the cluster, spanning a range of dynamical mass and redshift values relevant for optical cluster surveys. Our results reveal a negative covariance at small radial scales (R ≲ R200c) and a null covariance at large scales (R ≳ R200c) across most mass and redshift bins. We also find that this covariance results in a $2{\!-\!}3~{{\ \rm per\ cent}}$ bias in the halo mass estimates in most bins. Furthermore, by modelling Ngal and ΔΣ as multi-(log)-linear equations of secondary halo properties, we provide a quantitative explanation for the physical origin of the negative covariance at small scales. Specifically, we demonstrate that the Ngal–ΔΣ covariance can be explained by the secondary properties of haloes that probe their formation history. We attribute the difference between our results and the positive bias seen in other works with (mock)-cluster finders to projection effects. These findings highlight the importance of accounting for the covariance between observables in cluster mass estimation, which is crucial for obtaining accurate constraints on cosmological parameters.

Astronomy & Astrophysics↗
DOE OSTI2020

Mixed ortho- H 2 and para- H 2 clusters studied by vibrational coherent anti-Stokes Raman spectroscopy

The search for macroscopic quantum effects, including superfluidity, in molecular hydrogen is mostly focused on its parahydrogen (p-H 2 ) nuclear spin modification because of weaker intermolecular interaction compared to orthohydrogen (o-H 2 ), both modifications being bosonic. In this work, mixed clusters of o-H 2 and p-H 2 containing similar to 10(4) molecules are prepared by supersonic expansion with helium and studied by vibrational coherent anti-Stokes Raman scattering (CARS) spectroscopy. At similar experimental conditions the neat p-H 2 clusters avoid freezing and remain fluid at 1-2 K, which is predicted to be the realm of their superfluid behavior [Phys. Rev. Lett. 101, 205301 (2008)]. Dependence of the vibrational frequencies and intensities of the main CARS peaks due to o-H 2 and p-H 2 versus the ratio of the o-H 2 and p-H 2 concentrations in the expanding gas suggests that o-H 2 and p-H 2 molecules are uniformly mixed in the interior of the clusters. A weak spectral feature at 4157 cm -1 that appears independent of the concentration ratio is assigned to the outer shell of the clusters enriched with p-H 2 molecules. Although the phase of the mixed clusters could not be unambiguously identified, the shift of the vibrational frequencies with respect to the bulk solid is consistent with the liquid state of the clusters.

75 CONDENSED MATTER PHYSICS, SUPERCONDUCTIVITY AND↗
DOE OSTI2020

Continuous momentum dependence in the dynamical cluster approximation

The dynamical cluster approximation (DCA) is a quantum cluster extension to the single-site dynamical mean-field theory that incorporates spatially nonlocal dynamic correlations systematically and nonperturbatively. The DCA + algorithm addresses the cluster shape dependence of the DCA and improves the convergence with cluster size by introducing a lattice self-energy with continuous momentum dependence. However, we show that the DCA + algorithm is plagued by a fundamental problem when its self-consistency equations are formulated using the bare Green's function of the cluster. This problem is most severe in the strongly correlated regime at low doping, where the DCA + self-energy becomes overly metallic and local, and persists to cluster sizes where the standard DCA has long converged. In view of the failure of the DCA + algorithm, we propose to complement DCA simulations with a post-interpolation procedure for single-particle and two-particle correlation functions to preserve continuous momentum dependence and the associated benefits in the DCA. We demonstrate the effectiveness of this practical approach with results for the half-filled and hole-doped two-dimensional Hubbard model.

75 CONDENSED MATTER PHYSICS, SUPERCONDUCTIVITY AND↗
DOE OSTI2024

Masses of Sunyaev-Zel’dovich galaxy clusters detected by the Atacama Cosmology Telescope: Stacked lensing measurements with Subaru HSC year 3 data

We present a stacked lensing analysis of 96 galaxy clusters selected by the thermal Sunyaev-Zel’dovich (SZ) effect in maps of the cosmic microwave background (CMB). We select foreground galaxy clusters with a 5 σ -level SZ threshold in CMB observations from the Atacama Cosmology Telescope, while we define background source galaxies for the lensing analysis with secure photometric redshift cuts in Year 3 data of the Subaru Hyper Suprime Cam survey. We detect the stacked lensing signal in the range of 0.1 < R [ h - 1 Mpc ] < 100 in each of three cluster redshift bins, 0.092 < z ≤ 0.445 , 0.445 < z ≤ 0.695 , and 0.695 < z ≤ 1.180 , with 32 galaxy clusters in each bin. The cumulative signal-to-noise ratios of the lensing signal are 14.6, 12.0, and 6.6, respectively. Using a halo-based forward model, we then constrain statistical relationships between the mass inferred from the SZ observation (i.e. SZ mass) and the total mass derived from our stacked lensing measurements. At the average SZ mass in the cluster sample ( 2.1 - 2.4 × 10 14 h - 1 M ⊙ ), our likelihood analysis shows that the average total mass differs from the SZ counterpart by a factor of 1.3 ± 0.2 , 1.6 ± 0.2 , and 1.6 ± 0.3 (68%) in the aforementioned redshift ranges, respectively. Our limits are consistent with previous lensing measurements, and we find that the cluster modeling choices can introduce a 1 σ -level difference in our parameter inferences.

79 ASTRONOMY AND ASTROPHYSICS↗
DOE OSTI2022

Efficient Clustering of Software Vulnerabilities using Self Organizing Map (SOM)

The common vulnerabilities and exposures (CVE) database was created with a mission to ``identify, define, and catalog publicly disclosed cybersecurity vulnerabilities''. This rich body of information can be used to enable rapid and efficient response to secure and defend cyber operations and protect critical cyber infrastructure. The main goal of this paper is to develop a visual analytics tool to enable deep analysis of CVEs using unsupervised clustering techniques. We enhance our analysis by first mapping CVEs to hierarchical-classes in Common Weakness Enumeration (CWE) using information in the National Vulnerability Database (NVD). Both the mapping and the numerical representation of CVEs are enabled by V2W-BERT, which uses natural language processing of the extensive information in NVD to generate a large tabular database of 137,226 CVE entries from 1999 to 2020, where each CVE is represented by a vector of 768 numerical features. The vectorized data is processed by Self-Organizing Maps (SOM), which is an unsupervised machine learning technique for dimensionality reduction, visual representation and clustering. Using a Torus map of 6417 units, we achieve ~10-fold data compression of ~140k CVEs using SOM. The trained map is further clustered using standard K-means clustering into 138 clusters of CVEs. We conducted a brief investigation of the rich mapping of CVEs to best-matching-units to K-means clusters, as well as CVEs to CWEs. For example, this novel mapping provided insight into the role of CWE-59 and CWE-264 in several CVEs that is otherwise hard to explore in the original data. We conclude that our this novel approach will not only enable deep analysis of the complex relationships between CVEs and CWEs, but also a mechanism to quickly respond to and design mitigation actions for rapidly evolving vulnerabilities that have not been mapped to existing CWEs.

Panchal, Khyati↗
DOE OSTI2023

Clustering High-dimensional Toxicogenomics Data with Rare Signals

Toxicogenomics studies the gene and protein activities to drug treatments or toxic exposures. As the drugs and genes are numerous, toxicogenomics data are naturally high dimensional, with dimension sizes up to millions. In addition, the distribution of toxicogenomics data is oftentimes skewed, and they contain rare but important signals representing a cell or organism’s response to toxicity. The combination of high dimension and extremely skewed distribution of toxicogenomics data makes clustering analysis extremely challenging.We present our study of clustering toxicogenomics data using classical approaches such as principal component analysis as well as deep learning approaches such as auto-encoders. Our experiments show that these approaches fail to preserve rare signals and produce high-quality clusters. We then explore augmenting matrix factorization with deep learning techniques such as attention mechanism to produce latent representations for clustering. Our technique is able to better preserve rare signals after dimensionality reduction than prior approaches. Furthermore, we combine our augmented matrix factorization with a mechanism similar to autoencoder to balance separable clusters and low regeneration errors. Our experiments demonstrate better clustering with our proposed approach.

Cong, Guojing↗
DOE OSTI2025

Investigation of the Cyanothece nitrogenase cluster in Synechocystis : a blueprint for engineering nitrogen-fixing photoautotrophs

ABSTRACT The nitrogenase gene cluster of unicellular diazotrophic cyanobacteria, such asCyanothece, is frequently selected by nature for nitrogen-fixing partnerships with eukaryotic phototrophs. The essential cluster components that confer an advantage in such partnerships remain underexplored. To use this cluster for the development of synthetic, phototrophic nitrogen-fixing systems, a thorough and systematic analysis of its constituent genes is necessary. An initial effort to assess the possibility of engineering this cluster into non-diazotrophic phototrophs led to the generation of aSynechocystis6803 strain with significant nitrogenase activity. In the current study, a refactoring approach was taken to determine the dispensability of the non-structural genes in the cluster and define a minimal gene set for constructing a functional nitrogenase for phototrophs. Using a bottom-up strategy, thenifgenes fromCyanothece51142 were re-organized to form new operons. The genes were then seamlessly removed to determine their essentiality in the nitrogen fixation process. We demonstrate that besides the structural genesnifHDK,nifBSUENPVZTXW, as well ashesAB, are important for optimal nitrogenase function in a phototroph. We also show that optimal expression of these genes is crucial for efficient nitrogenase activity. Our findings provide a solid foundation for generating synthetic systems that will facilitate solar-powered conversion of atmospheric nitrogen into nitrogen-rich compounds, a stride toward a greener world. IMPORTANCE Integrating nitrogen fixation genes into various photosynthetic organisms is an exciting strategy for converting atmospheric nitrogen into nitrogen-rich products in a green and energy-efficient way. In order to facilitate this process, it is essential that we understand the fundamentals of the functioning of a prokaryotic nitrogen-fixing machinery in a non-diazotrophic, photoautotrophic cell. This study examines a nitrogenase gene cluster that has been naturally selected on multiple occasions for a nitrogen-fixing partnership by eukaryotic photoautotrophs and provides a basic blueprint for designing a photosynthetic organism with nitrogen-fixing ability.

Microbiology↗
DOE OSTI2022

Profiling the BLAST bioinformatics application for load balancing on high-performance computing clusters

Abstract Background The Basic Local Alignment Search Tool (BLAST) is a suite of commonly used algorithms for identifying matches between biological sequences. The user supplies a database file and query file of sequences for BLAST to find identical sequences between the two. The typical millions of database and query sequences make BLAST computationally challenging but also well suited for parallelization on high-performance computing clusters. The efficacy of parallelization depends on the data partitioning, where the optimal data partitioning relies on an accurate performance model. In previous studies, a BLAST job was sped up by 27 times by partitioning the database and query among thousands of processor nodes. However, the optimality of the partitioning method was not studied. Unlike BLAST performance models proposed in the literature that usually have problem size and hardware configuration as the only variables, the execution time of a BLAST job is a function of database size, query size, and hardware capability. In this work, the nucleotide BLAST application BLASTN was profiled using three methods: shell-level profiling with the Unix “time” command, code-level profiling with the built-in “profiler” module, and system-level profiling with the Unix “gprof” program. The runtimes were measured for six node types, using six different database files and 15 query files, on a heterogeneous HPC cluster with 500+ nodes. The empirical measurement data were fitted with quadratic functions to develop performance models that were used to guide the data parallelization for BLASTN jobs. Results Profiling results showed that BLASTN contains more than 34,500 different functions, but a single function, RunMTBySplitDB, takes 99.12% of the total runtime. Among its 53 child functions, five core functions were identified to make up 92.12% of the overall BLASTN runtime. Based on the performance models, static load balancing algorithms can be applied to the BLASTN input data to minimize the runtime of the longest job on an HPC cluster. Four test cases being run on homogeneous and heterogeneous clusters were tested. Experiment results showed that the runtime can be reduced by 81% on a homogeneous cluster and by 20% on a heterogeneous cluster by re-distributing the workload. Discussion Optimal data partitioning can improve BLASTN’s overall runtime 5.4-fold in comparison with dividing the database and query into the same number of fragments. The proposed methodology can be used in the other applications in the BLAST+ suite or any other application as long as source code is available.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2020

Desulfatiglans anilini Initiates Degradation of Aniline With the Production of Phenylphosphoamidate and 4-Aminobenzoate as Intermediates Through Synthases and Carboxylases From Different Gene Clusters

The anaerobic degradation of aniline was studied in the sulfate-reducing bacterium Desulfatiglans anilini. Our aim was to identify the genes and their proteins that are required for the initial activation of aniline as well as to characterize intermediates of this reaction. Aniline-induced genes were revealed by comparison of the proteomes of D. anilini grown with different substrates (aniline, 4- aminobenzoate, phenol, and benzoate). Most genes encoding proteins that were highly abundant in aniline- or 4-aminobenzoate-grown D. anilini cells but not in phenol- or benzoate-grown cells were located in the putative gene clusters ani (aniline degradation), hcr (4-hydroxybenzoyl-CoA reductase) and phe (phenol degradation). Of these putative gene clusters, only the phe gene cluster has been studied previously. Based on the differential proteome analysis, four candidate genes coding for kinase subunits and carboxylase subunits were suspected to be responsible for the initial conversion of aniline to 4-aminobenzoate. These genes were cloned and overproduced in E. coli. The recombinant proteins were obtained in inclusion bodies but could be refolded successfully. Two subunits of phenylphosphoamidate synthase and two carboxylase subunits converted aniline to 4-aminobenzoate with phenylphosphoamidate as intermediate under consumption of ATP. Only when both carboxylase subunits, one from gene cluster ani and the other from gene cluster phe, were combined, phenylphosphoamidate was converted to 4-aminobenzoate in vitro, with Mn 2+ , K + , and FMN as co-factors. Thus, aniline is degraded by the anaerobic bacterium D. anilini only by recruiting genes for the enzymatic machinery from different gene clusters. We conclude, that D. anilini carboxylates aniline to 4-aminobenzoate via phenylphosphoamidate as an energy rich intermediate analogous to the degradation of phenol to 4-hydroxybenzoate via phenylphosphate.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2020

Comparative Genomic Analysis of Ochratoxin A Biosynthetic Cluster in Producing Fungi: New Evidence of a Cyclase Gene Involvement

The widespread use of Next-Generation Sequencing has opened a new era in the study of biological systems by significantly increasing the catalog of fungal genomes sequences and identifying gene clusters for known secondary metabolites as well as novel cryptic ones. However, most of these clusters still need to be examined in detail to completely understand the pathway steps and the regulation of the biosynthesis of metabolites. Genome sequencing approach led to the identification of the biosynthetic genes cluster of ochratoxin A (OTA) in a number of producing fungal species. Ochratoxin A is a potent pentaketide nephrotoxin produced by Aspergillus and Penicillium species and found as widely contaminant in food, beverages and feed. The increasing availability of several new genome sequences of OTA producer species in JGI Mycocosm and/or GenBank databanks led us to analyze and update the gene cluster structure in 19 Aspergillus and 2 Penicillium OTA producing species, resulting in a well conserved organization of OTA core genes among the species. Furthermore, our comparative genome analyses evidenced the presence of an additional gene, previously undescribed, located between the polyketide and non-ribosomal synthase genes in the cluster of all the species analyzed. The presence of a SnoaL cyclase domain in the sequence of this gene supports its putative role in the polyketide cyclization reaction during the initial steps of the OTA biosynthesis pathway. The phylogenetic analysis showed a clustering of OTA SnoaL domains in accordance with the phylogeny of OTA producing species at species and section levels. The characterization of this new OTA gene, its putative role and its expression evidence in three important representative producing species, are reported here for the first time.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2021

Photometric and Kinematic Study of the Open Clusters SAI 44 and SAI 45

We carry out a detailed photometric and kinematic study of the poorly studied sparse open clusters SAI 44 and SAI 45 using ground-based BVR {sub c} I {sub c} data supplemented by archival data from Gaia eDR3 and Pan-STARRS. The stellar memberships are determined using a statistical method based on Gaia eDR3 kinematic data, and we found 204 members in SAI 44 while only 74 members are identified in SAI 45. The average distances to SAI 44 and SAI 45 are calculated to be 3670 ± 184 and 1668 ± 47 pc. The logarithmic age of the clusters are determined to be 8.82 ± 0.10 and 9.07 ± 0.10 yr for SAI 44 and SAI 45, respectively. The color–magnitude diagram of SAI 45 hosts an extended main-sequence turnoff (eMSTO). The apparent age spread is found to be similar to the apparent age spread predicted on the basis of the age spread and cluster age relation predicted by rotation models. This indicates that eMSTO is a stellar evolution rather than star formation phenomenon in SAI 45. We conclude that eMSTO in SAI 45 is mainly caused by the different rotation rates of stars as the SYCLIST synthetic population with different rotation rates was able to reproduce the observed eMSTO, and stars in the red part of the eMSTO were preferentially concentrated in the inner region, which again hints at different rotations being the reason for the extension in the upper MS. This finding supports the theory attributing the origin of eMSTO to the different rotations of eMSTO stars. The mass function slopes are obtained as -2.24 ± 0.66 and -2.58 ± 3.20 in the mass rages 2.426–0.990 M{sub ⊙} and 2.167–1.202 M{sub ⊙} for SAI 44 and SAI 45, respectively. SAI 44 exhibits the signature of mass segregation while we found weak evidence of mass segregation in SAI 45 possibly due to tidal stripping. The dynamical relaxation times of these clusters indicate that both clusters are in a dynamically relaxed state. Using the AD-diagram method, the apex coordinates are found to be ([[Formula]], -[[Formula]]) for SAI 44 and (-[[Formula]], -[[Formula]]) for SAI 45. The average space velocity components of the clusters SAI 44 and SAI 45 are calculated in units of km s{sup -1} as (-15.14 ± 3.90, -19.43 ± 4.41, -20.85 ± 4.57) and (28.13 ± 5.30, -9.78 ± 3.13, -19.59 ± 4.43), respectively.

71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗
DOE OSTI2023

Variable Blue Straggler Stars in the Open Cluster NGC 6819 Observed in the Kepler “Superstamp” Field

Abstract NGC 6819 is an open cluster of age 2.4 Gyr that was in the NASA Kepler spacecraft’s field of view from 2009 to 2013. The central part of the cluster was observed in a 200 × 200 pixel “superstamp” during these four years in 30 minute cadence photometry, providing a unique, high-precision, long time-series data set. The cluster contains “blue straggler” stars, i.e., stars on the main sequence above the cluster turnoff that should have left the main sequence to become red giants. We present light curves and pulsation frequency analyses derived from custom photometric reductions for five confirmed cluster members—four blue stragglers and one star near the main-sequence turnoff. Two of these stars show a rich spectrum of δ Scuti pulsation modes, with 236 and 124 significant frequencies identified, respectively, while two stars show mainly low-frequency modes, characteristic of γ Doradus variable stars. The fifth star, a known active X-ray binary, shows only several harmonics of two main frequencies. For the two δ Scuti stars, we use a frequency separation–mean density relation to estimate their mean densities, and then use these values along with their effective temperature to derive their stellar masses and radii. For the two stars showing low frequencies, we searched for period-spacing sequences that may be representative of gravity-mode or Rossby-mode sequences, but found no clear sequences. The common age for the cluster members, considered along with the frequencies, will provide valuable constraints for asteroseismic analyses, and may shed light on the origin of the blue stragglers.

79 ASTRONOMY AND ASTROPHYSICS↗
DOE OSTI2023

SPT-CL J2215−3537: A Massive Starburst at the Center of the Most Distant Relaxed Galaxy Cluster

Abstract We present the discovery of the most distant, dynamically relaxed cool core cluster, SPT-CL J2215−3537 (SPT2215), and its central brightest cluster galaxy (BCG) at z = 1.16. Using new X-ray observations, we demonstrate that SPT2215 harbors a strong cool core with a central cooling time of 200 Myr (at 10 kpc) and a maximal intracluster medium cooling rate of 1900 ± 400 M ⊙ yr −1 . This prodigious cooling may be responsible for fueling the extended, star-forming filaments observed in Hubble Space Telescope imaging. Based on new spectrophotometric data, we detect bright [O ii ] emission in the BCG, implying an unobscured star formation rate (SFR) of 320 − 140 + 230 M ⊙ yr −1 . The detection of a weak radio source (2.0 ± 0.8 mJy at 0.8 GHz) suggests ongoing feedback from an active galactic nucleus (AGN), though the implied jet power is less than half the cooling luminosity of the hot gas, consistent with cooling overpowering heating. The extreme cooling and SFR of SPT2215 are rare among known cool core clusters, and it is even more remarkable that we observe these at such high redshift, when most clusters are still dynamically disturbed. The high mass of this cluster, coupled with the fact that it is dynamically relaxed with a highly isolated BCG, suggests that it is an exceptionally rare system that must have formed very rapidly in the early universe. Combined with the high SFR, SPT2215 may be a high- z analog of the Phoenix cluster, potentially providing insight into the limits of AGN feedback and star formation in the most massive galaxies.

79 ASTRONOMY AND ASTROPHYSICS↗
DOE OSTI2020

Evolution of a plant gene cluster in Solanaceae and emergence of metabolic diversity

Plants produce phylogenetically and spatially restricted, as well as structurally diverse specialized metabolites via multistep metabolic pathways. Hallmarks of specialized metabolic evolution include enzymatic promiscuity and recruitment of primary metabolic enzymes and examples of genomic clustering of pathway genes. Solanaceae glandular trichomes produce defensive acylsugars, with sidechains that vary in length across the family. We describe a tomato gene cluster on chromosome 7 involved in medium chain acylsugar accumulation due to trichome specific acyl-CoA synthetase and enoyl-CoA hydratase genes. This cluster co-localizes with a tomato steroidal alkaloid gene cluster and is syntenic to a chromosome 12 region containing another acylsugar pathway gene. We reconstructed the evolutionary events leading to this gene cluster and found that its phylogenetic distribution correlates with medium chain acylsugar accumulation across the Solanaceae. This work reveals insights into the dynamics behind gene cluster evolution and cell-type specific metabolite diversity.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2024

Cluster dynamics simulations of tritium and helium diffusion in lithium ceramics

Tritium (T) and He diffusion in LiAlO 2 and LiAl 5 O 8 phases influences the performance of tritium producing burnable absorber rods (TPBARs) by affecting the gas release, swelling and thermal conductivity of Li-bearing ceramic pellets. Frenkel pair defects and clusters created by irradiation can attract T and He interstitials and form clusters of the type He i x Li, He i x Al, He i x O, T i x Li, T i x Al, and T i x O, 1 ≤ x ≤ 4 in a Li, Al or O vacancy site (notation denotes x He or T atoms in a 1 Li, 1 Al or 1 O vacant site). The concentration and mobility of each of these clusters collectively contribute to the diffusion of the He and T gases in LiAlO 2 and LiAl 5 O 8 . Here, in this work, free energy cluster dynamics simulations implemented in the Centipede code, are used to obtain the concentration and diffusivities of these clusters which are then used to calculate the total diffusivity of T and He gases in LiAlO 2 and LiAl 5 O 8 . The results show that diffusivity of T is at least one order of magnitude higher in LiAlO 2 as compared to that in LiAl 5 O 8 whereas He diffusion is 2–13 orders of magnitude higher in LiAlO 2 as compared to that in LiAl 5 O 8 . There is a higher concentration of highly diffusive species (T interstitials and T i 03 Li for the case of tritium and He i 01 Li, He i 02 Li, and He i 03 Li for the case of He) in LiAlO 2 than in LiAl 5 O 8 which increase the total diffusion of T and He in LiAlO 2 .

36 MATERIALS SCIENCE↗
DOE OSTI2023

Tandem Mass-Selective Cryogenic Digital Ion Traps for Enhanced Cluster Formation

We present the implementation of tandem mass-selective cryogenic ion traps, designed to enhance the range of ion processing capabilities that can be performed prior to spectroscopic interrogation. We show that both the formation of ion clusters and mass filtering steps can be combined in a single cryogenic linear quadrupole ion trap driven by RF square waves. Mass filtering and mass isolation can be achieved by manipulation of the RF frequency and duty cycle. Very importantly, this scheme circumvents the need for high-amplitude RF voltages that can be incompatible with typical cryogenic ion processing conditions. In addition, proper adjustment of the stability boundaries during the clustering process allows for the preferential formation of a specific cluster size rather than a broad distribution of sizes. Lastly, we show that a specific cluster size can be formed, mass-selected, and then transferred to another ion trap for a second completely separate ion processing step. Furthermore, the instrumentation and modular design developed here expand the scope of ionic species and clusters that can be accessed by processing electrosprayed ions.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗