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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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At least 379 records · Page 21
All sourcesNASA NTRSDOE OSTI
DOE OSTI2023

Redshift Evolution of the Feedback–Cooling Equilibrium in the Core of 48 SPT Galaxy Clusters: A Joint Chandra–SPT–ATCA Analysis

We analyze the cooling and feedback properties of 48 galaxy clusters at redshifts 0.4 < z < 1.3 selected from the South Pole Telescope (SPT) catalogs to evolve like the progenitors of massive and well-studied systems at z ~ 0. We estimate the radio power at the brightest cluster galaxy (BCG) location of each cluster from an analysis of Australia Telescope Compact Array data. Assuming that the scaling relation between the radio power and active galactic nucleus (AGN) cavity power P cav observed at low redshift does not evolve with redshift, we use these measurements in order to estimate the expected AGN cavity power in the core of each system. We estimate the X-ray luminosity within the cooling radius L cool of each cluster from a joint analysis of the available Chandra X-ray and SPT Sunyaev–Zel'dovich (SZ) data. This allows us to characterize the redshift evolution of the P cav /L cool ratio. When combined with low-redshift results, these constraints enable investigations of the properties of the feedback–cooling cycle across 9 Gyr of cluster growth. We model the redshift evolution of this ratio measured for cool-core clusters by a log-normal distribution Log-N (α + βz, σ 2 ) and constrain the slope of the mean evolution to β = -0.05 ± 0.47. This analysis improves the constraints on the slope of this relation by a factor of two. We find no evidence of redshift evolution of the feedback–cooling equilibrium in these clusters, which suggests that the onset of radio-mode feedback took place at an early stage of cluster formation. High values of P cav /L cool are found at the BCG location of noncool-core clusters, which might suggest that the timescales of the AGN feedback cycle and the cool core–noncool core transition are different. This work demonstrates that the joint analysis of radio, SZ, and X-ray data solidifies the investigation of AGN feedback at high redshifts.

79 ASTRONOMY AND ASTROPHYSICS↗
DOE OSTI2022

Preparation and Characterization of Model Homotopic Catalysts: Rh Adatoms, Nanoparticles, and Mixed Oxide Surfaces on Fe 3 O 4 (001)

The atomic-level characterization of active sites is essential to understanding the mechanisms behind catalytic reactions. In this study, using scanning tunneling microscopy (STM) and X-ray photoelectron spectroscopy (XPS), we follow the morphological changes of a model Rh catalysts supported on Fe 3 O 4 (001) as a function of temperature and Rh coverage. Here, we identify the preparation conditions leading to model catalysts containing homotopic or nearly homotopic Rh species bound as adatoms, small clusters, substitutional within the Fe 3 O 4 (001), and nanoparticles. Adsorbates such as CO and CO 2 are further subsequently used to characterize the properties of different Rh sites. Using temperature programmed desorption (TPD), we demonstrate that adatoms, clusters, and nanoparticles exhibit high-temperature CO desorption (250-600 K). Strong binding on such sites further allows for CO oxidation to CO 2 via the Mars-van-Krevelen mechanism. In contrast, CO 2 was found to interact weakly with all Rh sites. Differences in desorption temperature enable the use of CO and CO 2 as titration methods for nanoparticles and Fe 3 O 4 (001), respectively. A small quantity of CO 2 was found to be reduced to CO on Rh adatoms and clusters.

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

Structural basis for catalysis by human lipoyl synthase

Abstract Lipoic acid is an essential cofactor in five mitochondrial multiprotein complexes. In each complex, it is tethered in an amide linkage to the side chain of a conserved lysyl residue on a lipoyl carrier protein or lipoyl domain to afford the lipoyl cofactor. Lipoyl synthase catalyzes the last step in the biosynthesis of the lipoyl cofactor, the addition of two sulfur atoms to carbons 6 and 8 of an octanoyllysyl residue of the H protein, the lipoyl carrier protein of the glycine cleavage system. Lipoyl synthase, a member of the radical S-adenosylmethionine superfamily, contains two [Fe 4 S 4 ] clusters, one of which is sacrificed during catalysis to supply the appended sulfur atoms. Herein, we use X-ray crystallography to characterize several stages in lipoyl synthase catalysis and present a structure of an intermediate wherein the enzyme is cross-linked to the H protein substrate through a 6-mercaptooctanoyl ligand to a [Fe 3 S 4 ] cluster.

Science & Technology - Other Topics↗
DOE OSTI2022

Solute segregation and precipitation across damage rates in dual-ion–irradiated T91 steel

We report that dual-ion irradiations using 5.0 MeV defocused Fe 2+ ions and co-injected energy degraded 2.00 to 2.85 MeV He 2+ ions were conducted on a Fe9CrMo ferritic-martensitic steel T91 to 17 dpa at a damage rate range of 5 × 10 -5 dpa/s to 3 × 10 -3 dpa/s at 445°C, followed by characterization of the microstructure using conventional and scanning transmission electron microscopy. Radiation induced Ni/Si clusters and radiation induced segregation were quantified using energy dispersive X-ray spectroscopy at each condition and were compared with the same material irradiated in the BOR-60 reactor and in the as-received condition. No significant Cr segregation was found at lath boundaries after dual-ion irradiation, while Ni and Si enrichments both decreased with increasing damage rate leading to a sharp decrease in the density of Ni/Si clusters with damage rate. Increased point defect recombination at higher ion damage rates likely reduced the Ni/Si cluster density compared with BOR-60. Although the overall vacancy concentration and diffusion are enhanced by the irradiation damage rate, the lack of time for thermal diffusion and ballistic displacements of solutes are significant limiting factors for Ni/Si cluster formation. This work demonstrates the effect of irradiation damage rate on elemental segregation and clustering when using ion irradiation to simulate reactor irradiation.

36 MATERIALS SCIENCE↗
DOE OSTI2026

Additively manufactured refractory high-entropy alloys with superior radiation resistance

Refractory high-entropy alloys (RHEAs) are promising candidates for next-generation nuclear and high-temperature applications. Among many approaches to manufacture RHEAs, additive manufacturing (AM) represents the most recent and advanced metal manufacturing method which allows near-net-shape manufacturing to reduce material waste and post-processing time. However, performance of AM RHEAs under complex irradiation conditions remains largely unexplored. Here, in this study, we demonstrate for the first time the response of directed energy deposition (DED) AM quaternary RHEAs (HfTaVW, CrTaVW) subjected to sequential dual-beam ion irradiation, consisting of helium pre-implantation followed by high-dose heavy ion bombardment. Compositions of DED AM RHEAs were selected using Monte Carlo (MC) simulations based on a cluster expansion (CE) Hamiltonian parameterized by density functional theory (DFT). Post-irradiation microstructural characterization revealed that the AM RHEA maintained remarkable stability, with suppressed helium bubble growth and reduced defect accumulation compared to conventional alloys. Even at high doses (∼100 dpa), the alloy exhibited no void swelling, a low density of dislocation loops, and no evidence of severe degradation. These results highlight the intrinsic ability of AM-derived microstructures and multicomponent chemistry to synergistically mitigate irradiation effects. Our findings establish AM RHEAs as a class of materials with superior resistance to radiation damage under conditions relevant to advanced fusion and fission environments and demonstrate the importance of sequential ion beam studies in evaluating their long-term performance.

36 MATERIALS SCIENCE↗
DOE OSTI2021

Spin Reorientation in Antiferromagnetic Layered FePt 5 P

FePt 5 P, a substitutional variant of the anti-CeCoIn 5 structure type in the space group P4/mmm, was synthesized by a high-temperature solid-state method and structurally characterized by X-ray diffraction. FePt 5 P contains layers of FePt 12 clusters formed by magnetically active Fe and heavy Pt with strong spin-orbit coupling (SOC); the layers are separated by P atoms. The various Fe–Pt distances in FePt 12 clusters generate complex magnetic orders in FePt 5 P. According to temperature-dependent magnetic and specific heat measurements, FePt 5 P shows a stripe-type antiferromagnetic order at T N ≈ 90 K, which is also confirmed by resistivity measurements. Furthermore, a spin reorientation occurs at ~74 and ~68 K in and out of the ab plane based on the specific heat measurements. The temperature-dependent neutron powder diffraction patterns demonstrate the antiferromagnetic order in FePt 5 P, and the spins orientate up to 58.4° with respect to the c axis at 10 K. First-principles calculations of FePt 5 P show the band splitting at the Fermi level by strong SOC and the s–d hybridization between P and Fe/Pt electrons enhances the structural stability and affects the magnetic ordering.

36 MATERIALS SCIENCE↗
DOE OSTI2025

Controlling N speciation in solution synthesis of N-doped carbon materials

Carbon-based materials, such as graphite and its functionalized/doped derivatives, are promising lightweight layered materials for hydrogen activation and storage. Their propensity to control the thermodynamics of hydrogen binding and the kinetics of hydrogen mobility strongly depends on the speciation and the arrangement of dopants. In this study, we demonstrate precise control over dopant speciation and clustering in nitrogen-containing layered carbon materials during hydrothermal synthesis. Through extensive spectroscopic characterization and first principles simulations, we demonstrate that the formation of N-motifs can be controlled by the choice of precursor and synthesis temperature. The distinct three-dimensional architecture and porosity in graphene oxide and carbon nitride-derived materials furnish a synthetic pathway for precise control over the local and global structure of nitrogen-doped carbon materials and their activity toward the activation of molecular hydrogen.

Byun, Mi Yeon [Pacific Northwest National Laborato↗
DOE OSTI2021

Detection of significant antiviral drug effects on COVID-19 with reasonable sample sizes in randomized controlled trials: A modeling study

Development of an effective antiviral drug for Coronavirus Disease 2019 (COVID-19) is a global health priority. Although several candidate drugs have been identified through in vitro and in vivo models, consistent and compelling evidence from clinical studies is limited. The lack of evidence from clinical trials may stem in part from the imperfect design of the trials. We investigated how clinical trials for antivirals need to be designed, especially focusing on the sample size in randomized controlled trials. A modeling study was conducted to help understand the reasons behind inconsistent clinical trial findings and to design better clinical trials. We first analyzed longitudinal viral load data for Severe Acute Respiratory Syndrome Coronavirus 2 (SARS-CoV-2) without antiviral treatment by use of a within-host virus dynamics model. The fitted viral load was categorized into 3 different groups by a clustering approach. Comparison of the estimated parameters showed that the 3 distinct groups were characterized by different virus decay rates (p-value < 0.001). The mean decay rates were 1.17 d -1 (95% CI: 1.06 to 1.27 d -1 ), 0.777 d -1 (0.716 to 0.838 d -1 ), and 0.450 d -1 (0.378 to 0.522 d -1 ) for the 3 groups, respectively. Such heterogeneity in virus dynamics could be a confounding variable if it is associated with treatment allocation in compassionate use programs (i.e., observational studies). Subsequently, we mimicked randomized controlled trials of antivirals by simulation. An antiviral effect causing a 95% to 99% reduction in viral replication was added to the model. To be realistic, we assumed that randomization and treatment are initiated with some time lag after symptom onset. Using the duration of virus shedding as an outcome, the sample size to detect a statistically significant mean difference between the treatment and placebo groups (1:1 allocation) was 13,603 and 11,670 (when the antiviral effect was 95% and 99%, respectively) per group if all patients are enrolled regardless of timing of randomization. The sample size was reduced to 584 and 458 (when the antiviral effect was 95% and 99%, respectively) if only patients who are treated within 1 day of symptom onset are enrolled. We confirmed the sample size was similarly reduced when using cumulative viral load in log scale as an outcome. We used a conventional virus dynamics model, which may not fully reflect the detailed mechanisms of viral dynamics of SARS-CoV-2. The model needs to be calibrated in terms of both parameter settings and model structure, which would yield more reliable sample size calculation. In this study, we found that estimated association in observational studies can be biased due to large heterogeneity in viral dynamics among infected individuals, and statistically significant effect in randomized controlled trials may be difficult to be detected due to small sample size. The sample size can be dramatically reduced by recruiting patients immediately after developing symptoms. We believe this is the first study investigated the study design of clinical trials for antiviral treatment using the viral dynamics model.

60 APPLIED LIFE SCIENCES↗
DOE OSTI2020

Biological Electron Transfer and Catalysis EFRC

The focus of the Biological Electron Transfer and Catalysis (BETCy) EFRC research is elucidating mechanisms of conversion of electrochemical potential into chemical bond energy and is organized into two integrated Thrusts: Electron Bifurcation Catalysis and Electron Transfer Kinetics. We are developing a collective knowledge of metalloenzymes as models for redox reactions by applying physical science and computational tools to characterize biochemical reactions catalyzed by multi- subunit enzymes harboring arrays of iron-sulfur clusters and flavin cofactors. Understanding these mechanisms is central to overcoming the thermodynamic barriers that currently limit production of reduced products and fuels. Biological systems have elegant strategies for converting electrochemical potential energy into chemical bond energy (e.g., C-H, H-H, and N-H) stored in reduced compounds that can serve as advanced biofuels. One significant limitation for the production of highly reduced compounds is that their production in natural and industrial processes relies on low oxidation-reduction potential chemicals as feedstocks.

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

Nearby stellar substructures in the Galactic halo from DESI Milky Way Survey Year 1 Data Release

We report five nearby ($d_{\mathrm{helio}} < 5$ kpc) stellar substructures in the Galactic halo from a subset of 138 661 stars in the Dark Energy Spectroscopic Instrument (DESI) Milky Way Survey Year 1 Data Release. With an unsupervised clustering algorithm, HDBSCAN*, these substructures are independently identified in Integrals of Motion ($E_{\rm tot}$, $L_{\rm z}$, $\log {J_r}$, $\log {J_z}$) space and Galactocentric cylindrical velocity space ($V_{R}$, $V_{\phi }$, $V_{z}$). We associate all identified clusters with known nearby substructures (Helmi streams, M18-Cand10/MMH-1, Sequoia, Antaeus, and ED-2) previously reported in various studies. With metallicities precisely measured by DESI, we confirm that the Helmi streams, M18-Cand10, and ED-2 are chemically distinct from local halo stars. We have characterized the chemodynamic properties of each dynamic group, including their metallicity dispersions, to associate them with their progenitor types (globular cluster or dwarf galaxy). Our approach for searching substructures with HDBSCAN* reliably detects real substructures in the Galactic halo, suggesting that applying the same method can lead to the discovery of new substructures in future DESI data. With more stars from future DESI data releases and improved astrometry from the upcoming Gaia Data Release 4, we will have a more detailed blueprint of the Galactic halo, offering a significant improvement in our understanding of the formation and evolutionary history of the Milky Way Galaxy.

dynamics↗
DOE OSTI2020

A Clustering-based biased Monte Carlo Approach to Protein Titration Curve Prediction

We develop and implement a novel approach to computing the ensemble averages in systems characterized by pair-wise interactions between the entities. Methods involving full enumeration of the configuration space result in exponential complexity. Sampling methods such as Markov Chain Monte Carlo (MCMC) algorithms have been proposed to tackle the exponential complexity of these problems. In certain scenarios where significant energetic coupling exists between the entities, the accuracy of the such algorithms can be diminished. We propose a strategy to improve the accuracy of the MCMC runs by taking advantage of the cluster structure in the interaction energy matrix. We propose two different schemes for performing the biased MCMC runs on the partitioned systems and show that they are valid MCMC schemes. We then apply these algorithms to the problem of computing the protonation fractions and hence the titration curves of titratable protein residues that constitute a given protein. We leverage both synthesized and real-world systems and show the improved performance of our biased MCMC methods when compared to the regular MCMC method.

Visweswara Sathanur, Arun↗
DOE OSTI2020

Enzalutamide response in a panel of prostate cancer cell lines reveals a role for glucocorticoid receptor in enzalutamide resistant disease

Representative in vitro model systems that accurately model response to therapy and allow the identification of new targets are important for improving our treatment of prostate cancer. Here we describe molecular characterization and drug testing in a panel of 20 prostate cancer cell lines. The cell lines cluster into distinct subsets based on RNA expression, which is largely driven by functional Androgen Receptor (AR) expression. KLK3 , the AR-responsive gene that encodes prostate specific antigen, shows the greatest variability in expression across the cell line panel. Other common prostate cancer associated genes such as TMPRSS2 and ERG show similar expression patterns. Copy number analysis demonstrates that many of the most commonly gained (including regions containing TERC and MYC ) and lost regions (including regions containing TP53 and PTEN) that were identified in patient samples by the TCGA are mirrored in the prostate cancer cell lines. Assessment of response to the anti-androgen enzalutamide shows a distinct separation of responders and non-responders, predominantly related to status of wild-type AR. Surprisingly, several AR-null lines responded to enzalutamide. These AR-null, enzalutamide-responsive cells were characterized by high levels of expression of glucocorticoid receptor (GR) encoded by NR3C1 . Treatment of these cells with the anti-GR agent mifepristone showed that they were more sensitive to this drug than enzalutamide, as were several of the enzalutamide non-responsive lines. This is consistent with several recent reports that suggest that GR expression is an alternative signaling mechanism that can bypass AR blockade. This study reinforces the utility of large cell line panels for the study of cancer and identifies several cell lines that represent ideal models to study AR-null cells that have upregulated GR to sustain growth.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2023

Bottom-up evolution of perovskite clusters into high-activity rhodium nanoparticles toward alkaline hydrogen evolution

Self-reconstruction has been considered an efficient means to prepare efficient electrocatalysts in various energy transformation process for bond activation and breaking. However, developing nano-sized electrocatalysts through complete in-situ reconstruction with improved activity remains challenging. Herein, we report a bottom-up evolution route of electrochemically reducing Cs 3 Rh 2 I 9 halide-perovskite clusters on N-doped carbon to prepare ultrafine Rh nanoparticles (~2.2 nm) with large lattice spacings and grain boundaries. Various in-situ and ex-situ characterizations including electrochemical quartz crystal microbalance experiments elucidate the Cs and I extraction and Rh reduction during the electrochemical reduction. These Rh nanoparticles from Cs 3 Rh 2 I 9 clusters show significantly enhanced mass and area activity toward hydrogen evolution reaction in both alkaline and chlor-alkali electrolyte, superior to liquid-reduced Rh nanoparticles as well as bulk Cs 3 Rh 2 I 9 -derived Rh via top-down electro-reduction transformation. Theoretical calculations demonstrate water activation could be boosted on Cs 3 Rh 2 I 9 clusters-derived Rh nanoparticles enriched with multiply sites, thus smoothing alkaline hydrogen evolution.

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

A minimal SufB 2 C 2 complex functions as a [4Fe-4S] cluster scaffold in methanogenic archaea

Iron-sulfur clusters are essential cofactors in all domains of life, yet their biogenesis in obligately anaerobic archaea remains poorly understood. Here, we characterized the minimal two-protein SUF system in methanogenic archaea, composed solely of SufB and SufC. Using Methanococcus maripaludis as a model, we demonstrate that the SUF proteins from its native host form a stable SufB 2 C 2 heterotetramer that binds a [4Fe-4S] cluster via three conserved cysteines in SufC. Mutations of conserved cysteine and histidine residues of SufB do not impair cluster binding. The complex interacts with the SAM-containing methanogenesis marker protein 10 (MmpX), suggesting direct Fe-S cluster transfer from SufB 2 C 2 to target proteins. Mutational analysis of Methanothermococcus thermolithotrophicus proteins confirmed that SufC is the primary cluster-binding component, while SufB enhances ATPase and cluster transfer activities. Evolutionary comparisons suggest that this two-protein SUF system represents an ancestral form of Fe-S cluster biogenesis.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2025

Statistical relationships across epigenomes using large-scale hierarchical clustering

Recent advances in genomics and sequencing platforms have revolutionized our ability to create immense data sets, particularly for studying epigenetic regulation of gene expression. However, the avalanche of epigenomic data is difficult to parse for biological interpretation given nonlinear complex patterns and relationships. This attractive challenge in epigenomic data lends itself to machine learning for discerning infectivity and susceptibility. In this study, we explore over 3000 epigenomes of uninfected individuals and provide a framework to characterize the relationships among epigenetic modifiers, their modifiers, genetic loci, and specific immune cell types across all chromosomes using hierarchical clustering. Hierarchical clustering of epigenomic data revealed consistent epigenetic patterns across chromosomes, demonstrating that variation due to epigenetic modifiers is greater than variation between cell types. Gene Ontology and KEGG pathway analyses indicated significant enrichment of genes involved in chromatin remodeling, mRNA splicing, immune responses, and the regulation of microRNAs and snoRNAs. Epigenetic modifiers frequently formed biologically relevant clusters, including the cohesin complex, RNA Polymerase II transcription factors, and PRC2 complex members. These clustering behaviors remained consistent across all chromosomes, supported by entropy analysis and high Adjusted Rand Index scores, indicating robust cross-chromosomal similarity. Co-occurrence analysis further revealed specific sets of modifiers that consistently appeared together within clusters, reflecting shared biological functions and interactions. Validation using another dataset confirmed the reproducibility of these clustering patterns and modifier co-occurrence relationships, underscoring the reliability and generalizability of the methodology.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2020

Cluster Difference Imaging Photometric Survey. II. TOI 837: A Young Validated Planet in IC 2602

We report the discovery of TOI 837b and its validation as a transiting planet. We characterize the system using data from the NASA Transiting Exoplanet Survey Satellite mission, the ESA Gaia mission, ground-based photometry from El Sauce and ASTEP400, and spectroscopy from CHIRON, FEROS, and Veloce. We find that TOI 837 is a T = 9.9 mag G0/F9 dwarf in the southern open cluster IC 2602. The star and planet are therefore 35$_{-5}^{+11}$ million years old. Combining the transit photometry with a prior on the stellar parameters derived from the cluster color–magnitude diagram, we find that the planet has an orbital period of 8.3 days and is slightly smaller than Jupiter (R p =0.77$_{-0.07}^{+0.09}$ R Jup ). From radial velocity monitoring, we limit M p sin i to less than 1.20 M Jup (3σ). The transits either graze or nearly graze the stellar limb. Grazing transits are a cause for concern, as they are often indicative of astrophysical false-positive scenarios. Our follow-up data show that such scenarios are unlikely. Our combined multicolor photometry, high-resolution imaging, and radial velocities rule out hierarchical eclipsing binary scenarios. Background eclipsing binary scenarios, though limited by speckle imaging, remain a 0.2% possibility. TOI 837b is therefore a validated adolescent exoplanet. The planetary nature of the system can be confirmed or refuted through observations of the stellar obliquity and the planetary mass. Such observations may also improve our understanding of how the physical and orbital properties of exoplanets change in time.

79 ASTRONOMY AND ASTROPHYSICS↗
DOE OSTI2023

Limits of Detection for EXAFS Characterization of Heterogeneous Single-Atom Catalysts

Single-atom catalysts (SACs), consisting of individual metal atoms dispersed on a support, attract attention due to their unique reactivity, efficient use of precious metals, and precise chemical tunability. Characterization of the metal species is crucial to substantiate structure–function relationships. Authors often use—and referees often require—X-ray absorption spectroscopy (XAS) data to prove the absence of clustered metal (or metal oxide) structures after pre-treatment and under in situ or operando conditions. However, there has been no critical assessment of the limitations of XAS in substantiating such conclusive statements, which is particularly important given the potential outsized influence of minority catalyst structures in dictating catalytic activity. Here, in this article, we quantitatively assess the detection limits of XAS to identify metal (or metal oxide) clusters in samples containing predominantly single atoms by modeling the extended X-ray absorption fine structure (EXAFS) of mixtures of structures. We identified that a significant fraction of clusters can coexist with SAC active sites (e.g., ~10% metallic Pt or ~40% oxidized Pt clusters in Pt/CeO 2 SACs), while eluding detection via EXAFS with any statistical significance. To generalize these conclusions, a descriptor-based screening of bulk metal oxides using a continuous Cauchy wavelet transform was proposed that suggests certain materials for which differentiating atomically dispersed metal species and metal oxide clusters would be infeasible by EXAFS (e.g., ReO x ). Based on this analysis, we suggest best practices for the study of SACs using EXAFS and provide recommendations to ensure that conclusions do not outpace the evidence used to support them. In this rapidly expanding research area, rigorous characterization will lead to greater understanding of the behavior of SACs and ultimately improved catalytic materials.

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

Tuning Metal–Organic Framework (MOF) Topology by Regulating Ligand and Secondary Building Unit (SBU) Geometry: Structures Built on 8-Connected M 6 (M = Zr, Y) Clusters and a Flexible Tetracarboxylate for Propane-Selective Propane/Propylene Separation

Topology evolution originating from variations of linker and SBU (Secondary Building Unit) geometries could largely enrich the chemistry of metal–organic frameworks (MOFs). Here we report the synthesis and characterization of three MOF structures built on the same organic linker, N,N,N',N'-Tetrakis(4-carboxyphenyl)-1,4-phenylenediamine (tcppda) and similar 8-connected M 6 (M = Zr or Y) clusters. The three compounds, HIAM-402, HIAM-403, and HIAM-311, feature 4,8-connected sqc, scu, and flu topology, respectively. Detailed structural analysis revealed that different geometries of the inorganic M 6 SBUs as well as the organic linker have led to the formation of distinct MOF nets. In particular, HIAM-402 features exceptional framework stability and high porosity and acts as a propane-selective adsorbent for the discrimination of propane and propylene. Its balanced adsorption selectivity (S propane/propylene = 1.43) and capacity (Q propane = 133.3 cm 3 /g, 298 K and 1 bar) endow it with the capability of separating propane and propylene mixtures and one-step production of highly pure propylene (purity >99.9%), as validated by column breakthrough measurements, with the presence of moisture or propyne. As a result, ab initio calculations further confirm that the propane-selective behavior of HIAM-402 is a result of its higher binding energy toward propane compared to that of propylene.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗