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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 127 records · Page 7
All sourcesNASA NTRSDOE OSTI
DOE OSTI2022

Hydration-driven stabilization and volume collapse of grain boundaries in Mg2SiO4 forsterite predicted by first-principles simulations

Grain boundaries in mantle minerals are of critical importance to geophysical and geochemical processes of the Earth’s interior. One of the fundamental issues is to understand how the water (H 2 O) component influences the properties of grain boundaries in silicate materials. Here, we report the results of the structure and stability of several tilt grain boundaries in Mg 2 SiO 4 forsterite over the pressure range 0 to 15 GPa using density functional theory-based first-principles simulations. Here, the results suggest greater energetic stability and hydration-driven volume collapse (negative excess volume) at zero pressure for the majority of hydrous grain boundaries relative to the anhydrous (dry) ones. All the hydrous grain boundaries become increasingly favorable at elevated pressures as the calculated hydration enthalpy systematically decreases with increasing pressure. The hydrous components at the interfacial regions are predominantly in the hydroxyl form and, to a lesser extent, in the molecular H 2 O form. Their calculated ratio ranges from 1.6 to 8.7 among the different grain boundary configurations. Our structural analysis also reveals that the hydroxyls are bound to either both Mg and Si or to Mg only. In comparison, the molecular species are bound only to Mg sites. Besides direct oxygen-hydrogen bonding, intermolecular hydrogen bonding becomes important with compression. On the basis of our results, we suggest that local atomic rearrangements caused by dissociative adsorption of water facilitate efficient compaction of the boundary interfaces, which, in turn, results in greater relative stability of hydrous grain boundaries. This means that water prefers to be incorporated within the grain boundaries over the bulk of silicate materials.

12 MANAGEMENT OF RADIOACTIVE AND NON-RADIOACTIVE W↗
DOE OSTI2021

FY2020 performance assessment annual review for the E-area low-level waste facility

The Savannah River Site (SRS) E-Area Low-Level Waste Facility (ELLWF) consists of six types of disposal units described in the Performance Assessment (PA) (WSRC, 2008): Low Activity Waste Vault (LAWV), Intermediate Level Vault (ILV), Trenches [Slit Trenches (STs), Engineered Trenches (ETs), and Component-in-Grout (CIG) Trenches], and Naval Reactor Component Disposal Areas (NRCDAs). The ELLWF is a part of the Solid Waste Management Facility (SWMF). SWMF is managed and operated by the SRS Management and Operations prime contractor, Savannah River Nuclear Solutions (SRNS). Within SRNS, the Solid Waste Management (SWM) organization is responsible for operating the SWMF, and the Savannah River National Laboratory (SRNL) is the technical agency responsible for preparing and maintaining the PA. SWMF operations have been performed at SRS since 1952. The mission of the SWMF is to provide storage, processing, disposal, and shipment of radioactive, hazardous, and mixed waste. The SWMF is committed to treat, store, and dispose of these waste products in a manner that protects the environment and the health and safety of the facility worker, the co-located worker, and the offsite general public. Wastes handled in the SWMF include low level waste, transuranic waste, hazardous waste, Toxic Substances Control Act waste, and mixed waste (containing both hazardous and radioactive constituents). The FY2020 PA Annual Review for the ELLWF affirms that the disposal facility continued to operate within the bounds of the current PA and Composite Analysis (CA) baseline and the subsequent SA’s and satisfied all the requirements, conditions, and limitations identified in the 2008 DAS (DOE 2008a), RWMB SRNL_STI-2020-00588 Revision 0 vi (McGill, 2020), and ELLWF Low-Level Waste Acceptance Criteria (SRS-1S, 2014). This annual review affirms that the supporting studies performed in FY2020 do not alter the conclusions of the ELLWF PA (WSRC, 2008) and that there is a reasonable expectation that the ELLWF will meet the performance objectives delineated in DOE Manual 435.1-1 (DOE 2011)

12 MANAGEMENT OF RADIOACTIVE AND NON-RADIOACTIVE W↗
DOE OSTI2021

Nuclear Physics Multimessenger Astrophysics Constraints on the Neutron Star Equation of State: Adding NICER’s PSR J0740+6620 Measurement

In the past few years, new observations of neutron stars (NSs) and NS mergers have provided a wealth of data that allow one to constrain the equation of state (EOS) of nuclear matter at densities above nuclear saturation density. However, most observations were based on NSs with masses of about 1.4 M ⊙ , probing densities up to ~three to four times the nuclear saturation density. Even higher densities are probed inside massive NSs such as PSR J0740+6620. Very recently, new radio observations provided an update to the mass estimate for PSR J0740+6620, and X-ray observations by the NICER and XMM telescopes constrained its radius. Based on these new measurements, we revisit our previous nuclear physics multimessenger astrophysics constraints and derive updated constraints on the EOS describing the NS interior. By combining astrophysical observations of two radio pulsars, two NICER measurements, the two gravitational-wave detections GW170817 and GW190425, detailed modeling of the kilonova AT 2017gfo, and the gamma-ray burst GRB 170817A, we are able to estimate the radius of a typical 1.4 M ⊙ NS to be ${11.94}_{-0.87}^{+0.76}\,\mathrm{km}$ at 90% confidence. Finally, our analysis allows us to revisit the upper bound on the maximum mass of NSs and disfavors the presence of a strong first-order phase transition from nuclear matter to exotic forms of matter, such as quark matter, inside NSs.

60 APPLIED LIFE SCIENCES↗
DOE OSTI2023

Towards resolving protein structures at the atomic scale using atom probe tomography

In the field of Structural Biology, Atom Probe Tomography (APT) is in the nascent stages of development wherein coarse-grained visuals of proteins have been captured. The characterization of organic samples or biomolecules through the technique is currently limited to the detection of a few dominant signatures. The problem of indecipherable characterization can inherently be traced back to multiple forms of technique-specific responses to organic samples and consequent triggers leading to organic-sample and sample-medium interactions. While it is possible for captured manifestations of protein reconstructions to seemingly appear intact from a basic visual purview, the parameter-protein associative responses throughout the structure as a direct consequence of the inherent workings of the technique (until harmonized with organic sample complexity and behavior) and field evaporation-based factors make non-aberrative atomic associations infeasible. The work focused on identifying and theorizing the (above stated and other) fundamental mechanisms that stronghold the study of intricate atomic to higher order associations in proteins through APT. Attempts at structure elucidation of the cryogenic sample under study, through indirect associations (and methods) based on other imaging techniques, further revealed the distinct and highly distortive nature at the atomic scale deterring structural tunability and thus characterization of APT based cryogenic samples under analysis. As a direct counter to the atomic scale characterization problem, by taking the experiment-specific uncertainties, and probable APT-centric organic sample-based variabilities into account, a basic result is extracted and presented. Through mass-spectrometric and computational analysis, specific individual amino acids (Sulfur-containing protein-bound amino acids) in proteins and aspects of protein structure (probable backbone fragments, partial sequence - partial backbone portions) have been identified and characterized. Under analysis considerations, a few of the simplest known and easily inferable segments that favor structural deteriorations in the reconstructions are stated. Additionally, to overcome technique-specific deterrents to the characterization of biomolecules in cryogenic sample medium, the development of a protein-labeling strategy tailored to APT is suggested.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2026

Interpretation of high-harmonic fast-wave propagation in the scrape-off layer of NSTX-U as a geometrically bounded-waveguide mode

This paper revisits the onset of high-harmonic fast-wave (HHFW) propagation in the scrape-off layer (SOL) plasma of the NSTX/NSTX-U spherical tokamak, motivated by past HHFW heating and current drive experiments and modelling. Previously, the fast-wave propagation in the SOL was correlated with the opening (suppression) of the fast-wave right-hand cutoff layer in front of the antenna. In this work, the SOL propagation is interpreted as a geometric waveguide mode guided by the SOL geometry, whose radial width can be comparable to the wave’s perpendicular wavelength in the HHFW regime. A two-dimensional circular model is first employed using full-wave solvers to characterise the poloidal eigenmode structures and to clarify their relationship to annulus resonance. By progressively adding a tokamak-like magnetic-field configuration, starting from a uniform axial field, the effects of magnetic-field gradients and pitch on the SOL waveguide mode are characterised. The poloidal mode numbers supported by the SOL plasma agree well with analytic estimates, indicating that an anisotropic plasma in a bounded geometry selectively supports and amplifies the resonant poloidal mode number. Additionally, two-dimensional axisymmetric NSTX-U simulations demonstrate that the SOL eigenmode features identified in the circular model persist in the experimentally relevant configurations. A control approach based on lengthening the wave perpendicular wavelength relative to the SOL width, including a higher magnetic (B)-field operation, is discussed. The analysis here shows the key role of a bounded geometry in interpreting HHFW eigenmode coupling and propagation in the NSTX-U SOL plasma.

plasma heating↗
DOE OSTI2024

Robustness and Eventual Slow Decay of Bound States of Interacting Microwave Photons in the Google Quantum AI Experiment

Integrable models are characterized by the existence of stable excitations that can propagate indefinitely without decaying. This includes multimagnon bound states in the celebrated 𝑋⁢𝑋⁢𝑍 spin-chain model and its integrable Floquet counterpart. A recent Google Quantum AI experiment [A. Morvan et al., Nature 612, 240 (2022)] realizing the Floquet model has demonstrated the persistence of such collective excitations even when the integrability is broken: this observation is at odds with the expectation of ergodic dynamics in generic nonintegrable systems. Here, we study the spectrum of the model realized in the experiment using exact diagonalization and physical arguments. We find that isolated bands corresponding to the descendants of the exact bound states of the integrable model are clearly observable in the spectrum for a large range of system sizes. However, our numerical analysis of the localization properties of the eigenstates suggests that the bound states become unstable in the thermodynamic limit. A perturbative estimate of the decay rate agrees with the prediction of an eventual instability for large system sizes.

Exact diagonalization↗
DOE OSTI2025

Sharp detection of low-dimensional structure in probability measures via dimensional logarithmic Sobolev inequalities

Identifying low-dimensional structure in high-dimensional probability measures is an essential pre-processing step for efficient sampling. To identify this structure, we approximate the target measure as a perturbation of an arbitrary reference measure along a few directions in $\mathbb{R}^{d}$. These directions are determined by minimizing an upper bound on the Kullback–Leibler (KL) divergence between the target and its approximation. Our contribution improves upon previous works by leveraging dimensional logarithmic Sobolev inequalities to refine the bound on the KL divergence. These inequalities lead to a uniformly tighter bound on the KL divergence, thereby enhancing the identification of the most significant perturbation directions. In particular, when the target and reference are both Gaussian, minimizing the resulting bound is equivalent to minimizing the KL divergence. We further demonstrate the applicability of this analysis to the squared Hellinger distance, where analogous reasoning shows that the dimensional Poincaré inequality offers improved bounds.

Bayesian inference↗
DOE OSTI2024

On the measurement of shape: With applications to lunar regolith

With the renewed commitment from NASA and other commercial entities for a presence on the Moon, the importance of understanding the characteristics of lunar regolith and how to utilize it have become the target of increasing scrutiny. Much of what is known about lunar regolith was collected during and immediately after the Apollo program, however, analytical techniques and instrumentation have advanced in leaps and bounds in the subsequent decades. Specifically, dynamic image analysis systems have advanced to the point that millions of particles can have morphological characteristics automatically determined in relatively short time frames. Particle morphological data was collected on several lunar samples and a pair of widely used regolith simulants to ascertain the accuracy of these simulants and to explore statistical analysis methods of these large datasets. It is found that these morphology datasets can vary widely depending on the particle size of the particles, and simple averaging of the data skews the results heavily towards the numerically abundant size ranges, the fines. Different reporting methods are suggested to ameliorate these problems. When applied to the lunar regolith, the particles are noted to be less morphologically complex than initially suspected. Compared to the lunar material, the simulants are found to contain some more morphological variability and angular grains. Such difference is likely due to the wildly different comminution processes that these different powder systems are subjected to.

2D shape↗
DOE OSTI2022

A catalytic dyad modulates conformational change in the CO 2 -fixing flavoenzyme 2-ketopropyl coenzyme M oxidoreductase/carboxylase

2-Ketopropyl-coenzyme M oxidoreductase/carboxylase (2-KPCC) is a member of the flavin and cysteine disulfide containing oxidoreductase family (DSOR) that catalyzes the unique reaction between atmospheric CO 2 and a ketone/enolate nucleophile to generate acetoacetate. However, the mechanism of this reaction is not well understood. Here, we present evidence that 2-KPCC, in contrast to the well-characterized DSOR enzyme glutathione reductase, undergoes conformational changes during catalysis. Using a suite of biophysical techniques including limited proteolysis, differential scanning fluorimetry, and native mass spectrometry in the presence of substrates and inhibitors, we observed conformational differences between different ligand-bound 2-KPCC species within the catalytic cycle. Analysis of site-specific amino acid variants indicated that 2-KPCC-defining residues, Phe501-His506, within the active site are important for transducing these ligand induced conformational changes. We propose that these conformational changes promote substrate discrimination between H + and CO 2 to favor the metabolically preferred carboxylation product, acetoacetate.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2022

Fuzzy dark matter and the Dark Energy Survey Year 1 data

ABSTRACT Gravitational weak lensing by dark matter haloes leads to a measurable imprint in the shear correlation function of galaxies. Fuzzy dark matter (FDM), composed of ultralight axion-like particles of mass m ∼ 10−22 eV, suppresses the matter power spectrum and shear correlation with respect to standard cold dark matter. We model the effect of FDM on cosmic shear using the optimized halo model HMCode, accounting for additional suppression of the mass function and halo concentration in FDM as observed in N-body simulations. We combine Dark Energy Survey Year 1 (DES-Y1) data with the Planck cosmic microwave background anisotropies to search for shear correlation suppression caused by FDM. We find no evidence of suppression compared to the preferred cold dark matter model, and thus set a new lower limit to the FDM particle mass. Using a log-flat prior and marginalizing over uncertainties related to the non-linear model of FDM, we find a new, independent 95 per cent C.L. lower limit log10m > −23 combining Planck and DES-Y1 shear, an improvement of almost two orders of magnitude on the mass bound relative to CMB-only constraints. Our analysis is largely independent of baryonic modelling, and of previous limits to FDM covering this mass range. Our analysis highlights the most important aspects of the FDM non-linear model for future investigation. The limit to FDM from weak lensing could be improved by up to three orders of magnitude with $\mathcal {O}(0.1)$ arcmin cosmic shear angular resolution, if FDM and baryonic feedback can be simultaneously modelled to high precision in the halo model.

79 ASTRONOMY AND ASTROPHYSICS↗
DOE OSTI2024

DOE Final Report on Virginia Tech’s contribution to “Tokamak Disruption Simulation”

This work was performed by Virginia Tech in collaboration with multiple institutions led by Los Alamos National Laboratory as a part of the Tokamak Disruption Simulation SciDAC (Scientific Discovery through Advanced Computing) project supported jointly by the Department of Energy Office of Science and Ad- vanced Scientific Computing Research. This report summarizes Virginia Tech’s contributions to the Sci- DAC project. Virginia Tech researchers (presently University of Washington researchers) focused on the fundamental role of plasma-material interaction on transport, which could then have macroscopic effects on simulations of tokamak disruptions. The plasma sheath, which regulates plasma particle and energy fluxes to the wall, is an essential component in the study of plasma-material interaction (PMI). Understanding sheath theory by accounting for finite sheath thickness and transport in the vicinity of the sheath entrance can sig- nificantly modify typical assumptions that are made in the Bohm speed analysis, where the Bohm speed provides the lower bound of the plasma exit flow speed. Our work provides a modified Bohm speed formu- lation that accounts for the critical role of transport and for applications that are away from the asymptotic limits that are typically assumed.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗
DOE OSTI2025

Near-Efficient and Non-Asymptotic Multiway Inference

We establish non-asymptotic efficiency guarantees for tensor decomposition–based inference in count data models. Under a Poisson framework, we consider two related goals: (i) parametric inference , the estimation of the full distributional parameter tensor, and (ii) multiway analysis , the recovery of its canonical polyadic (CP) decomposition factors. Our main result shows that in the rank-one setting, a rank-constrained maximum-likelihood estimator achieves multiway analysis with variance matching the Cramér–Rao Lower Bound (CRLB) up to absolute constants and logarithmic factors. This provides a general framework for studying “near-efficient” multiway estimators in finite-sample settings. For higher ranks, we illustrate that our multiway estimator may not attain the CRLB; nevertheless, CP-based parametric inference remains nearly minimax optimal, with error bounds that improve on prior work by offering more favorable dependence on the CP rank. Numerical experiments corroborate near-efficiency in the rank-one case and highlight the efficiency gap in higher-rank scenarios.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2020

Summary of Expedited Results from Samples Supporting Tank Closure Cesium Removal (TCCR) Batch 3

Savannah River Remediation (SRR) is currently operating the Tank Closure Cesium Removal (TCCR) process to remove 137 Cs from tank waste supernate using an ion exchange process. As part of that process, Savannah River National Laboratory (SRNL) receives and analyzes samples in support of the qualification of each batch to be processed. SRNL recently received supernate samples retrieved from Tank 10H as well as in-tank batch contact samples for characterization in support of qualifying Batch 3 for processing through the TCCR unit. SRNL received and characterized a set of dip samples collected from Tank 10H (one surface and one variable depth sample). No solids were observed in either sample and therefore the samples were combined, and a suite of analyses were performed on the composite sample. The density of the combined sample was 1.174 g/mL (0.18 %RSD), which was consistent with the measured sodium concentration of 3.54 M (0.08 %RSD). The 137Cs activity in the sample was 4.75E+07 dpm/mL (4.28 %RSD) and the total Cs concentration was calculated to be 1.54 mg/L (1.16E-05 M). The in-tank batch contact samples consist of 0.1 g of crystalline silicotitanate (CST) contained within a teabag device. Duplicate samples were submerged in Tank 10H supernate for a period of about 13 days, after which time they were retrieved and transferred to SRNL for analysis. At SRNL the CST was rinsed to remove excess salt solution and the CST was then air dried before being digested for analysis. Results of the analysis indicated a 137 Cs loading of 3.66E+10 ± 1.40E+09 dpm/g or 16.5 ± 0.63 Ci/kg CST . This value represents a bounding upper limit as it includes the addition of two sigma uncertainty from replicate analysis of the individual teabag samples as well as the addition of the small amount of 137 Cs activity measured in the rinse solutions. The above values are based on the air-dried mass of CST. Correcting to the true dry mass using a F-factor of 0.8191 results in a maximum loading of 20.2 ± 0.77 Ci/kg CST .

12 MANAGEMENT OF RADIOACTIVE AND NON-RADIOACTIVE W↗
DOE OSTI2022

Region-adaptive, Error-controlled Scientific Data Compression using Multilevel Decomposition

The increase of computer processing speed is significantly outpacing improvements in network and storage bandwidth, leading to the big data challenge in modern science, where scientific applications can quickly generate much more data than that can be transferred and stored. As a result, big scientific data must be reduced by a few orders of magnitude while the accuracy of the reduced data needs to be guaranteed for further scientific explorations. Moreover, scientists are often interested in some specific spatial/temporal regions in their data, where higher accuracy is required. The locations of the regions requiring high accuracy can sometimes be prescribed based on application knowledge, while other times they must be estimated based on general spatial/temporal variation. In this paper, we develop a novel multilevel approach which allows users to impose region-wise compression error bounds. Our method utilizes the byproduct of a multilevel compressor to detect regions where details are rich and we provide the theoretical underpinning for region-wise error control. With spatially varying precision preservation, our approach can achieve significantly higher compression ratios than single-error bounded compression approaches and control errors in the regions of interest.We conduct the evaluations on two climate use cases – one targeting small-scale, node features and the other focusing on long, areal features. For both use cases, the locations of the features were unknown ahead of the compression. By selecting approximately 16% of the data based on multi-scale spatial variations and compressing those regions with smaller error tolerances than the rest, our approach improves the accuracy of post-analysis by approximately 2 × compared to single-error-bounded compression at the same compression ratio. Using the same error bound for the region of interest, our approach can achieve an increase of more than 50% in overall compression ratio.

Gong, Qian↗
DOE OSTI2023

Unusual modifications of protein biomarkers expressed by plasmid, prophage, and bacterial host of pathogenic Escherichia coli identified using top‐down proteomic analysis

Rationale Pathogenic bacteria often carry prophage (bacterial viruses) and plasmids (small circular pieces of DNA) that may harbor toxin, antibacterial, and antibiotic resistance genes. Proteomic characterization of pathogenic bacteria should include the identification of host proteins and proteins produced by prophage and plasmid genomes. Methods Protein biomarkers of two strains of Shiga toxin–producingEscherichia coli(STEC) were identified using antibiotic induction, matrix‐assisted laser desorption/ionization tandem time‐of‐flight (MALDI‐TOF‐TOF) tandem mass spectrometry (MS/MS) with post‐source decay (PSD), top‐down proteomic (TDP) analysis, and plasmid sequencing. Alphafold2 was also used to compare predicted in silico structures of the identified proteins to prominent fragment ions generated using MS/MS‐PSD. Strain samples were also analyzed with and without chemical reduction treatment to detect the attachment of pendant groups bound by thioester or disulfide bonds. Results Shiga toxin was detected and/or identified in both STEC strains. For the first time, we also identified the osmotically inducible protein (OsmY) whose sequence unexpectedly had two forms: a full and a truncated sequence. The truncated OsmY terminates in the middle of an α‐helix as determined by Alphafold2. A plasmid‐encoded colicin immunity protein was also identified with and without attachment of an unidentified cysteine‐bound pendant group (~307 Da). Plasmid sequencing confirmed top‐down analysis and the identification of a promoter upstream of the immunity gene that is activated by antibiotic induction, that is, SOS box. Conclusions TDP analysis, coupled with other techniques (e.g., antibiotic induction, chemical reduction, plasmid sequencing, and in silico protein modeling), is a powerful tool to identify proteins (and their modifications), including prophage‐ and plasmid‐encoded proteins, produced by pathogenic microorganisms.

Biochemistry & Molecular Biology↗
DOE OSTI2021

Three-dimensional atomic scale characterization of {11$\overline{2}$2} twin boundaries in titanium

The {11$\overline{2}$2}<11$\overline{23}$> compression twin can accommodate a considerable amount of strain under c-axis compression in Ti. However, unlike the tensile twin, the structure of the {10$\overline{1}$2}$\langle$$\overline{1}$011$\rangle$ compressive twins has not been completely characterized. In this study, we apply a combined technique of HR-TEM characterization, topological analysis, and atomistic simulations to explore the facets that bound the {11$\overline{2}$2}<11$\overline{23}$> twin in Ti. In addition to the currently known facets (CTB and B-Py), six new facets are observed and categorized for the first time from atomic-scale TEM observations along five crystallographic directions. The six new facets are (11$\overline{2}$0)//(11$\overline{2}$6), PrPr1, PyPy1, (2$\overline{11}$1)//($\overline{1}$2$\overline{1}$2), (1$\overline{1}$04)//(01$\overline{11}$), and (01$\overline{1}$0)//(2$\overline{11}$4). Results from the topological and computational analysis are in reasonable agreement with and support the HRTEM observations. Specifically, (1) the observed facets align with low-index interfaces in both twin and matrix domains, (2) the facets with lower surface energies are found to form extended interfaces, and (3) high-surface-energy facets are found at the twin tip region and explained by the fact that the energy of the combined facet and facet junction configuration is energetically preferred in the twin tip region. These results not only provide a comprehensive understanding of the 3D structure of the {11$\overline{2}$2}<11$\overline{23}$> compressive twins in Ti, but also validate the MD procedure and the Ti interatomic potential employed. This is extremely important for future study of the {11$\overline{2}$2} twin mobility and interactions with other defects, both features that remain extremely challenging to capture in experiments.

36 MATERIALS SCIENCE↗
DOE OSTI2021

Bounding uncertainty in functional data: A case study

Functional data are fast becoming a preeminent source of information across a wide range of industries. A particularly challenging aspect of functional data is bounding uncertainty. In this unique case study, we present our attempts at creating bounding functions for selected applications at Sandia National Laboratories (SNL). The first attempt involved a simple extension of functional principal component analysis (fPCA) to incorporate covariates. Though this method was straightforward, the extension was plagued by poor coverage accuracy for the bounding curve. This led to a second attempt utilizing elastic methodology which yielded more accurate coverage at the cost of more complexity.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2023

Enantioselective catalysts based on metal-organic framework-supported nucleotides

Adenosine triphosphate (ATP) and other nucleotides can be irreversibly bound to the metal-organic framework (MOF) MIL-101(Cr). Analysis of X-ray diffraction data suggests that the location of the adsorbed ATP molecule is in proximity of the Cr 3 clusters. Solid-state NMR and DFT calculations indicate that ATP is bound to MIL-101(Cr) through linkages of the terminal phosphate group with Cr(III) of the framework. In the presence of Cu(II) ions, the MOF-supported nucleotides can function as stable and reusable enantioselective heterogeneous catalysts for reactions like Diels-Alder and Michael addition. In conclusion, compared to the corresponding homogeneous nucleotide-based artificial metalloenzymes (ArMs), the MOF-supported nucleotide-based ArMs exhibit significantly enhanced activity and selectivity in certain cases, demonstrating their potential as a new class of enantioselective heterogeneous catalysts.

36 MATERIALS SCIENCE↗