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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 631 records · Page 35
All sourcesNASA NTRSDOE OSTI
DOE OSTI2020

An Exceptionally Stable Metal–Organic Framework Constructed from Chelate-Based Metal–Organic Polyhedra

In this paper, we report the rational design and synthesis of a new, water-stable metal-organic framework (MOF), Fe-HAF-1, constructed from supramolecular, Fe3+-hydroxamate-based polyhedra with mononuclear metal nodes. Owing to its chelate-based con-struction, Fe-HAF-1 displays exceptional chemical stability in organic and aqueous solvents over a wide pH range (pH 1-14), including in the presence of 5 M NaOH. Despite the charge-neutrality of the Fe 3+ -tris(hydroxamate) centers, Fe-HAF-1 crystals are negatively charged above pH 4. This unex-pected property is attributed to the formation of defects during crystallization that results in uncoordinated hydroxamate ligands or hydroxide-coordinated Fe centers. The anionic na-ture of Fe-HAF-1 crystals enables selective adsorption of pos-itively charged ions in aqueous solution, resulting in efficient separation of organic dyes and other charged species in a size-selective fashion. Fe-HAF-1 presents a new addition to a small group of chelate-based MOFs and provides a rare framework whose 3D connectivity is exclusively formed by metal-hydroxamate coordination.

36 MATERIALS SCIENCE↗
DOE OSTI2021

Redox-Responsive, Reconfigurable All-Liquid Constructs

Using host-guest chemistries in a biphasic system, a novel supramolecular nanoparticle surfactant (s-NPS) with redox-responsiveness is presented to structure liquids. Additionally, the in situ assembly/jamming and disassembly/unjamming of s-NPSs at the oil-water interface are reversibly controlled by a switchable redox process, imparting a nanoscale redox-responsiveness, affecting the assemblies on all length scales. "Smart" all-liquid constructs including structured emulsions and programmable liquid devices are easily prepared, showing promising applications in responsive delivery, release, and reaction systems.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2020

A new method to construct a horizontal resolution-dependent wind speed adjustment factor for tropical cyclones in global climate model simulations

A new method to construct a horizontal resolution-dependent wind speed adjustment factor for evaluating tropical cyclones (TCs) in global climate models (GCMs) is presented here. In contrast to the previous studies that used idealized axisymmetric wind fields, this study analyzes 48 hours of 10-second surface wind fields from 1-km TC simulations. The adjustment factor is derived from filtering the simulated TC wind fields onto various horizontal grid spacings typical of those used in GCMs. The new adjustment factor leads to TCs with greater intensity than the existing adjustment factors for horizontal grid spacings smaller than 30 km. This difference is attributed to more realistic wind fields in the TC simulations that contain highly asymmetric, localized patches of higher wind speeds instead of axisymmetric wind fields. Applying the new adjustment factor to select GCM simulations suggests the common interpretation of low-intensity bias in GCM-simulated TCs might be slightly exaggerated.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2021

Tuning of lattice oxygen reactivity and scaling relation to construct better oxygen evolution electrocatalyst

Developing efficient and low-cost electrocatalysts for oxygen evolution reaction is crucial in realizing practical energy systems for sustainable fuel production and energy storage from renewable energy sources. However, the inherent linear scaling relation for most catalytic materials imposes a theoretical overpotential ceiling, limiting the development of efficient electrocatalysts. Herein, using modeled Na x Mn 3 O 7 materials, we report an effective strategy to construct better oxygen evolution electrocatalyst through tuning both lattice oxygen reactivity and scaling relation via alkali metal ion mediation. Specifically, the number of Na + is linked with lattice oxygen reactivity, which is determined by the number of oxygen hole in oxygen lone-pair states formed by native Mn vacancies, governing the barrier symmetry between O–H bond cleavage and O–O bond formation. On the other hand, the presence of Na + could have specific noncovalent interaction with pendant oxygen in *OOH to overcome the limitation from linear scaling relation, reducing the overpotential ceiling. Combining in situ spectroscopy-based characterization with first-principles calculations, we demonstrate that an intermediate level of Na + mediation (NaMn 3 O 7 ) exhibits the optimum oxygen evolution activity. This work provides a new rational recipe to develop highly efficient catalyst towards water oxidation or other oxidative reactions through tuning lattice oxygen reactivity and scaling relation.

36 MATERIALS SCIENCE↗
DOE OSTI2023

Guided construction of single cell reference for human and mouse lung

Accurate cell type identification is a key and rate-limiting step in single-cell data analysis. Single-cell references with comprehensive cell types, reproducible and functionally validated cell identities, and common nomenclatures are much needed by the research community for automated cell type annotation, data integration, and data sharing. Here, we develop a computational pipeline utilizing the LungMAP CellCards as a dictionary to consolidate single-cell transcriptomic datasets of 104 human lungs and 17 mouse lung samples to construct LungMAP single-cell reference (CellRef) for both normal human and mouse lungs. CellRefs define 48 human and 40 mouse lung cell types catalogued from diverse anatomic locations and developmental time points. We demonstrate the accuracy and stability of LungMAP CellRefs and their utility for automated cell type annotation of both normal and diseased lungs using multiple independent methods and testing data. We develop user-friendly web interfaces for easy access and maximal utilization of the LungMAP CellRefs.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2023

Discovery and construction of surface kagome electronic states induced by p-d electronic hybridization in Co3Sn2S2

Abstract Kagome-lattice materials possess attractive properties for quantum computing applications, but their synthesis remains challenging. Herein, based on the compelling identification of the two cleavable surfaces of Co 3 Sn 2 S 2 , we show surface kagome electronic states (SKESs) on a Sn-terminated triangular Co 3 Sn 2 S 2 surface. Such SKESs are imprinted by vertical p-d electronic hybridization between the surface Sn (subsurface S) atoms and the buried Co kagome-lattice network in the Co 3 Sn layer under the surface. Owing to the subsequent lateral hybridization of the Sn and S atoms in a corner-sharing manner, the kagome symmetry and topological electronic properties of the Co 3 Sn layer is proximate to the Sn surface. The SKESs and both hybridizations were verified via qPlus non-contact atomic force microscopy (nc-AFM) and density functional theory calculations. The construction of SKESs with tunable properties can be achieved by the atomic substitution of surface Sn (subsurface S) with other group III-V elements (Se or Te), which was demonstrated theoretically. This work exhibits the powerful capacity of nc-AFM in characterizing localized topological states and reveals the strategy for synthesis of large-area transition-metal-based kagome-lattice materials using conventional surface deposition techniques.

75 CONDENSED MATTER PHYSICS, SUPERCONDUCTIVITY AND↗
DOE OSTI2020

Constructing protein polyhedra via orthogonal chemical interactions

Many proteins exist naturally as symmetrical homooligomers or homopolymers. The emergent structural and functional properties of such protein assemblies have inspired extensive efforts in biomolecular design2–5. As synthesized by ribosomes, proteins are inherently asymmetric. Therefore, they must acquire multiple surface patches that selectively associate to generate the different symmetry elements needed to form higher-order architectures—a daunting task for protein design. Here we address this problem using an inorganic chemical approach, whereby multiple modes of protein–protein interactions and symmetry are simultaneously achieved by selective, ‘one-pot’ coordination of soft and hard metal ions. We show that a monomeric protein (protomer) appropriately modified with biologically inspired hydroxamate groups and zinc-binding motifs assembles through concurrent Fe 3+ and Zn 2+ coordination into discrete dodecameric and hexameric cages. Our cages closely resemble natural polyhedral protein architectures and are, to our knowledge, unique among designed systems in that they possess tightly packed shells devoid of large apertures. At the same time, they can assemble and disassemble in response to diverse stimuli, owing to their heterobimetallic construction on minimal interprotein-bonding footprints. With stoichiometries ranging from [2 Fe:9 Zn:6 protomers] to [8 Fe:21 Zn:12 protomers], these protein cages represent some of the compositionally most complex protein assemblies—or inorganic coordination complexes—obtained by design.

36 MATERIALS SCIENCE↗
DOE OSTI2022

Optical recognition of constructs using hyperspectral imaging and detection (ORCHID)

Abstract Challenges to deep sample imaging have necessitated the development of special techniques such as spatially offset optical spectroscopy to collect signals that have travelled through several layers of tissue. However, these techniques provide only spectral information in one dimension (i.e., depth). Here, we describe a general and practical method, referred to as Optical Recognition of Constructs Using Hyperspectral Imaging and Detection (ORCHID). The sensing strategy integrates (1) the spatial offset detection concept by computationally binning 2D optical data associated with digital offsets based on selected radial pixel distances from the excitation source; (2) hyperspectral imaging using tunable filter; and (3) digital image binding and collation. ORCHID is a versatile modality that is designed to collect optical signals deep inside samples across three spatial (X, Y, Z) as well as spectral dimensions. The ORCHID method is applicable to various optical techniques that exhibit narrow-band structures, from Raman scattering to quantum dot luminescence. Samples containing surface-enhanced Raman scattering (SERS)-active gold nanostar probes and quantum dots embedded in gel were used to show a proof of principle for the ORCHID concept. The resulting hyperspectral data cube is shown to spatially locate target emitting nanoparticle volumes and provide spectral information for in-depth 3D imaging.

47 OTHER INSTRUMENTATION↗
DOE OSTI2020

Two-in-one: construction of hydroxyl and imidazolium-bifunctionalized ionic networks in one-pot toward synergistic catalytic CO 2 fixation

Here, a succinct strategy was demonstrated for constructing a hydroxyl group and imidazolium-bifunctionalized ionic network via a onepot quaternization. Key to success lies in the rational design of multi-imidazole precursor and hydroxyl-containing counterpart. Unique properties of the resultant ionic network render its high catalytic efficiency toward CO 2 fixation under ambient conditions.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2021

Alkaline salt-promoted construction of hydrophilic and nitrogen deficient graphitic carbon nitride with highly improved photocatalytic efficiency

Graphitic carbon nitride (g-C 3 N 4 ) possesses fascinating merits, but its practical applications are limited by the inferior properties of limited visible-light sorption, rapid recombination of photo-excited charge carriers and low electrical conductivity. Introduction of N-defects is an efficient approach to tune its optical properties, but strategies capable of creating abundant vacancies and simultaneously maintaining the highly crystalline architecture are still limited and highly desired. In this work, a facile construction methodology was demonstrated to afford g-C 3 N 4 with abundant N vacancies, high crystallinity, a hydrophilic surface structure, a small particle size, and an increased surface area under neat and mild conditions. Furthermore, the essence of our approach lies in the treatment of the bulk g-C 3 N 4 precursor with an alkaline salt (LiN(SiMe 3 ) 2 ) with a low melting point, moderate nucleophilicity, and easy removal procedures. The unique structural properties of the afforded ND-g-C 3 N 4 allow for a significantly redshifted absorption edge and enhanced charge carrier separation, leading to superior photocatalytic hydrogen evolution performance three times that obtained by pristine g-C 3 N 4 . The modification strategy developed herein sheds light on the fabrication of g-C 3 N 4 -based materials with improved photocatalytic efficiency via efficient introduction of N defects, variation of the surface structure, and retention of the high crystallinity.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2023

Constructing “Li-rich Ni-rich” oxide cathodes for high-energy-density Li-ion batteries

The current exploration of high-energy-density cathode materials for Li-ion batteries is mainly concentrated on either so-called “Li-rich” or “Ni-rich” oxides. However, both are suffering from formidable practical challenges. Here, we combine these two concepts to obtain “Li-rich Ni-rich” oxides in pursuit of more practical high-energy-density cathodes. As a proof of concept, we synthesized an array of Li 1+y Ni( 3-5y)/3 Mo 2y/3 O 2 oxides, whose structures were identified to be the coexistence of LiNiO 2 -rich and Li 4 MoO 5 -rich domains with the aid of XRD, TEM, and NMR techniques. Such an intergrowth structure of 5–20 nm size enables excellent mechanical and structural reversibility for the layered rock-salt LiNiO 2 -rich domain upon cycling thanks to the robust cubic rock-salt Li 4 MoO 5 -rich domain enabling an “epitaxial stabilization” effect. As a result, we achieved high capacities (>220 mA h g -1 ) with Ni contents as low as 80%; the Li 1.09 Ni 0.85 Mo 0.06 O 2 member (y = 0.09) shows much improved cycling performances (91% capacity retention for 100 cycles at C/10) compared with pure LiNiO 2 . Further, this work validates the feasibility of constructing Li-rich Ni-rich compounds in the form of intergrowing domains and hence unlocks vast possibilities for future cathode design.

25 ENERGY STORAGE↗
DOE OSTI2026

Construction of generalized quasilinear diffusion coefficient using neural networks with physical restrictions

The quasilinear diffusion coefficient (D QL ) derived from our machine learning framework shows comparable trends with the ground truth D QL obtained from GENRAY-CQL3D simulations. Additionally, for the strong absorption cases, the radial current drive profiles generated using the D QL from our model exhibit consistent behavior with those obtained from the original simulation. These findings indicate the potential of our surrogate modeling approach with physical restrictions to replicate key wave–plasma interaction characteristics while reducing computational costs. Traditionally, calculating D QL for wave–particle interactions relies on computationally intensive wave simulations coupled with Fokker–Planck solvers. To address this challenge, we developed a machine learning-based surrogate model with physical restrictions derived from cold plasma theory and bounce-averaged damping effects. First, we establish the propagation domain of Lower Hybrid Waves in the (N∥, ρ) space by identifying the accessibility limit and determining the upper and lower bounds of N∥ using the Potential Power Deposition (PPD) method. Subsequently, leveraging a database constructed using Latin hypercube sampling alongside the underlying physical restrictions (e.g. PPD), machine learning methods including U-Net and Recurrent Neural Networks are employed to design a physics-restricted machine learning framework capable of reconstructing D QL .

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗
DOE OSTI2020

Constructing auxiliary dynamics for nonequilibrium stationary states by variance minimization

We present a strategy to construct guiding distribution functions (GDFs) based on variance minimization. Auxiliary dynamics via GDFs mitigates the exponential growth of variance as a function of bias in Monte Carlo estimators of large deviation functions. The variance minimization technique exploits the exact properties of eigenstates of the tilted operator that defines the biased dynamics in the nonequilibrium system. We demonstrate our techniques in two classes of problems. In the continuum, we show that GDFs can be optimized to study the interacting driven diffusive systems where the efficiency is systematically improved by incorporating higher correlations into the GDF. On the lattice, we use a correlator product state ansatz to study the 1D weakly asymmetric simple exclusion process. We show that with modest resources, we can capture the features of the susceptibility in large systems that mark the phase transition from uniform transport to a traveling wave state. Our work extends the repertoire of tools available to study nonequilibrium properties in realistic systems.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2021

Construction of linearly independent non-orthogonal AGP states

We show how to construct a linearly independent set of antisymmetrized geminal power (AGP) states, which allows us to rewrite our recently introduced geminal replacement models as linear combinations of non-orthogonal AGPs. Furthermore, this greatly simplifies the evaluation of matrix elements and permits us to introduce an AGP-based selective configuration interaction method, which can reach arbitrary excitation levels relative to a reference AGP, balancing accuracy and cost as we see fit.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2021

Constructing tensor network influence functionals for general quantum dynamics

Here, we describe an iterative formalism to compute influence functionals that describe the general quantum dynamics of a subsystem beyond the assumption of linear coupling to a quadratic bath. We use a space-time tensor network representation of the influence functional and investigate its approximability in terms of its bond dimension and time-like entanglement in the tensor network description. We study two numerical models, the spin-boson model and a model of interacting hard-core bosons in a 1D harmonic trap. We find that the influence functional and the intermediates involved in its construction can be efficiently approximated by low bond dimension tensor networks in certain dynamical regimes, which allows the quantum dynamics to be accurately computed for longer times than with direct time evolution methods. However, as one iteratively integrates out the bath, the correlations in the influence functional can first increase before decreasing, indicating that the final compressibility of the influence functional is achieved via non-trivial cancellation.

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

Construction of meta-GGA functionals through restoration of exact constraint adherence to regularized SCAN functionals

The strongly constrained and appropriately normed (SCAN) meta-GGA exchange–correlation functional is constructed as a chemical environment-determined interpolation between two separate energy densities: one describes single-orbital electron densities accurately and another describes slowly varying densities accurately. To conserve constraints known for the exact exchange–correlation functional, the derivatives of this interpolation vanish in the slowly varying limit. While theoretically convenient, this choice introduces numerical challenges that degrade the functional’s efficiency. We have recently reported a modification to the SCAN meta-GGA, termed restored-regularized-SCAN (r 2 SCAN) , that introduces two regularizations into SCAN, which improve its numerical performance at the expense of not recovering the fourth order term of the slowly varying density gradient expansion for exchange. Here, we show the derivation of a progression of density functional approximations [regularized SCAN (rSCAN), r++SCAN, r 2 SCAN, and r 4 SCAN] with increasing adherence to exact conditions while maintaining a smooth interpolation. The greater smoothness of r 2 SCAN seems to lead to better general accuracy than the additional exact constraint of SCAN or r 4 SCAN does.

, correlation energy↗