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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 OSTI2020

Rational Construction of Porous Metal–Organic Frameworks for Uranium(VI) Extraction: The Strong Periodic Tendency with a Metal Node

Although metal-organic frameworks (MOFs) have been reported as important porous materials for the potential utility in metal ion separation, coordinating the functionality, structure, and component of MOFs remains a great challenge. Herein, a series of anionic rare earth MOFs (RE-MOFs) were synthesized via a solvothermal template reaction and for the first time explored for uranium(VI) capture from an acidic medium. The unusually high extraction capacity of UO2 2 + (e.g., 538 mg U per g of Y-MOF) was achieved through ion-exchange with the concomitant release of Me 2 NH 2 + , during which the uranium(VI) extraction in the series of isostructural RE-MOFs was found to be highly sensitive to the ionic radii of the metal nodes. That is, the uranium(VI) adsorption capacities continuously increased as the ionic radii decreased. Finally, in-depth mechanism insight was obtained from molecular dynamics simulations, suggesting that both the accessible pore volume of the MOFs and hydrogen-bonding interactions contribute to the strong periodic tendency of uranium(VI) extraction.

36 MATERIALS SCIENCE↗
DOE OSTI2026

Nanocluster Rearrangement Forms a Family of Ordered Cerium–Titanium Bimetallic Metal–Organic Frameworks with Three Different Nodes, Nanocavities, and Thermal Stabilities

Metal–organic frameworks (MOFs) provide a versatile platform for incorporating multiple metal ions within a single crystalline framework, yet achieving spatial and stoichiometric order in heterometallic nodes remains a synthetic challenge. Building on our previously reported, highly thermally stable Ce/Ti bimetallic MOF NU-3000, we identified and isolated two additional crystalline phases, NU-2998 and NU-2999, that arise from the same Ce/Ti nanocluster precursor under modified solvothermal conditions. Systematic variation of reaction temperature, time, solvent ratio, and modulator concentration directs the assembly of these distinct frameworks. Structural analysis and comprehensive characterization studies reveal that these MOFs each feature an unreported nodal geometry with nanocavities of different sizes. NU-2998 even adopts an unreported topology, denoted nui , that features an elongated pore spanning 4 nm. Together, these findings establish a synthesis route that starts with a nanocluster and ends with a set of bimetallic MOFs, offering a glimpse into the pathway-dependent assembly of multimetallic porous materials. Finally, we evaluated the thermal stability of each additional analogue and compared them to NU-3000, providing further insight into material stability. NU-3000 maintained the highest thermal stability and was evaluated as a catalyst for CO oxidation at elevated temperatures.

bimetallic MOFs↗
DOE OSTI2025

..delta..-Learning of High-Fidelity Electronic Structure Using Graph Neural Networks with Modified Node-Level Features

In this work, we present a ..delta..-learning approach for predicting the eigenvalues calculated with the hybrid functional HSE06 (..epsilon..nkHSE) for a set of metal and nitrogen doped graphene catalysts (MNCs) from Perdew-Burke-Ernzerhof (PBE) inputs. The model presented here incorporates electronic scalar features along with structural information in a graph neural network (GNN). In particular, the PBE eigenvalues for different bands and k-points and orbital-resolved projectors are combined with the applied potential as node-level features along with structural information within the Atomistic Line Graph Neural Network (ALIGNN) architecture. These features enable flexibility for systems with electrified interfaces, such as in electrocatalysts and achieves mean absolute error (MAE) of less than 0.1 eV. The machine learning model reported here achieves a strong generalization to left-out adsorbates (MAE = 0.074 eV) and leave-one-chemical-space-out (MAE = 0.08 eV) and completely left-out metals (MAE = 0.072 eV), confirming the robustness of the machine learning (ML) model in predicting ..epsilon..nkHSE.

36 MATERIALS SCIENCE↗
DOE OSTI2025

Facile Generation of Active Sites in Nodes of Ni-MFU-4l Metal–Organic Framework for Hydrogenation Reaction

Metal–organic frameworks (MOFs) represent a well-defined class of materials capable of incorporating catalytically active sites for gas-phase catalysis. However, the reducing conditions of hydrogenation catalysis can lead to nanoparticle formation in MOFs, which can significantly diminish the catalytic activity of single-site metals and reduce the longevity of MOF-based hydrogen solutions. In this work, we present a straightforward approach to accessing catalytically active single metal sites in a robust Ni-MFU-4l MOF for gas-phase hydrogenation without the formation of Ni nanoparticles. By carefully tuning the local node chemistry through postsynthetic exchange of the terminal ligand coordinated to the Ni(II) centers in the MOF, from −Cl to −OH or −HCOO, we can readily generate Ni–H active species. We further demonstrate, using in situ pair-distribution function analysis, that these Ni–H sites are the sole catalytically active sites in the terminal ligand-exchanged counterparts, whereas nanoparticles readily form in the parent Ni-MFU-4l-Cl under otherwise identical catalytic conditions.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2024

Chemical Bonding and the Role of Node-Induced Electron Confinement

The chemical bond is the cornerstone of chemistry, providing a conceptual framework to understand and predict the behavior of molecules in complex systems. However, the fundamental origin of chemical bonding remains controversial and has been responsible for fierce debate over the past century. Here, in this study, we present a unified theory of bonding, using a separation of electron delocalization effects from orbital relaxation to identify three mechanisms [node-induced confinement (typically associated with Pauli repulsion, though more general), orbital contraction, and polarization] that each modulate kinetic energy during bond formation. Through analysis of a series of archetypal bonds, we show that an exquisite balance of energy-lowering delocalizing and localizing effects are dictated simply by atomic electron configurations, nodal structure, and electronegativities. The utility of this unified bonding theory is demonstrated by its application to explain observed trends in bond strengths throughout the periodic table, including main group and transition metal elements.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2026

From Oxo to Oxyl to Biradical: Systematic Multireference Calculations of Methane Activation at MOF Nodes

Methane C–H activation at transition-metal sites often involves electronic structures that challenge conventional single-reference electronic structure descriptions. Although Kohn–Sham density functional theory (DFT) is widely used to study catalytic trends, its reliability for reactions involving strongly correlated species remains uncertain. Here we present a systematic multireference investigation of methane activation at metal–organic framework (MOF) node catalysts across the 3d transition-metal series. We introduce an automated workflow for active space selection to enable consistent application of multireference methods, including multiconfiguration pair-density functional theory and n-electron valence state perturbation theory, to these catalytic systems. These calculations show substantial static correlation in the C–H activation reaction step and predict activation barriers that differ from DFT by 30–70 kJ mol–1, with DFT often qualitatively disagreeing in barrier height trends across transition metals. Analysis of multireference wave functions shows that reactivity is governed by the electronic structure of the M–O moiety along a continuum from metal–oxo to oxyl radical and O biradical character. Increased oxygen-centered spin density and weakened M–O bonding are identified as descriptors of catalytic activity which correlate with lower activation barriers.

Wardzala, Jacob↗
DOE OSTI2023

AZD5582 plus SIV-specific antibodies reduce lymph node viral reservoirs in antiretroviral therapy-suppressed macaques

The main barrier to HIV cure is a persistent reservoir of latently infected CD4 + T cells harboring replication-competent provirus that fuels rebound viremia upon antiretroviral therapy (ART) interruption. A leading approach to target this reservoir involves agents that reactivate latent HIV proviruses followed by direct clearance of cells expressing induced viral antigens by immune effector cells and immunotherapeutics. We previously showed that AZD5582, an antagonist of inhibitor of apoptosis proteins and mimetic of the second mitochondrial-derived activator of caspases (IAPi/SMACm), induces systemic reversal of HIV/SIV latency but with no reduction in size of the viral reservoir. In this study, we investigated the effects of AZD5582 in combination with four SIV Env-specific Rhesus monoclonal antibodies (RhmAbs) ± N-803 (an IL-15 superagonist) in SIV-infected, ART-suppressed rhesus macaques. Here we confirm the efficacy of AZD5582 in inducing SIV reactivation, demonstrate enhancement of latency reversal when AZD5582 is used in combination with N-803 and show a reduction in total and replication-competent SIV-DNA in lymph-node-derived CD4 + T cells in macaques treated with AZD5582 + RhmAbs. Further exploration of this therapeutic approach may contribute to the goal of achieving an HIV cure.

60 APPLIED LIFE SCIENCES↗
DOE OSTI2022

Path integral Monte Carlo approach to the structural properties and collective excitations of liquid $$^3{\text {He}}$$ without fixed nodes

Abstract Due to its nature as a strongly correlated quantum liquid, ultracold helium is characterized by the nontrivial interplay of different physical effects. Bosonic $$^4{\text {He}}$$ 4 He exhibits superfluidity and Bose-Einstein condensation. Its physical properties have been accurately determined on the basis of ab initio path integral Monte Carlo (PIMC) simulations. In contrast, the corresponding theoretical description of fermionic $$^3{\text {He}}$$ 3 He is severely hampered by the notorious fermion sign problem, and previous PIMC results have been derived by introducing the uncontrolled fixed-node approximation. In this work, we present extensive new PIMC simulations of normal liquid $$^3{\text {He}}$$ 3 He without any nodal constraints. This allows us to to unambiguously quantify the impact of Fermi statistics and to study the effects of temperature on different physical properties like the static structure factor $$S({\mathbf {q}})$$ S ( q ) , the momentum distribution $$n({\mathbf {q}})$$ n ( q ) , and the static density response function $$\chi ({\mathbf {q}})$$ χ ( q ) . In addition, the dynamic structure factor $$S({\mathbf {q}},\omega )$$ S ( q , ω ) is rigorously reconstructed from imaginary-time PIMC data. From simulations of $$^3{\text {He}}$$ 3 He , we derived the familiar phonon–maxon–roton dispersion function that is well-known for $$^4{\text {He}}$$ 4 He and has been reported previously for two-dimensional $$^3{\text {He}}$$ 3 He films (Nature 483:576–579 (2012)). The comparison of our new results for both $$S({\mathbf {q}})$$ S ( q ) and $$S({\mathbf {q}},\omega )$$ S ( q , ω ) with neutron scattering measurements reveals an excellent agreement between theory and experiment.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2021

Tailoring Lewis/Brønsted acid properties of MOF nodes via hydrothermal and solvothermal synthesis: simple approach with exceptional catalytic implications

The Lewis/Brønsted catalytic properties of the Metal–Organic Framework (MOF) nodes can be tuned by simply controlling the solvent employed in the synthetic procedure. In this work, we demonstrate that Hf-MOF-808 can be prepared from a material with a higher amount of Brønsted acid sites, via modulated hydrothermal synthesis, to a material with a higher proportion of unsaturated Hf Lewis acid sites, via modulated solvothermal synthesis. The Lewis/Brønsted acid properties of the resultant metallic clusters have been studied by different characterization techniques, including XAS, FTIR and NMR spectroscopies, combined with a DFT study. The different nature of the Hf-MOF-808 materials allows their application as selective catalysts in different target reactions requiring Lewis, Brønsted or Lewis– Brønsted acid pairs.

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

Fundamental gap of fluorographene by many-body GW and fixed-node diffusion Monte Carlo methods

Fluorographene (FG) is a promising graphene-derived material with a large bandgap. Currently existing predictions of its fundamental gap (Δ f ) and optical gap (Δ opt ) significantly vary when compared with experiment. We provide here an ultimate benchmark of Δ f for FG by many-body GW and fixed-node diffusion Monte Carlo (FNDMC) methods. Both approaches independently arrive at Δf ≈ 7.1 ± 0.1 eV. In addition, the Bethe–Salpeter equation enabled us to determine the first exciton binding energy, Eb = 1.92 eV. We also point to the possible misinterpretation problem of the results obtained for gaps of solids by FNDMC with single-reference trial wave functions of Bloch orbitals. We argue why instead of Δ opt , in the thermodynamic limit,

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

Empirically-calibrated H100 node power models for accurate AI training energy estimation

Accurately quantifying the energy use of artificial intelligence (AI) training is critical for infrastructure planning, carbon accounting, and sustainable data center operation, but few studies have directly measured the power consumption of production workloads on contemporary hardware. By combining empirical measurements from Brookhaven National Laboratory during AI training on 8-graphics-processing-unit H100 systems with open-source benchmarking data, we develop statistical models relating computational intensity to node-level power consumption. We measure the gap between manufacturer-rated thermal design power (TDP) and actual power demand during AI training. Our analysis reveals that even computationally intensive workloads operate at only 76% of the 10.2 kW TDP rating. Our architecture-specific model, calibrated to floating-point operations, predicts energy consumption with 11.4% mean absolute percentage error, significantly outperforming TDP-based approaches (27%–37% error). We identified distinct power signatures between transformer and convolutional neural network architectures, with transformers showing characteristic fluctuations that may impact grid stability. These results provide a measurement-grounded basis for improving AI training energy estimates, enabling more reliable infrastructure sizing, cost projections, and environmental impact assessments.

Newkirk, Alex C↗
DOE OSTI2022

Electronic structure of α - RuCl 3 by fixed-node and fixed-phase diffusion Monte Carlo methods

Layered material α-RuCl 3 has caught wide attention due to its possible realization of Kitaev's spin liquid and its electronic structure that involves the interplay of electron-electron correlations and spin-orbit effects. Several DFT+U studies have suggested that both electron-electron correlations and spin-orbit effects are crucial for accurately describing the band gap. This work studies the importance of these two effects using fixed-node and fixed-phase diffusion Monte Carlo calculations both in spin-averaged and explicit spin-orbit formalisms. In the latter, the Slater-Jastrow trial function is constructed from two-component spin orbitals using our recent quantum Monte Carlo (QMC) developments and thoroughly tested effective core potentials. Our results show that the gap in the ideal crystal is already accurately described by the spin-averaged case, with the dominant role being played by the magnetic ground state with significant exchange and electron correlation effects. We find qualitative agreement between hybrid DFT, DFT+U, and QMC. In addition, QMC results agree very well with available experiments, and we identify the values of exact Fock exchange mixing that provide comparable gaps. Explicit spin-orbit QMC calculations reveal that the effect of spin-orbit coupling on the gap is minor, of the order of 0.2 eV, which corresponds to the strength of the spin orbit of the Ru atom.

36 MATERIALS SCIENCE↗
DOE OSTI2020

Grid-based diffusion Monte Carlo for fermions without the fixed-node approximation

A diffusion Monte Carlo algorithm is introduced that can determine the correct nodal structure of the wave function of a few-fermion system and its ground-state energy without an uncontrolled bias. This is achieved by confining signed random walkers to the points of a uniform infinite spatial grid, allowing them to meet and annihilate one another to establish the nodal structure without the fixed-node approximation. An imaginary-time propagator is derived rigorously from a discretized Hamiltonian, governing a non-Gaussian, sign-flipping, branching, and mutually annihilating random walk of particles. The accuracy of the resulting stochastic representations of a fermion wave function is limited only by the grid and imaginary-time resolutions and can be improved in a controlled manner. Here, the method is tested for a series of model problems including fermions in a harmonic trap as well as the He atom in its singlet or triplet ground state. For the latter case, the energies approach from above with increasing grid resolution and converge within 0.015 E h of the exact basis-set-limit value for the grid spacing of 0.08 a.u. with a statistical uncertainty of 10 –5 E h without an importance sampling or Jastrow factor.

74 ATOMIC AND MOLECULAR PHYSICS↗
DOE OSTI2025

Type-II Weyl nodes, flat bands, and evidence for a topological Hall-effect in the new ferromagnet FeCr 3 Te 6

The interplay between linearly dispersing, or Dirac-like, and flat electronic bands, for instance, in the kagome ferromagnets, has attracted attention due to a possible interplay between topology and electronic correlations. Here, we report the synthesis, structural, electrical, and magnetic properties of a single-crystalline ferromagnetic compound, namely Fe 1/3 ⁢CrTe 2 or FeCr 3 ⁢Te 6 , which crystallizes in the 𝑃$\overline{3}$⁢𝑚⁢1 space group instead of the 𝐼⁢2/𝑚 previously reported for FeCr 2 ⁢Te 4 . Electronic band structure calculations reveal type-II Dirac nodes and relatively flat bands near the Fermi level (ε 𝐹 ). This compound shows onset Curie temperature 𝑇 c ≃ 120K, followed by an additional ferromagnetic transition near 𝑇 c2 ∼ 92.5K. Below 𝑇 c , FeCr 3 ⁢Te 6 displays a pronounced anomalous Hall effect, as well as sizable coercive fields that exceed 𝜇 0 ⁢𝐻=1 T at low 𝑇⁢s. However, a scaling analysis indicates that the anomalous Hall effect results from a significant intrinsic contribution, as expected from the calculations, and also from the extrinsic mechanism, i.e., scattering. The extrinsic contribution probably results from occupational disorder at the 1b Fe-site within the van der Waals gap of the CrTe 2 host. We also observe evidence for a topological Hall component superimposed onto the overall Hall response, suggesting the presence of chiral spin textures akin to skyrmions in this centrosymmetric system. Their possible presence will require experimental confirmation.

36 MATERIALS SCIENCE↗
DOE OSTI2025

Anomalous Hall effect emerging from field-induced Weyl nodes in SmAlSi

The intrinsic anomalous Hall effect (AHE) has been reported in numerous ferromagnetic Weyl semimetals. However, the AHE in the antiferromagnetic (AFM) or paramagnetic (PM) state of Weyl semimetals has rarely been observed experimentally. Different mechanisms have been proposed to account for the emergence of the AHE from different types of magnetic order. Here, in this Letter, we propose a new model that explains the observed AHE in both the AFM and PM states of the noncentrosymmetric Weyl semimetal SmAlSi. The newly proposed mechanism is based on magnetic-field-induced Weyl node evolution, which qualitatively explains the temperature dependence of the anomalous Hall conductivity, which displays unconventional power-law behavior in both the AFM and PM states of SmAlSi.

Gao, Yuxiang [Rice University, Houston, TX (United↗
DOE OSTI2025

A Graph-Net with Node Embeddings to Detect False Data Injection Attacks in Photovoltaic Systems

Distributed energy resources (DER) contribute to the operational stability of the larger power grid both at utility-scale as well as commercial and residential scales in aggregated forms. These DER in-turn are susceptible to increasing cyber threats. An adversary can plug into the same local network that a field photovoltaic (PV) system uses to interconnect its data loggers and inverters and manipulate certain measurements collected from the network or trick existing irradiance and inverter readings through false data injection attacks (FDIA). Control routines that rely on these measurements can propagate the false data, impacting critical decisions that result in a suboptimal operation or even cause intentional harm leading to inverter-tripping or unscheduled loads that need to be shed. To detect FDIA in PV systems, the paper introduces an attention-based graph neural network with node embeddings and applied it to a simple prototypical DC-coupled microgrid with PV, energy storage, and load. The algorithm shows a detection accuracy of up to 98.95%. The proposed FDIA detection technique will provide micro-grid operators with an effective method to safeguard their systems, guaranteeing the secure and reliable operation.

Parvez, Imtiaz [Utah Valley University]↗
DOE OSTI2023

A Task Based Approach for Co-Scheduling Ensemble Workloads on Heterogeneous Nodes

Scientific workflows consist of multiple, connected applications, with data and results flowing from one to another in a pipeline. Traditionally, such workflows are executed in sequential order, storing intermediate data in storage disks. Co-scheduling application workflows concurrently on the same compute nodes would greatly reduce the cost of moving data to/from storage and allow real-time analysis of intermediate results. Nevertheless, most parallel programming runtimes do not allow seamless integration of various applications in a scientific workflow, in part due to the complexity of managing data and resources. The situation is even more complicated for heterogeneous systems. In this work we extend the Minos Computing Library (MCL) runtime to accelerate pipe-lined and parallel workloads where multiple applications are running in the same system. MCL’s asynchronous task library and runtime dynamically manages resources to allow co-scheduling of multiple processes sharing heterogeneous resources. In addition, we design a custom ex- tension of the Open Compute Language (OpenCL) to enable multiple processes to share device memory. We enable MCL to coordinate these shared buffers to allow for easy, fast data sharing between applications. Using malleable micro-benchmarks and two application workflows that combine scientific simulation and AI-based analysis, we show that our method outperforms traditional approaches.

Index Terms—Parallel systems, Scheduling and Task ↗