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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 325 records · Page 18

Identification of In Situ Generated High-Spin Fe(II)-N 4 Active Sites for Acidic Oxygen Reduction Reaction via Operando 57 Fe Mössbauer Spectroscopy

Iron-nitrogen-carbon (FeNC) catalysts are considered among the most promising alternative to Pt catalysts in acidic oxygen reduction reaction (ORR), yet the geometric and electronic structures of the true active site under reaction conditions have not been clearly elucidated. Herein, we synthesized a representative FeNC catalyst by pyrolyzing Fe 3+ absorbed on ZIF-8-derived N-doped carbon at a mild temperature under the H 2 /Ar atmosphere, where a formation mechanism of FeN 4 sites through a Zn-mediated Fe nanoparticle atomization process was proposed. The resulting FeNC-750 catalyst shows high acidic ORR activity with a half-wave potential of 0.838 V and a peak power density of 1 W cm -2 in proton-exchange membrane fuel cell (PEMFC). By using operando 57 Fe Mössbauer spectroscopy on FeNC-750, it was revealed that the pyrrolic N-coordinated high-spin Fe 2+ N 4 sites, which are in situ generated from high-spin Fe 3+ N 4 during ORR, are identified as catalytic active states. Density functional theory calculations further verified that, compared to the pyridinic N-coordinated low-spin Fe 2+ N 4 , the pyrrolic N-coordinated high-spin Fe 2+ exhibits optimized adsorption energy for reaction intermediates, thereby lowering the energy barrier of the rate-determining step (RDS) and facilitating OH* desorption. In conclusion, this work provides both experimental and theoretical evidence of the true active site in the FeNC during acidic ORR, offering significant insights for the rational design of high-performance materials for acidic fuel cells.

FeNC catalyst↗

Transient Triamidoamine Neptunium(V)–Mono(Imido) Complexes: C–H Activations and Hydrogen Atom Transfer Driven by Effective Nuclear Charge

Metal-mono(imido) linkages have been known for seven decades, and they are found in transition metal, main group, lanthanide, thorium, and uranium complexes. However, transuranium-mono(imido) complexes remain unknown in any scenario. Here, we present evidence for transient neptunium(V)–mono(imido) complexes. Treatment of [Np III (Tren TIPS )] (1, Tren TIPS = {N(CH 2 CH 2 NSiPr i 3 ) 3 } 3– ) with N 3 R (R = SiMe 3 ; 1-adamantyl, Ad) results in N 2 evolution and dark purple solutions consistent with the formation of [Np V (Tren TIPS )(NR)] (3NpNR). However, solutions of 3NpNR rapidly turn orange, where for R = SiMe 3 the isolated 1:1 products are [Np IV (Tren TIPS ){N(H)SiMe 3 }] (4a) and [Np IV (Tren TIPS-2H ){N(H)SiMe 3 }] (4b, Tren TIPS-2H = {N(CH 2 CH 2 NS i Pri 3 ) 2 (NCH 2 CH 2 NSiPr i 2 C[Me]=CH 2 )} 3– ). The latter contains a dehydrogenated-Pr i vinyl functionality accounting for the source of the two amido H atoms. The reaction for R = Ad proceeds similarly, but only [Np IV (Tren TIPS ){N(H)Ad}] (5a) could be unequivocally confirmed, though its isolation suggests generality of the imido-to-amido functional group transformation. Complexes 4a/4b exhibit slow relaxation of their magnetization, adding to the small number of transuranium single ion magnets. Experimental and computational analysis suggests that the amido products are formed by C–H activation and two sequential hydrogen atom transfer reactions involving a three-step proton-coupled electron-transfer sequence of H • radical abstraction, electron transfer, then another H • radical abstraction step. In contrast to transient 3NpNR, the 5f 2 uranium(IV)-imido complex [K(2.2.2-cryptand)][U IV (Tren TIPS )(NSiMe 3 )] (8UNSiMe 3 ) is robust, even in boiling THF, suggesting the transience of 5f 2 3NpNR is not due to the 5f n -count but the increased effective nuclear charge of neptunium vs uranium. This work highlights divergence of uranium- and neptunium-imido stabilities, emphasizing that the latter is an inherently challenging synthetic target.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

Downfolding from ab initio to interacting model Hamiltonians: comprehensive analysis and benchmarking of the DFT+cRPA approach

Abstract Model Hamiltonians are regularly derived from first principles to describe correlated matter. However, the standard methods for this contain a number of largely unexplored approximations. For a strongly correlated impurity model system, here we carefully compare a standard downfolding technique with the best possible ground-truth estimates for charge-neutral excited-state energies and wave functions using state-of-the-art first-principles many-body wave function approaches. To this end, we use the vanadocene molecule and analyze all downfolding aspects, including the Hamiltonian form, target basis, double-counting correction, and Coulomb interaction screening models. We find that the choice of target-space basis functions emerges as a key factor for the quality of the downfolded results, while orbital-dependent double-counting corrections diminish the quality. Background screening of the Coulomb interaction matrix elements primarily affects crystal-field excitations. Our benchmark uncovers the relative importance of each downfolding step and offers insights into the potential accuracy of minimal downfolded model Hamiltonians.

Chemistry↗

Forming a database to study reversed magnetic shear from the National Spherical Torus eXperiment using machine learning

Achieving a long-lived reversed magnetic shear (RMS) target plasma in the National Spherical Torus eXperiment Upgrade will require developing various sustainment scenarios. To help with the ongoing plasma control efforts, the development of a new analysis for the motional Stark effect (MSE) diagnostic using a machine learning algorithm, namely, MSE-ML, is described. MSE-ML will be used to identify patterns during RMS discharges, some of which suffer magnetohydrodynamic (MHD) events resulting in current redistribution and monotonic q-profiles. A database consisting of q and magnetic shear profiles is being constructed primarily based on the existing National Spherical Torus eXperiment data with equilibrium reconstructions constrained by the magnetic field pitch angle profile measured using the multi-channel MSE diagnostic. An unsupervised k-means clustering of the data is developed to study the RMS formation as a function of time. The initial clustering from the q-profiles shows significant differences in both amplitude and the duration of the RMS period. As a goal, the clustering results that detect and distinguish shots with substantial and sustained RMS are to be used as a preprocessing step in a supervised algorithm to identify the underlying conditions that lead to long-lasting improved confinement with RMS. Another aim of the MSE-ML study is to identify precursors of RMS-destroying MHD events in either derived data such as the q-profile or directly measured data such as the magnetic field pitch angle profile.

Uzun-Kaymak, I. U. (ORCID:0000000276251493)↗

Moment extraction using an unfolding protocol without binning

Deconvolving (“unfolding”) detector distortions is a critical step in the comparison of cross-section measurements with theoretical predictions in particle and nuclear physics. However, most existing approaches require histogram binning while many theoretical predictions are at the level of statistical moments. We develop a new approach to directly unfold distribution moments as a function of another observable without having to first discretize the data. Our moment unfolding technique uses machine learning and is inspired by Boltzmann weight factors and generative adversarial networks (GANs). We demonstrate the performance of this approach using jet substructure measurements in collider physics. With this illustrative example, we find that our moment unfolding protocol is more precise than bin-based approaches and is as or more precise than completely unbinned methods.

72 PHYSICS OF ELEMENTARY PARTICLES AND FIELDS↗

FedOSAA: Improving Federated Learning with One-Step Anderson Acceleration

Federated learning (FL) is a distributed machine learning approach that enables multiple local clients and a central server to collaboratively train a model while keeping the data on their own devices. First-order methods, particularly those incorporating variance reduction techniques, are the most widely used FL algorithms due to their simple implementation and stable performance. However, these methods tend to be slow and require a large number of communication rounds to reach the global minimizer. We propose FedOSAA, a novel approach that preserves the simplicity of first-order methods while achieving the rapid convergence typically associated with second-order methods. Our approach applies one Anderson acceleration (AA) step following classical local updates based on first-order methods with variance reduction, such as FedSVRG and SCAFFOLD, during local training. This AA step is able to leverage curvature information from the history points and gives a new update that approximates the Newton-GMRES direction, thereby significantly improving the convergence. We establish a local linear convergence rate to the global minimizer of FedOSAA for smooth and strongly convex loss functions. Numerical comparisons show that FedOSAA substantially improves the communication and computation efficiency of the original first-order methods, achieving performance comparable to second-order methods like GIANT.

Feng, Xue [University of California, Davis]↗

Stepped hosting capacity for maximizing distributed solar on Guam

Guam Power Authority (GPA) sought national lab assistance through the Energy Technology Innovations Partnership Project as part of the second cohort of applicants (i.e. the program’s second year). GPA is leading an effort to evolve the island’s energy generation portfolio to 50% renewable by 2030, and 100% renewable by 2040. These goals for renewable penetration are a function of public law and GPA is legally required to comply, though GPA’s timeline is more aggressive by five years in each case than the law requires.

14 SOLAR ENERGY↗

Single-Step Nonthermal Plasma Synthesis of Water-Soluble and Near-Infrared-Emitting Si Quantum Dots for Bioimaging Applications

Here, we present a single-step nonthermal plasma method for the synthesis of near-infrared (NIR)-emitting and water-soluble Si quantum dots (QDs) for bioimaging applications. Oxygen gas and water vapor were introduced together with acrylic acid (AA) into the afterglow region of the synthesis plasma leading to the surface functionalization of the upstream synthesized Si QDs. The simultaneous surface oxidation and ligand grafting enabled solubility and colloidal stability of the Si QDs in water, as evidenced by strongly reduced hydrodynamic diameters. Aged Si QDs in water emitted NIR photoluminescence (PL) at around 830 nm. The PL quantum yield of the Si QDs in water increased over time from initially undetectable to ~30% after 8 days. Cell viability tests showed that >70% of 3T3 cells survived for 24 h at a concentration of 200 μg/mL of oxidized AA grafted Si QDs. The water solubility, NIR emission with a high quantum yield, and cell viability make the Si QDs promising for bioimaging applications.

36 MATERIALS SCIENCE↗

In situ atomic-resolution imaging of water vapor–driven multistep oxidation dynamics in strontium cobaltite

Understanding how water vapor interacts with transition metal oxides (TMOs) is critical for tailoring material properties to improve performance and enable new technologies. Despite extensive research efforts, atomic-scale mechanisms underpinning dynamic reactions and reaction-induced phase transitions remain elusive. Here, we use in situ environmental transmission electron microscopy to investigate how water vapor oxidizes vacancy-ordered SrCoO 2.5 at moderately elevated temperatures, demonstrating that water molecules can initiate oxidation more effectively than oxygen under comparable conditions. We discover a distinct “staging” behavior during the oxidation process: A fully ordered intermediate phase, SrCoO 2.75 , forms before transitioning into a near-perovskite SrCoO 3−δ . In addition, antiphase boundaries, originating at step terraces of SrTiO 3 , alleviate strain by creating reversible nanoscale “gaps” during lattice contraction under oxidation, providing a pathway for preserving structural integrity throughout redox cycling. This work provides atomic-level guidance for engineering TMOs by leveraging water vapor to control their redox behavior and tailor functional properties.

Science & Technology - Other Topics↗

SIREN: Scaling Ion-Traps by REquiring iNnovative Heterogenous Integration

The SIREN (Scaling Ion Traps by Requiring iNnovative heterogenous integration) project explores the feasibility of heterogeneous integration (HI) as a transformative approach to scaling ion traps, a critical technology for advancing quantum computers and atomic clocks. Traditional ion trap architectures face significant challenges in scalability due to limitations in optical access, fabrication techniques, and material constraints. SIREN addresses these challenges by leveraging HI, which combines different materials and fabrication processes to create more complex and efficient ion trap structures. HI integrated structures can be manufactured without compromising the process to maintain compatibility to ion traps. This project focuses on integrating a separately fabricated waveguide with a fully functional ion trap. The respective alignment between the pieces needs to be accurate to less than 2 µm to ensure that the light from the waveguide can overlap with the trapping region. The fine alignment must also be maintained through an ultra-high vacuum bake, a critical step in preparing an ion trap experiment. The project's outcomes suggest that heterogeneous integration is a promising pathway for overcoming current scalability barriers, paving the way for the next generation of quantum technologies. SIREN's findings contribute significantly to the field, offering a scalable solution that could accelerate the development of practical quantum computers and highly accurate atomic clocks.

42 ENGINEERING↗

A spline-based method to obtain spatially dependent viscosity in confined flows

Coupling chemical physics to continuum theories is a critical step to understanding multi-scale phenomena. This paper will connect non-equilibrium molecular dynamics simulations to a continuum-based Navier-Stokes equation that has relaxed the assumption of spatial uniformity in viscosity. Using a form for viscosity based on spline interpolation, viscosity as a function of position is obtained from the least squares fit of the velocity profile measured from molecular simulations of flow in a nanochannel. Viscosity can vary widely, particularly near the channel boundaries, indicating that uniform viscosity is no longer appropriate. Variations of the viscosity near the channel surfaces imply that considering solution and surface chemistry could be necessary to rigorously understand molecular-scale flows in nanochannels.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

The safety of magnetic resonance imaging contrast agents

Gadolinium-based contrast agents are increasingly used in clinical practice. While these pharmaceuticals are verified causal agents in nephrogenic systemic fibrosis, there is a growing body of literature supporting their role as causal agents in symptoms associated with gadolinium exposure after intravenous use and encephalopathy following intrathecal administration. Gadolinium-based contrast agents are multidentate organic ligands that strongly bind the metal ion to reduce the toxicity of the metal. The notion that cationic gadolinium dissociates from these chelates and causes the disease is prevalent among patients and providers. We hypothesize that non-ligand-bound (soluble) gadolinium will be exceedingly low in patients. Soluble, ionic gadolinium is not likely to be the initial step in mediating any disease. The Kidney Institute of New Mexico was the first to identify gadolinium-rich nanoparticles in skin and kidney tissues from magnetic resonance imaging contrast agents in rodents. In 2023, they found similar nanoparticles in the kidney cells of humans with normal renal function, likely from contrast agents. We suspect these nanoparticles are the mediators of chronic toxicity from magnetic resonance imaging contrast agents. This article explores associations between gadolinium contrast and adverse health outcomes supported by clinical reports and rodent models.

59 BASIC BIOLOGICAL SCIENCES↗

HfZr_BCC_SolidSolution_128atoms_VASP6

We performed density functional theory (DFT) calculations for body-centered-cubic (BCC) structures with 128 lattices sites of solid solution binary alloys hafnium-zirconium (Hf-Zr). The electronic structures of alloys have been calculated using Vienna Ab initio Simulation Package (VASP). Within this package the DFT approach is used to reduce many-body Schrodinger equation to set of single particle Kohn-Sham (KS) equations. The generalized electronic exchange-correlation functional is described by generalized gradient approximation with the Perdew-Burke-Ernzerhof parametrization. The electron-ion interactions is described by pseudopotentials developed within the plane-wave basis projector augmented-wave (PAW) approach. These pseudopotentials are available at the VASP portal (http://cms.mpi.univie.ac.at/vasp/). Our calculations have been run with the pseudopotentials treating s and p semi-core states as valence in case for the elements Hf and Zr. The electronic densities and potentials are expanded over plane-waves with energy cutoff of 350 eV. 2x2x2 k-mesh and normal precision were used. The alloys were modeled by supercell containing 128 randomly distributed atoms. At initial step the atoms occupy perfect bcc lattice cites. This initial structure was optimized until energy changes less than 1e-6 eV, while forces acting on atoms don't exceed 1e-2 eV/angstrom. The electron-ion interaction is described by PAW pseudopotentials. The calculations have been collected by sampling chemical compositions across the entire compositional range. The chemical compositions have been sampled by progressively changing the number of atoms per constituent by 4. For each chemical composition of binaries and ternaries, the first-principle calculations have been run for 100 randomized arrangements of the constituents on the BCC lattice sites. We collected data for a total of 3,100 randomized atomic structures over 31 chemical compositions.

36 MATERIALS SCIENCE↗

Physics-informed latent neural operator for real-time predictions of time-dependent parametric PDEs

Deep operator network (DeepONet) has shown significant promise as surrogate models for systems governed by partial differential equations (PDEs), enabling accurate mappings between infinite-dimensional function spaces. However, when applied to systems with high-dimensional input-output mappings arising from large numbers of spatial and temporal collocation points, these models often require heavily overparameterized networks, leading to long training times. Latent DeepONet addresses some of these challenges by introducing a two-step approach: first learning a reduced latent space using a separate model, followed by operator learning within this latent space. While efficient, this method is inherently data-driven and lacks mechanisms for incorporating physical laws, limiting its robustness and generalizability in data-scarce settings. Here, in this work, we propose PI-Latent-NO, a physics-informed latent neural operator framework that integrates governing physics directly into the learning process. Our architecture features two coupled DeepONets trained end-to-end: a Latent-DeepONet that learns a low-dimensional representation of the solution, and a Reconstruction-DeepONet that maps this latent representation back to the physical space. By embedding PDE constraints into the training via automatic differentiation, our method eliminates the need for labeled training data and ensures physics-consistent predictions. The proposed framework is both memory and compute-efficient, exhibiting near-constant scaling with problem size and demonstrating significant speedups over traditional physics-informed operator models. We validate our approach on a range of parametric PDEs, showcasing its accuracy, scalability, and suitability for real-time prediction in complex physical systems.

Latent representations↗

Ammonium-coordinated exchanger (ACE) functionalized silica sorbents for recovering/removing aqueous anionic contaminants

There are limited studies of functionalized silica anion exchange sorbents used for critical/heavy metal recovery/removal relative to polymeric and other inorganic materials. This work features ammonium-coordinated exchanger (ACE) anion exchange particle sorbents prepared by either acid-washing epoxy-crosslinked polyethylenimine (PEI) hydrogen bonded within/to a silica particle sorbent (two-step method) or reacting a di-chlorinated crosslinker, α,α-dichloro-p-xylene (DPX), with PEI within silica (single-step method). Energy dispersive X-ray spectroscopy (EDS) and infrared spectroscopy confirmed the presence of -NH 2 + ···Cl - and -NH 3 + ···Cl - groups, which removed oxyanionic species –arsenate, selenate, chromate, sulfate, phosphate, and nitrate– plus bromide from ideal solutions, authentic acid mine drainage (AMD), and authentic flue gas desulfurization (FGD) wastewater. Affinity of the anions for ACE varied across single- and mixed-element solutions. However, affinity for CrO 4 2- was among the highest in both cases. Total anion uptake by the optimized ACE, PEI-E3-HCl_1.1, reached 1.2 mmol anion/g-sorb. (0.56 mmol CrO 4 2- /g), or ∼2.3 mmol negative charge/g-sorb. This was close to the 0.52 mmol CrO 4 2- /g of a commercial anion exchange resin. Near-consistent removal of 20–80 % of each anion from FGD during an eight-cycle adsorption-desorption (1 M NaCl) test predicted good ACE viability for testing under practical conditions at larger scale.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

Fundamental benchmarking of the discharge properties of negative electrodes in lead acid batteries

The unprecedented scale of energy storage deployment needed to allow high penetration of intermittent renewable energy sources into the electrical grid places significant economic cost and performance targets on battery technologies. Lead batteries, owing to their highly abundant and inexpensive raw materials, can be considered an important solution to grid storage as long as they achieve high material utilization, fast recharge rates, and long cycle life. To address the limitations in material utilization, we need to revisit the electrochemical processes during the discharge step and answer the following question: what are the fundamental limits of the discharge reaction? In this work we discuss how well-defined lead metal surfaces with nanometer scale roughness allow us to resolve the accessible discharge capacity for both faradaic and non-faradaic processes as a function of electrolyte concentration and in the presence of traditional additives. The direct connection between PbSO 4 layer morphology and discharge rates gives us important insights on the mechanism of discharge as related to the dissolution and passivation events. In conclusion, this work sets the stage for reimagining the design of lead batteries with implications to grid storage applications.

25 ENERGY STORAGE↗

Heterogenous catalysis for oxygen tolerant photoredox atom transfer radical polymerization and small-molecule dehalogenation

Heterogeneous photocatalysts (PCs) have garnered attention for their sustainability and cost-effectiveness. Despite the existence of various types of these PCs, their synthesis often involves complex, multi-step procedures and laborious purification. Herein, we propose a simple method for attaching small-molecule photocatalytic species onto crosslinked 3-D polymer networks as insoluble scaffolds to create robust heterogeneous PCs. The highly swellable poly(ethylene glycol)-based ChemMatrix (CM) resin, known for its amphiphilic properties and high functional group loading, facilitated the covalent immobilization of the photoredox dye Eosin Y (EY), but also streamlined functionalization with Ir( III ) complexes. The resulting heterogeneous CM-EY demonstrated efficient photocatalytic performance in open-to-air dual photoredox catalysis of atom transfer radical polymerization (photo-ATRP) under green light. This was confirmed by the well-controlled synthesis of polymers with molecular masses ranging from 20 kDa to 300 kDa and low dispersities. Furthermore, CM-EY exhibited excellent photostability and recyclability over multiple cycles of ATRP. The heterogeneous catalysis of photo-ATRP provided high temporal control and enabled benign conditions for synthesizing protein-polymer hybrids (PPH). When combined with the initiator-modified CM (CM-BIB), CM-EY facilitated the solid-phase synthesis of homopolymers and block copolymers with recyclable performance. However, the coordinatively bound Ir@CM showed decreased catalytic activity and efficiency toward photoredox dehalogenation due to the leaching of active species during recycling. This study highlights the advantages of the covalent linking of catalysts to solid supports over non-covalent interactions, underscoring the potential of functionalized polymer resin as a promising scaffold. Such an approach offers customization and tunability, presenting opportunities for innovation in green chemistry.

Kapil, Kriti↗

Ultrafast solvent-to-solute proton transfer mediated by intermolecular coherent vibrations

Ultrafast photoinduced excited-state proton transfer (ESPT) plays a crucial role in protecting biomolecules and functional materials from photodamage. However, the influence of solute-solvent interactions on ESPT dynamics remains under active investigation. Here, we present an ultrafast spectroscopic study of ESPT in the photobase 2-(2´-pyridyl)benzimidazole (PBI) in methanol. Ultrafast absorption spectroscopy, supported by quantum chemical calculations, reveals three distinct kinetic steps: (1) a 2.2 ps solvent-to-solute proton transfer, (2) subsequent nonradiative relaxation to the ground state within 31 ps, producing a vibrationally hot ensemble with substantial excess kinetic energy, and (3) equilibration as this energy dissipates into the surrounding solvent bath over 186 ps. Femtosecond-resolved dynamics exhibit oscillatory signals indicative of coherent wavepacket motion on the S 1 potential energy surface. A phase flip in the excited-state absorption maximum confirms this assignment. Fourier analysis resolves two dominant periods (∼117 fs and ∼340 fs), corresponding to in-plane and out-of-plane vibrational modes coupled between PBI and the hydrogen-bonded methanol molecule. The rapid dephasing ( < 300 fs) suggests that the nuclear wavefunction evolves on an anharmonic potential energy surface while traversing the ESPT reaction coordinate.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗