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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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Halide-induced rate enhancements are correlated with the desorption barriers of aqueous metal–anion complexes on electrodes, which can guide electrode and electrolyte selection to enhance redox kinetics of metal ion charge transfer reactions.
Er 2 Sn 2 O 7 pyrochlore was irradiated with swift heavy Au ions (2.2 GeV), and the induced structural modifications were systematically examined using complementary characterization techniques including transmission electron microscopy (TEM), X-ray diffraction (XRD), and neutron total scattering with pair distribution function (PDF) analysis. Each technique probes different aspects and length scales of the transformed material regions. TEM revealed a core–shell ion track structure—an amorphous core surrounded by a disordered, anion-deficient fluorite shell—which was confirmed by XRD. Neutron total scattering, with sensitivity to the oxygen sublattice, provided relative fractions of amorphous and disordered fluorite phases and confirmed the presence of a defective pyrochlore phase, which largely maintains its structural ordering but is clearly distinct from the pristine pyrochlore matrix. This defect-rich pyrochlore phase forms a halo extending radially beyond the well-characterized core–shell track morphology observed in electron micrographs. Despite their differing long-range periodicity, the short-range structures of the amorphous, disordered, and defective pyrochlore phases are all modeled well with a weberite-type configuration. Evolution of the phase fractions with increasing ion fluence was examined to ascertain the phase-to-phase pathways that occur during primary and secondary ion impact. Furthermore, this approach extends knowledge about the multi-scale response of stannate pyrochlores to swift heavy ion irradiation in the electronic energy loss regime and improves existing track-overlap models.
Here monometallic Rh/MCM-41 and bimetallic RhM 3 /MCM-41 (M = Fe, Co, Ni, Cu, or Zn) catalysts are synthesized and tested for vapor-phase ethylene hydroformylation reaction. Co is found to exhibit a significant promotion effect on the selectivity of hydroformylation to C 3 oxygenates, followed by Fe and Cu, with Ni and Zn showing a negative effect. DFT calculations reveal that the addition of a secondary metal can provide a new type of site, being able to selectively tune the binding energies of reaction intermediates, and thus lead to different catalytic performances.
The entanglements of dynamically asymmetric polymer layers influence relaxations of nanoparticles in polymer nanocomposites.
The formation of ice in the atmosphere affects precipitation and cloud properties, and plays a key role in the climate of our planet. Although ice can form directly from liquid water at deeply supercooled conditions, the presence of foreign particles can aid ice formation at much warmer temperatures. Over the past decade, experiments have highlighted the remarkable efficiency of feldspar minerals as ice nuclei compared to other particles present in the atmosphere. However, the exact mechanism of ice formation on feldspar surfaces has yet to be fully understood. Here, we develop a first-principles machine-learning model for the potential energy surface aimed at studying ice nucleation at microcline feldspar surfaces. The model is able to reproduce with high-fidelity the energies and forces derived from density-functional theory (DFT) based on the SCAN exchange and correlation functional. Our training set includes configurations of bulk supercooled water, hexagonal and cubic ice, microcline, and fully-hydroxylated feldspar surfaces exposed to vacuum, liquid water, and ice. In this work, we apply the machine-learning force field to study different fully-hydroxylated terminations of the (100), (010), and (001) surfaces of microcline exposed to vacuum. Our calculations suggest that terminations that do not minimize the number of broken bonds are preferred in vacuum. We also study the structure of supercooled liquid water in contact with microcline surfaces, and find that water density correlations extend up to around 10 Å from the surfaces. Finally, we show that the force field maintains a high accuracy during the simulation of ice formation at microcline surfaces, even for large systems of around 30,000 atoms. Future work will be directed towards the calculation of nucleation free energy barriers and rates using the force field developed herein, and understanding the role of different microcline surfaces on ice nucleation.
The spatial distribution of copper (Cu) dopant in CdSe quantum dots (QDs) significantly impact the photophysical properties including emission characteristics at ambient conditions. The dopant state fluctuates more widely for surface Cu doping.
The BT-15BLT relaxor ferroelectric exhibits local T distortions within 100 K to 500 K. Through RMC fitting, it was revealed that T distortions originate from Bi/Li clusters and relaxor phase transition is induced by localized polarization rotations.
We highlight the challenges and recent progress in using semiconductors to harvest solar energy for carrying out alcohol oxidation.
Excitons in organic thin films vary on the nanometer length scale.
Individual lanthanide elements have physical/electronic/magnetic properties that make each useful for specific applications. Several of the lanthanides cations (Ln 3+ ) naturally occur together in the same ores. They are notoriously difficult to separate from each other due to their chemical similarity. Predicting the Ln 3+ differential binding energies (ΔΔE) or free energies (ΔΔG) at different binding sites, which are key figures of merit for separation applications, will help design of materials with lanthanide selectivity. We apply ab initio molecular dynamics (AIMD) simulations and density functional theory (DFT) to calculate ΔΔG for Ln 3+ coordinated to ligands in water and embedded in metal–organic frameworks (MOFs), and ΔΔE for Ln 3+ bonded to functionalized silica surfaces, thus circumventing the need for the computational costly absolute binding (free) energies ΔG and ΔE. Perturbative AIMD simulations of water-inundated simulation cells are applied to examine the selectivity of ligands towards adjacent Ln 3+ in the periodic table. Static DFT calculations with a full Ln 3+ first coordination shell, while less rigorous, show that all ligands examined with net negative charges are more selective towards the heavier lanthanides than a charge-neutral coordination shell made up of water molecules. Amine groups are predicted to be poor ligands for lanthanide-binding. Finally, we also address cooperative ion binding, i.e., using different ligands in concert to enhance lanthanide selectivity.
Surface characterization at the atomic scale is essential for understanding the catalytic properties of supported metal nanoparticles. Secondary electron (SE) imaging in scanning transmission electron microscopy (STEM) provides three-dimensional surface topographic information, enabling the characterization of the size, morphology, and distribution of supported nanoparticles. Furthermore, real-time observation of catalyst materials in a gaseous environment would enhance the understanding of catalyst dynamics under operational conditions. Ongoing technical developments in SE-STEM and advancements in computational methods are expected to facilitate atomic-scale surface observations and enable more quantitative and statistical analyses. This progress will not only elucidate fundamental mechanisms at the atomic level but also provide comprehensive and universal insights into catalyst performances. Here, this minireview showcases the recent advancements and research findings in surface-sensitive SE imaging in STEM for the characterization of active catalyst materials.
Structure-activity relationship of surface immobilized electrocatalysts shows overpotential dependence on ligand basicity and steric accessibility.
Completely or partially ordered intermetallic compounds possess unique geometric ensembles, electronic structure and chemical bonding scenarios, establishing them as an emergent class of catalytic materials for selective hydrogenation reactions.
Aqueous Zn/MnO 2 batteries are a promising, safe alternative for grid-scale energy storage, owing to their environmentally safe and low-cost nature. The dissolution–deposition reaction mechanism in a mild aqueous pH regime has recently gained significance due to its relevance in battery design. Comprehending both the specific locations and the way reaction progresses is crucial for efficient batteries. This study demonstrates that Zinc Hydroxy Sulfate (ZHS) formed during discharge primarily near the dissolved MnO2 particles. Acting as a host for charge reactants in subsequent cycles, the charge product morphology was visualized using operando X-ray fluorescence microscopy. After ∼400 hours of cycling, capacity fade was linked to the formation of a Zn–Mn core–shell phase which is attributed to an irreversible core phase in the electrode, visualized through three-dimensional chemical mapping. Altogether, this research underscores the importance of understanding local morphological evolution in designing electrodes and chemistries for advanced grid-scale energy storage technologies.
Multi-twinned structures have been observed in technologically important crystal systems, for example diamond cubic and face-centered cubic (FCC) lattices, that include materials such as diamond, silicon, a wide range of noble metals, and their nanoscale counterparts. Beyond atomic building blocks, the special arrangements also occur in the self-assembly of nanoparticles (NP) and μm-sized colloidal particles and occupy parts of their phase diagrams. Spanning a wide range of length scales, the universality of the structures arises when the systems attempt to achieve multitwinned structures by overcoming geometric misfits during minimizing surface energies with entirely {111} or close-packing facets. While it is fundamental to understand how strain is sustained upon twinned structures and symmetry breaking, the knowledge will be paramount in practical aspects such as guiding and controlling the thin film growth, anisotropic NP growth, and self-assembly of NPs. Au decahedral (Dh) NP, as the most prevalent multi-twinned model system, fits five tetrahedral motifs into a circle by sharing an axis resulting in a geometric misfit angle of 7.35°, or a disclination with power of -7.35°. Postulating how Au FCC lattice adopts the misfit, theoretical models have been developed to address the underlying lattice symmetry and inhomogeneous strain distribution separately. Yet, experimental reports regarding the former have been limited due to the relatively large X-ray beam sizes that do not fit the sizes of NPs. On the other hand, though the latter has been widely adapted in the thermodynamics of small (<10 nm) multi-twinned nanoparticles, previous literature has shown that, at edge length of 17 nm, the theory’s is invalidated by shear strain that is observed in a defect-free Au Dh NP by high-resolution transmission electron microscopy (HR-TEM) imaging. Though the advancement of aberrationcorrected scanning transmission electron microscopy (AC-STEM) imaging and ab initio calculation techniques brings new opportunities, along with challenges in complicated image analysis and limitation in particle size (usually below 10 nm), the gap between nanoscale and mesoscale has never been extended to gain insight from atomic system with straightforward interaction potentials.
Multiphysics simulations for nuclear reactor analysis are usually performed by resorting to operator splitting and fixed point iterations between single-physics solvers. This enables the separate solution of each physics, such as neutronics, fuel performance, and thermal hydraulics, on meshes tailored to the requirements of the respective numerical discretizations of the equations. As the equations are coupled, several fields must be transferred between single-physics solves. Projecting fields between meshes while preserving order of accuracy, conservation properties, and mapping non-overlapping geometries is a complex endeavor. This conference paper will present the transfers as implemented in MOOSE, which can handle arbitrary meshes, arbitrary mappings, conservation of integral quantities, and are made to scale with distributed simulations on both ends of the transfers. Their adequacy for advanced nuclear reactor multiphysics coupling is shown through examples and numerical studies.
With the large dataset expected from 2030 onwards by the HL-LHC at CERN, the ATLAS experiment is reaching the limits of the current data processing model in terms of traditional CPU resources based on x86_64 architectures and an extensive program for software upgrades towards the HL-LHC has been set up. The ARM CPU architecture is becoming a competitive and energy efficient alternative. Accelerators like GPUs are available in any recent HPC. In the past years ATLAS has successfully ported its full data processing and simulation software framework Athena to ARM and has invested significant effort in porting parts of the reconstruction and simulation algorithms to GPUs. We report on the successful usage of the ATLAS experiment offline and online software framework Athena on ARM and GPUs through the PanDA workflow management system at various WLCG sites. Furthermore we report on performance optimizations of the builds for ARM CPUs and the GPU integration efforts. We will discuss performance comparisons of different ARM and x86_64 architectures on WLCG resources and Cloud compute providers like GCP and AWS using ATLAS productions workflows as used in the Hep-Score23 benchmark suite.
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