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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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For carbon dots, careful purification and electronic structure calculations facilitate learning about the origin of optical properties.
Hollow metal halide perovskites, while a relatively recent discovery, have already been shown to push the boundaries of tuneability within an inherently limited compositional space. Here, we further expand our knowledge of these complex materials demonstrating the ability to control optical properties and local structure, notably lone-pair induced off-centering. We focus on the mixed metal FA 1−x en x Pb η−y Sn y Br 3 hollow perovskites. These compounds have wide ranging optical gaps from 1.9 eV (deep red) to 2.6 eV (light yellow), combining the anomalous bandgap red-shifting of Pb/Sn mixing with the blue-shifting effects of the organic substitution. Average and local structural studies employing single crystal X-ray diffraction and total X-ray scattering pair distribution function analyses respectively suggest strong incoherent off-centering distortions that are locally correlated with Sn concentration. The inclusion of ethylenediammonium dications appears to regulate metal off-centering, opening new opportunities of research into this phenomenon.
Indolicidin, a cationic antimicrobial peptide, interacts with lipid bilayers through electrostatic and hydrophobic interactions, disrupting microbial membranes. We investigated the depth-dependent localization of gold-nanoparticle-labeled indolicidin in a supported model membrane using X-ray fluorescence standing wave (SWXF) analysis. Liposomes composed of DMPC and DMPG were incubated with indolicidin labeled at its C-terminus with a 1.8 nm gold nanoparticle, then deposited onto a Si/Mo multilayer substrate via vesicle bursting. SWXF measurements revealed that at low peptide incubation concentrations (2–5 μM), gold-nanoparticle-labeled indolicidin remains primarily associated with the bilayer's outer leaflet. At higher concentrations (10 μM), the peptide penetrates deeper into the bilayer, with the labeled C-terminal region either localizing near the membrane's hydrophobic core or inducing membrane breakup. In conclusion, these findings suggest a concentration-dependent insertion mechanism.
Electrochemical conversion of dissolved CO 2 in bicarbonate electrolytes, i.e., bicarbonate electrolysis, offers distinct advantages over gas diffusion electrode systems by enabling direct utilization of the CO 2 capture electrolyte while bypassing the energy-intensive CO 2 release step. However, bicarbonate electrolysis faces challenges such as CO 2 mass-transfer limitation, local pH-driven CO 2 depletion, and high cathodic potentials. The higher potential often causes catalyst surface reorganization, leading to a gradual loss of active sites and variations in selectivity during CO 2 reduction. Here, we report a directed, in situ activation and regeneration method that allows precatalysts to equilibrate under dynamic (pulsed) electrolysis conditions. We demonstrate in situ activation of a scalable Cu 2 O/Cu mesh that, under short-width (t = 4 s) pulsed electrolysis, provides stable mixed oxidation states of Cu, favoring the formation of an ethanol-rich crude mixture. The pulsed electrolysis waveform, consisting of six distinct segments, is tuned to form Cu + oxides, which are then reduced to generate local alkaline conditions favoring C–C coupling. This synergistic effect results in FEs of 73% for C2+ products and 39% for ethanol at an applied current density of −150 mA cm −2 and a cathodic potential of −1.45 V (vs. RHE). The overall half-cell energy efficiency is ∼30% for C 2+ products. The in situ Raman experiments confirm the role of pCO 2 R in dynamically regenerating Cu+-containing surface species during pulsed operation, thereby steering selectivity towards C 2+ products. A comprehensive multiscale, multiphysics model is developed to investigate the dynamic behavior of copper surface species (Cu, Cu + , and Cu 2+ ) and local microenvironmental conditions during the pCO 2 R. The results reveal that the coexistence of different copper oxidation states, especially the Cu+ intermediate, is critical in steering selectivity towards multicarbon (C 2+ ) products. The dynamic modulation of surface redox states via tailored pulsing strategies favors C–C coupling pathways by inducing localized alkaline conditions and stabilizing reactive intermediates. This work establishes a predictive modeling platform that links pulse waveform design with mechanistic insights into catalyst state evolution and product selectivity. Overall, this study provides valuable insights into the synergistic effect of in situ activation of pre-catalysts and pulsed electrolysis for higher selectivity towards C 2+ products.
Erbium-doped TiO 2 materials are promising candidates for advancing quantum technologies, necessitating a thorough understanding of their electronic and crystal structures to tailor their properties and enhance coherence times. This study explored epitaxial erbium-doped rutile TiO 2 films deposited on r-sapphire substrates using molecular beam epitaxy. Photoluminescence excitation spectroscopy demonstrated decreasing photoluminescence lifetimes with erbium doping, indicating limited optical coherence times. Lattice distortions associated with Er 3+ were probed by x-ray absorption spectroscopy, indicating that erbium primarily occupies Ti 4+ sites and influences oxygen vacancies. Significant lattice distortions in the higher-order shells and apparent full coordination around erbium suggest that additional defects are likely prevalent in these regions. These findings indicate that defects contribute to limited coherence times by introducing alternative decay pathways, leading to shorter photoluminescence lifetimes.
Here, in this paper, we demonstrate area-selective crystallization of amorphous Si into tunable crystal orientations enabled by atomic imprint crystallization (AIC), where an amorphous Si layer is crystallized by solid phase epitaxy (SPE) from an externally impressed single-crystalline Si template. Using micro-patterned single-crystalline Si templates, a limited area of an amorphous Si film, where the film surface and patterned template surface are in contact, is crystallized via SPE to create an array of crystallographically aligned dots embedded in amorphous matrix. Combining AIC from the top surface and conventional SPE from the substrate, we demonstrate the fabrication of an array of crystalline dots embedded in single-crystalline matrix with tunable in-plane rotation angle. The results indicate the high tunability of the crystallization process enabled by AIC, allowing precise control of crystallographic properties of thin films with area-selectivity; such capability opens opportunities for the design of new materials for a wide range of applications in materials science.
Qualitative and quantitative orbital properties such as bonding/antibonding character, localization, and orbital energies are critical to how chemists understand reactivity, catalysis, and excited-state behavior. Despite this, representations of orbitals in deep learning models have been very underdeveloped relative to representations of molecular geometries and Hamiltonians. Here, we apply state-of-the-art equivariant deep learning architectures to the task of assigning global labels to orbitals, namely energies characterizations, given the molecular coefficients from Hartree–Fock or density functional theory. The architecture we have developed, the Cartesian Equivariant Orbital Network (CEONET), shows how molecular orbital coefficients are readily featurized as equivariant node features common to all graph-based machine-learned potentials. We find that CEONET performs well at predicting difficult quantitative labels such as the orbital energy and orbital entropy. Furthermore, we find that the CEONET representation provides an intuitive latent space for differentiating orbital character for the qualitative assignment of e.g. bonding or antibonding character. In addition to providing a useful representation for further integrating deep learning with electronic structure theory, we expect CEONET to be useful for automatizing and interpreting the results of advanced electronic structure methods such as complete active space self-consistent field theory. In particular, the ability of CEONET to infer multireference character via the orbital entropy paves the way toward the machine-learned selection of active spaces.
Modern wide-field time-domain surveys facilitate the study of transient, variable and moving phenomena by conducting image differencing and relaying alerts to their communities. Machine learning tools have been used on data from these surveys and their precursors for more than a decade, and convolutional neural networks (CNNs), which make predictions directly from input images, saw particularly broad adoption through the 2010s. Since then, continually rapid advances in computer vision have transformed the standard practices around using such models. It is now commonplace to use standardized architectures pre-trained on large corpora of everyday images (e.g., ImageNet). In contrast, time-domain astronomy studies still typically design custom CNN architectures and train them from scratch. Here, we explore the effects of adopting various pre-training regimens and standardized model architectures on the performance of alert classification. We find that the resulting models match or outperform a custom, specialized CNN like what is typically used for filtering alerts. Moreover, our results show that pre-training on galaxy images from Galaxy Zoo tends to yield better performance than pre-training on ImageNet or training from scratch. We observe that the design of standardized architectures are much better optimized than the custom CNN baseline, requiring significantly less time and memory for inference despite having more trainable parameters. On the eve of the Legacy Survey of Space and Time and other image-differencing surveys, these findings advocate for a paradigm shift in the creation of vision models for alerts, demonstrating that greater performance and efficiency, in time and in data, can be achieved by adopting the latest practices from the computer vision field.
Four-dimensional scanning transmission electron microscopy (4D-STEM) is powerful for rapidly characterizing arrays of nanoparticles produced via high-throughput synthesis. However, such 4D-STEM datasets typically contain thousands of nanoparticles, each characterized by thousands of diffraction patterns spatially distributed across the nanoparticle, necessitating efficient and comprehensive analysis. We propose an end-to-end segmentation framework to automatically segment each nanoparticle into regions with distinct composition/orientation of crystal grains, using only the 4D-STEM data. Bragg disk information is extracted in a physics-informed manner from the diffraction patterns at each spatial location and combined with the real space coordinates to form feature vectors. These feature vectors are then used as inputs to a Gaussian mixture model (GMM) to segment the nanoparticle into distinct regions. We also develop two visualization tools based on the GMM outputs to infer the interface transition and the degree of superposition. Our framework comprehensively integrates machine learning tools and physics knowledge, and provides a basis for substantially compressing enormous 4D-STEM datasets, e.g., by replacing the full 4D-STEM dataset for each nanoparticle with only a single set of Bragg disk features for each distinct crystal grain identified in the nanoparticle. In this article, we demonstrate the power of our framework by presenting results for real, complex datasets.
Radio haloes are diffuse synchrotron sources that trace the turbulent intracluster medium (ICM) of galaxy clusters. However, their origin remains unknown. Two main formation models have been proposed: the hadronic model, in which relativistic electrons are continuously injected by cosmic-ray protons; and the leptonic turbulent re-acceleration model, where cluster mergers re-energize electrons in situ. A key discriminant between the two models would be the existence of ultra-steep spectrum radio haloes (USSRHs), which can only be produced through turbulent re-acceleration. Here, we report the discovery of an USSRH in the galaxy cluster SPT-CLJ2337–5942 at redshift $z = 0.78$ in the MeerKAT-South Pole Telescope 100 deg$^2$ UHF (0.58–1.09 GHz) survey. This discovery is noteworthy for two primary reasons: it is the highest redshift USSRH system to date; and the close correspondence of the radio emission with the thermal ICM as traced by Chandra X-ray observations, further supporting the leptonic re-acceleration model. The halo is underluminous for its mass, consistent with a minor merger origin, which produces steep-spectrum, lower luminosity haloes. This result demonstrates the power of wide-field, high-fidelity, low-frequency ($\lesssim 1$ GHz) surveys like the MeerKAT-SPT 100 deg$^2$ programme to probe the origin and evolution of radio haloes over cosmic time, ahead of the Square Kilometre Array.
We introduce an array-scalable, magnon-based detector to search for the spin-dependent interactions of electron-coupled axion dark matter with mass in the 1−100 μeV range. These axions can excite single magnons in magnetic targets, such as yttrium iron garnet (YIG) spheres, which are subsequently sensed by the detector. In our concept, this sensing is implemented by coupling the magnons in the YIG spheres to magnetic-field-resilient single-electron charge-qubits, whose state is then interrogated with a quantum nondemolition measurement. Using standard superconducting fabrication techniques, it is possible to integrate many YIG sphere-qubit sensors, forming a large detector array. We outline the detector design and operation for our concept, and determine its sensitivity to axion dark matter. We find that using available technology can already exceed the sensitivity of previous ferromagnetic haloscopes, and further improvements in performance would search for electron-coupled axion dark matter in unexplored parameter space.
There are strong arguments that quantum mechanics may be nonlinear in its dynamics. A discovery of nonlinearity would hint at a novel understanding of the interplay between gravity and quantum field theory, for example. As such, experiments searching for potential nonlinear effects in the electromagnetic sector are important. Here, in this study, we outline such an experiment, consisting of a stream of random bits (which were generated using Rigetti’s Aspen-M-3 chip) as input to an rf signal generator coupled to a cryogenic detector. Projective measurements of the qubit state, which is originally prepared in an equal superposition, serve as the random binary output of a signal generator. Thereafter, spectral analysis of the rf detector would yield a detectable excess signal predicted to arise from such a nonlinear effect. A comparison between the projective measurements of the quantum bits vs the classical baseline showed no power excess. This sets a new limit on the electromagnetic nonlinearity parameter |ε| ⪅ 1.15 x 10 -12 , at a 90.0% confidence level. This is the most stringent limit on nonlinear quantum mechanics thus far and an improvement by nearly a factor of 50 over the previous experimental limit.
We report measurements of anisotropic triple-𝑞 charge density wave (CDW) fluctuations in the transition metal dichalcogenide 1𝑇−TiSe 2 over a large volume of reciprocal space with x-ray diffuse scattering. Above the transition temperature, 𝑇 CDW , the in-plane diffuse scattering is marked by ellipses which reveal that the in-plane fluctuations are anisotropic. In addition, the out-of-plane diffuse scattering is characterized by rodlike structures which indicate that the CDW fluctuations in neighboring layers are largely decoupled. Furthermore, our analysis of the diffuse scattering line shapes and orientations suggests that the three charge density wave components contain independent phase fluctuations with a hierarchy of length scales, leading to intricate fluctuation patterns that go beyond the conventional 2D-to-3D crossover picture.
A quadrupole wiggler consisting of a row of alternating-polarity permanent magnet-excited quadrupoles is used in a collinear wakefield accelerator under development at Argonne National Laboratory. Fine translational and angular adjustment mechanisms are implemented in all quadrupoles to obtain a better than 1−μm precision in the alignment of quadrupole wiggler assemblies. The quadrupole’s magnetic and mechanical designs are described. Two wiggler prototypes were fabricated, aligned, and characterized performing pulsed wire magnetic measurements. The sensitivity of the quadrupole wiggler alignment to the ambient temperature was measured.
Magnetotransport measurements of Pr4Ni3O10 single crystals performed under externally applied pressures up to 73 GPa in diamond anvil cells with either KBr or Nujol oil as pressure media yield signatures of superconductivity with a maximum onset temperature of approximately 31 K. True zero resistance was not observed, consistent with a nonpercolating superconducting volume fraction. Magnetization measurements provided corroborating evidence of superconductivity, with a pressure-dependent diamagnetic signal occurring below the onset temperature, and an estimate from the absolute value of the susceptibility suggests a superconducting volume fraction on the order of 10%. We observe sample to sample variations in the magnitude and pressure dependence of 𝑇𝑐 as well as a dependence on the configuration of electrical contacts on a given sample. Possible causes of this behavior may be significant inhomogeneities in the pressure and/or damage to the samples induced by the pressure media as well as inhomogeneities in the crystals themselves. The results imply that our as-grown Pr4Ni3O10 single crystals are not bulk superconductors but that there is a minority structure present within the crystals that is indeed superconductin
Here, we have conducted a comprehensive investigation into the magnetic properties of the chiral multiferroic material CoTeMoO 6 . In contrast with the previous claim of canted antiferromagnetic order with ferromagnetic components [Y. Doi et al., J. Solid State Chem. 182, 3232 (2009)], our investigation reveals an antiferromagnetic ground state with compensated moments, providing an interesting platform for exploring exotic material properties. Through careful measurements of magnetization under a series of applied fields, we demonstrate that there exist two sequential field-induced magnetic transitions in CoTeMoO 6 , with one occurring at 𝐻 𝑐1 =460 Oe along the 𝑎 axis, and the other at 𝐻 𝑐2 =1.16 T with the field along the 𝑏 axis. The values of 𝐻 𝑐1 and 𝐻 𝑐2 exhibit strong angular dependence and diverge with different rates as the applied field is rotated 90 ° within the 𝑎𝑏 plane. This reflects the distinct nature of these transitions, which is further supported by the different critical behavior of 𝐻 𝑐1 and 𝐻 𝑐2 , characterized by the values of 𝛾, in the function of 𝐻 𝑐 =𝐻 0 (1−𝑇/𝑇 𝑐 ) 𝛾 . Furthermore, we have demonstrated that there exist structural and magnetic twin domains in CoTeMoO 6 that strongly affect the experimental measurement of their macroscopic properties. Intriguingly, these twin domains can be related to the orthorhombicity/chirality of the crystal structure with the space group 𝑃2 1 2 1 2. We further explored the magnetic and structural domains with uniaxial pressure and polarized light microscopy. Our results suggest that CoTeMoO 6 could be used as a unique platform for investigating the intriguing physics involving intertwined degrees of freedom. The tunability of the underlying domain distribution and its strong anisotropy could also be useful for developing functional devices and applications.
Unitary 𝑡-designs are distributions on the unitary group whose first 𝑡 moments appear maximally random. Previous work has established several upper bounds on the depths at which certain specific random quantum circuit ensembles approximate 𝑡-designs. Here we show that these bounds can be extended to any fixed architecture of Haar-random two-site gates. This is accomplished by relating the spectral gaps of such architectures to those of one-dimensional brickwork architectures. Our bound depends on the details of the architecture only via the typical number of layers needed for a block of the circuit to form a connected graph over the sites. When this quantity is bounded, the circuit forms an approximate 𝑡-design in at most linear depth. We give numerical evidence for a stronger bound that depends only on the number of connected blocks into which the architecture can be divided. We also give an implicit bound for nondeterministic architectures in terms of properties of the corresponding distribution over fixed architectures.
Quantifying the carbon (C) uptake of Miscanthus × giganteus ( M × g ) in both aboveground and belowground structures (e.g., net primary productivity (NPP)) and differences among methodological approaches is crucial. Our objectives were to directly measure Mxg NPP and evaluate the effects of nitrogen application, location, and belowground biomass sampling methods. We hypothesize that increased nitrogen application increases the overall NPP of M × g and that quantifying rhizome biomass using excavations will produce the lowest variability between replicates. We collected biomass from mature M × g stands from three locations in Iowa with three nitrogen application rates and one site in Illinois. We destructively sampled at two time points, when rhizome mass is anticipated to be at a minimum (initial) and anticipated to be at its maximum (peak). Biomass was collected from 1 × 1 m quadrats in which one in-clump and one beside-clump cores were collected and then excavated to 30 cm depth to extract all rhizomes. We found that aboveground M × g NPP ranged from 15.4 Mg DM ha –1 year –1 to 36.4 Mg DM ha –1 year–1 and belowground M × g NPP ranged from 4.4 Mg DM ha –1 year –1 to 19.6 Mg DM ha –1 year –1 . M × g NPP varied across sites, fertilization, and calculation assumptions. Aboveground NPP (yield) was on average 68.7% of the total NPP. Root-to-shoot ratios at peak biomass decreased with nitrogen application rate, from an average of 1.9 for 0 N plots to 0.89 for 224 N fertilized plots. There was more variation in core data than from excavations; however, when in-clump and beside-clump cores were averaged together, core and excavation averages were not different. Overall, these results show that the range of mature M × g NPP is driven by aboveground productivity, influenced by nitrogen application and site. Our results provide useful data to constrain agro-ecosystem models and provide crucial insights for future perennial belowground sampling.