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At least 523 records · Page 29

Curvature-mediated spin textures in magnetic multi-layered nanotubes

The scientific and technological exploration of artificially designed three-dimensional magnetic nanostructures opens the path to exciting novel physical phenomena, originating from the increased complexity in spin textures, topology, and frustration in three dimensions. Theory predicts that the equilibrium magnetic ground state of two-dimensional systems which reflects the competition between symmetric (Heisenberg) and antisymmetric (Dzyaloshinskii-Moriya interaction (DMI)) exchange interaction is significantly modified on curved surfaces when the radius of local curvature becomes comparable to fundamental magnetic length scales. Here, we present an experimental study of the spin texture in an 8 nm thin magnetic multilayer with growth-induced in-plane anisotropy and DMI deposited onto the curved surface of a 1.8 {\mu}m long non-magnetic carbon nanowire with a 67 nm radius. Using magnetic soft x-ray tomography the three-dimensional spin configuration in this nanotube was retrieved with about 30nm spatial resolution. The transition between two vortex configurations on the two ends of the nanotube with opposite circulation occurs through a domain wall that is aligned at an inclined angle relative to the wire axis. Three-dimensional micromagnetic simulations support the experimental observations and represent a visualization of the curvature-mediated DMI. They also allow a quantitative estimate of the DMI value for the magnetic multilayered nanotube.

Josten, Elisabeth↗

Exciton management in organic photovoltaic multi-donor energy cascades

Disclosed herein are organic photosensitive optoelectronic devices, such as organic photovoltaics, including a photoactive region, wherein the photoactive region contains an energy-cascading multilayer donor region. The energy-cascading multilayer donor region may drive exciton transfer from an anode to a dissociating interface while reducing exciton quenching, improving overlap with the solar spectrum, and minimizing polaron pair recombination, resulting in improved device performance.

Forrest, Stephen R.↗

Measurements of Magnetic Field Penetration of Materials for Superconducting Radiofrequency Cavities

Superconducting Radio Frequency (SRF) cavities used in particle accelerators are typically formed from or coated with superconducting materials. Currently high purity niobium is the material of choice for SRF cavities which have been optimized to operate near their theoretical field limits. This brings about the need for significant R&D efforts to develop next generation superconducting materials which could outperform Nb and keep up with the demands of new accelerator facilities. To achieve high quality factors and accelerating gradients, the cavity material should be able to remain in the superconducting Meissner state under high RF magnetic field without penetration of quantized magnetic vortices through the cavity wall. Therefore, the magnetic field at which vortices penetrate in a supercon- ductor is one of the key parameters of merit of SRF cavities. Techniques to measure the onset of magnetic field penetration on thin film samples need to be developed to mitigate the issues with the conventional magnetometry measurements which are strongly influenced by the film orientation and shape and edge effects. The applied magnetic field is also needed to be parallel to the one side of the superconductor to resemble the magnetic field profile at the surface of the SRF cavities operating at fundamental accelerating mode. In this work we report the development of an experimental setup called Magnetic Field Penetration (MFP) magnetometer to measure the field of full flux penetration through bulk, thin films and multilayered superconductors. Our system combines a small superconducting solenoid which can generate the magnetic field up to 500 mT at the sample surface and three Hall probes to detect the full flux penetration through the planner superconductor with 2 inch diameter. This setup was used to study alternative materials which could potentially outperform niobium, as well as SIS multilayer coatings on niobium.

Senevirathne, Iresha↗

High-data throughput reconfigurable computing platform

A reconfigurable computing platform includes a reconfigurable computing device, electro-optical transceiver, and first voltage converter disposed on a multilayer board. The electro-optical transceiver converts an optical signal at least one of to and from an electrical signal, and the electrical signal is operatively coupled to the reconfigurable computing device. The electro-optical transceiver is disposed in proximity to the reconfigurable computing device, and the first voltage converter is operatively coupled to a common voltage distributed around a periphery of the multilayer board. The first voltage converter converts the common voltage to a first operating voltage, and the first voltage converter is disposed in proximity to the reconfigurable computing device. The first operating voltage is provided to the reconfigurable computing device as a first power source. A reconfigurable computing system includes a plurality of reconfigurable computing platforms operatively coupled together using an optical signal. A corresponding method of providing a reconfigurable computing platform is also disclosed.

Tang, Shaochun↗

Analysis and Design for Sustainable Circularity of Barrier Films Used in Sheet Molding Composites Production

Sheet molding composites (SMC) are thermoset based molding compounds with a global market size of USD 2.1 billion in 2020. SMC is usually processed with multilayer barrier/carrier films to prevent emissions from volatile organic compounds (VOC). The plastic barriers are separated from SMC after the curing process and discarded. To illustrate the high consumption volume of SMC barrier/carrier films, Kohler Co., a company which uses SMC in their bath and showering product lines, alone generates over 1M lb/year of SMC barrier/carrier film waste. Therefore, high amount of SMC barrier/carrier film plastic waste creates a great opportunity for reusing, recycling, or valorization at its end of life. This can be achieved through transition from a linear to a circular supply chain design. However, this transition will not be feasible without overcoming the technical and economic barriers. This project aims to tackle this by making the film circular. Different end of life alternatives will be evaluated experimentally. The reusability of the film will be studied through applying different mechanical and solvent cleaning techniques. The operability concerns regarding the utilization of the cleaned film for long run operations will be addressed by thermally stitching the film. Pelletizing of the cleaned film will also be investigated as a viable technique for recycling or downcycling of the film as molded products. In addition to technical barriers, designing a sustainable circular supply chain for SMC carrier film products requires uncovering the collaboration opportunities between suppliers and users at different stages of the value chain to expand its use to other products. These opportunities will be investigated by finding companies willing to buy or treat the plastic film waste. Finally, the economic viability and environmental impacts of these circular design alternatives will be evaluated through techno-economic assessment (TEA) and life cycle analysis (LCA). Techno-economic and life cycle inventory data for various pathways will also be made available as one of the main outcomes of this project. Preliminary LCA results indicate that the current SMC film supply chain (base case) emits 5.81 tonne CO2 eq. and consumes 104 GJ energy per tonne of SMC film. It is estimated that alternative circular pathways result in 14-20% less CO2 emissions and 34-44% reduction in embodied energy. This project will develop a tool to analyze the circularity and sustainability of hundreds of combinations of alternatives in different life cycle stages. Users of this tool will be able to choose the best combination among these alternatives with respect to the selected economic, environmental and circularity objectives.

circular economy↗

Design of 3D Oxide–Metal Hybrid Metamaterial for Tailorable Light–Matter Interactions in Visible and Near-Infrared Region

Dielectric–metallic hybrid metamaterials exhibit extraordinary optical properties due to the light–matter interactions at the dielectric–metallic interfaces. The ability in precision control of the light–matter interactions in nanoscale is key to tailor the optical properties of hybrid metamaterials. In this work, a complex 3D framework of multilayered self-assembled BaTiO 3 (BTO)-Au hybrid thin films is demonstrated with such precision control of the light–matter interaction in nanoscale. Here, unique “bamboo-like” Au nanostructures are formed via the bilayer and trilayer stacking of BTO-Au hybrid layers with interlayers of SrTiO 3 , CeO 2 , or MgO. Different film strain states introduced by the three interlayers result in variable diameter and density of Au nanopillars. Both simulated and experimental optical data demonstrate the localized surface plasmon resonance change and hyperbolic dispersion wavelength shift in visible to near-infrared because of the effective tuning of the Au nanopillar aspect ratio and free electron density. The highly tunable optical properties along with the ferroelectric behavior and thermal robustness of the 3D hybrid film enable it to be a great candidate for multifunctional applications. This study demonstrates a unique 3D approach for precision optical property tuning and combined functionalities in oxide–metal metamaterial systems toward future integrated photonic and electronic devices.

36 MATERIALS SCIENCE↗

Comparison of DeePMD, MTP, GAP, ACE and MACE Machine‐Learned Potentials for Radiation‐Damage Simulations: A User Perspective

Accurate and efficient interatomic potentials are essential for molecular dynamics (MD) simulations of radiation damage, gas diffusion, and phase stability in complex ceramics such as LiAlO 2 , especially under extreme conditions relevant to tritium production. Here, we evaluate the performance of six machine-learned interatomic potentials (MLIPs), moment tensor potential (MTP), Gaussian approximation potential, deep potential (DeePMD), atomic cluster expansion (ACE), message-passing ACE (multilayer atomic cluster expansion (MACE) pretrained) and MACE (trained from-scratch), all trained on the same density functional theory dataset with inclusion of tritium. The MLIPs are benchmarked against traditional Buckingham and ReaxFF potentials in terms of energy accuracy, density predictions, thermal equilibration behavior, threshold displacement energy (E d ), tritium diffusivity, and computational cost. Among the models, MTP shows the best overall balance between efficiency and accuracy, with low force and energy errors and realistic E d values for Li and Al. The ACE and MACE (pretrained and trained from scratch) models exhibit high E d (>200 eV) and unphysical pair interactions. DeePMD underestimates Ed due to overly repulsive behavior even at equilibrium distances. All models over-estimate tritium diffusion but the pretrained MACE model behaves well during tritium-diffusion simulations up to 500 K, maintaining diffusivities in the physically consistent 10 −11 m 2 /s range. Finally, we quantify the computational cost of each potential in large-scale atomic/molecular massively parallel simulator, finding that only MTP is more efficient than traditional empirical potentials, while others are significantly more expensive. These findings explain the trade-offs between accuracy and computational cost in MLIP development and provide essential guidance for use in high-throughput radiation damage and gas diffusion simulations in nuclear ceramics.

74 ATOMIC AND MOLECULAR PHYSICS↗

Estimation of the Surface Fluxes for Heat and Momentum in Unstable Conditions with Machine Learning and Similarity Approaches for the LAFE Data Set

Abstract Measurements of three flux towers operated during the land atmosphere feedback experiment (LAFE) are used to investigate relationships between surface fluxes and variables of the land–atmosphere system. We study these relations by means of two machine learning (ML) techniques: multilayer perceptrons (MLP) and extreme gradient boosting (XGB). We compare their flux derivation performance with Monin–Obukhov similarity theory (MOST) and a similarity relationship using the bulk Richardson number (BRN). The ML approaches outperform MOST and BRN. Best agreement with the observations is achieved for the friction velocity. For the sensible heat flux and even more so for the latent heat flux, MOST and BRN deviate from the observations while MLP and XGB yield more accurate predictions. Using MOST and BRN for latent heat flux, the root mean square errors (RMSE) are 107 Wm $$^{-2}$$ - 2 and 121 Wm $$^{-2}$$ - 2 , respectively, as well as the intercepts of the regression lines are $$\approx 110$$ ≈ 110 Wm $$^{-2}$$ - 2 . For the ML methods, the RMSEs reduce to 31 Wm $$^{-2}$$ - 2 for MLP and 33 Wm $$^{-2}$$ - 2 for XGB as well as the intercepts to just 4 Wm $$^{-2}$$ - 2 for MLP and $$-1$$ - 1 Wm $$^{-2}$$ - 2 for XGB with slopes of the regression lines close to 1, respectively. These results indicate significant deficiencies of MOST and BRN, particularly for the derivation of the latent heat flux. In fact, in contrast to the established theories, feature importance weighting demonstrates that the ML methods base their improved derivations on net radiation, the incoming and outgoing shortwave radiations, the air temperature gradient, and the available water contents, but not on the water vapor gradient. The results imply that further studies of surface fluxes and other turbulent variables with ML techniques provide great promise for deriving advanced flux parameterizations and their implementation in land–atmosphere system models.

54 ENVIRONMENTAL SCIENCES↗

Single molecule characterization of anomalous transport in a thin, anisotropic film

Here, the diffusion of small, charged molecules incorporated in an anisotropic polyelectrolyte multilayers (PEMs) was tracked in three dimensions by combining single-molecule fluorescence localization (to characterize lateral diffusion) with Förster resonance energy transfer (FRET) between diffusing molecules and the supporting surface (to measure diffusion in the surface-normal direction). Analysis of the surface-normal diffusion required model-based statistical analysis to account for the inherently noisy FRET signal. Combining these distinct single-molecule methods, which are inherently sensitive to different length scales, permitted simultaneous characterization of severely anisotropic diffusion, which was more than three orders of magnitude slower in the surface-normal direction. We hypothesize that the anomalously slow surface-normal diffusion was related to the periodic distribution of charge in the PEM, which created electrostatic barriers. The motion was strongly subdiffusive, with anomalous temporal scaling exponents in lateral and normal directions, suggesting a connection to the transient, random fractal conformation of polymer chains in the film’s matrix.

36 MATERIALS SCIENCE↗

Refractory-based thermal energy storage for industrial process heat: one-dimensional modeling, control, and optimization

The variable and weather-dependent output of wind and solar power plants present a substantial challenge for planning and operating electricity-systems, particularly in the absence of cost-effective and dispatchable energy storage technologies. This study investigates a high-temperature, electrically heated, refractory-based thermal energy storage (RTES) system that stores electrical energy as sensible heat in dense ceramic bricks over the 950–1800 °C range. The stored heat can be discharged as a controlled hot-gas stream for industrial heating, fuel substitution in high-temperature processes, or electricity generation. The main novelty is a comprehensive modelling, control, mapping, and optimization framework that integrates one-dimensional transient gas–solid heat transfer, fan-assisted discharge, bypass-flow regulation, reheating logic, fan-power evaluation, insulation-loss assessment, and genetic-algorithm-based design optimization. The model uses feedback from outlet temperature and delivered power to regulate discharge, while a two-stage genetic algorithm optimizes brick-channel geometry, gas-flow operation, and multilayer insulation thicknesses. Storage capacities below 50 MWh and discharge powers of 5–30 MW are analyzed to evaluate hold time, thermal delivery, fan-power penalty, heat loss, state-of-charge evolution, and indicative capital cost. Results demonstrate that optimized and well-insulated refractory-based thermal energy storage units can provide stable, efficient, and repeatable heat delivery over multiple discharge cycles. The generated performance and cost maps support modular refractory thermal energy storage as a practical option for large-scale integration of wind and solar generation and for high-temperature industrial process heat.

25 ENERGY STORAGE↗

From atomistic models to machine learning: Predictive design of nanocarbons under extreme conditions

The formation of technologically valuable nanocarbon structures under extreme conditions, such as those produced during high-explosive detonations, remains poorly understood but holds significant potential for the development of controlled synthesis pathways. While detonation shockwaves provide the high-pressure, high-temperature environment required for nanodiamond formation, subsequent cooling and decompression dictate whether the diamond phase is preserved or transformed into other nanocarbon structures. Here, in this study, we employ GPU-accelerated reactive molecular dynamics (ReaxFF) simulations to investigate the graphitization and structural remodeling of detonation nanodiamond under nonlinear quench and pressure-release trajectories. We further investigate how the initial nanodiamond morphology; cuboctahedral, octahedral, or hexagonal prism influences the resulting transformation products. Evolution of nanostructure, allotrope (via simulated x-ray diffraction), carbon hybridization, and ring statistics are tracked during a two-stage quench from 5000 K to 60 GPa. Rapid cooling combined with slow decompression optimizes cubic diamond retention, whereas slow cooling with rapid pressure release promotes surface-to-core graphitization, producing concentric sp 2 -hybridized layers and hollowed inner shells. Octahedral nanodiamonds evolve into carbon nano-onions, initially forming bucky diamonds that progressively transform into fully sp 2 -hybridized structures, while hexagonal prisms preferentially form parallel-stacked graphite layers resembling carbon dots. Transient hexagonal diamond (lonsdaleite) emerges as an interfacial phase, suggesting potential reversibility in the shock-induced graphite-to-diamond transformation pathway transformation route. To extend predictive capabilities, we trained machine learning (ML) regressors on over 10 5 node-hours of molecular dynamics (MD) trajectories. A multilayer perceptron (MLP) model reliably predicts the number of graphitized layers from temperature–pressure trajectories with a coefficient of determination (R 2 ) exceeding 0.90. This high predictive fidelity enables efficient, high-throughput mapping of the synthesis parameter space for optimized graphitization outcomes. Collectively, morphological control combined with optimized quench–decompression conditions promote the selective synthesis of nanocarbon allotropes. This work establishes a data-driven framework for the rational, a priori design of carbon nanomaterials for applications in energy storage, sensing, and biomedicine.

Detonation nanodiamond remodeling↗

In-service corrosion and grain boundary oxidation in neutron-irradiated 316 stainless steel baffle-former bolts

Reactor core internal components such as baffle-former bolts (BFBs) are subjected to significant mechanical stress, corrosive environment, and neutron irradiation from the reactor core during the plant operation. Over the long operation period, these conditions lead to potential degradation and of the bolts. In this work, characterization was performed on the oxidized surface of stainless steel BFBs harvested from a commercial pressurized water reactor (PWR) after 40 years of operation. The analysis shows that a complex multilayered surface oxide with six identified layers formed that is different from 2-layer structure commonly observed in model experiments. The oxide varies by composition – predominantly Fe, Cr, and Ni, grain size, and phase, and has features resembling both unirradiated and radiation/ corrosion experiments likely due to the low radiation flux compared to ion-irradiation or the test reactor radiation. In addition, grain boundary oxidative attack featured a pathway for Fe and other elements to move from the metal matrix to the outermost oxide. In conclusion, the results help assess PWR lifetime extension, put into context previous experimental studies, and provide input for designing experiments combining radiation and corrosion effects.

Baffle-former bolt↗

Methane liquefaction with an active magnetic regenerative refrigerator

This manuscript reports liquefaction of methane using an active magnetic regenerative refrigerator (AMRR). The AMRR used to cool from 285 K to 135 K has two identical regenerators fabricated with adjacent layers of four ferromagnetic refrigerants, each with sequentially lower Curie temperatures and lesser masses from hot to cold temperatures. The dual multilayer regenerators were assembled in opposition with a single cold region between them. For this set of experiments equal mass of helium gas was pumped through all layers of the regenerators during the two flow steps of the four-step AMR cycle. After successfully reaching 135 K, a compact condensing coil-fin tube heat exchanger (HEX) with a small storage vessel was mounted in the cold region of the dual regenerator assembly to be cooled during the hot-to-cold helium flow from alternatively demagnetized regenerators. The cold HEX was used to cool and liquefy a process stream of methane gas supplied at 295 K and different pressures in different runs. Further, by measuring time to liquefy a known volume of methane at three different pressures, cooling powers of the AMRR as a function of temperature were determined. The resultant data were compared to those predicted by the AMRR performance model. Conclusions from these experiments and suggestions for future work are presented.

32 ENERGY CONSERVATION, CONSUMPTION, AND UTILIZATI↗

Selective concentration of multivalent cations via electrodialysis through tandem membranes

Selective electrodialysis is attractive for recovering and recycling valuable ions. However, most studies in this field focus on membranes that are selective for monovalent ions. Multivalent cations preferentially partition into cation-exchange membranes, but low mobilities and concentration polarization limit electrodialysis selectivities for these cations. This work employs electrodialysis through an “in-series” combination of a Nafion membrane and a multilayer polyelectrolyte film (MPF)-coated Nafion membrane to concentrate and isolate La 3+ or Mg 2+ from monovalent ions. The bare Nafion membrane gives a La 3+ /Na + selectivity up to 4 (depending on conditions), which enables concentration of La 3+ with a high current efficiency. The MPF-coated membrane allows selective passage of Na + while rejecting La 3+ to increase the purity of the concentrated multivalent cation. For example, the concentration of La 3+ in the accumulation solution can reach 9 times its original concentration in the feed solution with a purity of 93 mol% (99 wt%) when starting with equimolar mixtures of NaNO 3 and La(NO 3 ) 3 . This study examines how the separation varies with the type of polyelectrolyte, the applied voltage, and the composition of feed, accumulation, and cathode solutions. Here, a high nitric acid concentration (0.5 M) in the cathode compartment allows monovalent anions to pass through the MPF-coated Nafion membrane to maintain the electroneutrality of the accumulation solution. With a low acid concentration (0.04 M) in the cathode chamber, water splitting occurs at the MPF-coated membrane and La(OH) 3 precipitates.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

High temperature nanoindentation of Cu–TiN nanolaminates

Here, we examined the high temperature indentation response of physical vapor deposited Cu–TiN multilayered nanocomposites with layer thicknesses ranging from 5 nm to 200 nm. A decrease in hardness with increasing temperature was observed, along with a strong correlation between the hardness and the nanometer-level TiN grain sizes, rather than layer thickness. The apparent activation energies calculated from the high temperature indentation experiments indicated that, for all but the smallest layer thicknesses, the deformation of copper in the nanolaminates dominate the plastic response in these composites. In the finest layer thicknesses, a decrease in the apparent activation energy value indicated possible co-deformation of Cu and TiN.

36 MATERIALS SCIENCE↗

Machine learning maximized Anderson localization of phonons in aperiodic superlattices

Nanostructuring materials to achieve ultra-low lattice thermal conductivity has proven to be extremely attractive for numerous applications such as thermoelectric energy conversion. Anderson localization of phonons due to aperiodicity can reduce thermal conductivity in superlattices, but the lower limit of thermal conductivity remains elusive due to the prohibitively large design space. In this work, we demonstrate that an intuition-based manual search for aperiodic superlattice structures (random multilayers or RMLs) with the lowest thermal conductivity yields only a local minimum, while a genetic algorithm (GA) based approach can efficiently identify the globally minimum thermal conductivity by only exploring a small fraction of the design space. Our results show that this minimum value occurs at an average RML period that is, surprisingly, smaller than the period corresponding to the minimum SL thermal conductivity. Interestingly, above this critical period, scattering of incoherent phonons at interfaces is less, whereas below this period, the room for randomization becomes less, thus putting more coherent phonons out of Anderson localization and causing increased thermal conductivity. Moreover, the lower limit of the thermal conductivity occurs at a moderate rather than maximum randomness of the layer thickness. Our machine learning approach demonstrates a general process of exploring an otherwise prohibitively large design space to gain non-intuitive physical insights.

42 ENGINEERING↗

Nanoscale phase transition in impact indented Mo/Cu thin films

The study reveals a size effect in deformation mechanisms via unique structural transitions in sputter deposited fcc/bcc nanolayers under high strain rate impact nanoindentation as layer thickness is reduced from around 100-200 nm to around 5 nm. Here, the indented 5 nm Cu/5 nm Mo multilayer films characterized via cross-sectional scanning/transmission electron microscopy have revealed a phase transition in the 5 nm thick Mo layers from BCC to a coherent metastable FCC structure and fine deformation twins in the 5 nm Cu layers inside a shear band that is approximately 500 nm long and inclined to the layer interfaces. In contrast, thicker layers, 80 nm Cu/180 nm Mo, show different deformation behavior with uneven layer thickness reduction, shearing of Cu layers, and bending of the columnar Mo grains beneath the indentation without any sign of shear band and localized phase transformation.

36 MATERIALS SCIENCE↗

Maximized Hole Trapping in a Polystyrene Transistor Dielectric from a Highly Branched Iminobis(aminoarene) Side Chain

We synthesized highly branched and electron donating side chain subunits and attached them to polystyrene (PS) used as a dielectric layer in a pentacene field effect transistor. The influence of these groups on dielectric function, charge retention and threshold voltage shifts (ΔV th ) depending on their positions in dielectric multilayers was determined. We compared the observations made on an N-perphenylated iminobisaniline side chain with those from the same side chains modified with ZnO nanoparticles and with an adduct formed from tetracyanoethylene (TCNE). We also synthesized an analogue in which six methoxy groups are present instead of two amine nitrogens. At 6 mol % side chain, hopping transport was sufficient to cause shorting of the gate, while at 2 mol %, charge trapping was observable as transistor threshold voltage shifts (ΔV th ). Here, we created three types of devices: with the substituted PS layer as single layer dielectric, on top of a crosslinked PS layer but in contact with the pentacene (bilayers), and sandwiched between two PS layers in trilayers. Particularly large bias stress effects and ΔV th , larger than the hexamethoxy and previously studied dimethoxy analogs, were observed in the second case and the effects increased with the increasing electron donating properties of the modified side chains. The highest ΔV th was consistent with a majority of the side chains stabilizing trapped charge. Trilayer devices showed decreased charge storage capability compared to previous work in which we used less donating side chains but in higher concentrations. The ZnO and TCNE modifications resulted in slightly more and less negative ΔV th , respectively, when the side chain polystyrene was not in contact with the pentacene and isolated from the gate electrode. The results indicate a likely maximum combination of molecular charge stabilizing activity and side chain concentration that still allows gate dielectric function.

36 MATERIALS SCIENCE↗