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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 793 records · Page 44
All sourcesNASA NTRSDOE OSTI
DOE OSTI2020

Hydration structure and water exchange kinetics at xenotime–water interfaces: implications for rare earth minerals separation

Hydration of surface ions gives rise to structural heterogeneity and variable exchange kinetics of water at complex mineral–water interfaces. In this work, we employ ab initio molecular dynamics (AIMD) simulations and water adsorption calorimetry to examine the aqueous interfaces of xenotime, a phosphate mineral that contains predominantly Y 3+ and heavy rare earth elements. Consistent with natural crystal morphology, xenotime is predicted to have a tetragonal prismatic shape, dominated by the {100} surface. Hydration of this surface induces multilayer interfacial water structures with distinct OH orientations, which agrees with recent crystal truncation rod measurements. The exchange kinetics between two adjacent water layers exhibits a wide range of underlying timescales (5–180 picoseconds), dictated by ion–water electrostatics. Adsorption of a bidentate hydroxamate ligand reveals that {100} xenotime surface can only accommodate monodentate coordination with water exchange kinetics strongly depending on specific ligand orientation, prompting us to reconsider traditional strategies for selective separation of rare-earth minerals.

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

A combined SECM and electrochemical AFM approach to probe interfacial processes affecting molecular reactivity at redox flow battery electrodes

Redox flow batteries are attractive technologies for grid energy storage since they use solutions of redox-active molecules that enable a superior scalability and the decoupling of power and energy density. However, the reaction mechanisms of the redox active components at RFB electrodes are complex, and there is currently a pressing need to understand how interfacial processes impact the kinetics and operational reversibility of RFB systems. Here, we developed a combined electrochemical imaging methodology rooted in scanning electrochemical microscopy (SECM) and atomic force microscopy (AFM) for exploring the impact of electrode structure and conditioning on the electron transfer properties of model redox-active dialkoxybenzene derivatives, 2,5-di-tert-butyl-1,4-bis(2-methoxyethoxy)benzene (C1) and 2,3-dimethyl-1,4-dialkoxybenzene (C7). Using AFM and secondary-ion mass spectrometry (SIMS), we observed the formation of interfacial films with distinct mechanical properties compared to those of cleaved graphitic surfaces, and exclusively during reduction of electrogenerated radical cations. These films had an impact on the median rate and distribution of the electron transfer rate constant at the basal plane of multilayer and single layer graphene electrodes, displaying kinetically-limited values that did not yield the activation expected per the Butler–Volmer model with a transfer coefficient ~0.5. These changes were dependent on redoxmer structure: furthermore, SECM showed strong attenuation of C7 kinetics by a surface layer on MLG and SLG, while C1 kinetics were only affected by SLG. SECM and AFM results together show that these limiting films operate exclusively on the basal plane of graphite, with the edge plane showing a relative insensitivity to cycling and operation potential. Ultimately, this integrated electrochemical imaging methodology creates new opportunities to understand the unique role of interfacial processes on the heterogeneous reactivity of redoxmers at electrodes for RFBs, with a future role in elucidating phenomena at high active concentrations and spatiotemporal variations in electrode dynamics.

25 ENERGY STORAGE↗
DOE OSTI2021

Interplay between microstructure, defect states, and mobile charge generation in transition metal dichalcogenide heterojunctions

Two-dimensional transition metal dichalcogenides (2D-TMDCs) have gained attention for their promise in next-generation energy-harvesting and quantum computing technologies, but realizing these technologies requires a greater understanding of TMDC properties that influence their photophysics. To this end, we discuss here the interplay between TMDC microstructure and defects with the charge generation yield, lifetime, and mobility. As a model system, we compare monolayer-only and monolayer-rich MoS 2 grown by chemical vapor deposition, and we employ the TMDCs in Type-II charge-separating heterojunctions with semiconducting single-walled carbon nanotubes (s-SWCNTs). Our results suggest longer lifetimes and higher yields of mobile carriers in samples containing a small fraction of defect-rich multilayer islands on predominately monolayer MoS 2 . Compared to the monolayer-only heterojunctions, the carrier lifetimes increase from 0.73 μs to 4.71 μs, the hole transfer yield increases from 23% to 34%, and the electron transfer yield increases from 39% to 59%. We reach these conclusions using a unique combination of microwave photoconductivity (which probes only mobile carriers) along with transient absorption spectroscopy (which identifies spectral signatures unique to each material and type of photoexcited quasiparticle, but does not probe mobility). Overall, our results highlight the substantial changes in photophysics that can occur from small changes in TMDC microstructure and defect density, where the presence of defects does not necessarily preclude improvements in charge generation.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2021

Design nanoporous metal thin films via solid state interfacial dealloying

Thin-film solid-state interfacial dealloying (thin-film SSID) is an emerging technique to design nanoarchitecture thin films. The resulting controllable 3D bicontinuous nanostructure is promising for a range of applications including catalysis, sensing, and energy storage. Using a multiscale microscopy approach, we combine X-ray and electron nano-tomography to demonstrate that besides dense bicontinuous nanocomposites, thin-film SSID can create a very fine (5–15 nm) nanoporous structure. Not only is such a fine feature among one of the finest fabrications by metal-agent dealloying, but a multilayer thin-film design enables creating nanoporous films on a wider range of substrates for functional applications. Through multimodal synchrotron diffraction and spectroscopy analysis with which the materials’ chemical and structural evolution in this novel approach is characterized in details, we further deduce that the contribution of change in entropy should be considered to explain the phase evolution in metal-agent dealloying, in addition to the commonly used enthalpy term in prior studies. Here, the discussion is an important step leading towards better explaining the underlying design principles for controllable 3D nanoarchitecture, as well as exploring a wider range of elemental and substrate selections for new applications.

36 MATERIALS SCIENCE↗
DOE OSTI2023

Exploration of LIBS as a novel and rapid elemental mapping technique of nuclear fuels in the form of surrogate TRISO particles

Laser-induced breakdown spectroscopy (LIBS) was employed to characterize coatings on surrogate fuel particles. Tri-structural isotropic (TRISO) particles are a proposed nuclear fuel alternative for high temperature reactors. These particles are constructed of a ZrO 2 kernel (as a surrogate to uranium), surrounded by an inner pyrolytic carbon layer and are surrounded by an outer carbide layer (ZrC, presented here) to act as a barrier to fission products generated during nuclear reactions. These particles are embedded within a graphite compact and housed within the reactor core. Simply put, due to their robust nature, performing elemental analysis of these particles poses a challenge. Presented here, LIBS is explored as a method for characterizing elemental constituents of these particles, with the focus being on rapid elemental mapping and depth profiling. Different from traditional elemental analysis techniques (e.g., inductively coupled plasma – based methods), LIBS is advantageous because it can directly analyze the sample surface and can detect light elements such as C and O, making it a viable technique for the analysis of small, multilayered particles as spatial elemental information is warranted in the production of these particles. In the work presented here, LIBS was successfully used for discerning small layers (30–50 μm), detecting the location of carbon and oxygen layers, providing fast 2-D mapping (<5 min per particle) and rapid depth profiling (10 s per particle).

11 NUCLEAR FUEL CYCLE AND FUEL MATERIALS↗
DOE OSTI2024

A type-I van der Waals heterostructure formed by monolayer WS 2 and trilayer PdSe 2

Two-dimensional (2D) heterostructures, formed by stacking 2D semiconductors through the van der Waals force, have been extensively studied recently. However, the majority of the heterostructures discovered so far possess type-II interfaces that facilitate interlayer charge separation. Type-I interfaces, on the other hand, confine both electrons and holes in one layer, which is beneficial for optical applications that utilize electron–hole radiative recombination. So far, only a few type-I 2D heterostructures have been achieved, which has limited the construction of multilayer heterostructures with sophisticated band landscapes. Here, we report experimental evidence of a type-I interface between monolayer WS 2 and trilayer PdSe 2 . Two-dimensional PdSe 2 has emerged as a promising material for infrared optoelectronic and other applications. We fabricated the heterostructure by stacking an exfoliated monolayer WS 2 flake on top of a trilayer PdSe 2 film, synthesized by chemical vapor deposition. Photoluminescence spectroscopy measurements revealed that the WS 2 exciton peak is significantly quenched in the heterostructure, confirming efficient excitation transfer from WS 2 to PdSe 2 . Femtosecond transient absorption measurements with various pump/probe configurations showed that both electrons and holes photoexcited in the WS 2 layer of the heterostructure can efficiently transfer to PdSe 2 , while neither type of carriers excited in PdSe 2 can transfer to WS 2 . These experimental findings establish a type-I band alignment between monolayer WS 2 and trilayer PdSe 2 . Furthermore, our results further highlight PdSe 2 as an important 2D material for constructing van der Waals heterostructures with emergent electronic and optoelectronic properties.

77 NANOSCIENCE AND NANOTECHNOLOGY↗
DOE OSTI2025

X-ray fluorescence standing wave study of the interaction of the antimicrobial peptide indolicidin with a supported model membrane

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.

Basnet, Gobind [Northern Illinois Univ., DeKalb, I↗
DOE OSTI2025

River Dissolved Oxygen Prediction Using Machine Learning Models and Wireless Sensor Measurements

Simultaneous flooding&heat and droughts&heat events can potentially destabilize hydro-meteorological conditions to deteriorate the water quality of Neches River. Machine learning (ML) models utilizing wireless sensor measurements have been applied to predict water quality and optimize various water management strategies. This study aims to develop ML models to predict dissolved oxygen (DO) prediction under various hydro-meteorological conditions and enhance water management decision-making. Wireless sensor measurements of DO, water temperature, sample depth, conductivity, turbidity, and pH, along with discharge from the United States Geological Survey stations, are collected for model inputs at the Pine Island Bayou C749 station (PIB-C749) and Neches River Saltwater Barrier (SWB). Multilayer perceptron neural networks, recurrent neural networks, long short-term memory (LSTM), and bidirectional LSTM (BiLSTM) with and without attention mechanism (AT) are tested to determine the best model, which is applied the rolling forecast method to predict 14-day DO. Traditional and recurrent transfer learning (TL and RTL) methods are adopted to overcome insufficient data at the SWB. The input feature importance analysis using the integrated gradients (IG) algorithm is applied to determine dominant inputs. The results show LSTM-based models are capable handling long sequential data. AT-BiLSTM and RTL-LSTM demonstrate the best performance at the PIB-C749 (RMSE=0.054) and the SWB (RMSE=0.028), respectively. TL and RTL methods significantly improve model performance at the SWB. DO, temperature, and pH show higher importance, consistent with hydrodynamics and water chemistry. Both best models are applied to predict 14-day DO and demonstrate reasonable performance for decision-making. Hydro-meteorological conditions of 2017 flood and 2012 drought events are simulated and reveal that possible hypoxia occurs after flooding due to increasing temperature and turbidity, and DO concentration decreases significantly under heat and drought conditions. In conclusion, LSTM-based models utilizing wireless sensor data can be a timely and effective approach to make appropriate decisions on water resource management.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2020

Machine learning surrogate models for Landau fluid closure

The first result of applying the machine/deep learning technique to the fluid closure problem is presented in this letter. As a start, three different types of neural networks (multilayer perceptron (MLP), convolutional neural network (CNN) and two-layer discrete Fourier transform (DFT) network) were constructed and trained to learn the well-known Hammett-Perkins Landau fluid closure in configuration space. We found that in order to train a well-preformed network, a minimum size of training data set is needed; MLP also requires a minimum number of neurons in the hidden layers equals to the degrees of freedom in Fourier space despite training data is fed in configuration space. Out of three models DFT performs the best for the clean data most likely due to the existence of nice Fourier expression for Hammett-Perkins closure but it is least robust with respect to input noise. Overall, with appropriate tuning and optimization, all three neural networks are able to accurately predict Hammett-Perkins closure and reproduce the inherit nonlocal feature, suggesting a promising path to calculate more sophisticated closures with the machine/deep learning technique.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗
DOE OSTI2020

Differential effect of magnetic alignment on additive manufacturing of magnetocaloric particles

Additive manufacturing of materials using magnetic particles as feedstock has attracted tremendous attention during the past decade owing to its ability to tune both shape and magnetocrystalline anisotropy, which can significantly enhance the magnetic characteristics of materials. We demonstrate that the magnetic response of multilayered thin films of Gd5Si4 can be tailored by controlling the external magnetic field during inkjet printing. The external magnetic field aligns the magnetic particles along their magnetic easy axis, enhancing the magnetic anisotropy of the printed films. Our work demonstrates the ability to print thin magnetic films with a defined anisotropy in any chosen direction with the potential to approaching magnetic properties of corresponding single crystalline materials.

36 MATERIALS SCIENCE↗
DOE OSTI2020

X-ray detection of ultrashort spin current pulses in synthetic antiferromagnets

Here, we explore the ultrafast generation of spin currents in magnetic multilayer samples by applying fs laser pulses to one layer and measuring the magnetic response in the other layer by element-resolved x-ray spectroscopy. In Ni(5 nm)/Ru(2 nm)/Fe(4 nm), the Ni and Fe magnetization directions couple antiferromagnetically due to the Ruderman–Kittel–Kasuya–Yosida interaction but may be oriented parallel through an applied magnetic field. After exciting the top Ni layer with a fs laser pulse, we also find that the Fe layer underneath demagnetizes, with a 4.1±1.9% amplitude difference between parallel and antiparallel orientation of the Ni and Fe magnetizations. We attribute this difference to the influence of a spin current generated by the fs laser pulse that transfers angular momentum from the Ni into the Fe layer. Our results confirm that superdiffusive spin transport plays a role in determining the sub-ps demagnetization dynamics of synthetic antiferromagnetic layers, but also evidence large depolarization effects due to hot electron dynamics, which are independent of the relative alignment of the magnetization in Ni and Fe.

36 MATERIALS SCIENCE↗
DOE OSTI2020

Deep learning surrogate model for kinetic Landau-fluid closure with collision

In this work, the kinetic Landau-fluid (LF) closure with collision and periodic boundary condition is used in the development of the deep learning (DL) surrogate model. A classical neural network, namely, feedforward neural network or sometimes termed multilayer perceptron, is constructed and trained to learn the kinetic LF closure in the static limit and arbitrary mean free path in configuration space. The preliminary relation between best hyperparameters and critical parameters for data generation is found. Compared with the numerical approach (non-Fourier method) of the LF closure, the deep learning surrogate model shows an order of magnitude of improvement in terms of accuracy. Perhaps most importantly, the surrogate model closure has been integrated for the first time with fluid simulations. Our DL-enabled fluid simulations, for the first time, give the correct Landau damping rate for a wide range of wave vectors, while the Hammett–Perkins closure cannot produce the correct damping rate. We correctly connect the collisionless Hammett–Perkins closure and collisional Braginskii closure to reproduce the intrinsic nonlocal feature of the heat flux with DL techniques. We address the most concerning error accumulation problem and find that simulations with the deep learning surrogate model are as good as, if not better than, simulations with the analytic closure in terms of long-term numerical stability in the linear Landau damping test.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗
DOE OSTI2020

Metal-ion-controlled growth and nanoindentation response of 3D, bicontinuous Cu–Fe thin films

Bicontinuous, nanocomposite thin film morphologies depend largely on the deposition conditions applied during physical vapor deposition. With the introduction of high power impulse magnetron sputtering (HiPIMS), the range of potential morphologies achieved during deposition has been increased. In this work, we compare the deposition outcomes between traditional direct-current magnetron sputtering (DCMS) and HiPIMS for a thin film co deposit of Cu and Fe. Modular control of the columnarity, porosity and roughness was achieved by varying the Cu and Fe metal ion currents during deposition. The directionality of the nanostructured phase-separated morphology was also controlled as the ion current increased. At zero ion current for both Cu and Fe sputtered species during DCMS, the film exhibited lateral concentration modulations of Cu and Fe. The directionality of the Cu- and Fe-rich phases shifted to vertical concentration modulations at low ion currents of I Fe = 1A and I Cu = 0:1A and to lateral concentration modulations at relatively moderate ion currents of I Fe = 5A and I Cu = 2A: At high ion currents of I Fe = 18A and I Cu = 2A; a more randomized phase domain structure was observed on the nanoscale. This structural shift is rationalized using an interdiffusion model. Here, the role of different kinds of phase separated morphologies, achieved during DCMS deposition, on the mechanical properties has also been studied. Results indicated increase in hardness, indentation modulus and flow strength values with the increase in indentation strain rates. Bicontinuous Cu-Fe nanocomposites are found to be stronger than multilayer Cu-Fe samples.

36 MATERIALS SCIENCE↗
DOE OSTI2020

Degradation of REBCO coated conductors due to a combination of epoxy impregnation, thermal cycles, and quench: Characteristics and a method of alleviation

REBa2Cu3Ox (REBCO) coated conductors are an enabling technology for >1 GHz nuclear magnetic resonance spectrometers that need >23.5 T solenoids, compact high-field fusion reactors beyond the International Thermonuclear Experimental Reactor, and 20 T class accelerator magnets. An in-depth understanding of stress and strain management is critically needed for these applications. Here, we report experimental data and an analysis of damages of REBCO-coated conductors in several scenarios relevant for their applications in high-field magnets and unique to their multi-layer thin film structure. The examined scenarios include failure induced by quench, failure induced by epoxy impregnation, and failure induced by a combination of epoxy impregnation and quench. The root cause is film blistering and peeling induced by thermally interfacial stresses characteristic of multilayered heteroepitaxial thin film structures on thick substrates utilized. The quantitative stress analysis is introduced using simple and easy to use formulas and clearly indicates how materials and structural characteristics affect the magnitude and the distribution of stresses and deflections. Finally, a simple method is introduced for removing degradation of REBCO coated conductors due to epoxy impregnation. Our data and analysis help our understanding of the practical limit of REBCO-coated conductors and can be utilized as a guidance for the physical design of REBCO coated conductors and high-current cables assembled from them and for minimizing damages.

Yin, Shijian (ORCID:0000000224312274)↗
DOE OSTI2020

Thermal Insulation for a High Temperature Molten Salt Storage Tank in a CSP Plant

A ternary molten chloride has been suggested as a high temperature (550-720 °C) sensible heat storage medium for a two-tank system. An effective thermal insulation is proposed to provide an opportunity for the fabrication of both the hot and cold storage tanks from lower cost metals, e.g. A240-347H, by maintaining the tank wall below 500 °C. To achieve this, the hot storage tank mainly comprises of inner shell (11.4 cm of a refractory brick as liner (KX-99®), 30 cm of insulation brick) and outer metal shell, where 5 cm of frozen layer of PCM800 (NaCl), and 5 cm of ceramic wool fill the annular space between the shells. Another layer of ceramic wool was introduced at the outer side of the metal shell to keep the temperature lower than 60 °C. ANSYS Fluent was used for the numerical study of the cool down behavior of the system during idle period when tank is quarter-filled. The heat transfer modes were considered as radiation and natural convection heat transfer from the hot molten salt at 720 °C, conduction through the solid layers and convection heat transfer from the outer shell to the environment at 15 °C. The results showed that the proposed insulation system including a frozen layer of PCM800 maintains the temperature at the metal wall lower than 500 °C, and lower than 60°C at the outer side of the tank. Apart from the insulation property of the frozen layer of PCM800, it absorbs any leak of hot molten salt, acting as a barrier between salt and the metal shell. The thermal performance analysis provide an insight into the benefits of the multilayer insulation.

41 EE - Solar Energy Technologies Office (EE-4S)↗
DOE OSTI2021

Instrument for in situ hard x-ray nanobeam characterization during epitaxial crystallization and materials transformations

Solid-phase epitaxy (SPE) and other three-dimensional epitaxial crystallization processes pose challenging structural and chemical characterization problems. The concentration of defects, the spatial distribution of elastic strain, and the chemical state of ions each vary with nanoscale characteristic length scales and depend sensitively on the gas environment and elastic boundary conditions during growth. The lateral or three-dimensional propagation of crystalline interfaces in SPE has nanoscale or submicrometer characteristic distances during typical crystallization times. Here, an in situ synchrotron hard x-ray instrument allows these features to be studied during deposition and crystallization using diffraction, resonant scattering, nanobeam and coherent diffraction imaging, and reflectivity. The instrument incorporates a compact deposition system allowing the use of short-working-distance x-ray focusing optics. Layers are deposited using radio-frequency magnetron sputtering and evaporation sources. The deposition system provides control of the gas atmosphere and sample temperature. The sample is positioned using a stable mechanical design to minimize vibration and drift and employs precise translation stages to enable nanobeam experiments. Results of in situ x-ray characterization of the amorphous thin film deposition process for a SrTiO 3 /BaTiO 3 multilayer illustrate implementation of this instrument.

47 OTHER INSTRUMENTATION↗
DOE OSTI2021

Modeling laser-driven ion acceleration with deep learning

Developments in machine learning promise to ameliorate some of the challenges of modeling complex physical systems through neural-network-based surrogate models. High-intensity, short-pulse lasers can be used to accelerate ions to mega-electronvolt energies, but to model such interactions requires computationally expensive techniques such as particle-in-cell simulations. Multilayer neural networks allow one to take a relatively sparse ensemble of simulations and generate a surrogate model that can be used to rapidly search the parameter space of interest. In this study, we created an ensemble of over 1,000 simulations modeling laser-driven ion acceleration and developed a surrogate to study the resulting parameter space. A neural-network-based approach allows for rapid feature discovery not possible for traditional parameter scans given the computational cost. A notable observation made during this study was the dependence of ion energy on the pre-plasma gradient length scale. While this methodology harbors great promise for ion acceleration, it has ready application to all topics in which large-scale parameter scans are restricted by significant computational cost or relatively large, but sparse, domains.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗