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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 739 records · Page 41
All sourcesNASA NTRSDOE OSTI
DOE OSTI2022

Ultra-high SERS detection of consumable coloring agents using plasmonic gold nanostars with high aspect-ratio spikes

Solution-based SERS detection by using a portable Raman instrument has emerged as an important tool due to its simplicity, and flexibility for rapid and on-site screening of analyte molecules. However, this method has several shortcomings, including poor sensitivity especially for weak-affinity analyte molecules, where there is no close contact between the plasmonic metal surface and analyte molecule. Examples of weak-affinity molecules include pigment molecules that are commonly used as a consumable coloring agent, such as allura red (AR), and sunset yellow (SY). As high consumption of colorant agents has been shown to cause adverse effects on human health, there is a strong need to develop a simple and practical sensing system with high sensitivity for these agents. Here we present a novel, highly sensitive solution-based SERS detection method for AR, and SY by using CTAC capped gold nanostars (GNS) having different aspect ratios (GNS-2, GNS-4, and GNS-5) without utilizing any aggregating agents which can enhance SERS signal however it reduces batch to batch reproducibility. The influence of the aspect ratio of GNS on SERS properties was investigated. We have achieved a limit of detection (LOD) of AR and SY as low as 0.5 and 1 ppb, respectively by using GNS-5 with the advantages of minimal sample preparation by just mixing the analyte solution into a well plate containing GNS solution. In addition, excellent colloidal stability and reproducibility have further enhanced the applicability in real-world samples. Altogether, our results evidence that the solution-based SERS detection platform using high aspect-ratio GNS can be applied for practical application to detect pigment molecules in real samples with satisfactory results.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2022

Correlation between oxygen evolution reaction activity and surface compositional evolution in epitaxial La 0.5 Sr 0.5 Ni 1– x Fe x O 3– δ thin films

Water electrolysis can use renewable electricity to produce green hydrogen, a portable fuel and sustainable chemical precursor. Improving electrolyzer efficiency hinges on the activity of the oxygen evolution reaction (OER) catalyst. Earth-abundant, ABO 3 -type perovskite oxides offer great compositional, structural, and electronic tunability, with previous studies showing compositional substitution can increase the OER activity drastically. However, the relationship between the tailored bulk composition and that of the surface, where OER occurs, remains unclear. Here, we study the effects of electrochemical cycling on the OER activity of La 0.5 Sr 0.5 Ni 1– x Fe x O 3– δ ( x = 0–0.5) epitaxial films grown by oxide molecular beam epitaxy as a model Sr-containing perovskite oxide. In this work, electrochemical testing and surface-sensitive spectroscopic analyses show Ni segregation, which is affected by electrochemical history, along with surface amorphization, coupled with changes in OER activity. Our findings highlight the importance of surface composition and electrochemical cycling conditions in understanding OER performance, suggesting common motifs of the active surface with high surface area systems.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2022

A visible to near-infrared nanocrystalline organic photodetector with ultrafast photoresponse

Organic photoelectron conversion devices, due to their solution process and wide use in portable devices, have attracted intensive interest. In this work, a newly developed active layer of D18:Y6 is used to fabricate an organic photodetector and the device of ITO/PEDOT:PSS/D18:Y6/Phen-NaDPO/Ag shows a responsivity of 680 mA W –1 and a detectivity of 6.35 × 10 13 Jones (1 Jones = 1 cm Hz 1/2 W –1 ) at a wavelength of 850 nm. Additionally, this device shows a wide linear dynamic range of 120 dB, indicating a potential near-infrared region (NIR) detector system. Owing to the minimal exciton binding energy of 37.6 meV for Y6, a desirable energy offset for efficient electron–hole pair dissociation and an ultrafast charge transfer of ~58 ps at the interface of D18:Y6, the obtained organic photodetector has demonstrated a photoresponse time as fast as 1.8 μs upon laser light excitation without an external driven voltage. More importantly, D18 shows a preferred out-of-plane orientation with strong intensities and Y6 exhibits a preferred orientation along the in-plane direction on lamellar stacking, which facilitates charge transport. This work has demonstrated significant progress in exploring D18:Y6 NIR organic devices with a wide photosensitivity linearity and ultrafast photoresponse.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2024

Additive manufacturing of LiCoO 2 electrodes via vat photopolymerization for lithium ion batteries

Additive manufacturing has the potential to revolutionize the fabrication of lithium-ion batteries for a diversity of applications including in portable, biomedical, aerospace, and the transportation fields. Standard commercial batteries consist of stacked layers of various components (current collectors, cathode, anode, separator and electrolyte) in a two-dimensional manner. By leveraging the latest advances in additive manufacturing and computer-aided design, an improved geometric and electrochemical configuration of these batteries can maximize energy efficiency while allowing design optimization to reduce dead space for a given application. In this work, a composite UV photosensitive resin was prepared and used as feedstock in a vat photopolymerization system. The resin was loaded with LiCoO 2 acting as electrochemically active material for the cathode of a lithium-ion battery, and was further improved with the addition of conductivity-enhancing carbonaceous additives. Challenges to additive manufacturing arise from the opacity and high viscosity of the composite nature of these electrochemically-active resins, which cause light refraction during selective UV curing. Subsequently, items were printed and subjected to a thermal post-processing step to obtain an adequate compromise between electrochemical performance and mechanical integrity. Both sintered and green state 3D printed cathodes were assembled into half-cell lithium-ion batteries using lithium metal as a reference and counter electrode. Electrochemical cycling of these batteries yielded satisfactory results approaching commercial LiCoO 2 cathodes’ performance, with the potential advantages of additive manufacturing – high surface area anode–cathode configurations for power performance as well as shape conformability.

25 ENERGY STORAGE↗
DOE OSTI2020

A compact filtered x-ray diode array spectrometer for the National Ignition Facility: SENTINEL

Sentinel is a 16-channel, filtered x-ray diode array spectrometer that has been developed to measure ~1 keV–20 keV x-ray emission generated by the National Ignition Facility (NIF) laser. Unlike the large, fixed-port versions of this diagnostic that currently exist on the NIF (known as Dante), Sentinel is a Diagnostic Instrument Manipulator compatible such that it can be fielded along the polar or equatorial lines-of-sight—an essential new capability for characterizing the often anisotropic x-ray emission from laser-driven sources. Here, we present the diagnostic design along with preliminary diode calibrations and performance results. The novel, small-form-factor x-ray diode design allows for ≳5×–25× increased channel areal density over that of Dante, simultaneously enabling improved diagnostic robustness and fidelity of spectral reconstructions. While the Sentinel diagnostic is anticipated to improve line-of-sight spectral characterization of x-ray sources for a wide variety of programs on the NIF, the compact and portable design is also attractive to small- and mid-scale facilities with limited diagnostic real estate.

47 OTHER INSTRUMENTATION↗
DOE OSTI2021

High pressure, high flow rate batch mixing apparatus for high throughput experiments

An automated, high pressure, high flow rate batch mixing apparatus has been designed and constructed for rapid, stable, and repeatable mixing of multiple gases and vapors. The apparatus operates as an intermittent batch mixer with cycles of topping off fresh mixture to maintain pressure in an accumulator tank until consumed in an experimental apparatus. At high duty cycles, the apparatus can also function at steady state. This style of mixing is suitable for experiments such as high repetition rate shock tubes and other devices with intermittent flow demands. It is compact and portable, facilitating use in locations such as synchrotron light sources. The entire apparatus is heated to permit the mixing of vapors from species with low volatilities. The apparatus is fully automated and runs for extended periods with the only intervention being to refresh reagent supplies. Here, the accuracy and repeatability of the apparatus were verified by periodic gas sampling and analysis with gas chromatography. Multi-component mixtures spanning a wide range of complexity, dilution, and volatility of constituents have been prepared. The compositions of the majority of the mixture were found to be stable over several filling cycles, repeatable, and with the proper calibration of set-point conditions, accurate. Challenges were encountered preparing a mixture from multi-component liquids, and potential solutions are discussed.

47 OTHER INSTRUMENTATION↗
DOE OSTI2022

CO 2 laser heating system for in situ radial x-ray absorption at 16-BM-D at the Advanced Photon Source

Here we present a portable CO 2 laser heating system for in situ x-ray absorption spectroscopy (XAS) studies at 16-BM-D (High Pressure Collaborative Access Team, Advanced Photon Source, Argonne National Laboratory). Back scattering optical measurements are made possible by the implementation of a Ge beamsplitter. Optical pyrometry is conducted in the near-infrared, and our temperature measurements are free of chromatic aberration due to the implementation of the peak-scaling method and mode scrambling of the input signal. Laser power stabilization is established using electronic feedback, providing a steady power over second timescales - crucial for longer XAS collections. Examples of in situ high pressure–temperature extended x-ray absorption fine structure measurements of ZrO 2 are presented to demonstrate this new capability.

36 MATERIALS SCIENCE↗
DOE OSTI2022

Droplet formation simulation using mixed finite elements

Droplet formation happens in finite time due to the surface tension force. The linear stability analysis is useful to estimate the size of a droplet but fails to approximate the shape of the droplet. This is due to a highly nonlinear flow description near the point where the first pinch-off happens. A one-dimensional axisymmetric mathematical model was first developed by Eggers and Dupont [“Drop formation in a one-dimensional approximation of the Navier–Stokes equation,” J. Fluid Mech. 262, 205–221 (1994)] using asymptotic analysis. This asymptotic approach to the Navier–Stokes equations leads to a universal scaling explaining the self-similar nature of the solution. Numerical models for the one-dimensional model were developed using the finite difference [Eggers and Dupont, “Drop formation in a one-dimensional approximation of the Navier–Stokes equation,” J. Fluid Mech. 262, 205–221 (1994)] and finite element method [Ambravaneswaran et al., “Drop formation from a capillary tube: Comparison of one-dimensional and two-dimensional analyses and occurrence of satellite drops,” Phys. Fluids 14, 2606–2621 (2002)]. The focus of this study is to provide a robust computational model for one-dimensional axisymmetric droplet formation using the Portable, Extensible Toolkit for Scientific Computation. The code is verified using the Method of Manufactured Solutions and validated using previous experimental studies done by Zhang and Basaran [“An experimental study of dynamics of drop formation,” Phys. Fluids 7, 1184–1203 (1995)]. The present model is used for simulating pendant drops of water, glycerol, and paraffin wax, with an aspiration of extending the application to simulate more complex pinch-off phenomena.

71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗
DOE OSTI2023

TAMM: Tensor algebra for many-body methods

Tensor algebra operations such as contractions in computational chemistry consume a significant fraction of the computing time on large-scale computing platforms. The widespread use of tensor contractions between large multi-dimensional tensors in describing electronic structure theory has motivated the development of multiple tensor algebra frameworks targeting heterogeneous computing platforms. In this paper, we present Tensor Algebra for Many-body Methods (TAMM), a framework for productive and performance-portable development of scalable computational chemistry methods. TAMM decouples the specification of the computation from the execution of these operations on available high-performance computing systems. With this design choice, the scientific application developers (domain scientists) can focus on the algorithmic requirements using the tensor algebra interface provided by TAMM, whereas high-performance computing developers can direct their attention to various optimizations on the underlying constructs, such as efficient data distribution, optimized scheduling algorithms, and efficient use of intra-node resources (e.g., graphics processing units). The modular structure of TAMM allows it to support different hardware architectures and incorporate new algorithmic advances. We describe the TAMM framework and our approach to the sustainable development of scalable ground- and excited-state electronic structure methods. We present case studies highlighting the ease of use, including the performance and productivity gains compared to other frameworks.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2023

Accelerated kinetic model for global macro stability studies of high-beta fusion reactors

The field reversed configuration (FRC), such as studied in the C-2W experiment at TAE Technologies, is an attractive candidate for realizing a nuclear fusion reactor. In an FRC, kinetic ion effects play the majority role in macroscopic stability, which allows global stability studies to make use of fluid-kinetic hybrid (also referred to as Ohm's law) models wherein ions are treated kinetically while electrons are treated as a fluid. The development and validation of such a hybrid particle-in-cell algorithm in the Exascale Computing Project code WarpX are reported here. Implementation of this model in the WarpX framework benefits from the numerical efficiency of WarpX as well as its scalability on large HPC systems and portability to different architectures. Performance benchmarks of the new algorithm for large, 3-dimensional, full device simulations from the Perlmutter supercomputer are presented. Results of a series of FRC simulations are discussed in which the impact of two-fluid effects on the tilt-mode growth rate was studied. It was observed that, in agreement with previous Hall-MHD studies, two-fluid effects have a stabilizing impact on the tilt mode.

Physics↗
DOE OSTI2026

Design and simulation of a muon detector to characterize geological overburden

This study presents the design, construction, and simulation of a mobile muon detector tailored for geological overburden characterization. The detector employs plastic scintillator paddles with silicon photomultipliers (SiPMs) and a QuarkNet data acquisition system, offering a portable solution suitable for remote field deployment. The simulator’s modular aluminum frame allows for adjustable geometry and directional sensitivity, while its battery system supports over a week of autonomous operation. Preliminary experimental tests confirmed that its muon flux measurements were consistent with theoretical expectations. A comprehensive simulation framework using Geant4 and CORSIKA was developed to model detector response and overburden effects. Analytical and Monte Carlo methods were used to assess quadrant resolution and infer muon directionality. This work lays the foundation for future overburden mapping and supports the development of reconstruction algorithms for geological applications.

72 - PHYSICS OF ELEMENTARY PARTICLES AND FIELDS↗
DOE OSTI2022

Achieving complete electrooxidation of ethanol by single atomic Rh decoration of Pt nanocubes

Significance Direct ethanol fuel cells are attracting growing attention as portable power sources due to their advantages such as higher mass-energy density than hydrogen and less toxicity than methanol. However, it is challenging to achieve the complete electrooxidation to generate 12 electrons per ethanol, resulting in a low fuel utilization efficiency. This manuscript reports the complete ethanol electrooxidation by engineering efficient catalysts via single-atom modification. The combined electrochemical measurements, in situ characterization, and density functional theory calculations unravel synergistic effects of single Rh atoms and Pt nanocubes and identify reaction pathways leading to the selective C–C bond cleavage to oxidize ethanol to CO 2 . This study provides a unique single-atom approach to tune the activity and selectivity toward complicated electrocatalytic reactions.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2023

Scientific machine learning for modeling and simulating complex fluids

The formulation of rheological constitutive equations—models that relate internal stresses and deformations in complex fluids—is a critical step in the engineering of systems involving soft materials. While data-driven models provide accessible alternatives to expensive first-principles models and less accurate empirical models in many engineering disciplines, the development of similar models for complex fluids has lagged. The diversity of techniques for characterizing non-Newtonian fluid dynamics creates a challenge for classical machine learning approaches, which require uniformly structured training data. Consequently, early machine-learning based constitutive equations have not been portable between different deformation protocols or mechanical observables. Here, we present a data-driven framework that resolves such issues, allowing rheologists to construct learnable models that incorporate essential physical information, while remaining agnostic to details regarding particular experimental protocols or flow kinematics. These scientific machine learning models incorporate a universal approximator within a materially objective tensorial constitutive framework. By construction, these models respect physical constraints, such as frame-invariance and tensor symmetry, required by continuum mechanics. We demonstrate that this framework facilitates the rapid discovery of accurate constitutive equations from limited data and that the learned models may be used to describe more kinematically complex flows. This inherent flexibility admits the application of these “digital fluid twins” to a range of material systems and engineering problems. We illustrate this flexibility by deploying a trained model within a multidimensional computational fluid dynamics simulation—a task that is not achievable using any previously developed data-driven rheological equation of state.

Science & Technology - Other Topics↗
DOE OSTI2024

Rapid, antibiotic incubation-free determination of tuberculosis drug resistance using machine learning and Raman spectroscopy

Tuberculosis (TB) is the world’s deadliest infectious disease, with over 1.5 million deaths and 10 million new cases reported anually. The causative organism Mycobacterium tuberculosis (Mtb) can take nearly 40 d to culture, a required step to determine the pathogen’s antibiotic susceptibility. Both rapid identification and rapid antibiotic susceptibility testing of Mtb are essential for effective patient treatment and combating antimicrobial resistance. Here, we demonstrate a rapid, culture-free, and antibiotic incubation-free drug susceptibility test for TB using Raman spectroscopy and machine learning. We collect few-to-single-cell Raman spectra from over 25,000 cells of the Mtb complex strain Bacillus Calmette-Guérin (BCG) resistant to one of the four mainstay anti-TB drugs, isoniazid, rifampicin, moxifloxacin, and amikacin, as well as a pan-susceptible wildtype strain. By training a neural network on this data, we classify the antibiotic resistance profile of each strain, both on dried samples and on patient sputum samples. On dried samples, we achieve >98% resistant versus susceptible classification accuracy across all five BCG strains. In patient sputum samples, we achieve ~79% average classification accuracy. We develop a feature recognition algorithm in order to verify that our machine learning model is using biologically relevant spectral features to assess the resistance profiles of our mycobacterial strains. Finally, we demonstrate how this approach can be deployed in resource-limited settings by developing a low-cost, portable Raman microscope that costs <$5,000. We show how this instrument and our machine learning model enable combined microscopy and spectroscopy for accurate few-to-single-cell drug susceptibility testing of BCG.

60 APPLIED LIFE SCIENCES↗
DOE OSTI2022

A Dynamic Risk Framework for the Physical Security of Nuclear Power Plants

This paper describes ongoing work within the Light Water Reactor Sustainability pathway at Idaho National Laboratory (INL) to optimize the security and cost of nuclear power plants. It introduces the dynamic risk assessment tool developed at INL, Event Modeling Risk Assessment using Linked Diagrams (EMRALD). EMRALD is leveraged to optimize the security posture of a nuclear power plant by integrating force-on-force (FOF) simulations and operator mitigation actions, including dynamic and flexible coping strategies (FLEX). To illustrate the methodology, four attack scenarios are modeled in a commercially available FOF simulation tool using a hypothetical nuclear power plant facility. The simulation results provide valuable insights into possible attack outcomes, as well as the probabilistic risk of a core damage event given these outcomes. Safety mitigation procedures are modeled in EMRALD dependent on the attack outcomes by considering human operator uncertainties. The results demonstrate that the number of armed responders can be optimized, while still maintaining the same protection level as the initial security posture. The proposed modeling and simulation framework of integrating FLEX equipment with FOF models enables the nuclear power plants to credit FLEX portable equipment in the plant security posture, resulting in an efficient and optimized physical security system.

22 GENERAL STUDIES OF NUCLEAR REACTORS↗
DOE OSTI2023

Sensitivity Analysis of Effectiveness of FLEX Strategies Using a CDF-Based Importance Measure Under Accident Conditions

One of the lessons learned from the Fukushima Daiichi nuclear power plant (NPP) accident is strengthening the station blackout (SBO) mitigation capabilities by enhancing defense in depth for all existing and new NPPs. One of the possible remedies is diverse and flexible coping strategies (FLEX). The objective of this study is to address the benefits of FLEX in various accident scenarios in terms of both risk and cost. FLEX was originally devised against SBO accidents. In this research, we investigate the fundamental plant responses against accidents considering two fundamentally different cases: accidents that lead to high pressure on the primary side and accidents that lead to low pressure on the primary side. Several uncertainties are associated with the characteristics of the FLEX portable equipment. Specifically, the time for FLEX deployment may depend on several factors such as type of accident, point of injection, availability of safety systems, battery backup timings, and human actions. This study utilizes a dynamic risk assessment framework to analyze accident scenarios and suggests a novel importance measure, which is a cumulative distribution function– based importance metric that characterizes the influence of input distribution on complete output distribution. The importance of the existing and newly developed FLEX strategy based on risk significance is illustrated with examples. The suggested measure provides clear insight into how FLEX affects risk of the whole system and additional risk margins thanks to new safety systems.

22 GENERAL STUDIES OF NUCLEAR REACTORS↗
DOE OSTI2026

A novel compact end-loaded piston cylinder cell for high pressure neutron scattering up to 5 GPa

Here, a miniature sized end-loaded piston cylinder cell with radial side windows for neutron scattering experiments is described. The principle of the bicone-shaped cylinders used was first presented by McWhan in 1974. The present cell is of compact portable design yet significantly enlarges the scattering angles. Its small size allows neutron scattering experiments at low temperatures. The bicone-shaped cylinders are made from various ceramics or a highly neutron-transmissive Ni-free Cr–Mo–V steel. Successful neutron scattering experiments up to 5 GPa have been demonstrated on the CORELLI single-crystal diffractometer and the VISION vibrational spectrometer of the Spallation Neutron Source at the Oak Ridge National Laboratory.

Neutrons↗