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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 1,027 records · Page 57

Developing tools and process controls to manufacture energy-efficient powders for additive manufacturing feedstocks: Computational analysis of metal powder manufacturing via machining

Traditionally, metal powders have been produced through methods such as grinding, atomization, and electrolysis. In contrast to these techniques, Metal Powder Works, Inc. has pioneered a methodology based on metal cutting. This innovative approach utilizes a vibrating cutting tool to machine metal particles, in the form of chips, from a workpiece. This technique allows for control of powder particle size, morphology, and avoids any thermally induced material changes. This collaboration aims to elucidate metal cutting characteristics and assess performance on tough materials like Inconel alloys. Computational models, using FEA and SPH techniques, will be developed initially, focusing on aluminum alloy (Al 7075-T6) for studying mesh sensitivity, cutting forces, and chip morphology.

99 GENERAL AND MISCELLANEOUS↗

Developing tools and process controls to manufacture energy-efficient powders for additive manufacturing feedstocks

Traditionally, metal powders have been produced through methods such as grinding, atomization, and electrolysis. In contrast to these techniques, Metal Powder Works, Inc. has pioneered a methodology based on metal cutting. This innovative approach utilizes a vibrating cutting tool to machine metal particles, in the form of chips, from a workpiece. This technique allows for control of powder particle size, morphology, and avoids any thermally induced material changes. This collaboration aims to elucidate metal cutting characteristics and assess performance on tough materials like Inconel alloys. Computational models, using FEA and SPH techniques, will be developed initially, focusing on aluminum alloy (Al 7075- T6) for studying mesh sensitivity, cutting forces, and chip morphology.

36 MATERIALS SCIENCE↗

Precision Polishing of Spheres Via In-Situ Process Monitoring and Machine-Learning-Based Optimization

In inertial confinement fusion (ICF) experiments seeking output gains of unity and beyond, the quality of the ablator capsule is paramount for minimizing hydrodynamic mix that quenches the central hot spot. Defects in the form of foreign particles or missing mass on the surface and within the wall of the capsule are primary offenders. High density carbon capsules made for ICF experiments on the National Ignition Facility (NIF) are precision polished to achieve the surface smoothness in the order of a few nm as well as to minimize isolated defects in the form of pits. Given the critical role of this process, we are developing smart manufacturing techniques with goal of elevating the efficiency of this process. Our approach is to use MEMS-based sensors to capture the fine vibrational signals generated during the polishing process and combine it with synchronized visual feedback as needed. Beyond using these sensors for process monitoring, we use specific deep learning methods to analyze the data and extract correlations with both the process parameters and the final performance of the polishing run. Here, we describe the multiple fronts that we have explored in this regard and the results we have gotten so far. This approach promises to have the potential to ultimately provide real-time feedback that can be used for ensuring the progress of the run as well as a means for faster optimization.

36 MATERIALS SCIENCE↗

Multi-fidelity is the new annealing: Gradient-free learning of posterior densities via transport maps

To tackle concentrated, multi-modal Bayesian inference problems, we propose using an annealed importance sampling procedure. To do this, we form a sequence of annealed distributions and employ transport maps to act as a surrogate of each distribution. This process is demonstrated on a few examples, favorably showing its potential for efficiently parallelizing the process of PDE evaluations and allowing for surrogates that we can sample from exactly.

van Bloemen Waanders, Bart G [Sandia National Labo↗

Plasmonic nanoring fabrication tuned to pitch: Efficient, deterministic, and large scale realization of ultra-small gaps for next generation plasmonic devices

A double-patterning process for scalable, efficient, and deterministic nanoring array fabrication is presented. It enables gaps and features below a size of 20 nm. A writing time of 3 min/cm{sup 2} makes this process extremely appealing for scientific and industrial applications. Numerical simulations are in agreement with experimentally measured optical spectra. Therefore, a platform and a design tool for upcoming next generation plasmonic devices like hybrid plasmonic quantum systems are delivered.

75 CONDENSED MATTER PHYSICS, SUPERCONDUCTIVITY AND↗

Petascale turbulence simulation using a highly parallel fast multipole method on GPUs

This paper reports large-scale direct numerical simulations of homogeneous-isotropic fluid turbulence, achieving sustained performance of 1.08 petaflop/s on gpu hardware using single precision. The simulations use a vortex particle method to solve the Navier–Stokes equations, with a highly parallel fast multipole method (fmm) as numerical engine, and match the current record in mesh size for this application, a cube of computational points solved with a spectral method. The standard numerical approach used in this field is the pseudo-spectral method, relying on the fft algorithm as the numerical engine. The particle-based simulations presented in this paper quantitatively match the kinetic energy spectrum obtained with a pseudo-spectral method, using a trusted code. In terms of parallel performance, weak scaling results show the fmm-based vortex method achieving 74% parallel efficiency on 4096 processes (one gpu per mpi process, 3 gpus per node of the tsubame-2.0 system). The fft-based spectral method is able to achieve just 14% parallel efficiency on the same number of mpi processes (using only cpu cores), due to the all-to-all communication pattern of the fft algorithm. The calculation time for one time step was 108 s for the vortex method and 154 s for the spectral method, under these conditions. Computing with 69 billion particles, this work exceeds by an order of magnitude the largest vortex-method calculations to date.

Computer Science↗

On the need for the light elements primary process (LEPP)

Extant chemical evolution models underestimate the galactic production of Sr, Y, and Zr as well as the solar system abundances of s-only isotopes with 90 < A < 130. To solve this problem, an additional (unknown) process has been invoked, the so-called light element primary process (LEPP). In this paper we investigate possible alternative solutions. Based on Full Network Stellar evolutionary calculations, we investigate the effects on the solar system s-only distribution induced by the inclusion of some commonly ignored physical processes (e.g., rotation) or by the variation of the treatment of convective overshoot, mass loss, and the efficiency of nuclear processes. Our main findings are (1) at the epoch of the formation of the solar system, our reference model produces supersolar abundances for the whole s-only distribution, even in the range 90 < A < 130, (2) within errors, the s-only distribution relative to {sup 150}Sm is flat, (3) the s-process contribution of the less massive AGB stars (M < 1.5 M {sub ⊙}) as well as of the more massive ones (M > 4.0 M {sub ⊙}) are negligible, (4) the inclusion of rotation implies a downward shift of the whole distribution with a higher efficiency for the heavy s-only isotopes, leading to a flatter s-only distribution, (5) different prescriptions on convection or mass loss produce nearly rigid shifts of the whole distribution. In summary, a variation of the standard paradigm of AGB nucleosynthesis would allow reconciliation of model predictions with solar system s-only abundances. Nonetheless, the LEPP cannot be definitely ruled out because of the uncertainties still affecting stellar and galactic chemical evolution models.

79 ASTRONOMY AND ASTROPHYSICS↗

Sustainable conversion of biomass to rationally designed lithium-ion battery graphite

The carbon net negative conversion of bio-char, the low value byproduct of pyrolysis bio-oil production from biomass, to high value, very high purity, highly crystalline flake graphite agglomerates with rationally designed shape and size tailored for lithium-ion battery energy storage material is reported. The process is highly efficient, 0.41 g/Wh; the energy content of its co-product of the process, bio-oil, exceeds that needed to power the process. It is shown that the shape of the starting material is retained during the transformation, allowing the ultimate morphology of the graphite agglomerates to be engineered from relatively malleable biomass. In contrast to commercial graphite production, the process can be performed at small scale with low equipment costs, enabling individual research laboratories to produce Li-ion grade graphite with customizable shape, size and porosity for Si/graphite composite and other graphite involved anodes. The mechanism of the graphitization of bio-char, a “non-graphitizable” carbon, is explored, suggesting the molten metal catalyst is absorbed into the pore structure, transported through and transforming the largely immobile biochar. Finally, the transformation of biomass to rationally designed graphite morphologies with Li-ion anode performance that closely mimic commercial shaped graphite is demonstrated.

09 BIOMASS FUELS↗

Precision Polishing of Ablator Capsules via in situ Process Monitoring and Machine Learning–Based Optimization

In inertial confinement fusion (ICF) experiments seeking output gains of unity and beyond, the quality of the ablator capsule is paramount for minimizing the hydrodynamic mix that quenches the central hot spot. Defects in the form of foreign particles or missing mass on the surface and within the wall of the capsule are primary offenders. High-density carbon capsules made for ICF experiments at the National Ignition Facility are precision polished to achieve surface smoothness on the order of a few nanometers as well as to minimize isolated defects in the form of pits. Given the critical role of this process, we are developing smart manufacturing techniques with the goal of elevating the efficiency of this process. Our approach is to use MEMS (micro-electromechanical systems)–based sensors to capture the fine vibration signals generated during the polishing process and combine them with synchronized visual feedback as needed. Beyond using these sensors for process monitoring, we use specific deep learning methods to analyze the data and extract correlations with both the process parameters and the final performance of the polishing run. Here, in this work, we describe the multiple fronts we have explored in this regard and the results we have gotten so far. This approach promises to have the potential to ultimately provide real-time feedback that can be used to ensure the progress of the run as well as a means for faster optimization.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗

Model emulation and closure tests for (3+1)D relativistic heavy-ion collisions

In nuclear and particle physics, reconciling sophisticated simulations with experimental data is vital for understanding complex systems like the Quark Gluon Plasma (QGP) generated in heavy ion collisions. However, computational demands pose challenges, motivating using Gaussian Process emulators for efficient parameter extraction via Bayesian calibration. We conduct a comparative analysis of Gaussian Process emulators in heavy-ion physics to identify the most adept emulator for parameter extraction with minimal uncertainty. Furthermore, our study contributes to advancing computational techniques in heavy-ion physics, enhancing our ability to interpret experimental data and understand QGP properties.

73 NUCLEAR PHYSICS AND RADIATION PHYSICS↗

Close-Space Sublimation-Deposited Ultra-Thin CdSeTe/CdTe Solar Cells for Enhanced Short-Circuit Current Density and Photoluminescence

This work describes the complete fabrication process of thin-absorber cadmium selenium telluride/cadmium telluride photovoltaic devices for enhanced efficiency. Here, the process utilizes an automated in-line vacuum system for close-space sublimation deposition which is scalable from fabrication of small area research devices to large-scale modules.

14 SOLAR ENERGY↗

Abstract for CRADA between Birla Carbon USA, Inc. and NETL (AGMT-0903)

NETL researchers will be collaborating with Birla Carbon USA to leverage NETL's patented catalyst work on methane decomposition to commercialize an efficient and cost-effective process for production of hydrogen and carbon from natural gas. This catalytic methane decomposition is a promising technology but finding an appropriate catalyst to perform all the functions has been a challenge. NETL has developed a suitable catalyst for the process which has shown promising results. The heat required for this endothermic catalytic decomposition process is provided by either combustion of hydrogen or chemical looping process. This process is cost effective, energy efficient, and environmentally friendly, with minimal CO 2 mitigation costs. The objective of the project is to obtain data necessary for economic evaluation of the process to produce carbon suitable for applications at Birla Carbon USA.

03 NATURAL GAS↗

Hydrogen storage in formic acid: A comparison of process options

Formic acid (53 g H2/liter) is a promising liquid storage and delivery option for hydrogen for fuel cell power applications. In this work we compare and evaluate several process options using formic acid for energy storage. Each process requires different steps, which contribute to the overall energy demand. The first step, i.e. production of formic acid, is thermodynamically unfavorable. However, the energy demand can be reduced if a formate salt is produced via a bicarbonate route instead of forming the free acid from hydrogen and carbon dioxide. This bicarbonate / formate approach also turns out to be comparatively more efficient in terms of hydrogen release than the formic acid route. Even though less energy efficient, catalytic decomposition of formic acid has the advantage of reaching higher volumetric power densities during hydrogen release. Efficiencies of all process options involve aqueous media and are dependent on concentration. Heating water leads to additional energy demand for hydrogen release and thus lowers the overall efficiency. Separation and purification of hydrogen contributes a minor impact to the overall energy demand. However, its effect on efficiency is not negligible. Other process options like thermal decomposition of formic acid or direct formic acid fuel cells thus far do not appear competitive.

Muller, Karsten W.↗

Improving Cooperative Interactions Between Halogenated Aromatic Additives and Aromatic Side Chain Acceptors for Realizing 19.22% Efficiency Polymer Solar Cells

Processing additive plays an important role in the standard operation procedures for fabricating top performing polymer solar cells (PSCs) through efficient interactions with key photovoltaic materials. However, improving interaction study of acceptor materials to high performance halogenated aromatic additives such as diiodobenzene (DIB) is a widely neglected route for molecular engineering toward more efficient device performances. Here, in this work, two novel Y-type acceptor molecules of BTP-TT and BTP-TTS with different aromatic side chains on the outer positions are designed and synthesized. The resulting aromatic side chains significantly enhanced the interactions between the acceptor molecules and DIB through an arene/halogenated arene interaction, which improved the crystallinity of the acceptor molecules and induced a polymorph with better photovoltaic performances. Thus, high power conversion efficiencies (PCEs) of 18.04% and 19.22% are achieved in binary and ternary blend devices using BTP-TTS as acceptor and DIB as additive. Aromatic side chain engineering for improving additive interactions is proved to be an effective strategy for achieving much higher performance photovoltaic materials and devices.

36 MATERIALS SCIENCE↗

Effects of processing on the efficacy and metabolites of Cistanche tubulosa using ultra‐performance liquid chromatography coupled with quadrupole time‐of‐flight mass spectrometry

Abstract Cistanche tubulosa (CT), a well‐known traditional Chinese medicine, has always been processed with rice wine for the treatment of kidney‐yang deficiency syndrome (KYDS) since time immemorial. To explore the effect of processing on the efficacy and metabolites of CT in vivo , a comprehensive method using ultra‐performance liquid chromatography coupled with quadrupole time‐of‐flight mass spectrometry was established for the analysis of the altered endogenous metabolites in response to the intervention of the raw and processed CT in KYDS model and the metabolites of the absorbed compounds in rats after gastric perfusion. It was shown that CT could improve KYDS, and the effect of the processed product was more significant. A total of 47 differential metabolites were identified in urine. Pathway analysis proved that purine metabolism; alanine, aspartate, and glutamate metabolism; and citrate cycle were the main pathways. Furthermore, 53 prototypes and 48 metabolites have been detected in rats. This was the first systematic research focus on the metabolites of raw and processed CT in vivo , which could provide a scientific basis for explaining the increasing efficiency of the processed CT. Moreover, it provides a valuable strategy for analyzing the chemical components and metabolites of other TCM prescriptions.

Lei, Huibo↗

An easy-to-fabricate low-temperature TiO{sub 2} electron collection layer for high efficiency planar heterojunction perovskite solar cells

Organometal trihalide perovskite solar cells arguably represent the most auspicious new photovoltaic technology so far, as they possess an astonishing combination of properties. The impressive and brisk advances achieved so far bring forth highly efficient and solution processable solar cells, holding great promise to grow into a mature technology that is ready to be embedded on a large scale. However, the vast majority of state-of-the-art perovskite solar cells contains a dense TiO{sub 2} electron collection layer that requires a high temperature treatment (>450 °C), which obstructs the road towards roll-to-roll processing on flexible foils that can withstand no more than ∼150 °C. Furthermore, this high temperature treatment leads to an overall increased energy payback time and cumulative energy demand for this emerging photovoltaic technology. Here we present the implementation of an alternative TiO{sub 2} layer formed from an easily prepared nanoparticle dispersion, with annealing needs well within reach of roll-to-roll processing, making this technology also appealing from the energy payback aspect. Chemical and morphological analysis allows to understand and optimize the processing conditions of the TiO{sub 2} layer, finally resulting in a maximum obtained efficiency of 13.6% for a planar heterojunction solar cell within an ITO/TiO{sub 2}/CH{sub 3}NH{sub 3}PbI{sub 3-x}Cl{sub x}poly(3-hexylthiophene)/Ag architecture.

36 MATERIALS SCIENCE↗

Integrated RMP-based ELM-crash-control process for plasma performance enhancement during ELM crash suppression in KSTAR

The integrated Resonant Magnetic Perturbation (RMP)-based Edge-Localized Mode (ELM)-crash-control process aims to enhance the plasma performance during the RMP-driven ELM crash suppression, where the RMP induces an unwanted confinement degradation. In this study, the normalized beta ($\beta_\textrm{N}$) is introduced as a metric for plasma performance. The integrated process incorporates the latest achievements in the RMP technique to enhance $\beta_\textrm{N}$ efficiently. The integrated process triggers the n = 1 Edge-localized RMP (ERMP) at the L–H transition timing using the real-time Machine Learning (ML) classifier. The pre-emptive RMP onset can reduce the required external heating power for achieving the same $\beta_\textrm{N}$ by over 10% compared to the conventional onset. During the RMP phase, the adaptive feedback RMP ELM controller, demonstrating its performance in previous experiments, plays a crucial role in maximizing $\beta_\textrm{N}$ during the suppression phase and sustaining the $\beta_\textrm{N}$-enhanced suppression state by optimizing the RMP strength. The integrated process achieves $\beta_\textrm{N}$ up to ~2.65 during the suppression phase, which is ~10% higher than the previous KSTAR record but ~6% lower than the target of the K-DEMO first phase ($\beta_\textrm{N}$ = 2.8), and maintains the suppression phase above the lower limit of target $\beta_\textrm{N}$ (= 2.4) for ~4 s (~60$\tau_\textrm{E}$). In addition to $\beta_\textrm{N}$ enhancement, the integrated process demonstrates quicker restoration of the suppression phase and recovery of $\beta_\textrm{N}$ compared to the adaptive control with the n = 1 Conventional RMP (CRMP). The post-analysis of the experiment shows the localized effect of the ERMP spectrum in radial and the close relationship between the evolution of $\beta_\textrm{N}$ and the electron temperature.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗