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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 1,729 records · Page 96
All sourcesNASA NTRSDOE OSTI
DOE OSTI2021

Machine learning assisted modeling of mixing timescale for LES/PDF of high-Karlovitz turbulent premixed combustion

Accurate modeling of mixing in the transported probability density function (PDF) method remains a great challenge, especially for turbulent premixed combustion under extreme conditions such as high Karlovitz number Ka. Recently, a power-law based mixing timescale model was developed for the large-eddy simulations (LES)/PDF modeling of high-Ka number turbulent premixed flames. It is found in this work that the power-law mixing timescale model is highly sensitive to the model parameters. It is thus critically needed to develop accurate calibration of these model parameters. The empirical specification of the model parameters developed in Zhang et. al. is found to be inadequate for accurate modeling of the mixing timescale. Here, machine learning is introduced as an attractive alternative in this work for the specification of the model parameters. A high-Ka number DNS jet flame is used as the training and validation of the machine learning models. The choices of the input parameters are discussed and compared for the machine learning models. The effect of differential molecular diffusion on mixing is examined by including the effect of the Lewis number in the training of the machine learning models. The performance of different machine learning algorithms is compared for the specification of the mixing model parameters. Overall, excellent performance of the machine learning models is observed for assisting the mixing modeling. The feasibility, interpretability, applicability, generality, and portability of using machine learning are discussed in general to provide a perspective on applying data-driven machine learning for turbulent combustion modeling studies.

42 ENGINEERING↗
DOE OSTI2024

A simultaneous depolymerization and hydrodeoxygenation process to produce lignin-based jet fuel in continuous flow reactor

Economical production of lignin-based jet fuel (LJF) can improve the sustainability of sustainable aviation fuels (SAFs) as well as can reduce the overall greenhouse gas emissions. However, the challenge lies in converting technical lignin polymer from biorefinery directly to jet fuel in a continuous operation. In this work, we demonstrate a simultaneous depolymerization and hydrodeoxygenation (SDHDO) process to produce lignin-based jet fuel from the alkali corn stover lignin (ACSL) using engineered Ru-HY-60-MI catalyst in a continuous flow reactor at first time. The maximum carbon yield of LJF of 17.9wt% was obtained, and it comprised of 60.2wt% monocycloalkanes, and 21.6wt% polycycloalkanes. Catalyst characterization of Ru-HY-60-MI suggested there was no significant change in HY zeolite structure and its crystallinity after catalyst engineering. Catalyst characterizations performed post the SDHDO experiments indicate presence of carbon and K content in the catalyst. K content presence in the spent catalyst was due to K + ion was exchanged between lignin solution and HY-60 while carbon presence validated the SDHDO chemistry on the catalyst surface. Tier a fuel property testing indicates that LJF production using SDHDO chemistry can offer SAF with high compatibility, good sealing properties, low emissions, and high energy density for aircraft.

09 BIOMASS FUELS↗
DOE OSTI2023

Evolving radon diffusion through earthen barriers at uranium waste disposal sites

Field measurements of Rn-222 fluxes from the tops and bottoms of compacted clay radon barriers were used to calculate effective Rn diffusion coefficients (D Rn ) at four uranium waste disposal sites in the western United States to assess cover performance after more than 20 years of service. Values of D Rn ranged from 7.4 × 10 -7 to 6.0 × 10 -9 m 2 /s, averaging 1.42 × 10 -7 . Water saturation (S W ) from soil cores indicated that there was relatively little control of D Rn by S W , especially at higher moisture levels, in contrast to estimates from most steady-state diffusion models. Further, this is attributed to preferential pathways intrinsic to construction of the barriers or to natural process that have developed over time including desiccation cracks, root channels, and insect burrows in the engineered earthen barriers. A modification to some models in which fast and slow pathway D Rn values are partitioned appears to give a good representation of the data; 4% of the fast pathway was needed to fit the data regression. For locations with high S w and highest D Rn (and fluxes) at each site, the proportion of fast pathway ranged from 1.7% to 34%, but for many locations with lower fluxes, little if any fast pathway was needed.

12 MANAGEMENT OF RADIOACTIVE AND NON-RADIOACTIVE W↗
DOE OSTI2025

Carbon Mineralization of Sulfate Wastes Containing Pb: Synchrotron Pb M3-Edge XANES Analysis of Simultaneous Heavy Metal and Carbon Sequestration

Sulfate wastes are produced in large quantities and contain toxic heavy metals such as lead (Pb), posing environmental risks. Because of favorable solubility differences, these wastes can be repurposed for engineered carbon dioxide (CO 2 ) sequestration. Understanding the fate and mobility of heavy metals during this process is important. This study focuses on Pb and the effect of zinc (Zn) on Pb in carbon mineralization. Synthesized gypsum was treated with a carbonate-rich solution at pH 11.5 to convert the sulfates to carbonates. Aqueous solutions and mineral solids were analyzed. Synchrotron-based micro-X-ray fluorescence and a novel application of Pb M3-edge X-ray absorption near-edge structure provided detailed insights into Pb distribution and mineral forms. Results showed significant reductions in aqueous Pb and Zn concentrations, indicating effective metal sequestration. Carbon mineralization transformed Pb from soluble anglesite (PbSO 4 ) into insoluble cerussite (PbCO 3 ) and hydrocerussite (Pb 3 (CO 3 ) 2 (OH) 2 ). Pb primarily precipitated onto calcium carbonate surfaces through surface-mediated precipitation reactions. While the presence of Zn modified crystallization dynamics, it did not impede Pb sequestration and potentially enhanced surface reactivity, facilitating greater Pb immobilization. These findings highlight carbon mineralization as a sustainable approach to immobilize toxic metals in sulfate wastes while advancing CO 2 sequestration efforts.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2024

Trailblazing Kr/Xe Separation: The Birth of the First Kr-Selective Material

Efficient separation of Kr from Kr/Xe mixtures is pivotal in nuclear waste management and dark matter research. Thus far, scientists have encountered a formidable challenge: the absence of a material with the ability to selectively adsorb Kr over Xe at room temperature. This study presents a groundbreaking transformation of the renowned metal–organic framework (MOF) CuBTC, previously acknowledged for its Xe adsorption affinity, into an unparalleled Kr-selective adsorbent. This achievement stems from an innovative densification approach involving systematic compression of the MOF, where the crystal size, interparticle interaction, defects, and evacuation conditions are synergistically modulated. The resultant densified CuBTC phase exhibits exceptional mechanical resilience, radiation tolerance, and notably an unprecedented selectivity for Kr over Xe at room temperature. Simulation and experimental kinetic diffusion studies confirm reduced gas diffusion in the densified MOF, attributed to its small pore window and minimal interparticle voids. The lighter Kr element demonstrates facile surface passage and higher diffusivity within the material, while the heavier Xe encounters increased difficulty entering the material and lower diffusivity. This Kr-selective MOF not only represents a significant breakthrough in Kr separation but also demonstrates remarkable processability and scalability to kilogram levels. Furthermore, the findings presented herein underscore the transformative potential of engineered MOFs in addressing complex challenges, heralding a new era of Kr separation technologies.

36 MATERIALS SCIENCE↗
DOE OSTI2021

Combinatorial measurement of critical cooling rates in aluminum-base metallic glass forming alloys

Direct measurement of critical cooling rates has been challenging and only determined for a minute fraction of the reported metallic glass forming alloys. Here, we report a method that directly measures critical cooling rate of thin film metallic glass forming alloys in a combinatorial fashion. Based on a universal heating architecture using indirect laser heating and a microstructure analysis this method offers itself as a rapid screening technique to quantify glass forming ability. We use this method to identify glass forming alloys and study the composition effect on the critical cooling rate in the Al–Ni–Ge system where we identified Al 51 Ge 35 Ni 14 as the best glass forming composition with a critical cooling rate of 10 4 K/s.

36 MATERIALS SCIENCE↗
DOE OSTI2026

Kinetic-controlled transformations of group-III arsenide nanocubes

Tracking the structural evolution of colloidal nanocrystals (NCs) facilitates the mechanistic studies of their materials chemistry. NC engineering via phase transformation reveals the chemical and physical determinants that drive lattice-scale dynamic processes such as cation exchange. Here, in this study, we employed NCs to demonstrate the cation exchange process from Cu 3 As to InAs and GaAs within nanocubes. The symmetry conversion in unit cells from cubic Cu 3 As to hexagonal InAs and GaAs can be described using a schematic cellular automaton model, which suggests a simplified cube-to-sphere transition. The strong covalent characteristics of III–V materials highlight the kinetic control that navigates the tailorable transformation through either an isotropic trajectory, leading to hollow structures, or a topotaxial trajectory, with abundant stacking faults. The reconstruction of complex covalent bonds is envisioned as the foundation for the synthesis of NCs.

77 NANOSCIENCE AND NANOTECHNOLOGY↗
DOE OSTI2023

Surface enrichment dictates block copolymer orientation

Orientation of block copolymer (BCP) morphology in thin films is critical to applications as nanostructured coatings. Despite being well-studied, the ability to control BCP orientation across all possible block constituents remains challenging. Here, in this study, we deploy coarse-grained molecular dynamics simulations to study diblock copolymer ordering in thin films, focusing on chain makeup, substrate surface energy, and surface tension disparity between the two constituent blocks. We explore the multi-dimensional parameter space of ordering using a machine-learning approach, where an autonomous loop using a Gaussian process (GP) control algorithm iteratively selects high-value simulations to compute. The GP kernel was engineered to capture known symmetries. The trained GP model serves as both a complete map of system response, and a robust means of extracting material knowledge. We demonstrate that the vertical orientation of BCP phases depends on several counter-balancing energetic contributions, including entropic and enthalpic material enrichment at interfaces, distortion of morphological objects through the film depth, and of course interfacial energies. BCP lamellae are found more resistant to these effects, and thus more robustly form vertical orientations across a broad range of conditions; while BCP cylinders are found to be highly sensitive to surface tension disparity.

77 NANOSCIENCE AND NANOTECHNOLOGY↗
DOE OSTI2022

Detecting hidden transient events in noisy nonlinear time-series

The information impulse function (IIF), running Variance, and local Hölder Exponent are three conceptually different time-series evaluation techniques. These techniques examine time-series for local changes in information content, statistical variation, and point-wise smoothness, respectively. Using simulated data emulating a randomly excited nonlinear dynamical system, this study interrogates the utility of each method to correctly differentiate a transient event from the background while simultaneously locating it in time. Computational experiments are designed and conducted to evaluate the efficacy of each technique by varying pulse size, time location, and noise level in time-series. Our findings reveal that, in most cases, the first instance of a transient event is more easily observed with the information-based approach of IIF than with the Variance and local Hölder Exponent methods. While our study highlights the unique strengths of each technique, the results suggest that very robust and reliable event detection for nonlinear systems producing noisy time-series data can be obtained by incorporating the IIF into the analysis.

42 ENGINEERING↗
DOE OSTI2023

Proximity-enhanced valley Zeeman splitting at the WS 2 /graphene interface

The valley Zeeman physics of excitons in monolayer transition metal dichalcogenides provides valuable insight into the spin and orbital degrees of freedom inherent to these materials. Being atomically-thin materials, these degrees of freedom can be influenced by the presence of adjacent layers, due to proximity interactions that arise from wave function overlap across the 2D interface. Here, we report 60 T magnetoreflection spectroscopy of the A- and B- excitons in monolayer WS 2 , systematically encapsulated in monolayer graphene. While the observed variations of the valley Zeeman effect for the A- exciton are qualitatively in accord with expectations from the bandgap reduction and modification of the exciton binding energy due to the graphene-induced dielectric screening, the valley Zeeman effect for the B- exciton behaves markedly different. We investigate prototypical WS 2 /graphene stacks employing first-principles calculations and find that the lower conduction band of WS 2 at the <?CDATA $K/K^{^{\prime}}$?> K / K ′ valleys (the <:tex-math><?CDATA $\mathrm{CB}^-$?> C B − band) is strongly influenced by the graphene layer on the orbital level. Specifically, our detailed microscopic analysis reveals that the conduction band at the Q point of WS 2 mediates the coupling between <?CDATA $\mathrm{CB}^-$?> C B − and graphene due to resonant energy conditions and strong coupling to the Dirac cone. This leads to variations in the valley Zeeman physics of the B- exciton, consistent with the experimental observations. Our results therefore expand the consequences of proximity effects in multilayer semiconductor stacks, showing that wave function hybridization can be a multi-step energetically resonant process, with different bands mediating the interlayer interactions. Such effects can be further exploited to resonantly engineer the spin-valley degrees of freedom in van der Waals and moiré heterostructures.

36 MATERIALS SCIENCE↗
DOE OSTI2021

Identifying Entangled Physics Relationships Through Sparse Matrix Decomposition to Inform Plasma Fusion Design

We report a sustainable burn platform through inertial confinement fusion (ICF) has been an ongoing challenge for over 50 years. Mitigating engineering limitations and improving the current design involves an understanding of the complex coupling of physical processes. While sophisticated simulation codes are used to model ICF implosions, these tools contain necessary numerical approximation but miss physical processes that limit predictive capability. Identification of relationships between controllable design inputs to ICF experiments and measurable outcomes (e.g., neutron yield, neutron velocity, areal density) from performed experiments can help guide the future design of experiments and development of simulation codes, to potentially improve the accuracy of the computational models used to simulate ICF experiments. We use sparse matrix decomposition methods to identify clusters of a few related design variables. Sparse principal component analysis (SPCA) identifies groupings that are related to the physical origin of the variables (laser, hohlraum, and capsule). A variable importance analysis finds that in addition to variables highly correlated with neutron yield, such as picket power and laser energy, variables that represent a dramatic change of the ICF design, such as number of pulse steps, are also very important. The obtained sparse components are then used to train a random forest (RF) regression surrogate for predicting total yield. The RF performance on the training and testing data compares with the performance of the RF trained using all the design variables considered. This work is intended to inform design changes in future ICF experiments by augmenting the expert intuition and simulation results.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗
DOE OSTI2022

Absolute measurement of vacuum ultraviolet photon flux in an inductively coupled plasma using a Au thin film

A new method for absolute measurement of the vacuum ultraviolet (VUV) photon flux at the edge of a plasma is described. The light produced by the plasma was allowed to strike a negatively biased, gold-coated copper substrate remote from the plasma. The resulting photoelectron emission current was measured, and the absolute photon flux was then found from the known photoelectron yield of Au. The method was used to quantify the amount of VUV light produced by an Ar/He inductively coupled plasma (ICP). Strong emissions at 104.82 and 106.67 nm, corresponding to the 1s 2 and 1s 4 resonant states of Ar, were observed. The maximum, integrated VUV photon flux measured at the remote location was 3.2 × 10 13 photons/cm 2 s. This was estimated to correspond to a flux of 5 × 10 15 photons/cm 2 s at the edge of the ICP, in the range of reported values under similar conditions.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗
DOE OSTI2025

Topology-imprinting in nonlinear metasurfaces

Flat optical components, or metasurfaces, have transformed optical imaging, data storage, information processing, and biomedical applications by providing unprecedented control over light-matter interactions. These nano-engineered structures enable compact, multidimensional manipulation of light’s amplitude, phase, polarization, and wavefront, producing scalar and vector beams with unique properties such as orbital angular momentum and knotted topologies. This flexibility has potential applications in optical communication and imaging, particularly in complex environments such as atmospheric turbulence and undersea scattering. However, designing metasurfaces for shorter wavelengths, such as visible and ultraviolet light, remains challenging due to fabrication limitations and material absorption. Here, we introduce an innovative concept called topology imprinting using judiciously designed all-dielectric nonlinear optical metasurfaces to replicate desired waveforms at fundamental and harmonic frequencies, opening promising avenues for advanced photonic applications.

42 ENGINEERING↗
DOE OSTI2022

Introduction to the Special Issue on Software Tools for Quantum Computing: Part 1

Quantum computing is emerging as a remarkable technology that offers the possibility of achieving major scientific breakthroughs in many areas. Here, by leveraging the unique features of quantum mechanics, quantum computers may be instrumental in advancing many areas, including science, energy, defense, medicine, and finance. This includes solving complex problems whose solution lies well beyond the capacity of contemporary and even future supercomputers that are based on conventional computing technologies. As a foundation for future generations of computing and information processing, quantum computing represents an exciting area for developing new ideas in computer science and computational engineering.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2023

Introduction to the Special Issue on Software Tools for Quantum Computing: Part 2

Quantum computing is emerging as a remarkable technology that offers the possibility of achieving major scientific breakthroughs in many areas. By leveraging the unique features of quantum mechanics, quantum computers may be instrumental in advancing many areas, including science, energy, defense, medicine, and finance. This includes solving complex problems whose solution lies well beyond the capacity of contemporary and even future supercomputers that are based on conventional computing technologies. As a foundation for future generations of computing and information processing, quantum computing represents an exciting area for developing new ideas in computer science and computational engineering.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2023

U328 Electrical Reliability Project Soil Sampling and Analysis Plan

Lawrence Livermore National Laboratory's (LLNL’s) Project Management Office (PMO) is planning to install an underground electrical duct bank at the 3200 block of the Livermore Site (project). The proposed project will include a new electrical substation and feeders, demolition and replacement of the U328C utility building with a new structure to the west, re-routing of utilities, and update of the parking lot. This Sampling and Analysis Plan (SAP) outlines the procedures to collect and evaluate environmental samples for disposition of the excavated soil during the project and geotechnical samples for pavement design. This SAP has been prepared and is organized to be consistent with LLNL's Soils Screening and Management Plan (SSMP) (LLNL, 2022), as well as the U.S. Environmental Protection Agency's (EPA) Data Quality Objectives (DQO) process (EPA, 2006). In addition to the environmental samples, geotechnical samples will be collected by Consolidated Engineering Laboratories (CEL) on behalf of PMO. Geotechnical samples will be collected from a dedicated geotechnical boring location or co-located with environmental samples. Collection and evaluation of the geotechnical samples is determined by CEL and is therefore not discussed in this SAP.

54 ENVIRONMENTAL SCIENCES↗