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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 667 records · Page 37
All sourcesNASA NTRSDOE OSTI
DOE OSTI2025

Innovative approach to counterfeit and noncompliant refrigerant detection: A cost-effective, portable solution

The increasing prevalence of counterfeit and incompatible refrigerants presents significant risks to Heating, Ventilation, Air Conditioning, and Refrigeration (HVAC&R) systems, including compromised equipment performance, safety hazards, and non-compliance. This article details the development of a novel, cost-effective, and portable detection device designed to accurately verify refrigerants. The device utilizes a controlled gas sampling and analysis system within a sealed chamber, ensuring precise measurements while maintaining safety through a purging mechanism. The system features a high-sensitivity sensor integrated with an onboard control module that analyzes gas composition in real-time, providing feedback within a 2-minute duration. Laboratory validation demonstrated the device’s high accuracy (>95 % based on correct identification of compliant vs. non-compliant blends) in detecting unauthorized refrigerant blends. The projected cost of the product stands at ∼ $150, based on the retail pricing of individual components. Laboratory validation demonstrated the device’s high accuracy (>95 % for composition identification, 100 % rejection of tested counterfeit/incorrect blends) in detecting unauthorized refrigerant blends with a response time <2 min. The device correctly identified authentic R-454A/B/C blends and reliably rejected R-407F and closely related counterfeit mixtures. Key advantages include affordability, ease of use, rapid response time, and compatibility with a wide range of refrigerants. This solution supports compliance with regulatory frameworks, enhances safety in HVAC&R operations, and mitigates the risks associated with counterfeit refrigerants.

Counterfeit refrigerants↗
DOE OSTI2026

Determining the extent of potential fugitive fluid migration from geologic carbon storage in hydrocarbon-bearing reservoirs: Insights from one-dimensional numerical modeling

Numerical modeling of Geologic Carbon Sequestration in permeable reservoirs initially containing hydrocarbons is conducted using the multi-phase, multi-component thermohydrologic simulator TOGA (TOUGH Oil, Gas, Aqueous; TOUGH stands for Transport Of Unsaturated Groundwater and Heat), to determine how phase and composition of the original fluids influence the extent of the zone where upward fugitive fluid migration could potentially occur, denoted R f . The area within R f comprises regions of substantially elevated pressure and free-phase CO 2 saturation, where a breach in reservoir sealing capacity would lead to upward fugitive fluid migration. The model examines the conditions within the storage reservoir that could lead to fugitive flow, but does not model the fugitive flow itself. A one-dimensional radial model of the storage reservoir is used, and three initial phase conditions are considered: single-phase aqueous, two-phase gas-aqueous, and three-phase oil-gas-aqueous. Components that may be present are H 2 O, CO 2 , CH 4 , C 4 H 10 , and C 10 H 22 . The most important factors controlling Rf are (1) the initial gas-phase saturation within the reservoir, and (2) the lateral extent of multi-phase initial conditions, particularly CO 2 . The composition of liquid and gas phases has a secondary effect. The impact of reservoir depth, thickness, injection rate, and hydrologic properties are also briefly examined, with thickness (or equivalently injection rate) having the biggest effect. These results can help to understand important trends in potential response of CO 2 -EOR fields being considered for dedicated CO 2 storage.

CO₂ plume migration↗
DOE OSTI2024

Numerical analysis of coalescence-induced bubble departure for enhanced boiling heat transfer

Boiling heat transfer plays a crucial role in a wide range of applications, such as power generation, refrigeration, electronics cooling, and pharmaceutics. Among the various factors that influence boiling heat transfer, the dynamics of vapor bubble nucleation, growth, and departure from the heated surface stand out as particularly important. An emerging phenomenon that can promote the departure of bubbles smaller than the Fritz diameter is coalescence-induced departure. If the dynamics of this process are fully understood, then surfaces can be engineered to promote faster bubble departure and substantially increase the performance of boiling heat transfer. Further, this work expands on published results by presenting a detailed numerical analysis of bubble coalescence and departure for a range of initial bubble diameters and size ratios between coalescing bubbles. Analysis of the results is focused on explaining how the release of surface energy and bubble surface dynamics lead to bubble departure, as well as fundamentally distinguishing capillary–inertial jumping and buoyant–inertial departure mechanisms across different bubble sizes and size ratios. The results show that both the initial sizes of the coalescing bubbles and the ratio between their sizes can determine whether the merged bubble will leave the surface through capillary–inertial jumping or buoyant departure. Below a certain bubble size, the release of surface energy by the merger is not sufficient to propel the merged bubble from the surface.

42 ENGINEERING↗
DOE OSTI2023

A numerical study of an atomizing jet in a resonant acoustic field

By applying state-of-the-art, high-fidelity methods for compressible multiphase flows, this work features a parametric study of a turbulent liquid jet atomizing under the influence of standing acoustic waves with five different amplitude values. We perform these simulations in a semi-periodic domain to isolate interactions between acoustic and atomization processes and to emulate a pure liquid fuel spray placed at the pressure node of a resonant acoustic field. Characterization of the flow includes measurements of the mean dimensions, droplet number, and surface area of the liquid distribution, alongside qualitative depictions of the interface evolution, breakup events, and hydrodynamic fields. As acoustic forcing is provided to the flow, the added energy provokes atomization when shear would otherwise be insufficient for breakup. The magnitude of the forcing determines the rate of droplet production, which accelerates as the evolving liquid surface modifies the induced motion of the gas phase. At the nodal plane, the acoustic field produces an organizing effect on the liquid structures.

42 ENGINEERING↗
DOE OSTI2022

DECOVALEX-2019: An international collaboration for advancing the understanding and modeling of coupled thermo-hydro-mechanical-chemical (THMC) processes in geological systems

The DECOVALEX Project is an international research collaboration for advancing the understanding and modeling of coupled thermo-hydro-mechanical-chemical (THMC) processes in geological systems. DECOVALEX stands for “DEvelopment of COupled Models and VALidation against EXperiments”. The creation of this international initiative, now running for almost 30 years, was motivated by the recognition that prediction of these coupled effects is an essential part of the performance and safety assessment of geologic disposal systems for radioactive waste and spent nuclear fuel, and also for a range of other sub-surface engineering activities. DECOVALEX emphasizes joint analysis and comparative modeling of state-of-the-art field and laboratory experiments, across a range of host rock options and repository designs. Participating research teams are from radioactive waste management organizations, national research institutes, regulatory agencies, universities, and consulting groups, providing a wide range of perspectives and solutions to these complex problems. The most recent phase of the DECOVALEX Project, here referred to as DECOVALEX-2019, started in 2016 and ended in 2019. Modeling teams from 13 international partner organizations participated in the comparative evaluation of seven modeling tasks involving complex field and/or laboratory experiments. Furthermore, this Virtual Special Issue on DECOVALEX-2019 provides an in-depth overview of these collaborative research efforts and how these have advanced the state-of-the-art of understanding and modeling coupled THMC processes.

58 GEOSCIENCES↗
DOE OSTI2021

Clinical Natural Language Processing for Radiation Oncology: A Review and Practical Primer

Natural language processing (NLP), which aims to convert human language into expressions that can be analyzed by computers, is one of the most rapidly developing and widely used technologies in the field of artificial intelligence. Natural language processing algorithms convert unstructured free text data into structured data that can be extracted and analyzed at scale. In medicine, this unlocking of the rich, expressive data within clinical free text in electronic medical records will help untap the full potential of big data for research and clinical purposes. Recent major NLP algorithmic advances have significantly improved the performance of these algorithms, leading to a surge in academic and industry interest in developing tools to automate information extraction and phenotyping from clinical texts. Thus, these technologies are poised to transform medical research and alter clinical practices in the future. Radiation oncology stands to benefit from NLP algorithms if they are appropriately developed and deployed, as they may enable advances such as automated inclusion of radiation therapy details into cancer registries, discovery of novel insights about cancer care, and improved patient data curation and presentation at the point of care. However, challenges remain before the full value of NLP is realized, such as the plethora of jargon specific to radiation oncology, nonstandard nomenclature, a lack of publicly available labeled data for model development, and interoperability limitations between radiation oncology data silos. Successful development and implementation of high quality and high value NLP models for radiation oncology will require close collaboration between computer scientists and the radiation oncology community. Here, we present a primer on artificial intelligence algorithms in general and NLP algorithms in particular; provide guidance on how to assess the performance of such algorithms; review prior research on NLP algorithms for oncology; and describe future avenues for NLP in radiation oncology research and clinics.

62 RADIOLOGY AND NUCLEAR MEDICINE↗
DOE OSTI2025

Process intensification approach to enhancing heat and mass transfer: Radio frequency (RF) assisted drying of paper and board

Conventional multi-cylinder drying of paper and board typically relies on both conductive drying from steam-heated cylinders and convective drying, where heated air flows over the paper web surface. Conduction primarily contributes to heat transfer, while convection is the main driver of mass transfer. However, conventional drying systems are heavily dependent on steam, usually powered by fossil fuels, and are often energy-inefficient with high levels of waste. Additionally, these surface-driven processes result in a lower percentage of energy absorption compared to the energy supplied, leading to significant energy losses. To improve this long-standing process, an experimental system was developed to investigate a process intensification approach involving the integration of Radio Frequency (RF) heating, a volumetric electromagnetic technology, alongside traditional conduction and convection drying methods. This study also emphasizes the use of sensors to continuously monitor key parameters such as moisture content, supply system temperatures, sample temperatures, air flows, and drying rates in real-time. The effect of RF as an auxiliary energy source in localized environments at varying moisture levels was explored to optimize industrial drying systems, quantify potential improvements, and provide insights for future studies. Experimental results from trials combining RF with convection and with the base case alternating conduction-convection drying processes are presented. It is shown that RF is a viable process intensification approach for paper drying improving the drying rate and energy intensity at higher moisture contents. These findings offer valuable insights for process intensification and contribute to the process development, modeling, and simulation of advanced paper drying techniques.

42 ENGINEERING↗
DOE OSTI2023

Towards functionalized lignin and its derivatives for high-value material applications

In pursuit of low-carbon development, the production of diverse functional materials from renewable resources, especially lignocellulosic biomass, is of vital importance. Lignin is a major component of lignocellulose, and it is nature's only true high-volume aromatic polymer, which has the advantages of biodegradability, biocompatibility, and low acquisition cost. After modification by a variety of physicochemical strategies, it can be applied as an alternative to basic industrial materials, including polyurethanes, phenolic, and epoxy resins, which stands comparably to conventional synthetic polymers in terms of both performance and reduced cost. To further unlock the potential of lignin, an alluring opportunity is the exploitation of lignin for high-value materials, especially nanomaterials, that find extensive applications in energy and environment areas. This review provides a systematic summary and perspective of research that has been devoted to lignin transformation to high-value materials, ranging from industrially well-established engineering materials to the recently emerged nanomaterials that were used for energy and environment applications. Latest cutting-edge innovations on lignin modification, controlled depolymerization, and assembly during the last five years are summarized. Structure-function relationships of lignin materials in terms of their specific applications are analyzed. Furthermore, challenges and future opportunities for lignin conversion to high-value materials are also provided. We wish this review will stimulate further advances in lignin based high-value materials, and promote “waste” into “wealth”.

36 MATERIALS SCIENCE↗
DOE OSTI2026

Propagation method and planting density influence canopy developmental transition and biomass productivity in Miscanthus × giganteus

Understanding how establishment practices influence the mechanisms underlying Miscanthus × giganteus (miscanthus) productivity and canopy development is critical for optimizing management. Data was collected during the juvenile (2011–2013) and mature (2024) phases of a long-term field experiment established in Urbana, Illinois, to evaluate the effects of propagation method (plug propagation [PP] and rhizome propagation [RP]), planting density (1.0, 0.75, and 0.25 plants m⁻²), and nitrogen application (0 and 67 kg N ha⁻¹) on end-of-season biomass yield, tiller mass, tiller density, and tiller height. Linear regression models identified the dominant predictors of yield across stand ages and management regimes. Planting density, nitrogen (N) application, and propagation method significantly influenced early yield and canopy development. During the juvenile phase, biomass yield was driven by tiller density due to canopy expansion; in the mature phase, yield became driven by tiller mass. The PP plots produced higher tiller density than the RP plots, resulting in faster canopy closure and higher juvenile-phase yields. Rhizome-propagated (RP) plots produced lower tiller density, but individual tillers were 3.3–6.4 g tiller −1 heavier than PP tillers. After the canopy reached equilibrium, the PP and RP yields were similar because greater RP tiller mass compensated for its lower tiller density. Higher planting density resulted in greater yield and tiller density during the second year (2012), but this effect was absent from the third year (2013) onward. In the juvenile phase, N fertilization enhanced yield by 1.6–3.4 Mg ha −1 . Initiating fertilization in 2013 on unfertilized plots produced biomass similar to that in fertilized plots, suggesting yield recovery in the mature phase. These findings revealed that establishment strategies, including propagation method and planting density, influence juvenile miscanthus canopy development and productivity, transitioning from tiller-density- to mass-dominated yields, but not mature phase productivity.

09 BIOMASS FUELS↗
DOE OSTI2022

Machine learning magnetism classifiers from atomic coordinates

The determination of magnetic structure poses a long-standing challenge in condensed matter physics and materials science. Experimental techniques such as neutron diffraction are resource-limited and require complex structure refinement protocols, while computational approaches such as first-principles density functional theory (DFT) need additional semi-empirical correction, and reliable prediction is still largely limited to collinear magnetism. Here, we present a machine learning model that aims to classify the magnetic structure by inputting atomic coordinates containing transition metal and rare earth elements. By building a Euclidean equivariant neural network that preserves the crystallographic symmetry, the magnetic structure (ferromagnetic, antiferromagnetic, and nonmagnetic) and magnetic propagation vector (zero or non-zero) can be predicted with an average accuracy of 77.8% and 73.6%. In particular, a 91% accuracy is reached when predicting no magnetic ordering even if the structure contains magneticelement(s). Ourworkrepresents onestepforwardtosolvingthegrand challenge of full magnetic structure determination.

75 CONDENSED MATTER PHYSICS, SUPERCONDUCTIVITY AND↗
DOE OSTI2021

Enhanced superelasticity of nanocrystalline NiTi/NiTiNbFe laminar composite

This study explores a new concept of the synergy between two constituent shape memory alloys (SMAs) in a composite to achieve a wide superelastic temperature window. In this work, a nanocrystalline NiTi/NiTiNbFe dual-SMA composite is designed, in which two constituent SMAs are both capable of stress-induced martensitic transformation, but within different temperature ranges. Based on the principle of lattice strain matching between the two SMAs, superelastic martensitic transformation in one induces superelastic transformation in the other at temperatures the latter will not when standing alone. Furthermore, via this synergy the composite is able to achieve an ultra-wide superelastic temperature window of 336°C, from -196 to 140°C, with a ~5% tensile strain recovery and high superelastic stresses in the range of 700~1400 MPa. Such properties appear superior to all NiTi-based shape memory alloys to date.

36 MATERIALS SCIENCE↗
DOE OSTI2020

Solid-solid phase transition via the liquid in a Pd 43 Cu 27 Ni 10 P 20 bulk metallic glass under conventional conditions

The microscopic mechanism of solid-solid phase transitions is a long-standing fundamental issue in materials science. Here we directly report the experimental evidence of the existence of an intermediate liquid during the solid-solid phase transition in a bulk Pd 43 Cu 27 Ni 10 P 20 alloy by in situ high temperature high energy X-ray diffraction, combined with the differential scanning calorimetry at slow heating rates down to 5 K/min. We elucidate that this intermediate liquid is attributed to the melting of the low-melting-point crystalline phases, rather than induced by the elastic stress energy along the interface proposed in literatures. This could also be a general feature in multicomponent alloys if a low-melting-point crystalline phase is formed together with other crystalline phases during heating. Furthermore, all results obtained here are scientifically sound and provide new insight into the phase transition theory, which will trigger more studies on the microscopic mechanism of solid-solid phase transition via an intermediate liquid.

36 MATERIALS SCIENCE↗
DOE OSTI2020

Detecting an underground tunnel by applying joint traveltime and waveform inversion

Underground tunnel and void detection is a challenging geophysical problem, and many methods have been proposed. Seismic techniques are promising because of the large seismic velocity contrasts between the air-filled void and the surrounding sediment and concrete. We apply a joint seismic traveltime and waveform inversion method to image a buried tunnel with concrete walls and a void space inside. The joint inversion images the top of the concrete tunnel as a high-velocity anomaly and the void space as a low-velocity anomaly. The location of the velocity anomalies predicted by the method agrees with the known location of the tunnel. As a comparison, the stand-alone full waveform inversion is also applied to the data. The first-arrival traveltime tomography shows weak nonlinearity but fails to image the hidden low-velocity layer. Full waveform inversion is able to image complex near-surface structures, but fitting waveforms may not honor the traveltime fit, especially when the data contain noise. Synthetic and real data tests show that the joint inversion method retains the advantages of both traveltime inversion and full waveform inversion and overcomes their respective drawbacks at the same time. The field example shows the joint inversion provides a better reconstruction of the high-velocity feature representing the top of the concrete wall in terms of its magnitude and location.

58 GEOSCIENCES↗
DOE OSTI2020

Solving the auroral-arc-generator question by using an electron beam to unambiguously connect critical magnetospheric measurements to auroral images

Here, an active mapping mission is described that unambiguously connects measurements in the Earth's magnetosphere to visible aurora in the atmosphere. The core of the mission is an electron-beam source operated on a spacecraft in the equatorial magnetosphere, with the electron beam traveling along the Earth's magnetic-field lines to the atmosphere, depositing its energy to create an optical beam-spot in the atmosphere at the footpoint of the spacecraft's magnetic-field line. This optical spot can be imaged by ground-based cameras, putting the location of the spacecraft's magnetic footpoint into the context of the optical aurora. Scientific instruments carried on the spacecraft make critical measurements of the properties of the magnetosphere at the locations where the magnetosphere powers the aurora, allowing the determination of the plasma-physics mechanisms by which the magnetosphere drives the aurora, in particular answering the outstanding question of how the magnetosphere drives low-latitude auroral arcs. Long-standing questions in magnetosphere-ionosphere coupling that have not been answered because we could not unambiguously connect locations in the magnetosphere with their image in the ionosphere will finally be addressed. In this paper the properties of a “standard” growth-phase auroral arc are collected, theories of the magnetospheric generation of auroral arcs are reviewed, and critical magnetospheric measurements to discern the mechanisms that drive auroral arcs are determined. Further, the plasma physics of the experiment is investigated, including spacecraft-charging mitigation, beam stability, beam scattering, and electron orbit theory. Tradeoffs (keV versus MeV) concerning the energy of the electron beam are enumerated.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗
DOE OSTI2021

Unseeded, spontaneous nucleation of spherulitic magnesium calcite

Most of the sedimentary carbonates deposited in the marine environments are composed of calcium carbonate minerals with varying amounts of incorporated Mg 2+ . However, understanding how interactions of impurities with carbonate and their incorporation affect sediments behavior remains a challenge. Here, a new insight is obtained by monitoring solution composition, morphology, and electrokinetic potential of carbonate particles formed in a spontaneous unseeded batch precipitation experiment using electrochemical and scanning electron microscopy methods. The solid composition and growth rate are extracted from changes in the bulk composition and fitted to chemical affinity rate law, revealing that the precipitation pathway consists of second-order dissolution and first-order precipitation. The molecular dynamics simulations show that the lattice strain induced by randomly substituting Ca 2+ by Mg 2+ stabilizes spherical nanoparticles and reduces their surface area and volume. Combining kinetics and thermodynamics insight, we conclude that variation in the carbonate bulk and interfacial energies, along with the solution supersaturation, lead to the dissolution-precipitation transformation pathway from Mg-rich to Mg-poor carbonate phase that preserves spherulitic morphology. Furthermore, our findings are relevant for long-standing questions of how impurities influence diagenesis of carbonate sediments and spherulitic carbonate particles' origin.

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

Noise and error analysis and optimization in particle-based kinetic plasma simulations

In this paper we analyze the noise in macro-particle methods used in plasma physics and fluid dynamics, leading to approaches for minimizing the total error, focusing on electrostatic models in one dimension. We begin by describing kernel density estimation for continuous values of the spatial variable x, expressing the kernel in a form in which its shape and width are represented separately. The covariance matrix of the noise in the density is computed, first for uniform true density. The bandwidth of the covariance matrix C(x,y) is related to the width of the kernel. A feature that stands out is the presence of constant negative terms in the elements of the covariance matrix both on and off-diagonal. These negative correlations are related to the fact that the total number of particles is fixed at each time step; they also lead to the property ∫C(x,y)dy = 0. We investigate the effect of these negative correlations on the electric field computed by Gauss's law, finding that the noise in the electric field is related to a process called the Ornstein-Uhlenbeck bridge, leading to a covariance matrix of the electric field with variance significantly reduced relative to that of a Brownian process. For non-constant density, p(x), still with continuous x, we analyze the total error in the density estimation and discuss it in terms of bias-variance optimization (BVO). For some characteristic length l, determined by the density and its second derivative, and kernel width h, having too few particles within h leads to too much variance; for h that is large relative to l, there is too much smoothing of the density. The optimum between these two limits is found by BVO. For kernels of the same width, it is shown that this optimum (minimum) is weakly sensitive to the kernel shape. Next, we repeat the analysis for x discretized on a grid. In this case the charge deposition rule is determined by a particle shape. An important property to be respected in the discrete system is the exact preservation of total charge on the grid; this property is necessary to ensure that the electric field is equal at both ends, consistent with periodic boundary conditions. We find that if the particle shapes satisfy a partition of unity property, the particle charge deposited on the grid is conserved exactly. Further, if the particle shape is expressed as the convolution of a kernel with another kernel that satisfies the partition of unity, then the particle shape obeys the partition of unity. This property holds for kernels of arbitrary width, including widths that are not integer multiples of the grid spacing. Furthermore, we show results relaxing the approximations used to do BVO optimization analytically, by doing numerical computations of the total error as a function of the kernel width, on a grid in x. The comparison between numerical and analytical results shows good agreement over a range of particle shapes. We discuss the practical implications of our results, including the criteria for design and implementation of computationally efficient particle shapes that take advantage of the developed theory.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗
DOE OSTI2020

Homoepitaxial growth of 9,10-diphenylanthracene

Organic single crystals are often shown to have significantly improved optoelectronic properties over polycrystalline thin films such as exciton diffusivity and carrier mobility. There is growing interest in incorporating such crystals in organic electronics despite a number of challenges. In this work, the homoepitaxial vapor phase growth modes for 9,10-diphenylanthracene (DPA) homoepitaxy are mapped as a function of growth rate and temperature using in situ ultra-low current reflection high energy electron diffraction (RHEED), X-ray diffraction (XRD), and atomic force microscopy (AFM). Vapor phase deposition was performed on free-standing single crystal DPA substrates, which show clear Kikuchi patterns. At room temperature, a transition from Frank-Van der Merwe layer-by-layer growth to step-flow growth is observed as the deposition rate is decreased, while at lower temperatures a Stranski-Krastanov layer-plus-island growth is observed. This is the first demonstration of true step-flow growth from room temperature vapor phase deposition for organic semiconductors and is reminiscent of traditional semiconductor growth regimes. Accordingly, these results could lead to improved control over growth and doping of organic single crystals, and lead to enhanced single crystal organic optoelectronic applications.

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

The life and accomplishments of Alex Chernov

We report in the last two decades, crystal growth science has experienced explosive expansion. The primary driver has been the vast range of natural and engineered materials whose understanding and optimization require in-depth knowledge of how molecules cooperate to erect perfect three dimensional translationally-symmetric arrays - the miracle that we call crystallization. These huge fundamental and applied advances were possible only because we, the current generation of researchers, stand on the shoulders of our giant forefathers. Alex Chernov is among the tallest of the crystal growth giants.

99 GENERAL AND MISCELLANEOUS↗