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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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This work describes an analytical procedure, single particle-inductively coupled plasma-time-of-flight-mass spectrometry (SP-ICP-TOF-MS), that was developed to determine the platinum binding efficiency of protein-coated magnetic microparticles.
This work describes the examination of two derivatives of dipicolinic acid as the stripping reagents in the combined HEH[EHP], Cyanex-923 system TALSPEAK-MME. The investigation focused on the behavior of the lanthanides, Am, and the transition metals Zr, Mo, Pd, Ru and Rh in the extraction, solvent conditioning, and stripping steps. Solvent conditioning with glycine buffer solutions was shown to be effective for the removal of entrained HNO3¬ as well as managing Pd concentration prior to stripping. The stripping kinetics revealed very rapid phase transfer reactions. The DPA derivatives were shown to have comparable performance to traditional polyaminopolycarboxylate ligands in this system.
Our industrial client (Geo40) has developed and deployed a process to remove silica from geothermal fluids and produce a high-margin specialty colloidal silica product comparable to those of market leaders. Geo40 now wishes to explore opportunities to extend their mineral extraction operations to other elements that are present in these brines. Geo40 has identified cesium (Cs) that is present in Ohaaki brines (pH ~8–8.5) at parts per million levels and could be sold to customers if it could be produced at an attractive price. With support from the Department of Energy’s (DOE’s) Geothermal Technologies Office, a simple and highly cost-effective magnetic nanofluid method for extraction of rare earth elements (REEs) from geothermal brine solutions has been developed and demonstrated at the laboratory bench scale at Pacific Northwest National Laboratory (PNNL). Core shell sorbent particles are produced using an iron oxide core particle, which is used to anchor and grow a surrounding adsorbent shell functionalized with a chelating ligand that selectively binds REEs. We extended PNNL’s work by exploring new sorbent shells that are highly selective for Cs. Uptake of Cs was measured as a function of exposure time by analyzing solution samples extracted from batch sorption tests.
Here, in this study, we introduce a novel approach to coupled-cluster Green's function (CCGF) embedding by seamlessly integrating conventional CCGF theory with the state-of-the-art sub-system embedding sub-algebras coupled cluster (SES-CC) formalism. This integration focuses primarily on delineating the characteristics of the sub-system and the corresponding segments of the Green's function, defined explicitly by active orbitals. Crucially, our work involves the adaptation of the SES-CC paradigm, addressing the left eigenvalue problem through a distinct form of Hamiltonian similarity transformation. This advancement not only facilitates a comprehensive representation of the interaction between the embedded sub-system and its surrounding environment but also paves the way for the quantum mechanical description of multiple embedded domains, particularly by employing the emergent quantum flow algorithms. Our theoretical underpinnings further set the stage for a generalization to multiple embedded sub-systems. This expansion holds significant promise for the exploration and application of non-equilibrium quantum systems, enhancing the understanding of system–environment interactions. In doing so, the research underscores the potential of SES-CC embedding within the realm of quantum computations and multi-scale simulations, promising a good balance between accuracy and computational efficiency.
The need to determine scattering amplitudes of few-hadron systems for arbitrary kinematics expands a broad set of subfields of modern-day nuclear and hadronic physics. In this work, we expand upon previous explorations on the use of real-time methods, like quantum computing or tensor networks, to determine few-body scattering amplitudes. Such calculations must be performed in a finite Minkowski spacetime, where scattering amplitudes are not well defined. Our previous work presented a conjecture of a systematically improvable estimator for scattering amplitudes constructed from finite-volume correlation functions. Here we provide further evidence that the prescription works for larger kinematic regions than previously explored as well as a broader class of scattering amplitudes. Finally, we devise a new method for estimating the order of magnitude of the error associated with finite time separations needed for such calculations. In units of the lightest mass of the theory, we find that to constrain amplitudes using real-time methods within O ( 10 % ) , the spacetime volumes must satisfy m L ∼ O ( 10 – 10 2 ) ) and m T ∼ O ( 10 2 – 10 4 ) . Published by the American Physical Society 2024
New computational tools for solid-state synthesis recipe design are needed in order to accelerate the experimental realization of novel functional materials proposed by high-throughput materials discovery workflows. This work contributes a cellular automaton simulation framework for predicting the time-dependent evolution of intermediate and product phases during solid-state reactions as a function of precursor choice and amount, reaction atmosphere, and heating profile. The simulation captures the effects of reactant particle spatial distribution, particle melting, and reaction atmosphere. Reaction rates based on rudimentary kinetics are estimated using density functional theory data from the Materials Project and machine learning estimators for the melting point and the vibrational entropy component of the Gibbs free energy. The resulting simulation framework allows for the prediction of the likely outcome of a reaction recipe before any experiments are performed. We analyze five experimental solid-state recipes for BaTiO 3 , CaZrN 2 , and YMnO 3 found in the literature to illustrate the performance of the model in capturing reaction selectivity and reaction pathways as a function of temperature and precursor choice. This simulation framework offers an easier way to optimize existing recipes, aid in the identification of intermediates, and design effective recipes for yet unrealized inorganic solids in silico .
The goal of this paper was to assess the dynamic properties of a new class of materials, High entropy alloys (HEAs). Specifically, gas gun experiments coupled with recovery were performed on a specific HEA, FeCrMnNi, to measure its equation of state (EOS) and its spall strength, which is a measure of the stress required to nucleate voids under shock loading conditions. While there has been a plethora of work performed to assess the mechanical properties of these HEAs under uniaxial stress conditions as a function of strain rate, investigation of its properties in dynamic extremes remains rare. The current work fills this gap in knowledge for this novel class of materials. Our results show that the measured EOS for this material at one velocity was in reasonable agreement with an estimated Hugoniot. Furthermore, while the spall strength for this material was found to be ~1.9 GPa, with some variation based on sample location, the main failure mode was brittle. This brittle failure leading to formation of cracks in the material is different than the ductile failure observed in pure iron and its alloys.
The goal of this paper was to assess the dynamic properties of a new class of materials, High entropy alloys (HEAs). Specifically, gas gun experiments coupled with recovery were performed on a specific HEA, FeCrMnNi, to measure its equation of state (EOS) and its spall strength, which is a measure of the stress required to nucleate voids under shock loading conditions. While there has been a plethora of work performed to assess the mechanical properties of these HEAs under uniaxial stress conditions as a function of strain rate, investigation of its properties in dynamic extremes remains rare. The current work fills this gap in knowledge for this novel class of materials. Our results show that the measured EOS for this material at one velocity was in reasonable agreement with an estimated Hugoniot. Furthermore, while the spall strength for this material was found to be ~1.9 GPa, with some variation based on sample location, the main failure mode wasbrittle. This brittle failure leading to formation of cracks in the material is different than the ductile failure observed in pure iron and its alloys. DOE/NV/03624--1298
In 1941 G.I. Taylor proposed the cylinder test as an experiment to determine the properties of explosive products. The test consists of a hollow metal cylinder containing an unreacted cylindrical charge of explosives. The charge is detonated at one end of the cylinder and, as the detonation wave propagates, the product gas expands behind it. As the product gas is produced, the pressure acting on the metal increases and begins to push the walls outward. Consider the time at which the detonation wave has reached the halfway point between the two ends of the cylinder. In front of the wave nothing has changed and the metal tube has the same initial radius. Behind the wave, the radius of the tube has expanded. The farther behind the wave a section of tube is, the larger its radius has become. The longer the wall is exposed to the pressurized gas, the more it expands, so that the radius is largest where the detonation was initiated. The metal most commonly used for this experiment is soft copper. Its material properties are well known and soft copper is also easy to shape with precision machining. During the cylinder test the radial expansion of the cylinder is measured over time and this data is used to determine the amount of work applied to the cylinder wall by the product gas as a function of time. Since volume increases in this problem, the time dependence can be seen as a volume dependence. The volume dependent work yields a path in thermodynamic space. The cylinder test experiment can be modeled using simulation. The simulation gives you the answer, but it cannot tell you why. The goal of the proposed work is to use analytic analysis methods to give insight into the simulation solution.
Water content is the most influential factor in the performance of ion-exchange membranes (IEMs), controlling their mechanical rigidity, ionic conductivity, and degradation rates. Membranes absorb water exponentially at high water activity (a w ), making that region of the sorption isotherm the most influential on membrane properties. Plasticization of the polymer by water has been proposed to cause this exponential uptake at high a w . However, an integrated microscopic picture of the structure, thermodynamic, and mechanical properties of IEMs as a function of a w has remained elusive. In this work, we use large-scale molecular simulations validated with experimental measurements to compute the sorption isotherms, Young’s modulus, polymer dynamics, and structure of IEMs. The simulations unveil that the exponential increase in water uptake (WU) coincides in all cases with the glass to rubber transition of the membrane, as measured through its Young’s modulus and segmental polymer dynamics. Functionalization of the polymer with alkyl groups further contributes to its plasticization, increasing the WU at a given a w and ion-exchange capacity (IEC). The alkyl chains act synergistically with water to plasticize the polymer matrix and allow water penetration in the membrane. The simulations reveal that the width of the water channels depends on the ratio λ of water to ions in the polymer but is independent of its IEC. We conclude that differences in the polymer matrix–not the water channels–are responsible for the distinct uptake response of IEMs to the thermodynamic driving force of water activity.
In this work, we used a compact, high-resolution, and magnetic resonance imaging (MRI)-compatible positron emission tomography (PET) camera (VersaPET) to assess the feasibility of measuring the image-derived input function (IDIF) from arteries in the leg with the ultimate goal of enabling fully quantitative PET brain imaging without blood sampling. We used this approach in five 18 F-FDG PET/MRI brain studies in which the input function was also acquired using the gold standard of serial arterial blood sampling. After accounting for partial volume, dispersion, and calibration effects, we compared the metabolic rates of glucose (MRglu) quantified from VersaPET IDIFs in 80 brain regions to those using the gold standard and achieved a bias and variability of <5% which is within the range of reported test-retest values for this type of study. We also achieved a strong linear relationship (R 2 >0.97) against the gold standard across regions. The results of this preliminary study are promising and support further studies to optimize methods, validate in a larger cohort, and extend to the modeling of other radiotracers.
Accurate predictions of spatial power and temperature distributions require the coupling of a neutron transport solver with a thermal-hydraulic (TH) feedback. Nowadays, Monte Carlo (MC) codes are widely coupled to TH solvers, typically via a Picard iteration (PI) method, due to the higher fidelity that such frameworks can produce. To speed up a PI, a prediction step can produce an improved initial guess for a source distribution and feed it to the MC code. Recent work investigated a prediction step that uses generalized transfer functions (GTFs) to predict the macroscopic cross sections' variations following a perturbation in TH properties, such as coolant density. The previous method also relied on first order perturbation (FOP) theory to predict perturbed power profiles, rather than using an expensive MC iterate. The implemented FOP method relied on generating a fission matrix from which the forward and adjoint Eigenmodes were extracted and later used to for power calculations. The generation of the fission matrix can introduce a significant computational overhead, therefore undermining the performance of the proposed hybrid technique when applied to high-dimensional problems, e.g., full core calculations. This work attempts to improve the GTF-FOP prediction step by replacing the FOP solver with a nodal diffusion solver, thus eliminating the need to calculate a fission matrix. The GTF-diffusion step was tested for various moderator density perturbations. In each case, the predicted power distribution showed good agreement with the reference case. The latter is attributed to the generally good prediction of most spatially distributed macroscopic cross sections, except the transport cross section, which will become the focus of future work. (authors)
In this work, I explore the concept of quantization as a mapping from classical phase space functions to quantum operators. I discuss the early history of this notion of quantization with emphasis on the works of Schrödinger and Dirac, and how quantization fit into their overall understanding of quantum theory in the 1920's. Dirac, in particular, proposed a quantization map which should satisfy certain properties, including the property that quantum commutators should be related to classical Poisson brackets in a particular way. However, in 1946, Groenewold proved that Dirac's mapping was inconsistent, making the problem of defining a rigorous quantization map more elusive than originally expected. This result, known as the Groenewold-Van Hove theorem, is not often discussed in physics texts, but here I will give an account of the theorem and what it means for potential ``corrections” to Dirac's scheme. Other proposals for quantization have arisen over the years, the first major one being that of Weyl in 1927, which was later developed by many, including Groenewold, and which has since become known as Weyl Quantization in the mathematical literature. Another, known as Geometric Quantization, formulates quantization in differential-geometric terms by appealing to the character of classical phase spaces as symplectic manifolds; this approach began with the work of Souriau, Kostant, and Kirillov in the 1960's. I will describe these proposals for quantization and comment on their relation to Dirac's original program. Along the way, the problem of operator ordering and of quantizing in curvilinear coordinates will be described, since these are natural questions that immediately present themselves when thinking about quantization.
We demonstrate that surface-based mechanical testing can be used to quantify a wide range of mechanical properties determined using traditional uniaxial tension experiments. These include mapping of dynamic stress–strain behaviour, which can be used as a screening tool for uniaxial tensile ductility (uniform elongation), fracture toughness (K C ), which is shown to be in good agreement with reported plane-strain K IC , as well work-hardening exponents (n), activation volumes (V) energies (Q) and strain-rate sensitivity (m) exponents as a function of temperature. Advantages of the surface-based approach are the ability to work with significantly smaller volumes and accommodate processing defects like pores, voids and cracks. These methods are applied to ultra-fine grained tungsten (average grain size of 650 nm), as it is an ideal candidate for alloy development efforts in advanced energy systems. Tungsten is a useful baseline as it exhibits a near-ambient temperature (approx. 200°C) ductile-to-brittle transition temperature (DBTT), enabling validation efforts for the proposed methods, and extraordinary material properties, including the highest melting temperature of any metal and complex temperature and strain-rate dependencies linked to transitions in dislocation mechanisms.
Understanding time-dependent processes and light-matter interaction in strongly correlated materials, and the interplay between electronic, orbital, vibrational, and spin degrees of freedom, is a cornerstone of condensed matter. These mechanisms can be proven by measuring the response of the systems to time-dependent perturbations. The corresponding time scales are dictated by the way light couples to the different excitations, and how these excitations exchange energy and momentum. Our research advances our understanding of these processes, and the interpretation of different equilibrium and time-resolved spectroscopies. Our project encompasses two main themes: (i) developing and refining computational techniques to study non-equilibrium spectroscopies including non-perturbative effects and (ii) applications to non-equilibrium phenomena. We have developed a new computational approach that works directly in the time domain: by including all the degrees of freedom involved in the scattering process (e.g. electrons, photons, neutrons), we solve the time dependent problem: a faithful numerical simulation of the experiment. By measuring the energy and momentum of the outgoing particles, we can extract information about the energy and momentum absorbed by the system. Prior to our work, people attempting to model and calculate non-equilibrium spectral functions relied on a description of the scattering cross section based on a formulation in the frequency domain, a treatment that is extremely cumbersome and complex. Our technique works in and out of equilibrium and can reproduce spectra by several spectroscopic techniques, such as time-resolved photoemission, neutron scattering, Raman, X-ray spectroscopies (RIXS, Auger, XAS, XMCD), and, by not relying on analytical approximations, yields results that reveal novel overlooked transient mechanisms. These tools provide sorely needed intuition for understanding the phenomenology of strongly correlated materials and will help experimentalists in identifying signatures of relevant excitations in pump-probe experiments, such as those conducted in DOE supported facilities.
Cargo containers passing through ports are scanned by non-intrusive inspection systems to search for concealed illicit materials. By using two photon beams with different energy spectra, dual energy inspection systems are sensitive to both the area density and the atomic number of cargo contents. Most literature on the subject assumes a simple exponential attenuation model for photon intensity in which only free streaming photons are detected. However, this approximation neglects second order effects such as scattering, leading to a biased model and thus incorrect material predictions. This work studies the accuracy of the free streaming model by comparing it to simulation outputs, finding that the model shows poor atomic number reconstruction accuracy at high- Z and suffers significantly if the source energy spectra and detector response function are not known exactly. To address these challenges, this work introduces a semiempirical transparency model which modifies the free streaming model by rescaling different components of the mass attenuation coefficient, allowing the model to capture secondary effects ignored by the free streaming model. The semiempirical model displays improvement agreement with simulated results at high- Z and shows excellent extrapolation to materials and thicknesses which were not included during the calibration step. Furthermore, this work demonstrates that the semiempirical model yields accurate atomic number predictions even when the source spectra and detector response are not known exactly. In conclusion, using the semiempirical model, manufacturers can perform a simple calibration to enable more precise Z reconstruction capabilities, which has the potential to significantly improve the performance of existing dual energy radiographic systems.
This article addresses the problem of the transition between objective functions in optimal control for power inverters when switching between standalone and grid-connected modes. The work proposes the use of a synthetic reference during the transition between the corresponding objective functions. Moreover, the authors aim to show that a transition function can be imposed and controlled externally from the main optimal control routine. In the end, the simulation results demonstrate the importance of properly applying the proposed strategy for a smooth transition between the operating modes with minimal surge current. These results contrast with the strategies found in the literature where the smooth transition comes with the price of a few grid cycles to sync.
Workability and meltability of molten glass are properties important for balancing glass formulation with the design and operations of glass melting and forming facilities. The working and melting “lengths” are the temperature intervals within which glass viscosity allows the melting and forming glass to be performed. They are related to glass melt structure through the glass melt fragility, which, by the augmented Adam-Gibbs equation, is a function of configuration entropy. Both working length and melting length are high for strong glasses and decrease as the melt fragility increases. In this work, analytical formulas are obtained for three-parameter viscosity models VFT, AM, and MYEGA. These models agree with each other and with the Adam-Gibbs equation on the relationship between workability and fragility of glasses but diverge at high-temperatures. The compositional effects on workability and meltability are mediated via the fragility as a function of glass composition expressed in terms of mass and mole component coefficients.