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At least 1,477 records · Page 82

Accelerating commercialization of direct air capture technology

In 2022 Congress authorized the $25M National Energy Technology Laboratory Direct Air Capture Center. The facility will be specifically targeted at accelerating the commercialization of technologies beyond the conceptual stage which have not yet reached full pilot-scale (TRL 3 to 6). The ability to operate over a wide range of conditions will help the developers to understand how their technologies respond in different climates, from summer to winter and arid to tropical. NETL recognizes that DAC technology is still early in its evolution, and a wide variety of highly varied technologies are being explored. The Center will be designed with substantial flexibility to accommodate the rapidly evolving technological landscape. Testing systems at three scales will be included: lab-scale systems designed to examine the long-term stability of DAC materials, bench-scale module testing systems capable of probing flow dynamics, and small pilot-scale skid rooms able to test prototype DAC units under a wide variety of climate conditions. The NETL DAC Center will feature dedicated engineering, technician, scientific and logistical support for experimental system design, installation, operation of experiments, and interpretation of results for projects including but not limited to kinetics of absorption/desorption, thermal duty, and post-mortem elemental characterization to understand degradation. The NETL DAC Center projects will also have access to dedicated process modeling and analysis to evaluate the technoeconomic aspects of new technologies. NETL’s Systems Engineering and Analysis (SEA) team, the Carbon Capture Simulation Initiative (CCSI), and the Institute for the Design of Advanced Energy Systems (IDAES) are all potential collaborators with NETL’s testing partners from industry, academia, and other research institutions. NETL also has world class capabilities in device scale modeling (i.e., MFIX) that will be available to help design more efficient contactors and optimize unique internal configurations that can be realized by advanced manufacturing. The talk will cover the design and capabilities of the center, the planned availability, and feedback will be solicited from the audience on DAC testing needs.

Luebke, David↗

Oxidation of Glycolate in the Defense Waste Processing Facility (DWPF) Recycle Collection Tank - 20305

The Savannah River Site's Defense Waste Processing Facility (DWPF) operations are being upgraded with the introduction of the Nitric-Glycolic Flowsheet. Glycolic acid has been shown superior to formic acid as the reducing acid used during chemical processing. The new flowsheet improves or maintains necessary parameters such as 1) reduction of mercury, 2) adjustment of feed rheology and 3) adjustment of melter oxidation/reduction potential. Further, the potential for catalytic hydrogen generation in DWPF processing is virtually eliminated. DWPF process condensates are collected and returned to the SRS Concentration, Storage and Transfer Facilities (CSTF). The Recycle Collection Tank (RCT) collects off-gas condensate during chemical processing, vitrification, and other unit operations performed in DWPF and is the singular return vessel delivering recycle effluent back to CSTF. Each batch of recycle may contain a small amount of glycolate from chemical processing and melter off-gas condensates. To avoid potential flammability issues due to thermolysis of glycolate in the CSTF, chemical oxidation within the RCT has been investigated as an option for mitigating the transfer of glycolate. Sodium permanganate has been down-selected as the best option for oxidation of glycolate. Testing was performed using both 2-L and 22-L reactors (16,800:1 and 1,530:1 scale by volume) with non-radioactive waste simulants to approximate the expected RCT compositions. RCT simulants were evaluated at various process pH and temperature conditions. Also, RCT operations, namely the sequence of addition of corrosion inhibitors (NaOH and NaNO{sub 2}) versus a permanganate strike, were evaluated. Glycolate was introduced via a sludge simulant to mimic both expected entrainment and abnormal process foam-over conditions - the range being between 68 and 5100 mg/kg glycolate. Glycolate destruction was monitored by ion chromatography (IC). The corresponding manganese behavior was monitored in real-time using in situ ultraviolet-visible (UV-Vis) spectroscopy. RCT glycolate content can be reduced to below the IC detection limit within 90 minutes for all concentrations investigated. Ion Chromatography analysis revealed that under alkaline conditions, glycolate is primarily oxidized to oxalate with no significant formation of CO{sub 2} or carbonate, and nitrite is not oxidized to nitrate. Initially, complete oxidation of organics species and nitrite was assumed. Determination of the mechanistic chemical reaction has allowed the required amount of permanganate to be more accurately predicted and the total addition to be significantly reduced. UV-Vis measurements reveal that permanganate (Mn{sup 7+}) is reduced to manganate (Mn{sup 6+}) in the RCT. The oxidant stoichiometry is defined by using the initial permanganate to glycolate (P/G) molar ratio. At low initial glycolate concentration (68 and 140 mg/kg), the minimum required initial permanganate to glycolate (P/G) molar ratio was found to be 5-6. With high initial glycolate concentrations (5100 mg/kg) a lower (P/G) molar ratio of ∼2.5 was needed. The final portion of this effort supporting the nitric/glycolic flowsheet will be to test actual (fully radioactive) RCT samples as per the above simulant tests. (authors)

12 MANAGEMENT OF RADIOACTIVE AND NON-RADIOACTIVE W↗

Carbon chemistry in dense molecular clouds: Theory and observational constraints

For the most part, gas phase models of the chemistry of dense molecular clouds predict the abundances of simple species rather well. However, for larger molecules and even for small systems rich in carbon these models often fail spectacularly. Researchers present a brief review of the basic assumptions and results of large scale modeling of the carbon chemistry in dense molecular clouds. Particular attention is to the influence of the gas phase C/O ratio in molecular clouds, and the likely role grains play in maintaining this ratio as clouds evolve from initially diffuse objects to denser cores with associated stellar and planetary formation. Recent spectral line surveys at centimeter and millimeter wavelengths along with selected observations in the submillimeter have now produced an accurate inventory of the gas phase carbon budget in several different types of molecular clouds, though gaps in our knowledge clearly remain. The constraints these observations place on theoretical models of interstellar chemistry can be used to gain insights into why the models fail, and show also which neglected processes must be included in more complete analyses. Looking toward the future, larger molecules are especially difficult to study both experimentally and theoretically in such dense, cold regions, and some new methods are therefore outlined which may ultimately push the detectability of small carbon chains and rings to much heavier species.

Blake, Geoffrey A.↗

Importance of Nucleation during Morphology Evolution of the Blade-Cast PffBT4T-2OD-Based Organic Solar Cells

Different temperatures, solvents, and additives are used as influencing parameters to drive molecular packing and phase separation for the development of the controlled evolution of nanostructures for organic solar cells (OSCs). The temperature-dependent aggregation (TDA) features of polymers are explored by investigating aggregation in solution and solid thin-film states using solution small-angle neutron scattering (SANS), soft/hard X-ray scattering, and transmission electron microscopy (TEM) characterizations. In situ grazing incidence wide angle X-ray scattering (GIWAXS) reveals that the nucleation process is highly significant and responsible for the ultimate film morphology. Processing conditions such as temperatures, solvents, and additives were used to influence the nucleation and evolution of film morphology. The nucleation process may improve the polymer packing and phase separation. It may also translate into optimized multilength scale domains and efficient charge percolation pathways, a strong implication to control the nucleation process for the efficient separation and transportation of charges in bulk heterojunction (BHJ) devices.

14 SOLAR ENERGY↗

Tracking the Oxidation of Silicon Anodes Using Cryo-EELS upon Battery Cycling

Silicon is a high-capacity material for the anode of a rechargeable lithium-ion battery. One of the fundamental challenges for using Si in anodes is capacity fading, which has been revealed to be partially associated with the interfacial instability between the Si and liquid electrolyte due to the large volume swing of Si upon charging and discharging. Smart nanoscale design concepts, either pre-synthesized or formed in-situ, have led to the mitigation of the detrimental factors associated with the volume swing of Si. However, it has never been clear as how the chemical state of Si evolves and contributes to the capacity fading upon battery cycling. Here, we use cryo-electron energy loss spectroscopy (EELS) to directly monitor, at sub-nanometer scale, the chemical evolution of Si upon battery cycling. We discover that during the cycling process, Si particles are progressively oxidized to form SiO 2 , which is initiated from the particle surface and gradually penetrates toward the interior of the particle, directly contributing to the capacity fading. Possible mechanisms of Si oxidation are postulated. We further show how the cycling stability can be improved by an electrolyte additive to form an effective passivation layer, representatively, even a small concentration of fluoroethylene carbonate (FEC) causes the formation of an LiF layer on the Si nanoparticle surface that prevents Si oxidation and improves cycling stability. Furthermore, the present work unveils Si oxidation as a previously unrecognized factor that contributes to capacity fading, therefore providing insight into the design of anodes with Si based materials.

25 ENERGY STORAGE↗

Biomimetic Rebuilding of Multifunctional Red Blood Cells: Modular Design Using Functional Components

The design and synthesis of artificial materials that mimic the structures, mechanical properties, and ultimately functionalities of biological cells remains a current holy grail of materials science. Here based on a silica cell bio-replication approach, we report the design and construction of synthetic rebuilt red blood cells (RRBCs) that fully mimic the broad properties of native RBCs: size, biconcave shape, deformability, oxygen carrying capacity, long circulation time. Four successive nano-scale processing steps: RBC bioreplication, layer-by-layer polymer deposition, and precision silica etching, followed by RBC ghost membrane vesicles fusion are employed for RRBC construction. A panel of physicochemical analyses including zeta potential measurement, fluorescence microscopy, and antibody-mediated agglutination assay proved the recapitulation of RBC shape, size, and membrane structure. Flow-based deformation studies carried out in a microfluidic blood capillary model confirrned the ability of RRBCs to deform and pass through small slits and reconstitute themselves in a manner comparable to native RBCs. Circulation studies of RRBCs conducted ex-ovo in a chick embryo and in vivo in a mouse model demonstrated the requirement of both deformability and native cell membrane surface to achieve long-term circulation. To confer additional non-native functionalities to RRBCs, we developed modular procedures in which to load functional cargos such as hemoglobin, drugs, magnetic nanoparticles, and ATP biosensors within the RRBC interior to enable various functions, including oxygen delivery, therapeutic drug delivery, magnetic manipulation, and toxin biosensing and detection. Taken together, RRBCs represent a class of long circulating RBC-inspired artificial hybrid materials with a broad range of potential applications.

59 BASIC BIOLOGICAL SCIENCES↗

Excited states in variational Monte Carlo using a penalty method

Here, in this article, the authors present a technique using variational Monte Carlo to solve for excited states of electronic systems. This technique is based on enforcing orthogonality to lower energy states, which results in a simple variational principle for the excited states. Energy optimization is then used to solve for the excited states. This technique is applied to the well-characterized benzene molecule, in which ~10 000 parameters are optimized for the first 12 excited states. Agreement within ~0.2 eV is obtained with higher scaling coupled cluster methods; small disagreements with experiment are likely due to vibrational effects.

36 MATERIALS SCIENCE↗

Double photoionization of atomic oxygen: Feshbach resonances in the two-electron continuum

In this work, we describe a joint experimental and theoretical investigation on oxygen double photoionization—the emission of two electrons from atomic oxygen following single photon absorption. High-resolution experimental measurements were performed at the Advanced Light Source, revealing sharp resonance structure superimposed on the more familiar Wannier-like, nearly-linear background. These resonance features are attributed to ionization-plus-excitation Feshbach resonances embedded in the double ionization continuum, doubly-excited states that lie above the double-ionization threshold. Such features are absent in the double photoionization cross section of He, or other quasi-two-electron systems, for which the doubly-ionized atomic core remains inert. For a corresponding theoretical analysis, the R-matrix with pseudostates (RMPS) method was invoked by calculating final-state, two-electron resonances-plus-continua wavefunctions and corresponding single-photon absorption cross sections. Overall agreement is found in the direct, background double photoionization cross section. However, the RMPS method, using a small basis due to practical computational limitations, was unable to reproduce quantitatively the smooth background or the sharper resonance features observed in the measurements, showing instead large-scale oscillations about the experimental background, and characteristic pseudoresonance jitter, associated with an insufficient convergence of the pseudostate representation to the true two-electron infinite series of Feshbach resonances embedded in the two-electron continuum. The prominent resonance structure observed highlights the need to consider multiple excitation processes in atoms more complex than He or quasi-two-electron systems.

74 ATOMIC AND MOLECULAR PHYSICS↗

Phase space distribution functions and energy distributions of dark matter particles in haloes

ABSTRACT For a spherical dark matter halo with isotropic velocity distribution, the phase space distribution function (DF), the energy distribution, and the density profile form a set of self-consistent description of its equilibrium state, and knowing one is sufficient to determine the other two. The Navarro–Frenk–White density profile (NFW profile) is known to be a good approximation to the spherically averaged density distribution in simulated haloes. The DARKexp energy distribution is also known to compare well with the simulated energy distribution. We present a quantitative assessment of the NFW and DARKexp fits to the simulated DF and energy distribution for a wide range of haloes in a dark-matter-only simulation from the IllustrisTNG Project. As expected, we find that the NFW fits work well except at low energy when the density at small radii deviates from the NFW profile. Further, the NFW and DARKexp fits have comparable accuracy in the region where both fit well, but the DARKexp fits are better at low energy because they require matching of the central gravitational potential. We also find an approximate relation between the energy scale parametrizing the DARKexp energy distribution and that defined by the characteristic density and radius of the NFW profile. This relation may be linked to the relaxation process during halo formation.

Astronomy & Astrophysics↗

An Algebraic Sparsified Nested Dissection Algorithm Using Low-Rank Approximations

Here, we propose a new algorithm for the fast solution of large, sparse, symmetric positive-definite linear systems, spaND (sparsified Nested Dissection). It is based on nested dissection, sparsification, and low-rank compression. After eliminating all interiors at a given level of the elimination tree, the algorithm sparsifies all separators corresponding to the interiors. This operation reduces the size of the separators by eliminating some degrees of freedom but without introducing any fill-in. This is done at the expense of a small and controllable approximation error. The result is an approximate factorization that can be used as an efficient preconditioner. We then perform several numerical experiments to evaluate this algorithm. We demonstrate that a version using orthogonal factorization and block-diagonal scaling takes fewer CG iterations to converge than previous similar algorithms on various kinds of problems. Furthermore, this algorithm is provably guaranteed to never break down and the matrix stays symmetric positive-definite throughout the process. We evaluate the algorithm on some large problems show it exhibits near-linear scaling. The factorization time is roughly $\mathcal{O}$(N), and the number of iterations grows slowly with N.

97 MATHEMATICS AND COMPUTING↗

Crossflow Filtration of Hanford Tank AP-105 Supernatant

A small-scale test platform to demonstrate the solids filtration, Cs removal, and low-activity waste (LAW) vitrification was constructed and installed at the Pacific Northwest National Laboratory (PNNL) 325 Building. Bench scale testing was conducted to demonstrate cross flow filtration using the cells unit filter (CUF) on approximately 14 liters of 241-AP-105 feed to support the confirmation of the Low-Activity Waste Pretreatment System (LAWPS) equipment performance and design basis for entrained solids removal process. Despite the low solids content (~16 ppm) of the AP-105 feed, significant fouling of the filter was observed that required backpulsing of the filter to maintain the permeate flux within the LAWPS baseline design rate. The improvement from backpulsing was significant, but transitory, and lasted a few hours. Increasing the transmembrane pressure was shown to have limited impact on the permeate flux in terms of magnitude and duration, especially compared with backpulsing. Because LAWPS must operate three to eight days to throughput requirements, testing demonstrated that backpulsing or chemical cleaning may need to be done every 7 to 14 hours when processing feed from AP-105. Because of this, backpulsing capability is strongly recommended for the baseline design. The LAWPS prototypic filter cleaning was demonstrated at the end of testing and was shown to be very effective as it largely restored the filter permeability to near pre-test conditions.

12 MANAGEMENT OF RADIOACTIVE AND NON-RADIOACTIVE W↗

Scalable, In-situ Data Clustering Data Analysis for Extreme Scale Scientific Computing (Final Report)

The objective of this project is to address challenges in the design and development of scalable in-situ data clustering and analytics algorithms and software. Our goal is to develop parallel software consisting of a set of spatio-temporal data clustering and anomaly detection functions, both of which are very important for large-scale analysis and have wide applicability for in-situ runs as well as post-processing analysis. Our design principles for in-situ analysis consider the following: (1) identify parts of the computation can be done close to the data within the nodes, while it is still in memory; (2) extract analysis components can (and should) be performed in remote staging and analysis nodes; (3) develop error-bound approximation methods for applications tolerable for small errors; (4) identify the type of derived distributions and statistics, for spatio-temporal data, that can be kept locally in order to both accelerate computations and meet energy constraints in subsequent iterations and phases; (5) use a self-describing data format so that data can be consistent and understood among local storage (memory and SSDs) and at staging and analysis nodes, thereby providing portability and flexibility; (6) develop service-oriented functions that can schedule in-situ and post-hoc analysis tasks based on the dynamic requirements of applications. Our development focus is to produce the parallel data analysis software/library that will be scalable, reusable, extensible, and generic for applications in different disciplines. The software will be able to run in-situ with the simulations as well as post-hoc analysis. This approach will satisfy many synergistic requirements for data intensive applications executed on data coming from instruments and experiments. In particular, the proposed multilevel approach is directly applicable to perform design tradeoffs for running part of the algorithms near the instruments and the rest on remote (analysis) systems.

97 MATHEMATICS AND COMPUTING↗

DCMIP2016: the splitting supercell test case

Abstract. This paper describes the splitting supercell idealized test case used in the 2016 Dynamical Core Model Intercomparison Project (DCMIP2016). These storms are useful test beds for global atmospheric models because the horizontal scale of convective plumes is O(1 km), emphasizing non-hydrostatic dynamics. The test case simulates a supercell on a reduced-radius sphere with nominal resolutions ranging from 4 to 0.5 km and is based on the work of Klemp et al. (2015). Models are initialized with an atmospheric environment conducive to supercell formation and forced with a small thermal perturbation. A simplified Kessler microphysics scheme is coupled to the dynamical core to represent moist processes. Reference solutions for DCMIP2016 models are presented. Storm evolution is broadly similar between models, although differences in the final solution exist. These differences are hypothesized to result from different numerical discretizations, physics–dynamics coupling, and numerical diffusion. Intramodel solutions generally converge as models approach 0.5 km resolution, although exploratory simulations at 0.25 km imply some dynamical cores require more refinement to fully converge. These results can be used as a reference for future dynamical core evaluation, particularly with the development of non-hydrostatic global models intended to be used in convective-permitting regimes.

Zarzycki, Colin M.↗

Jacobian-based Model Diagnostics and Application to Equation Oriented Modeling of a Carbon Capture System

Equation-oriented (EO) modeling has the potential to enable the effective design and optimization of the operation of advanced energy systems. However, advanced modeling of energy systems results in a large number of variables and non-linear equations, and it can be difficult to search through these to identify the culprit(s) responsible for convergence issues. The Institute for the Design of Advanced Energy Systems Integrated Platform (IDAES-IP) contains a tool to identify poorly scaled constraints and variables by searching for rows and columns of the Jacobian matrix with small L2-norms so they can be rescaled. A further singular value decomposition can be per-formed to identify degenerate sets of equations and remaining scaling issues. This work presents an EO model of a flowsheet developed for post-combustion carbon capture using a monoethanolamine (MEA) solvent system as a case study. The IDAES diagnostics tools were successfully applied to this flowsheet to identify problems to improve model robustness and enable the optimization of process design and operating conditions of a carbon capture system.

Allan, Douglas↗

Information extraction from multivariate images

An overview of several multivariate image processing techniques is presented, with emphasis on techniques based upon the principal component transformation (PCT). Multiimages in various formats have a multivariate pixel value, associated with each pixel location, which has been scaled and quantized into a gray level vector, and the bivariate of the extent to which two images are correlated. The PCT of a multiimage decorrelates the multiimage to reduce its dimensionality and reveal its intercomponent dependencies if some off-diagonal elements are not small, and for the purposes of display the principal component images must be postprocessed into multiimage format. The principal component analysis of a multiimage is a statistical analysis based upon the PCT whose primary application is to determine the intrinsic component dimensionality of the multiimage. Computational considerations are also discussed.

Park, S. K.↗

Functional Flight Test Report for Positive Systems' ADAR System 5500 Sensor SN8 Linear

This report describes results of the functional flight test conducted with the Positive Systems' ADAR 5500 sensor system (serial number 8, linear configuration) near Winslow, Arizona on June 30 and July 1, 1999. The in-flight test is one component of the NASA Scientific Data Purchase (SDP) Validation and Verification (V&V) process. It allows to measure characteristics of the entire sensor system affected by both performance of the sensor during a flight and post-flight image processing. The following characteristics were analyzed: changes of dark digital numbers (DN's), radiometric linearity, signal-to-noise ratio (SNR), spatial resolution, and geolocation accuracy. The measured characteristics were compared with the image product specifications defined in the Positive Systems' SDP contract. Dependence of the dark DN's on several factors was analyzed, but no significant correlation was found. However, the observed changes in dark DN's were relatively small, which justifies usage of a constant value in the dark DN subtraction procedure during post-processing. Dependence of measured at-sensor, in-band radiance (in arbitrary units) on measured in-band ground reflectance is very well described by a linear function - The sensor fulfills the linearity requirement. Measured SNR values lower than the contract specifications, but accuracy of that test was possibly affected by non-uniformity of the employed gray-scale panels. The SNR values are generally sufficiently high for most applications. SNR can also be improved during standard flights by using longer exposure times. Full width at half maximum (FWHM) of an edge response derived line spread function was used as a measure of spatial resolution. FWHM was generally smaller than twice the ground sample distance (GSD), in agreement with the contract specifications. Accuracy of the geolocation information, which is provided for the particular images in a metadata file, was found to meet contract requirements as well.

Stanley, Tom↗

Renewable Energy for Industrial Environmental Management

Costs for renewable energy technologies have declined rapidly in the past decade and their use for residential, commercial, and utility scale electricity has grown exponentially as they become cost competitive. Simultaneously, industrial and manufacturing processes have been increasingly seeking ways to reduce emissions and operational costs in highly competitive sectors. With these combined drivers of lower cost and reduced environmental impact, renewable energy may become a viable energy provider for industrial processes such as oil and gas, mining, chemical refining, food production, and manufacturing. Renewable energy technologies may also partner with other reduced emission energy sources, such as small modular nuclear reactors and carbon capture and utilization, to create cleaner and circular industrial systems for reduced resource use. The Joint Institute for Strategic Energy Analysis (JISEA), which is a partnership of the National Renewable Energy Laboratory (NREL) and five universities and others, has been studying to potential for application of clean energy technologies to the heterogenous energy demands in industry. Dr. Jill Engel-Cox will present an overview of NREL and JISEA, the status and potential future of renewable energy technologies, and collaborations with the oil and gas industry and other industrial sectors to improve their environmental performance and reduce operational costs.

ENERGY PLANNING, POLICY, AND ECONOMY↗

Additive manufacturing of mullite ceramic by digital light processing

Mullite material was successfully additively manufactured using digital light processing (DLP). The printed geometry involves a one-step process of pyrolysis, de-binding, and sintering under a plain atmosphere to achieve an average of 76 % ceramic yield and linear shrinkage of 12 %. Furthermore, the thermal profile was carefully controlled to obtain consistent phases in which the XRD shows a mullite phase. Here, in addition, the Weibull analysis was conducted on the sintered flexural specimens, showing a Weibull modulus (m) of 13.05 with a characteristic strength (σ 0 ) of 94.96 MPa. Synchrotron microtomography was performed on the sintered specimens, which showed two distinct porosity distributions (small and large). Large porosity (non-spherical elongated) is the primary cause of decreased material strength, while small porosity (spherical) is the sintering product. The measured thermal conductivity of the specimens was in the range of 2.7–3.1 W/m∙k and decreased with an increase in temperature. Lastly, large-scale prototypes were printed concurrently with a fine resolution of 25 μm without any compromise on the predetermined design and structure.

Additive manufacturing↗