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Moisture-induced agining and degradation are continuing concerns in long-term storage and use of silicone materials. The silica fillers frequently used to provide mechanical reinforcement in silicone formulations have a high affinity for H2O and act as a source of moisture outgassing later when placed in dry or vacuum applications.
Neat alkoxythiophenes react with MOF HKUST-1 to form a core–shell composite where the HKUST-1 surface is coated with conjugated polymer, while hexane solutions of thiophenes form a filled composite with polythiophene inside MOF pores.
The price gap between the market and breakeven prices of cellulosic biomass for farmers represents a significant barrier to the development of a low-carbon cellulosic bioeconomy. Using a bottom-up, agent-based modeling tool that replicates the behaviors and interactions of key stakeholders, this study analyzes the emergence of a cellulosic bioeconomy at the local scale through a wedge approach that examines an integrated portfolio of multiple policy options, including subsidies for small-scale bioproducts and environmental credits. The role of collaboration among multiple stakeholders, such as biomass producers (farmers), bio-refinery industry, government, and society, is assessed for filling the price gap. Using the Sangamon River Basin as a case study site, we evaluate the effectiveness of the wedge approach by comparing simulation results from multiple scenarios, each incorporating different combinations of bioeconomy wedges, with and without stakeholder collaboration. Results underscore that active collaboration among stakeholders acts as a catalyst enlarging the effectiveness of bioeconomy wedges. Including the carbon credits and environmental value in the policy portfolio is found to bridge the price gap through collective contributions from diverse stakeholders, where the cellulosic biofuel and bioproduct industry plays a pivotal role. Although this study is conducted at the local watershed scale, the methodology and findings offer valuable insights for market development in other watersheds and the potential scaling of local markets to regional and national levels.
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Inertial confinement fusion capsules fielded at the National Ignition Facility are filled with deuterium and tritium fuel by means of a fill tube. The fill tube introduces a low-density pathway into the fuel region of the capsule that allows high Z contaminant to invade the hot spot during the course of the implosion. A recent series of nominally identical high-yield implosions on the NIF has exhibited significant variability in performance. We evaluate the impact of the fill tube in these implosions computationally to determine whether variations in fill tube geometry could have contributed to this variability. The main contrast between the fill tube geometry in the six shots was the outer diameter of the capsule bore hole, a conical hole into which the fill tube is inserted. In our simulations, the geometry of the bore hole can play a significant role in the development of nonlinear flows seeded by the fill tube. Additionally, we find that the amount of space between the bore hole and the fill tube is the primary factor that determines the amount of contaminant jetted into the hot spot by the fill tube and, in turn, the level of yield reduction due to the fill tube in our simulations. As a consequence, some capsules with 5 μm fill tubes are predicted to outperform capsules with 2 μm fill tubes. We also find that micrometer-scale changes to bore hole size can impact fusion yields by up to four times near the ignition threshold. Nevertheless, simulation trends do not reproduce experimental yield trends, suggesting that the fill tube geometry was not the primary factor contributing to the observed variability in performance and that the fill tube could be masking sensitivity to other asymmetries such as other micrometer-scale capsule defects like voids that were not included in our simulations.
Fill tubes are used to inject deuterium and tritium fuel into inertial confinement fusion capsules fielded on the National Ignition Facility. These fill tubes have been shown to have a detrimental effect on capsule performance, primarily by introducing a low-density pathway into the central fuel region that enables the jetting of ablation material into the hot spot. Due to the complexity of the highly nonlinear flow associated with the fill tube and the challenge of diagnosing the evolution of the fill tube jet late in the implosion experiments, the uncertainty in how this perturbation source evolves is great. In this work, we report on the results of a detailed code comparison performed to understand uncertainties in computational modeling of the impact of fill tubes on implosion performance. The study employed two radiation-hydrodynamics codes, HYDRA and xRAGE, which employ very different meshing strategies and hydrodynamics solvers, as well as two radiation transport methodologies, discrete ordinates and multi-group diffusion. Our results demonstrate generally good agreement between codes through most of the implosion although they indicate sensitivity to opacity averaging methods. Late in the implosion, differences arise in the distribution and amount of contaminant although these differences have a remarkably small impact on the amount of yield reduction due to the fill tube. While these results demonstrate sensitivity in fill tube modeling to algorithmic choices, the observed differences between codes are small relative to known sensitivities due to expected variations in the fill tube geometry. Finally, we have developed a methodology for performing multi-group diffusion simulations that show good agreement with the more accurate discrete ordinates method
The US DOE Office of Nuclear Energy is investigating the feasibility of direct disposal of dual-purpose canisters (DPCs) in a hypothetical geological repository to offset the potential requirement to repackage spent nuclear fuel (SNF) from existing DPCs into smaller, disposal-ready canisters. Oak Ridge National Laboratory (ORNL) is currently evaluating the feasibility of filling void space in loaded DPCs with an engineered material to prevent a criticality event caused by groundwater/moderator intrusion. Metal alloys are being investigated as a filler material because of their relatively low viscosities when molten, which may facilitate their injection via an existing drainpipe that runs almost the full length of the DPC. ORNL’s strategy for evaluating filler viability includes simulations and physical demonstrations of filling and casting behavior, as well as evaluations of materials for compatibility in the repository environment. Filling of DPCs in this manner is expected to mitigate the risk associated with a post-closure criticality event during the repository performance assessment time frame (10,000 years or greater). Efforts in this fiscal year focused on (1) destructive analysis of experimental filler castings made in FY 2022, (2) a report outlining a conceptual design of a DPC filling facility (Fortner et al., 2023, M3SF 23OR010305044/ ORNL/SPR-2023/2921, May 31, 2023), (3) a report on affected features, events, and processes (FEPs) due to DPC filling (Price et al., 2023, M3SF-23SN010305093, issuance pending), (4) developing and testing a more practical alloy filler based upon a Sn-Al eutectic, and (5) modeling the heating and cooling dynamics of a DPC subjected to molten metal filling. The preliminary results from each of these tasks support the feasibility of filling DPCs with metal as a strategy against the possibility of criticality in the repository. The FY 2022 casting was found to penetrate even very small orifices in the mold and internal structures. Preliminary testing of the Sn-Al eutectic indicate little interaction of the melt with Zircaloy cladding. Thermal modelling shows that a filled DPC will cool to manageable temperatures within 2-3 days, which is likely manageable in a facility.
Abstract. Gap-filling eddy covariance CO2 fluxes is challenging at dryland sites due to small CO2 fluxes. Here, four machine learning (ML) algorithms including artificial neural network (ANN), k-nearest neighbors (KNNs), random forest (RF), and support vector machine (SVM) are employed and evaluated for gap-filling CO2 fluxes over a semiarid sagebrush ecosystem with different lengths of artificial gaps. The ANN and RF algorithms outperform the KNN and SVM in filling gaps ranging from hours to days, with the RF being more time efficient than the ANN. Performances of the ANN and RF are largely degraded for extremely long gaps of 2 months. In addition, our results suggest that there is no need to fill the daytime and nighttime net ecosystem exchange (NEE) gaps separately when using the ANN and RF. With the ANN and RF, the gap-filling-induced uncertainties in the annual NEE at this site are estimated to be within 16 g C m−2, whereas the uncertainties by the KNN and SVM can be as large as 27 g C m−2. To better fill extremely long gaps of a few months, we test a two-layer gap-filling framework based on the RF. With this framework, the model performance is improved significantly, especially for the nighttime data. Therefore, this approach provides an alternative in filling extremely long gaps to characterize annual carbon budgets and interannual variability in dryland ecosystems.
Space-filling toolpaths are used to fill whatever space remains on a layer after closed-loop contours have been planned. They provide structure to the object, both supporting the geometry and creating solid surfaces. As such, there are two main types of space-filling toolpaths: infill and skin. Infill paths are sparse and meant to cover a large area quickly. Infill is typically not visible once a print is complete, because infill is covered by skins. Skins are the solid space-filling toolpaths meant to solidify the top and bottom of the object, which, unlike the sides of the object, are not completely covered by layering contours. Space-filling paths are typically planned by projecting a pattern over the layer, clipping the pattern at the boundary of the object, and then linking the remaining portions of the pattern. A subcategory of skin paths, called gradual infill, can be employed to densify the infill when approaching a top skin layer so that the print path of the top skin is sufficiently supported. Space-filling paths come in a variety of patterns to optimize how the space is filled. This chapter will discuss space-filling path categories, how to find the space for each path type, and how to apply the path type to generate toolpaths.
Time series of methane fluxes measured by eddy-covariance require gap-filling to estimate annual emissions. Gap-filling methane fluxes is challenging because of high variability and complex responses to multiple drivers. To date, there is no widely established gap-filling standard for methane, with regards both to the best model algorithms and predictors. In this study, we address the need for standardization by synthesizing results of gap-filling methods applied at 17 wetland sites spanning boreal to tropical regions including all major wetlands classes and two rice paddies. We introduce new procedures for: 1) creating realistic artificial gap scenarios, 2) training and evaluating gap-filling models without overstating performance, and 3) predicting half-hourly methane fluxes and annual emissions with robust uncertainty estimates. We tested a conventional method (marginal distribution sampling) and four machine learning algorithms - penalized linear regression, artificial neural networks, random forests, and boosted decision trees - and four predictor sets, including temporal, meteorological, ecosystem carbon and energy flux, and soil predictors. We find that the conventional method can achieve similar median performance to the machine learning models but is worse than the best machine learning models and relatively insensitive to predictor choices. Of the machine learning models, decision tree algorithms performed the best in cross-validation experiments, even with a baseline predictor set, and artificial neural networks showed comparable performance when using all predictors. Soil temperature was frequently the most important predictor whilst water table depth was important at sites with substantial water table fluctuations, highlighting the value of data on soil conditions. Raw gap-filling uncertainties from the machine learning models were underestimated and we propose a method to calibrate uncertainties to observations. Finally, we gap-fill and provide summary evaluation metrics for all 81 sites in the FLUXNET-CH4 community dataset and publicly release the python code for model development, evaluation, and uncertainty estimation.
Plasma jets, such as γ-ray burst jets, Herbig–Haro jets, μ-quasar jets, and active galactic nuclei jets, are found throughout the universe [S. Mendoza et al., Rev. Mex. Astron. Astrofis. 41, 453 (2005)]. Plasma jets are also present in indirect drive inertial confinement fusion experiments originating from the capsule's fill tube and occasionally from divots and voids in the capsules, particles on the exterior of the capsule, or from the tent holding the capsule in the target. This paper looks at two different gas-filled capsule implosions containing a plasma jet resulting from a capsule fill tube and fill channel, both of which utilized high density carbon ablators. Two models were developed, a drag and a snowplow model, which use the time-dependent motion of the injected mass through the hotspot to estimate the mass injected into the hotspot from the fill tube and channel, arriving at an average injected mass of ~84.5 ± 25.5 ng for the first experiment and 91 ± 20 ng for the second experiment. Furthermore, unlike previous methods to estimate fill tube injected mass, these techniques do not assume that the mixed mass is in thermal equilibrium with the hotspot or that the x-ray emission is only coming from within the hotspot itself. This paper also discusses the features seen in these experiments which include limb brightening in the shell for undoped ablators and flattening in the ablator from shadowing by the fill tube.
Shock-driven implosions with 100% deuterium (D 2 ) gas fill compared to implosions with 50:50 nitrogen-deuterium (N 2 D 2 ) gas fill have been performed at the OMEGA laser facility to test the impact of the added mid-Ζ fill gas on implosion performance. Ion temperature (Τ ion ) as inferred from the width of measured DD-neutron spectra is seen to be 34%±6% higher for the N 2 D 2 implosions than for the D 2 -only case, while the DD-neutron yield from the D 2 -only implosion is 7.2±0.5 times higher than from the N 2 D 2 gas fill. The T ion enhancement for N 2 D 2 is observed in spite of the higher Z, which might be expected to lead to higher radiative loss, and higher shock strength for the D 2 -only versus N 2 D 2 implosions due to lower mass, and is understood in terms of increased shock heating of N compared to D, heat transfer from N to D prior to burn, and limited amount of ion-electron-equilibration-mediated additional radiative loss due to the added higher-Z material. Further, this picture is supported by interspecies equilibration timescales for these implosions, constrained by experimental observables. The one-dimensional (1D) kinetic Vlasov-Fokker-Planck code ifp and the radiation hydrodynamic simulation codes hyades (1D) and xrage [1D, two-dimensional (2D)] are brought to bear to understand the observed yield ratio. Comparing measurements and simulations, the yield loss in the N 2 D 2 implosions relative to the pure D 2 -fill implosion is determined to result from the reduced amount of D 2 in the fill (fourfold effect on yield) combined with a lower fraction of the D 2 fuel being hot enough to burn in the N 2 D 2 case. The experimental yield and T ion ratio observations are relatively well matched by the kinetic simulations, which suggest interspecies diffusion is responsible for the lower fraction of hot D 2 in the N 2 D 2 relative to the D 2 -only case. The simulated absolute yields are higher than measured; a comparison of 1D versus 2D XRAGE simulations suggest that this can be explained by dimensional effects. The hydrodynamic simulations suggest that radiative losses primarily impact the implosion edges, with ion-electron equilibration times being too long in the implosion cores. The observations of increased T ion and limited additional yield loss (on top of the fourfold expected from the difference in D content) for the N 2 D 2 versus D 2 -only fill suggest it is feasible to develop the platform for studying CNO-cycle-relevant nuclear reactions in a plasma environment.
Laser-driven Hohlraums filled with gas at lower densities (<0.6 mg/cc) have higher efficiency compared to original ≥ 0.96 mg/cc fill because of reduced backscatter losses [Hall et al., Phys. Plasmas 24, 052706 (2017)]. However, using low-density filled Hohlraums with longer drive required for lower adiabat implosions, and hence potentially higher inertial confinement fusion gain designs, has been challenging since the Hohlraum wall blow-off is less tamped, thus altering the laser beam absorption regions and drive symmetry. A series of NIF experiments using optimized pulse shaping, beam pointing, and temporal phasing have demonstrated, through imaging of the Hohlraum and capsule dynamics, that a symmetric implosion using a 14-ns low-adiabat drive pulse {2× longer than high-density-carbon ablator designs using low gas-fill density Hohlraums [Divol et al., Phys. Plasmas 24, 056309 (2017)]} is possible in a low backscatter loss 0.45 mg/cc He-filled Hohlraum. The ingress of the Hohlraum walls was mitigated by revisiting the adiabat-shaped design [Clark et al., Phys. Plasmas 21, 112705 (2014)] that uses a low-power (1 TW) trough that delays the wall expansion. Low-mode P 2 and P 4 drive asymmetry swings caused by the drift of the laser spots were essentially zeroed out by employing temporal beam phasing between cones of beams [Turner et al., Phys. Plasmas 7, 333 (2000)]. So the results also indicate an improved coupling efficiency of ~30% compared to an earlier design using higher density filled Hohlraums and pave the way for revisiting low-adiabat, high convergence drives using CH ablators.
Reef-building corals and their aragonite (CaCO 3 ) skeletons support entire reef ecosystems, yet their formation mechanism is poorly understood. Here we used synchrotron spectromicroscopy to observe the nanoscale mineralogy of fresh, forming skeletons from six species spanning all reef-forming coral morphologies: Branching, encrusting, massive, and table. In all species, hydrated and anhydrous amorphous calcium carbonate nanoparticles were precursors for skeletal growth, as previously observed in a single species. The amorphous precursors here were observed in tissue, between tissue and skeleton, and at growth fronts of the skeleton, within a low-density nano- or microporous layer varying in thickness from 7 to 20 µm. Brunauer-Emmett-Teller measurements, however, indicated that the mature skeletons at the microscale were space-filling, comparable to single crystals of geologic aragonite. Nanoparticles alone can never fill space completely, thus ion-by-ion filling must be invoked to fill interstitial pores. Such ion-by-ion diffusion and attachment may occur from the supersaturated calcifying fluid known to exist in corals, or from a dense liquid precursor, observed in synthetic systems but never in biogenic ones. Concomitant particle attachment and ion-by-ion filling was previously observed in synthetic calcite rhombohedra, but never in aragonite pseudohexagonal prisms, synthetic or biogenic, as observed here. Models for biomineral growth, isotope incorporation, and coral skeletons’ resilience to ocean warming and acidification must take into account the dual formation mechanism, including particle attachment and ion-by-ion space filling.
Traditional ionic and covalent compound insulators arise from a commensuration between electron count and system volume. On the other hand, conventional topological insulators, outside of quantum Hall effect systems, do not typically display such a commensuration. Instead, they can undergo a phase transition to a trivial insulator that preserves the electron filling. Nevertheless, in some crystalline insulators, termed filling-enforced quantum band insulators (feQBIs), electron filling can dictate nontrivial topology in the insulating ground state. Currently, little is known about the relation between feQBIs and conventional topological invariants. In this work, we study such relations for a particularly interesting example of a half-filling feQBI that is realized in space group 106 with spinless electrons. In this work, we prove that any four-band feQBI in space group 106 with filling 2 must have a nontrivial topological invariant, namely, the $\mathbb{Z}$ 2 glide invariant, and thus must have a quantized magnetoelectric polarizability θ = π. We thus have found a three-dimensional example where electron filling and band topology are tied. Such a locking raises intriguing questions about the generality of the band-inversion paradigm in describing the transition between trivial and topological phases.
This report discusses the progress made at the Oak Ridge National Laboratory to support direct disposal of dual-purpose canisters (DPCs). Acceptable filler materials should demonstrate that the probability of criticality in DPCs during the disposal timeframe is below the probability threshold for inclusion in a repository performance assessment. This effort, which will ultimately result in a full-scale demonstration, includes computational fluid dynamics (CFD) modelling developed to gauge the filling process and to uncover any unforeseen issues. Filling simulations of the lower region (mouse holes) of a prototypic DPC show successfully simulate filling of the void space inside the canister and a smooth, even progression of the liquid level. Flow through a pipe that is similar to the drainpipe in a DPC is being investigated separately to gain valuable insight of the flow regime inside a pipe. Three physical experiments validating the computational filling model have been completed using surrogate liquids. One experiment using molten metal has been completed and the results demonstrate adequate filling of the canister void spaces. Although the scale experiment observed some void spaces related to shrinkage of the metal during cooling, the volume filled is expected to be sufficient to meet the purpose of moderator exclusion. Further experiments will scale up the geometry, moving towards a full-sized DPC demonstration, and provide a more rigorous investigation of candidate filler materials.
National Ignition Facility (NIF) targets used for inertial confinement fusion (ICF) experiments are precision-engineered assemblies composed of more than 100 components carefully and precisely assembled with accuracies no larger than a few micrometers in most cases. When individual components deviate from these strict specifications during the assembly process, they can induce target failure. An integral component essential to ICF targets is the capsule-fill-tube assembly. This assembly involves bonding the capsule to a fused silica tube less than 5 μm in thickness, through which the tritium and deuterium (T 2 + D 2 ) fuel mixture is injected into the capsule prior to the NIF shot. The filling tube is bonded to a larger fused silica capillary, about 130 μm in outer diameter, which is coated with a polymeric layer on the order of a 10-μm thickness or less. Only tubes exhibiting a deflection equivalent to less than 1% of their total length from a perfectly straight line are suitable for assembly. Slight curvatures on the order of 1 mm over 10 cm can induce unwanted stresses, potentially causing capsule misalignment and resulting in clogging or leaks during the filling process. Despite manually qualitatively sorting each tube for straightness prior assembly, it has been found that the treatments the tubes undergo once attached to the capsule can alter their curvature. Filling tubes that initially satisfy straightness tolerances can undergo geometric deformation, resulting in curvature deviations exceeding 1% of their total length and thus failing to meet target assembly requirements. Here, in this study, we propose a metric to assess the degree of curvature of the filling tubes and to gauge their changes in curvature caused by the standard thermal processing methods employed in target assembly. In addition, we suggest alternatives to mitigate tube curvature, ensuring they conform to specifications following assembly in the final targets.
Abstract The observation of superconductivity and correlated insulating states in twisted bilayer graphene has motivated much theoretical progress at integer fillings. However, little attention has been given to fractional fillings. Here we show that the three-peak structure of Wannier orbitals, dictated by the symmetry and topology of flat bands, facilitates the emergence of a state we name a “fractional correlated insulator” at commensurate fractional filling of ν = n ± 1/3. Specifically for the filling of 1/3 electrons per moiré unit cell, we show that short-range interactions lead to an extensive entropy due to the “breathing” degree of freedom of an irregular honeycomb lattice that emerges through defect lines. The leading further-range interaction lifts this degeneracy and selects a ferromagnetic nematic state that breaks AB/BA sublattice symmetry. The proposed fractional correlated insulating state might underlie the suppression of superconductivity at ν = 2 − 1/3 filling observed in ref. 1 .