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At least 793 records · Page 44
All sourcesNASA NTRSDOE OSTI
DOE OSTI2024

Bill Savings vs. Backup Power: Evaluating operational tradeoffs for home solar+storage systems [Slides]

This study explores tradeoffs between the use of home solar+storage systems for backup power versus day-to-day utility bill savings. The study focuses specifically on the “reserve setting” available with most home battery storage systems, which allow the customer to maintain some minimum level of storage in reserve in case of an unforeseen power interruption. The more capacity that is held in reserve, the greater the customer’s ability to ride-through possible power interruptions, but less capacity is then available to manage utility bills on a day-to-day basis. This study evaluates this operational tradeoff across a diverse set of locations and residential electricity tariff structures, relying on Berkeley Lab’s PRESTO model to stochastically simulate power interruption events, and exploring a range of sensitivities, including variations in customer value of lost load (VoLL), interruption frequency, and other key drivers. The results show that, in most circumstances, the opportunity cost of holding storage capacity in reserve, in terms of foregone bill saving, tends to outweigh any gains in reliability value associated with mitigated power interruptions. This finding is robust across tariff structures and across most of the sensitivities considered, including those related to rate level, customer load level, and storage sizing. There are a limited set of circumstances where raising the reserve setting improves the overall customer value (comprised of bill savings plus reliability value). Specifically, that exception occurs when all of the following conditions apply: (a) the customer resides in a location with exceptionally poor reliability, (b) the customer has exceptionally high VoLL; (c) the customer is on a net billing rate or on a TOU rate that allows grid discharging but not grid charging; and (d), depending on the location, the price arbitrage differential on that rate is relatively small. In all other circumstances analyzed, total customer value declines with reserve level.

14 SOLAR ENERGY↗
DOE OSTI2020

Locating Methyl-Etherified and Methyl-Esterified Uronic Acids in the Plant Cell Wall Pectic Polysaccharide Rhamnogalacturonan II

Rhamnogalacturonan II (RG-II) is a structurally complex pectic polysaccharide that exists as a borate ester cross-linked dimer in the cell walls of all vascular plants. The glycosyl sequence of RG-II is largely conserved, but there is evidence that galacturonic acid (GalA) methyl etherification and glucuronic acid (GlcA) methyl esterification vary in the A sidechain across plant species. Methyl esterification of the galacturonan backbone has also been reported but not confirmed. Here we describe a new procedure, utilizing aq. sodium borodeuteride (NaBD4)-reduced RG-II, to identify the methyl esterification status of backbone GalAs. Our data suggest that up to two different GalAs are esterified in the RG-II backbone. We also adapted a procedure based on methanolysis and NaBD4 reduction to identify 3-, 4-, and 3,4-O-methyl GalA in RG-II. These data, together with matrix-assisted laser desorption/ionization–time-of-flight mass spectrometry (MALDI-TOF) MS analysis of sidechain A generated from selected RG-IIs and their NaBD4-reduced counterparts, suggest that methyl etherification of the ß-linked GalA and methyl esterification of the GlcA are widespread. Nevertheless, the extent of these modifications varies between plant species. Our analysis of the sidechain B glycoforms in RG-II from different dicots and nonpoalean monocots suggests that this sidechain has a minimum structure of an O-acetylated hexasaccharide (Ara-[MeFuc]-Gal-AceA-Rha-Api-). To complement these studies, we provide further evidence showing that dimer formation and stability in vitro is cation and borate dependent. Taken together, our data further refine the primary sequence and sequence variation of RG-II and provide additional insight into dimer stability and factors controlling dimer self-assembly.

BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2022

Inverse Analysis with Variational Autoencoders: A Comparison of Shallow and Deep Networks

Inverse problems are applied to determine unknown properties by matching observational data with a physical model that often takes many parameters as input. To overcome the underconstrained nature of inverse problems and achieve good performance, an approach is presented involving regularization with a technique known as a variational autoencoder (VAE), which is trained to map a high-dimensional parameter space with a complex structure to a low-dimensional latent space with a simple structure. We apply this approach to unconditioned realizations of the parameters (heterogeneous hydraulic fields) for a hydrogeological inverse problem. Two types of hydraulic conductivity fields are used to evaluate the characterization for the different levels of heterogeneity complexity of the physical inputs. This approach keeps the computational cost of generating the training data low. The reason is unconditioned realizations neither rely on the observational data used to perform the inverse analysis nor require any groundwater flow model forward runs. In addition, this approach applies regularization on a low-dimensional latent space from the VAE and increases optimization efficiency through automatic differentiation. Furthermore, two different neural network (NN) structures are tested for their utility in using the VAE for inverse analysis. The performance of a deep, convolutional neural network strongly depends on the dimensionality of the latent space, which requires tuning. In contrast, a shallow, dense neural network provides consistently accurate characterization without tuning. Furthermore, our approach evaluates the advantages of the shallow, dense neural network over the deep, convolutional one and enables future application to a wide range of inverse problems.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2021

Understanding nanoscale structural distortions in Pb(Zr 0.2 Ti 0.8 )O 3 by utilizing X-ray nanodiffraction and clustering algorithm analysis

Hard X-ray nanodiffraction provides a unique nondestructive technique to quantify local strain and structural inhomogeneities at nanometer length scales. However, sample mosaicity and phase separation can result in a complex diffraction pattern that can make it challenging to quantify nanoscale structural distortions. In this work, a k-means clustering algorithm was utilized to identify local maxima of intensity by partitioning diffraction data in a three-dimensional feature space of detector coordinates and intensity. This technique has been applied to X-ray nanodiffraction measurements of a patterned ferroelectric PbZr 0.2 Ti 0.8 O 3 sample. The analysis reveals the presence of two phases in the sample with different lattice parameters. A highly heterogeneous distribution of lattice parameters with a variation of 0.02 Å was also observed within one ferroelectric domain. This approach provides a nanoscale survey of subtle structural distortions as well as phase separation in ferroelectric domains in a patterned sample.

73 NUCLEAR PHYSICS AND RADIATION PHYSICS↗
DOE OSTI2021

Diffusion-mediated chemical concentration variation and void evolution in ion-irradiated NiCoFeCr high-entropy alloy

High-entropy alloys (HEAs) are proposed as potential structural materials for advanced nuclear systems, but little is known about the response of matrix chemistry in HEAs upon irradiation. Here, we reveal a substantial change of matrix chemical concentration as a function of irradiation damage (depth) in equiatomic NiCoFeCr HEA irradiated by 3 MeV Ni ions. After ion irradiation, the matrix contains more Fe/Cr in depth shallower than ~900–1000 nm but more Ni/Co from ~900–1000 nm to the end of the ion-damaged region due to the preferential diffusion of vacancies through Fe/Cr. Preferential diffusion also facilitates migration of vacancies from high radiation damage region to low radiation damage region, leading to no void formation below ~900–1000 nm and void formation around the end of the ion-damaged region at a fluence of 5 × 10 16 cm -2 (~123 dpa, displacements per atom, peak dose under full cascade mode). As voids grow significantly at an increased fluence (8 × 10 16 cm -2 , 196 dpa), the matrix concentration does not change dramatically due to new voids formed below ~900–1000 nm.

22 GENERAL STUDIES OF NUCLEAR REACTORS↗
DOE OSTI2021

Diffusion-mediated chemical concentration variation and void evolution in ion-irradiated NiCoFeCr high-entropy alloy

High-entropy alloys (HEAs) are proposed as potential structural materials for advanced nuclear systems, but little is known about the response of matrix chemistry in HEAs upon irradiation. Here, we reveal a substantial change of matrix chemical concentration as a function of irradiation damage (depth) in equiatomic NiCoFeCr HEA irradiated by 3 MeV Ni ions. After ion irradiation, the matrix contains more Fe/Cr in depth shallower than ~900–1000 nm but more Ni/Co from ~900–1000 nm to the end of the ion-damaged region due to the preferential diffusion of vacancies through Fe/Cr. Preferential diffusion also facilitates migration of vacancies from high radiation damage region to low radiation damage region, leading to no void formation below ~900–1000 nm and void formation around the end of the ion-damaged region at a fluence of 5 × 10 16 cm –2 (~123 dpa, displacements per atom, peak dose under full cascade mode). As voids grow significantly at an increased fluence (8 × 10 16 cm –2 , 196 dpa), the matrix concentration does not change dramatically due to new voids formed below ~900–1000 nm.

36 MATERIALS SCIENCE↗
DOE OSTI2024

Detonation structure in the presence of mixture stratification using reaction-resolved simulations

Many investigations of detonation-based combustors have identified reactant mixture inhomogeneity as having a leading-order impact on wave dynamics and combustion efficiency. To examine this phenomenon in a simplified context, an array of two- and three-dimensional channel detonation simulations are conducted in the present work. The reactant mixture consists of stratified fuel and air, wherein the randomly distributed equivalence ratio field features a characteristic stratification length scale. Detailed chemical kinetics are implemented in an adaptive mesh refinement solution framework where the region near the shock front is resolved with Ο (100) cells per representative ZND induction length. The results show that in comparison to baseline cases with uniform reactant mixtures, reactant stratification has a marked impact on the detonation structure. Increasing the stratification length scale increases the size and irregularity of the detonation cells, yielding larger variations in wave speed. Triple point collisions in fuel-rich regions lead to local wave speeds above the notional mean CJ speed, but wave passage through inert regions causes the local wave speed and strength to diminish. Further, conditional statistics show that increasing the stratification length scale increases the variance in pressure and temperature in the primary reaction zone, as well as the variance in heat release over a range of mixture conditions. In addition to the reactant mixture, the impact of the boundary condition behind the detonation is also investigated. The results show that an inflow boundary condition acts to over-drive the wave, leading to higher peak pressures, smaller detonation cells, and increased reactant consumption. On the other hand, cases with a wall behind the wave exhibit weaker waves with lower peak pressures and heat release rates, as well as greater variance in conditional quantities. Comparisons between complementary two- and three-dimensional simulations show reasonable qualitative agreement in wave structure, speed, and conditional statistics.

42 ENGINEERING↗
DOE OSTI2025

Quantifying Impacts of Biomass Pelletization on Fast Pyrolysis Using a Single-Particle Reactor, X-ray Computed Tomography, and Computational Modeling

The pore structure and density of lignocellulosic feedstocks dictate intraparticle transport phenomena and thereby play an important role in thermochemical conversion processes such as fast pyrolysis for biofuel and biochemical production. Variations in microstructure are inherent from different biomass species and can be introduced by preprocessing techniques such as cutting and pelletization. Morphological changes also occur during conversion and lead to vastly different pore structures and behavior during pyrolysis, which impact required conversion times and product distributions. The current work presents a comprehensive comparison of fast pyrolysis of neat and pelletized pine feedstocks, which includes single-particle experiments, modeling, and 3D imaging by X-ray computed tomography (XCT). The particle-scale model included anisotropic heat and mass transport in a shrinking particle with pyrolysis reactions based on the CRECK mechanism with boundary conditions informed by reactor-scale simulations of the single-particle reactor. The models were validated by measurements of the temperature and mass loss from single-particle pyrolysis experiments of neat and pelletized pine. Quantitative analysis of XCT geometries revealed that pyrolytic conversion yielded chars with increased porosity and permeability compared to the unpyrolyzed materials, along with decreased tortuosity and anisotropy. Pelletization of the pine feedstock resulted in a much denser, less permeable material, which converted slower and produced more residual char after pyrolysis compared to neat pine. The results from particle modeling revealed that accounting for the dynamic and anisotropic heat and mass transport caused by differences in pore structure is critical to achieving agreement with experimental results. Overall, this study highlights the dramatic differences in conversion behavior imparted by pelletization and the importance of capturing microstructural attributes in computational models to guide the design and optimization of pyrolysis processes for specific biomass feedstocks.

09 BIOMASS FUELS↗
DOE OSTI2020

Integrated Harsh Environment Gas / Temperature Wireless Microwave Acoustic Sensor System for Fossil Energy Applications

There is a significant need for sensors capable of detecting gases, such as H 2 , O 2 , NO x , SO x within harsh environments encountered in power plants, industrial manufacturing, oil and gas exploration, and aerospace applications. This project successfully demonstrated the use of wireless microwave acoustic sensor technology for the detection of gases (H 2 or O 2 ) from ambient temperatures up to 650°C. The work focused on langasite (LGS) based surface acoustic wave resonator (SAWR) sensors as the harsh-environment sensor platform and explored multiple combinations of high-temperature thin films and device structures which were used to increase the sensor platform stability and detection capability at temperatures in the operational range of 150°C to 700°C. Specific material configurations that were investigated include: yttria-stabilized-zirconia (YSZ) decorated with Pt nanoparticles, atomic layer deposited (ALD) Al 2 O 3 , palladium, and Pt/Al 2 O 3 co-deposited electrode alloys. Through the deposition of YSZ at temperatures as high as 850°C and the use of graded alloy concentrations of Pt in the fabrication of the Pt/Al 2 O 3 electrode structures, film stress problems were mitigated, and sensor operation and stability achieved. To test and evaluate SAWR sensor performance for the detection of H 2 and O 2 under the influence of temperature variations, a comprehensive gas sensor control system and test apparatus was created to operate within a laboratory box furnace-controlled environment. In addition to the advancement in thin film materials through the deposition and fabrication techniques mentioned above, the work characterized the performance of sensors containing these films in the presence of oxidizing and reducing gases between 25°C and 700°C. In particular, the work revealed that the exposure of the SAWR sensor surfaces to oxidizing environments significantly improve the sensor response to H 2 , whereas the exposure of the sensor to reducing environments at high temperatures (≈ 500°C) renders the sensor irresponsive to H 2 , requiring sensor surface treatment at high temperatures (above 500°C) to recover the responsiveness to H 2 . The SAWR sensors have been also tested for wireless operation and array operation using multiple orientations to resolve the detection of gases under temperature variations. The work developed at the University of Maine was aided by a collaboration with the NETL Research and Innovation Center, Pittsburgh, PA, where thin film materials and device structures fabricated at UMaine were tested and characterized using NETL gas reactors and surface analysis techniques. SAWR sensors fabricated at UMaine were exposed multiple times to temperatures up to 700°C and H 2 concentrations up to 100% in the NETL facilities to measure the sensor performance. Environetix Technologies Corporation, a UMaine harsh-environment sensor spin-off company, also provided support and assistance in sensor system testing and implementation. The sensor small size and configuration allows flexible sensor placement and embedding of multiple sensor arrays into a variety of components within power systems and other aerospace or industrial settings that need to be interrogated wirelessly. The SAW platform is an attractive option for high-temperature harsh-environment gas sensing applications due to its inherent features, namely small size, capability of battery-free and wireless operation, and cost effective scale production using well-established production techniques from the semiconductor industry. The research findings achieved in this work, particularly advances regarding the fabrication and performance of the SAWR gas sensor platform, can be adapted and transferred to industrial power plants and other harsh environments.

01 COAL, LIGNITE, AND PEAT↗
DOE OSTI2025

Distinctive features of structural evolution and thermodynamic response in wide-bandgap semiconductors driven by intense electronic excitation

Radiation-tolerant material selection requires balancing lattice rigidity, defect dynamics, and electronic stability, as shown by covalent SiC outperforming ionic Ga 2 O 3 and GaN under extreme environments. Responding to intense electronic excitation, irradiation-driven phase segregation (β → δ/κ in Ga 2 O 3 ) and core–shell track (disordered structure in GaN), accompanied by elemental redistribution, contrastingly, exceptional radiation tolerance manifested by comparatively minimal lattice distortion (0.17 % strain variation) was demonstrated in SiC. These differential responses are primarily attributed to two fundamental mechanisms: (i) thermodynamic driving forces governing defect migration and phase separation, and (ii) the synergistic effects of robust covalent bonding composition coupled with efficient defect recombination processes. Here, the stronger electron–phonon (e-ph) coupling in Ga 2 O 3 (4.34 × 1018 W m −3 K −1 ) and GaN (3.55 × 10 18 W m −3 K −1 ) enhances lattice energy deposition, triggering thermal spikes (ΔT ≫ T m ) and structural transition behaviors, whereas weaker e-ph coupling in SiC (3.69 × 10 18 W m −3 K −1 ), relatively high thermodynamic parameters and efficient energy dissipation suppress thermal spikes to maintaining lattice integrity. The photoresponse degradation driven by enhanced radiative recombination is dominant in N-doped SiC, while V-doped systems achieve defect-mediated photoconduction optimization characterized by abrupt current transitions, matching fluorescence yield evolutions, and directly connecting defect engineering to optoelectronic performance.

Intense electronic excitation↗
DOE OSTI2024

Local lattice distortions and electronic phases in perovskite manganite Pr 0.5 Sr 0.5 MnO 3

We use variable temperature and magnetic field total x-ray scattering to study the crystal structure of the strongly correlated Pr 0.5 Sr 0.5 MnO 3 perovskite, which is a paramagnetic insulator at room temperature, becomes a ferromagnetic metal at 272 K and, upon further decreasing the temperature, turns into an antiferromagnetic insulator at 105 K. We find that a model featuring a monoclinic symmetry captures the structure and its temperature and field evolution well, eliminating the need to evoke a phase segregation scenario as done in prior studies. It appears that coupled variations in Mn–oxygen bonding distances and angles from their values in an undistorted perovskite lattice, i.e., coupled local lattice distortions, assist the phase transitions in Pr 0.5 Sr 0.5 MnO 3 , contributing to its unique physical properties. Local structural distortions thus emerge as an important degree of freedom in strongly correlated systems, in particular perovskite manganates, and, therefore, they should be fully accounted for when their fascinating physics is considered.

36 MATERIALS SCIENCE↗
DOE OSTI2022

Competition of magnetocrystalline anisotropy of uranium layers and zigzag chains in UNi 0.34 Ge 2 single crystals

Structural and thermodynamic properties of single-crystalline UNi 1-x Ge 2 with x = 0.66 have been investigated by measuring magnetization, specific heat, and thermal expansion over a wide range of temperatures and magnetic fields. The measurements revealed the emergence of a long-range antiferromagnetic ordering of uranium magnetic moments below the Néel temperature T N = 45.5 (1) K and the existence of two easy axes in the studied compound, namely b and c, which correspond to the planes of the uranium zig-zag chains. A magnetic field applied along these two crystallographic directions induces in the system a first-order metamagnetic phase transition (from antiferromagnetic to field-polarized paramagnetism), and the width of the magnetic hysteresis associated with that transition reaches as much as 40 kOe at the lowest temperatures. A magnetic phase diagram developed from the experimental data showed that the metastable region associated with that magnetic hysteresis forms a funnel that narrows toward the N´eel point in a zero magnetic field. The four-layer Ising model has successfully predicted the colinear antiferromagnetic structure in UNi 0.34 Ge 2 (known from earlier reports), its magnetic phase diagram, and temperature and field variations of its magnetization. Moreover, it suggests that the first-order phase transition extends down to zero magnetic field, although it is barely detectable in the experiments performed in low magnetic fields. According to this model, the second-order phase transition occurs in the compound only in zero field.

75 CONDENSED MATTER PHYSICS, SUPERCONDUCTIVITY AND↗
DOE OSTI2025

Deconvoluting the impact of current collector structure and electrolyte selection on Coulombic efficiency of lithium metal anodes

Lithium metal batteries are regarded as a promising avenue for significantly boosting the gravimetric energy density of batteries, particularly for electric vehicles. However, the instability of the lithium metal anode continues to hinder performance. While 3D structured current collectors for lithium metal anodes have been frequently proposed as a solution, few studies explore the impact of these structures when combined with various electrolytes and the inclusion of a lithium reservoir within the structure. This study pairs four commercially available copper current collectors with four different electrolytes to assess how these factors influence cycling performance with a 4 mAh/cm2 lithium reservoir. Coulombic efficiency (CE) measurements revealed no statistically significant difference in CE across different current collectors within the same electrolyte. However, significant variations were noted when the current collector remained intact, and the electrolyte was changed. Although polarization, electrochemical impedance, and lithium morphology varied between structures and electrolytes, no consistent patterns emerged to suggest superior performance by any specific current collector structure. Therefore, the choice of structure appears inconsequential when a lithium reservoir is present, and efforts should focus on selecting and designing the electrolyte.

White, Julia↗
DOE OSTI2023

Constraining AGN Torus Sizes with Optical and Mid-infrared Ensemble Structure Functions

We propose a new method to constrain the size of the dusty torus in broad-line active galactic nuclei (AGNs) using optical and mid-infrared (MIR) ensemble structure functions (SFs). Because of the geometric dilution of the torus, the MIR response to optical continuum variations has suppressed variability with respect to the optical that depends on the geometry (e.g., size, orientation, opening angle) of the torus. More extended tori have steeper MIR SFs with respect to the optical SFs. We demonstrate the feasibility of this SF approach using simulated AGN light curves and a geometric torus model. While it is difficult to use SFs to constrain the orientation and opening angle due to the insensitivity of the SF on these parameters, the size of the torus can be well determined. Applying this method to the ensemble SFs measured for 587 SDSS quasars, we measure a torus R–L relation of $\mathrm{log}\,{R}_{\mathrm{eff}}(\mathrm{pc})={0.51}_{-0.04}^{+0.04}\times \mathrm{log}({{L}}_{\mathrm{bol}}/{10}^{46}\,\mathrm{erg}\ {{\rm{s}}}^{-1})-{0.38}_{-0.01}^{+0.01}$ in the WISE W1 band and sizes ~1.4 times larger in the W2 band, which are in good agreement with dust reverberation mapping measurements. Compared with the reverberation mapping technique, the SF method is much less demanding in data quality and can be applied to any optical+MIR light curves for which a lag measurement may not be possible, as long as the variability process and torus structure are stationary. While this SF method does not extract all information contained in the light curves (i.e., the transfer function), it provides an intuitive interpretation for the observed trends of AGN MIR SFs compared with optical SFs.

79 ASTRONOMY AND ASTROPHYSICS↗
DOE OSTI2020

Caveat mutator: alanine substitutions for conserved amino acids in RNA ligase elicit unexpected rearrangements of the active site for lysine adenylylation

Naegleria gruberi RNA ligase (NgrRnl) exemplifies the Rnl5 family of adenosine triphosphate (ATP)-dependent polynucleotide ligases that seal 3'-OH RNA strands in the context of 3'-OH/5'-PO 4 nicked duplexes. Like all classic ligases, NgrRnl forms a covalent lysyl–AMP intermediate. A two-metal mechanism of lysine adenylylation was established via a crystal structure of the NgrRnl•ATP•(Mn 2+ ) 2 Michaelis complex. Here we conducted an alanine scan of active site constituents that engage the ATP phosphates and the metal cofactors. We then determined crystal structures of ligase-defective NgrRnl-Ala mutants in complexes with ATP/Mn 2+ . The unexpected findings were that mutations K170A, E227A, K326A and R149A (none of which impacted overall enzyme structure) triggered adverse secondary changes in the active site entailing dislocations of the ATP phosphates, altered contacts to ATP, and variations in the numbers and positions of the metal ions that perverted the active sites into off-pathway states incompatible with lysine adenylylation. Each alanine mutation elicited a distinctive off-pathway distortion of the ligase active site. Our results illuminate a surprising plasticity of the ligase active site in its interactions with ATP and metals. More broadly, they underscore a valuable caveat when interpreting mutational data in the course of enzyme structure-function studies.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2021

CASTELO: clustered atom subtypes aided lead optimization—a combined machine learning and molecular modeling method

Background: Drug discovery is a multi-stage process that comprises two costly major steps: pre-clinical research and clinical trials. Among its stages, lead optimization easily consumes more than half of the pre-clinical budget. We propose a combined machine learning and molecular modeling approach that partially automates lead optimization workflow in silico, providing suggestions for modification hot spots. Results: The initial data collection is achieved with physics-based molecular dynamics simulation. Contact matrices are calculated as the preliminary features extracted from the simulations. To take advantage of the temporal information from the simulations, we enhanced contact matrices data with temporal dynamism representation, which are then modeled with unsupervised convolutional variational autoencoder (CVAE). Finally, conventional and CVAE-based clustering methods are compared with metrics to rank the submolecular structures and propose potential candidates for lead optimization. Conclusion: With no need for extensive structure-activity data, our method provides new hints for drug modification hotspots which can be used to improve drug potency and reduce the lead optimization time. It can potentially become a valuable tool for medicinal chemists.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2023

Effect of Silica and Mixing Time on Microstructures of Porous Polymer Composite by Emulsion Templating

Porous polymer composite with tailored porosity is applied in the myriads of areas such as energy storage, oil/water absorption, bioengineering, and advanced areas of material science. The emulsion templating technology is one of the most popular methods for synthesizing porous polymer composite. It involves solidifying a two-phase mixture of porogen and polymer, then removing porogen to create pores within the continuous emulsion phase by polymerization or curing. The surfactant plays a pivotal role in accomplishing a stable emulsion, a key factor in designing the internal porous structure. This study highlights the effect of silica filler and mixing time on pore morphology, i.e., shape, size, and distribution. on polydimethylsiloxane (PDMS) porous structure utilizing the water-in-oil emulsion templating method. Span® 80 is used as a surfactant to reduce the surface tension between water, silica, and PDMS and simultaneously create a strong foaming effect. Different weight concentrations of silica (1-10 wt%) were chosen while keeping the internal phase, i.e., water (50 wt%) constant. The designed porous structures were further characterized through scanning electron microscopy (SEM). Porous composite specimens fabricated with higher silica content and mixing time consistently exhibit smaller pore sizes than specimens fabricated with lower mixing time and silica content. A breakthrough of pore morphology is seen at silica content higher than 5wt% at 1 min mixing, however, pore morphology drastically changes when mixing time increases from 1 min to 6 min. Variation of finer mixing time beyond 1 min shows stepwise changes in pore morphology from a large single-phase porous structure to a bi-modal porous structure which eventually become a smaller single-mode porous structure. Thus, the emulsion templating technique, in combination with different filler content and mixing time, will effectively aid in designing engineered porous polymer composite with varying stiffness and pore morphology.

Porous polymer, Emulsion templating, Surfactant, P↗
DOE OSTI2024

Weak boundary conditions for Lagrangian shock hydrodynamics: A high-order finite element implementation on curved boundaries

Here, we propose a new Nitsche-type approach for weak enforcement of normal velocity boundary conditions for a Lagrangian discretization of the compressible shock-hydrodynamics equations using high-order finite elements on curved boundaries. Specifically, the variational formulation is appropriately modified to enforce free-slip wall boundary conditions, without perturbing the structure of the function spaces used to represent the solution, with a considerable simplification with respect to traditional approaches. Total energy is conserved and the resulting mass matrices are constant in time. The robustness and accuracy of the proposed method are validated with an extensive set of tests involving nontrivial curved boundaries.

97 MATHEMATICS AND COMPUTING↗