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Search indexed NASA NTRS and DOE OSTI research on propulsion, heat transfer, battery materials and energy systems. Follow report and document links to the original sources.

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At least 19 records

The Alamo multiphysics solver for phase field simulations with strong-form mechanics and block structured adaptive mesh refinement

Alamo is a high-performance scientific code that uses block-structured adaptive mesh refinement to solve such problems as: the ignition and burn of solid rocket propellant, plasticity, damage and fracture in materials undergoing loading, and the interaction of compressible flow with eroding solid materials. Alamo is powered by AMReX, and provides a set of unique methods, models, and algorithms that enable it to solve solid-mechanics problems (coupled to other physical behavior such as fluid flow or thermal diffusion) using the power of block-structured adaptive mesh refinement.

36 MATERIALS SCIENCE↗

ASCEND: Asymptotically compatible strong form foundations for nonlocal discretization

Nonlocal models naturally handle a range of physics of interest to SNL, but discretization of their underlying integral operators poses mathematical challenges to realize the accuracy and robustness commonplace in discretization of local counterparts. This project focuses on the concept of asymptotic compatibility, namely preservation of the limit of the discrete nonlocal model to a corresponding well-understood local solution. We address challenges that have traditionally troubled nonlocal mechanics models primarily related to consistency guarantees and boundary conditions. For simple problems such as diffusion and linear elasticity we have developed complete error analysis theory providing consistency guarantees. We then take these foundational tools to develop new state-of-the-art capabilities for: lithiation-induced failure in batteries, ductile failure of problems driven by contact, blast-on-structure induced failure, brittle/ductile failure of thin structures. We also summarize ongoing efforts using these frameworks in data-driven modeling contexts. This report provides a high-level summary of all publications which followed from these efforts.

97 MATHEMATICS AND COMPUTING↗

The Impact of Ethylenediaminetetraacetic Acid (EDTA) on the Sorption of Nd(III), Th{sup (IV)}, and U(VI) onto Dolomite in WIPP-Relevant Brines, GWB and ERDA-6 - 20356

Storage of legacy, transuranic waste at the Waste Isolation Pilot Plant (WIPP) requires accurate risk models for performance assessments. These models must predict the long-term fate and transport of contaminants in the WIPP and surrounding environment. Laboratory support is necessary for the development of an accurate model through better understanding of contaminant behavior in the WIPP. The WIPP is a deep geologic repository that is characterized by high ionic strength due to evaporite deposits in the Salado formation (porewaters up to 7.4 M). High concentrations of sodium chloride (NaCl), calcium chloride (CaCl{sub 2}), and magnesium chloride (MgCl{sub 2}) are particularly of concern due to their potential impact on solubility and ultimately transport of contaminants of concern. Additionally, ligands capable of forming strong complexes with metals are found in significant concentrations in the WIPP environment due to their disposal from waste processing and formation during degradation of repository components (e.g. cellulose degradation by calcium hydroxide in cement). Consequently, there is a need to investigate the fate and transport of contaminants in the WIPP environment with a focus on the effects of high ionic strength and strongly coordinating ligands. Contaminants of high concern include the actinides (U(VI), Pu(IV), and Am(III)). Laboratory support of the WIPP modeling efforts was provided by this research. A series of batch experiments were utilized to study the impact of ionic strength, contaminant concentration, and the presence of ethylenediaminetetraacetic acid (EDTA) on the sorption of Nd(III), Th(IV), and U(VI) onto dolomite, a carbonate mineral found within the Culebra formation. The Culebra formation is the most transmissive layer above the WIPP, making transport of contaminants the most likely route in previous risk assessments. Two brines specifically designed to imitate conditions within the WIPP environment were used in these experiments. The U.S. Energy Research and Development Administration Well 6 (ERDA-6, 95%) brine simulates a low Mg environment, while the generic weep brine (GWB, 95%) simulates the WIPP environment with a high Mg concentration. Mg is added to the repository in the form of MgO as an engineered barrier and is naturally present in some formations. It is expected to scavenge carbonate from solutions decreasing formation of the highly soluble and competitive uranium-carbonate complexes. EDTA is used during manipulations of nuclear materials due to its ability to form strong, stable complexes with the actinides and may be found in high concentrations (up to 0.08 mM) within the WIPP as waste canisters degrade. Further, it may provide additional avenues for unwanted transport of contaminants. Nd(III) and Th(IV) were used as stable analogues of Am(III) and Pu(IV), respectively, to represent the most common oxidation states of actinides in the WIPP environment in addition to U(VI). The potential for colloid formation was also investigated with low and high concentrations of contaminants (10 and 1000 μg/L) using three size-dependent particle separation steps. The results of this research provide a better understanding of potential behavior of actinides in the presence of EDTA and within WIPP-relevant brines. (authors)

12 MANAGEMENT OF RADIOACTIVE AND NON-RADIOACTIVE W↗

Three-dimensional continuum point cloud method for large deformation and its verification

This study presents a strong form based meshfree collocation method, which is named Continuum Point Cloud Method, to solve nonlinear field equations derived from classical mechanics for deformed bodies in three-dimensional Euclidean space. The method and its implementation are benchmarked against a nonlinear vector field using manufactured solutions. The analysis of mechanical fields firstly focuses on the study of St. Venant Kirchhoff and compressible neo-Hookean materials. Results for various initial boundary value problems are presented, including benchmark cases involving unidirectional tension and simple shear. Subsequently, the study concludes with an analysis of a displacement-controlled simulation of a compressible neo-Hookean material, specifically a bar that is pulled to 50% of its original length and rotated 90°. The pure tension case yields a 1.5% error in displacement between computed and expected values and a combined tension and torsion loading case provides further insight into material behavior under complex loading conditions. The resulting normal axial and transverse stress-strain curves are also presented. Lastly, the consistency and robustness of the proposed nonlinear numerical schemes are successfully demonstrated through various numerical experiments.

Compressible neo-Hookean materials↗

Calibrating constitutive models with full‐field data via physics informed neural networks

Abstract The calibration of solid constitutive models with full‐field experimental data is a long‐standing challenge, especially in materials that undergo large deformations. In this paper, we propose a physics‐informed deep‐learning framework for the discovery of hyperelastic constitutive model parameterizations given full‐field surface displacement data and global force‐displacement data. Contrary to the majority of recent literature in this field, we work with the weak form of the governing equations rather than the strong form to impose physical constraints upon the neural network predictions. The approach presented in this paper is computationally efficient, suitable for irregular geometric domains, and readily ingests displacement data without the need for interpolation onto a computational grid. A selection of canonical hyperelastic material models suitable for different material classes is considered including the Neo–Hookean, Gent, and Blatz–Ko constitutive models as exemplars for general non‐linear elastic behaviour, elastomer behaviour with finite strain lock‐up, and compressible foam behaviour, respectively. We demonstrate that physics informed machine learning is an enabling technology and may shift the paradigm of how full‐field experimental data are utilized to calibrate constitutive models under finite deformations.

Hamel, Craig M.↗

Laser-Welded Seals for Polymer-Free Glass/Glass Modules

This project explored the use of femtosecond laser welding to form strong, hermetic seals for glass/glass modules. The results showed that glass/glass fs laser welds, when coupled to a new module design, are strong enough to enable a polymer-free module, potentially extending warrantees and forming an easily-recycled product.

DuraMAT↗

Additive manufacturing of strong silica sand structures enabled by polyethyleneimine binder

Abstract Binder Jet Additive Manufacturing (BJAM) is a versatile AM technique that can form parts from a variety of powdered materials including metals, ceramics, and polymers. BJAM utilizes inkjet printing to selectively bind these powder particles together to form complex geometries. Adoption of BJAM has been limited due to its inability to form strong green parts using conventional binders. We report the discovery of a versatile polyethyleneimine (PEI) binder for silica sand that doubled the flexural strength of parts to 6.28 MPa compared with that of the conventional binder, making it stronger than unreinforced concrete (~4.5 MPa) in flexural loading. Furthermore, we demonstrate that PEI in the printed parts can be reacted with ethyl cyanoacrylate through a secondary infiltration, resulting in an increase in flexural strength to 52.7 MPa. The strong printed parts coupled with the ability for sacrificial washout presents potential to revolutionize AM in various applications including construction and tooling.

36 MATERIALS SCIENCE↗

Powder X-ray diffraction of nintedanib esylate hemihydrate, (C 31 H 33 N 5 O 4 )(C 2 H 5 O 3 S)(H 2 O) 0.5

The crystal structure of nintedanib esylate hemihydrate was refined using synchrotron X-ray powder diffraction data and optimized using density functional theory techniques. Nintedanib esylate hemihydrate crystallizes in space groupP-1(#2) witha= 11.5137(1),b= 16.3208(4),c= 19.1780(5) Å,α= 69.0259(12),β= 84.4955(8),γ= 89.8319(6)°,V= 3347.57(3) Å 3 , andZ= 4 at 295 K. Hydrogen bonds are prominent in the crystal structure. The water molecule forms two medium-strength O–H⋯O hydrogen bonds to one of the esylate anions. The protonated nitrogen atom in each cation forms a N–H⋯O hydrogen bond to an esylate anion. The ring N–H groups form strong intramolecular N–H⋯O hydrogen bonds to carbonyl groups. The ring N–H groups form intramolecular N–H⋯O hydrogen bonds to esylate anions. Many C–H⋅⋅⋅O hydrogen bonds (and one C–H⋯N hydrogen bond), with aromatic C–H, methylene groups and methyl groups as donors, are present. The hydrogen bonding patterns of the two cations differ considerably. The powder pattern has been submitted to ICDD for inclusion in the Powder Diffraction File™ (PDF®)

Materials Science↗

Geometry-aware framework for deep energy method: An application to structural mechanics with hyperelastic materials

Here, in this work, we introduce a novel physics-informed framework named the Geometry-Aware Deep Energy Method (GADEM) for solving structural mechanics problems on different geometries. As the weak form of the physical system equation (or the energy-based approach) has demonstrated clear advantages compared to the strong form for solving solid mechanics problems, GADEM employs the weak form and aims to infer the solution on multiple shapes of geometries. Integrating a geometry-aware framework into an energy-based method results in an effective physics-informed deep learning model in terms of accuracy and computational cost. Different ways to represent the geometric information and to encode the geometric latent vectors are investigated in this work. We introduce a loss function of GADEM which is minimized based on the potential energy of all considered geometries. An adaptive learning method is also employed for the sampling of collocation points to enhance the performance of GADEM. We present some applications of GADEM to solve solid mechanics problems, including a loading simulation of a toy tire involving contact mechanics and large deformation hyperelasticity. The numerical results of this work demonstrate the remarkable capability of GADEM to infer the solution on various and new shapes of geometries using only one trained model.

97 MATHEMATICS AND COMPUTING↗

A Fluorinated Lewis Acidic Organoboron Tunes Polysulfide Complex Structure for High–Performance Lithium–Sulfur Batteries

Many challenges in lithium-sulfur (Li–S) batteries are associated with the radical change in lithium polysulfide (LPS) solubility during cycling, but chemical approaches to address such inconsistency are still lacking. Here, the use of a strong Lewis acidic fluorinated organoboron, tri(2,2,2-trifluoroethyl) borate (TFEB), is reported as a multi-functional mediator to simultaneously overcome multiple technical barriers in practical Li–S batteries. TFEB acts as an anion acceptor and forms strong molecular complexes with Lewis basic LPS. The TFEB-LPS complexes have consistent solubility across the full polysulfide spectrum and deliver several times improved better redox kinetics, unlocking a true redox catalytic mechanism that covers the majority of redox events in thick sulfur cathodes. As a result, Li–S batteries evaluated under practical conditions exhibit significantly improved discharge capacity, rate capability, and cycling stability with the addition of the TFEB additive. More importantly, TFEB also contributes to the stabilization of lithium anode in the presence of polysulfides by generating strong interfacial film. These attributes significantly improve the cycling stability of practical Li–S pouch cells, which are assembled with a unit energy density of 219 Wh kg –1 . Finally, the results provide new molecular insights on the design of unlocking solvation networks of practical Li–S systems.

77 NANOSCIENCE AND NANOTECHNOLOGY↗

Repulsive forces and the weak gravity conjecture

The Weak Gravity Conjecture is a nontrivial conjecture about quantum gravity that makes sharp, falsifiable predictions which can be checked in a broad range of string theory examples. However, in the presence of massless scalar fields (moduli), there are (at least) two inequivalent forms of the conjecture, one based on charge-to-mass ratios and the other based on long-range forces. We discuss the precise formulations of these two conjectures and the evidence for them, as well as the implications for black holes and for “strong forms” of the conjectures. Based on the available evidence, it seems likely that both conjectures are true, suggesting that there is a stronger criterion which encompasses both. We discuss one possibility.

71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗

Graph states of atomic ensembles engineered by photon-mediated entanglement

Abstract Graph states are a broad family of entangled quantum states, each defined by a graph composed of edges representing the correlations between subsystems. Such states constitute versatile resources for quantum computation and quantum-enhanced measurement. Their generation and engineering require a high level of control over entanglement. Here we report on the generation of continuous-variable graph states of atomic spin ensembles, which form the nodes of the graph. We program the entanglement structure encoded in the graph edges by combining global photon-mediated interactions in an optical cavity with local spin rotations. By tuning the entanglement between two subsystems, we either localize correlations within each subsystem or enable Einstein–Podolsky–Rosen steering—a strong form of entanglement that enables the extraction of precise information from one subsystem through measurements on the other. We further engineer a four-mode square graph state, highlighting the flexibility of our approach. Our method is scalable to larger and more complex graphs, laying groundwork for measurement-based quantum computation and advanced protocols in quantum metrology.

74 ATOMIC AND MOLECULAR PHYSICS↗

Exploiting chitosan to improve the interface of nanocellulose reinforced polymer composites

Cellulose nanofibrils (CNFs) have been widely used as a nanofiller for polymer composite reinforcement due to their excellent mechanical properties. However, CNF is produced in water and needs to be dried prior to use in composite materials. The presence of hydroxyl groups on the surface of CNF creates strong hydrogen bonding that makes it difficult and costly to dry. Additionally, the hydrophilicity at the fiber surface results in agglomeration of CNFs within many polymer matrices. In this study, chitosan (CS) was co-precipitated with CNF to produce a dual-bonding filler for use in poly (lactic acid) (PLA) composites. CS promotes improved interfacial interaction within the polymer matrix by forming strong hydrogen bonds with the CNF and potential covalent bonds with the PLA. Finally, the results confirmed that the addition of a small amount of CS significantly improved the mechanical properties compared to PLA + CNF composites and neat PLA. The detailed study of the PLA + CNF/CS composites reveals the synergetic effect of the hydrogen and covalent bonding mechanism for PLA reinforcement.

59 BASIC BIOLOGICAL SCIENCES↗

Impact of Seasonal Snow-Cover Change on the Observed and Simulated State of the Atmospheric Boundary Layer in a High-Altitude Mountain Valley

The structure and evolution of the atmospheric boundary layer (ABL) under clear-sky fair weather conditions over mountainous terrain is dominated by the diurnal cycle of the surface energy balance and thus strongly depends on surface snow cover. We use data from three passive ground-based infrared spectrometers deployed in the East River Valley in Colorado's Rocky Mountains to investigate the response of the thermal ABL structure to changes in surface energy balance during the seasonal transition from low to high snow cover. Temperature profiles were retrieved from the infrared radiances using the optimal estimation physical retrieval Tropospheric Remotely Observed Profiling via Optimal Estimation. A nocturnal surface inversion formed in the valley during clear-sky days, which was subsequently mixed out during daytime with the development of a convective boundary layer when snow cover was low. Over high snow cover, a very shallow convective boundary layer formed, above which the inversion persisted through the daytime hours. We compare these observations to NOAA's operational High-Resolution-Rapid-Refresh model and find large warm biases on clear-sky days resulting from the model's inability to form strong nocturnal inversions and to maintain the stable stratification in the valley during daytime when there was snow on the ground. We suggest several factors contributing to the large model errors. These are (a) the inability of the model to represent well-developed thermally driven flows likely due to the too coarse horizontal grid spacing (3 km), (b) too much convective mixing during daytime, and (c) too strong vertical coupling between the valley atmosphere and the free troposphere.

54 ENVIRONMENTAL SCIENCES↗

Resolving the kinetics of individual aqueous reaction steps of actinyl (AnO 2 + and AnO 2 2+ ; An=U, Np, and Pu) tricarbonate complexes with ferrous iron and hydrogen sulfide from first principles

The solubility and mobility of actinides (An), like uranium, neptunium, and plutonium, in the environment largely depends on their oxidation states. Actinyls (An V,VI O 2 +/2+ (aq) ) form strong complexes with available ligands, like carbonate (CO 3 2- ), which may inhibit reduction to relatively insoluble An IV O 2(s) . Here we use quantum-mechanical calculations to explore the kinetics of aqueous homogeneous reaction paths of actinyl tricarbonate complexes ([AnO 2 (CO 3 ) 3 ] 5-/4- ) with two different reductants, [Fe(OH) 2 (H 2 O) 4 ] 0 and [H 2 S(H 2 O) 6 ] 0 . Energetically-favorable outer-sphere complexes (OSC) are found to form rapidly, on the order of milliseconds to seconds over a wide actinyl concentration range (pM to mM). The systems then encounter energy barriers ( E a ), some of which are prohibitively high (>100 kJ/mol for some neptunyl and plutonyl reactions with Fe 2+ and H 2 S), that define the transition from outer- to inner-sphere complex (ISC; for example, calculated E a of ISC formation between UO 2 + and UO 2 2+ with Fe 2+ are 35 and 74 kJ/mol, respectively). In some reactions, multiple OSCs are observed that represent different hydrogen bonding networks between solvent molecules and carbonate. Even when forming ISCs, electron transfer to reduce An 6+ and An 5+ is not observed (no change in atomic spin values or lengthening of An–O ax bond distances). Proton transfer from bicarbonate and water to actinyl O was tested as a mechanism for electron transfer from Fe 2+ to U 6+ and Pu 6+ . Not all proton transfer reactions yielded reduction of An 6+ to An 5+ and only a few pathways were energetically-favorable (e. g. H + transfer from H 2 O to drive Pu 6+ reduction to Pu 5+ with Δ E = -5 kJ/mol). The results suggest that the tricarbonate complex serves as an effective shield against actinide reduction in the tested reactions and will maintain actinyl solubility at elevated pH conditions. The results highlight reaction steps, such as inner-sphere complex formation and electron transfer, which may be rate-limiting. Thus, this study may serve as the basis for future research on how they can be catalyzed by a mineral surface in a heterogeneous process.

Chemistry↗