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At least 1,135 records · Page 63

An Efficient High-Order Solver for Diffusion Equations with Strong Anisotropy on Non-Anisotropy-Aligned Meshes

This paper concerns numerical solution of the diffusion equation with strong anisotropy on meshes not aligned with the anisotropic vector field. In order to resolve the numerical pollution for simulations on a non-anisotropy-aligned mesh and reduce the associated high computational cost we propose an effective preconditioner, extending our previous work. Similar to the anisotropy-aligned mesh case, we apply the auxiliary space preconditioning framework to design a preconditioner where a continuous finite element space is used as the auxiliary space for the discontinuous finite element space. The key component is an effective line smoother that can mitigate the high-frequency errors perpendicular to the magnetic field. We design a graph-based approach to find such a line smoother that is approximately perpendicular to the vector fields when the mesh does not align with the anisotropy. Finally, numerical experiments for several benchmark problems are presented, demonstrating the effectiveness and robustness of the proposed preconditioner when applied to Krylov iterative methods.

97 MATHEMATICS AND COMPUTING↗

Report Summarizing the Mechanical Properties of a Large ODS Ferritic Alloy Ingot by Forging at High Temperatures for Future Mother Tube Production

Oxide dispersion strengthened (ODS) ferritic alloys are considered the benchmark fuel cladding and core structural material in advanced nuclear energy reactors that require high-temperature strength and creep properties and resistance to radiation damage. The ODS ferritic alloys including 14YWT are produced by mechanical alloying (MA), which is time-consuming and is associated with high manufacturing costs that are not beneficial to being used in advanced nuclear energy reactors. This report summarizes the accomplishments in FY24 in the INM program for producing an ODS ferritic alloy by high-deformation, high-temperature processing of reactive and ferritic alloy powders for advanced reactor fuel cladding applications. Following four hot forging experiments, it was concluded that several significant challenges were encountered that were difficult to overcome. These challenges were related to using high annealing temperatures for pressure assisted sintering processes to produce dense microstructures, but the high annealing temperatures result in long range diffusion of Ti through the bcc Fe lattice and react with the YIG particles that are distributed on the prior surfaces of the ferritic alloy powders. In addition, it was determined that the high deformations induced by forging at high temperatures were not very effective for fracturing the reactive YIG particles into smaller particles and distributing them into the interior of the ferritic alloy powders. Spark plasma sintering was attempted for shortening the time at high temperatures, which led to full densification but the microstructure characterization results still showed that Ti atoms diffused over long distances in the bcc Fe lattice and reacted with the YIG particles. Finally, a short 30 minute high intensity ball milling experiment was conducted on blended 14WT and YIG powders for inducing severe deformations that caused the initially spherical powders of 14WT decorated with the YIG particles on the surfaces to transform to flakes and fracturing of YIG particles into smaller particles that were incorporated into the bcc Fe lattice. Two forgings were performed with the high intensity milled powders: first annealing for 20 minutes at 850ºC followed by forging and second annealing for 20 minutes at 1,100ºC followed by forging. At 850ºC, Ti atoms are effectively immobile, thus allowing for densification albeit incomplete. The deformation by forging after annealing for 20 minutes at 1,100ºC favored dynamic recrystallization processes that led to nano-size grains with very high stored energy due to high dislocation density. The corresponding VH data showed significant hardening that correlated with estimated strengthening of ~1650 MPa. This hybrid processing approach combining high intensity ball milling of powder with annealing and forging showed the most promise for producing an oxide dispersing strengthened ferritic alloy.

36 MATERIALS SCIENCE↗

Printed circuit primary heat exchanger for power conversion in heat pipe microreactor applications

Here, in the present study, a model was developed for a recuperated air Brayton cycle for heat pipe microreactors, and the effect of the primary heat exchanger type assessed. An annular flow heat exchanger and a printed circuit heat exchanger (PCHE) were evaluated. A sub-sized diffusion bonded, PCHE test specimen was manufactured and tested with nitrogen as the working fluid to validate and improve the PCHE model. A comparison of the thermal cycle efficiency for the Brayton cycle coupled to a heat pipe microreactor using each of the two primary heat exchangers showed competitive performance for both options, with achievable cycle efficiencies of 34 % and 35 % for the annular and printed circuit heat exchangers, respectively. The impact of heat pipe length and additional reheating stages on cycle efficiency was studied. Increasing the heat pipe condenser length from 0.8 to 2.0 m resulted in an increase in cycle efficiency of 3.5 % and 3.2 % for the annular and printed circuit heat exchangers, respectively. The use of additional reheating stages showed a reduction in cycle efficiency since the heat pipe surface area limits the primary heat exchanger size and effectiveness. These results highlight the importance of the primary heat exchanger on the performance of a heat pipe microreactor. Overall, the cycle model, testing, and heat exchanger model showed the potential for the PCHE to improve the economics of a heat pipe microreactor relative to the annular flow heat exchanger, which also opens the possibility to use different heat transfer fluids such as supercritical CO 2 .

PCHE↗

Lower Temperature Annealing of Vapor Diffused Nb₃Sn for Accelerator Cavities

Nb₃Sn is a next-generation superconducting material for the accelerator cavities with higher critical temperature and superheating field, both twice compared to Nb. It promises superior performance and higher operating temperature than Nb, resulting in significant cost reduction. So far, the Sn vapor diffusion method is the most preferred and successful technique to coat niobium cavities with Nb₃Sn. Although several post-coating techniques (chemical, electrochemical, mechanical) have been explored to improve the surface quality of the coated surface, an effective process has yet to be found. Since there are only a few studies on the post-coating heat treatment at lower temperatures, we annealed Nb₃Sn-coated samples at 800 C - 1000 C to study the effect of heat treatments on surface properties, primarily aimed at removing surface Sn residues. This paper discusses the systematic surface analysis of coated samples after annealing at temperatures between 850 C and 950 C.

43 PARTICLE ACCELERATORS↗

Plausibility of the Formose Reaction in Alkaline Hydrothermal Vent Environments

Prebiotic processes required a reliable source of free energy and complex chemical mixtures that may have included sugars. The formose reaction is a potential source of those sugars. At moderate to elevated temperature and pH ranges, these sugars rapidly decay. Here it is shown that CaCO 3 -based chemical gardens catalyze the formose reaction to produce glucose, ribose, and other monosaccharides. These thin inorganic membranes are explored as analogs of hydrothermal vent materials—a possible place for the origin of life—and similarly exposed to very steep pH gradients. Supported by simulations of a simple reaction-diffusion model, this study shows that such gradients allow for the dynamic accumulation of sugars in specific layers of the thin membrane, effectively protecting formose sugar yields. Furthermore, the formose reaction may be a plausible prebiotic reaction in alkaline hydrothermal vent environments, possibly setting the stage for an RNA world.

59 BASIC BIOLOGICAL SCIENCES↗

Influence of implantation temperature and He implantation-induced defects on morphological evolution of co-deposited Cu-Mo nanocomposites

Here, we investigate the effect of high-temperature helium (He) implantation on microstructural evolution in physical-vapor-co-deposited nanocomposite thin films of copper (Cu) and molybdenum (Mo). The microstructure morphologies of He-implanted and He-free domains are characterized using transmission electron microscopy and statistical analysis. High implantation temperatures (500°C and 750°C) lead to coarsening of Cu and Mo domains and their eventual reorientation. The microstructure evolution in He-implanted and He-free domains is comparable, indicating that implantation-induced defects do not accelerate the coarsening of the nanocomposite as compared to annealing alone. This observation contrasts with previously reported effects of implantation-induced defects on single-phase nanocrystalline metals, which include enhancement of grain growth by increasing self-diffusivity or its inhibition by pinning of grain boundaries.

36 MATERIALS SCIENCE↗

Solid-State Side-Chain Functionalization of Conjugated Polymers for Expanded Chemical and Functional Versatility

Conjugated polymers that integrate diverse chemical functionalities with high electronic performance are essential for advanced organic electronic, optoelectronic, and biointerfaced technologies. Achieving such multifunctionality typically requires grafting functional units onto polymer side chains. However, conventional solution-phase approaches remain constrained by solubility limitations, side-chain-induced packing disruptions, and challenges in preserving charge transport. Here, we introduce a solid-state side-chain functionalization strategy that exploits a swellable polar side-chain architecture and azide–alkyne click chemistry to enable efficient molecular diffusion and reaction throughout predeposited polymer thin films. This approach substantially broadens the chemical compatibility of graftable units and mitigates the adverse effects on the electrical property. Moreover, the method supports spatially selective functionalization within a continuous film, enabling the patterned incorporation of chemically distinct groups to produce spatially defined optical properties. Here, this solid-state strategy thus provides a versatile platform for constructing conjugated polymers with expanded chemical versatility, preserved electronic performance, and programmable spatial functionality.

Conjugated polymers↗

The Stability Transition From Stable to Unstable Frictional Slip With Finite Pore Pressure

Pore fluids are ubiquitous throughout the lithosphere and are commonly invoked as the cause of induced seismicity and slow earthquakes. We perform lab experiments to address these questions for drained fault conditions and low pore pressure. We shear simulated faults at effective normal stress (σ' n ) of 20 MPa and pore pressures Pp from 1 to 4 MPa. We document the full range of lab earthquake behaviors from slow slip to elasto-dynamic rupture and show that slow slip can be explained by the slip rate dependence of the critical rheologic stiffness without dilatancy hardening or other fluid effects. Our fault permeabilities ranges from 10 –18 to 10 –17 m 2 with an initial porosity of 0.1 and estimated fluid diffusion time ≈1 s. Slow slip and quasi-dynamic fault motion may arise from high P p at higher pressures but dilatancy strengthening is not a general requirement.

58 GEOSCIENCES↗

Multi-resolution partial differential equations preserved learning framework for spatiotemporal dynamics

Traditional data-driven deep learning models often struggle with high training costs, error accumulation, and poor generalizability in complex physical processes. Physics-informed deep learning (PiDL) addresses these challenges by incorporating physical principles into the model. Most PiDL approaches regularize training by embedding governing equations into the loss function, yet this depends heavily on extensive hyperparameter tuning to weigh each loss term. To this end, we propose to leverage physics prior knowledge by “baking” the discretized governing equations into the neural network architecture via the connection between the partial differential equations (PDE) operators and network structures, resulting in a PDE-preserved neural network (PPNN). This method, embedding discretized PDEs through convolutional residual networks in a multi-resolution setting, largely improves the generalizability and long-term prediction accuracy, outperforming conventional black-box models. The effectiveness and merit of the proposed methods have been demonstrated across various spatiotemporal dynamical systems governed by spatiotemporal PDEs, including reaction-diffusion, Burgers’, and Navier-Stokes equations.

97 MATHEMATICS AND COMPUTING↗

Investigating the crust of neutron stars with neural-network quantum states

An accurate description of low-density nuclear matter is crucial for explaining the physics of neutron star crusts. In the density range between approximately 0.01 fm −3 and 0.1 fm −3 , matter transitions from neutron-rich nuclei to various higher-density pasta shapes, before ultimately reaching a uniform liquid. In this work, we introduce a variational Monte Carlo method based on a neural Pfaffian-Jastrow quantum state, which allows us to model the transition from the liquid phase to neutron-rich nuclei microscopically. At low densities, nuclear clusters dynamically emerge from the microscopic interactions among protons and neutrons, which we model based on pionless effective field theory. Our variational Monte Carlo approach represents a significant improvement over the state-of-the-art auxiliary-field diffusion Monte Carlo method, which is severely hindered by the fermion-sign problem in this low-density regime and cannot capture the onset of clusters. In addition to computing the energy per particle of symmetric nuclear matter and pure neutron matter, we analyze an intermediate isospin-asymmetry configuration to elucidate the formation of nuclear clusters. We also provide evidence that the presence of such nuclear clusters influences the amount of protons in the crust compared to protons in beta-equilibrated, neutrino-transparent matter.

Nuclear astrophysics↗

Stabilizing and Improving Qubit Coherence by Engineering the Noise Spectrum of Two-Level Systems

Superconducting circuits are a leading platform for quantum computing. However, their coherence times are still limited and exhibit temporal fluctuations. Those phenomena are often attributed to the coupling between qubits and material defects that can be well described as an ensemble of two-level systems (TLSs). Among them, charge fluctuators inside amorphous oxide layers contribute to both low-frequency 1 / f charge noise and high-frequency dielectric loss, causing fast qubit dephasing and relaxation. Moreover, spectral diffusion from mutual TLS interactions varies the noise amplitude over time, fluctuating the qubit lifetime. Here, we propose to mitigate those harmful effects by engineering the relevant TLS noise spectral densities. Specifically, our protocols smooth the high-frequency noise spectrum and suppress the low-frequency noise amplitude via depolarizing and dephasing the TLSs, respectively. As a result, we predict a drastic stabilization in qubit lifetime and an increase in qubit pure dephasing time. Our detailed analysis of feasible experimental implementations shows that the improvement is not compromised by spurious coupling from the applied noise to the qubit.

75 CONDENSED MATTER PHYSICS, SUPERCONDUCTIVITY AND↗

Thermal transport properties and some hydrodynamic-like behavior in three-dimensional topological semimetal $\mathrm{ZrTe}_5$

We report hydrodynamic fluidity in condensed matter physics has been experimentally demonstrated only in a limited number of compounds due to the stringent conditions that must be met. Herein, we performed thermal and electrical transport experiments in three-dimensional topological semimetal ZrTe 5 . By measuring the thermal properties in a wide temperature range, two representative experimental evidences of the hydrodynamics are observed in temperature window between the ballistic and diffusive regimes: a faster evolution of the thermal conductivity than in the ballistic regime and the non-monotonic temperature-dependent effective quasiparticle mean-free-path. In addition, magneto-thermal conductivity results indicate that charged quasiparticles, as well as phonons, may also play an important role in this hydrodynamic-like flow in ZrTe 5 .

75 CONDENSED MATTER PHYSICS, SUPERCONDUCTIVITY AND↗

Challenges to Reliable Production Nitrogen Doping of Nb for SRF Accelerating Cavities

Over the last several years, alloying of the surface layer of niobium SRF cavities has been demonstrated to beneficially lower the superconducting RF surface resistance. Nitrogen, titanium, and oxygen have all been demonstrated as effective alloying agents, occupying interstitial sites in the niobium lattice within the RF penetration depth and even deeper, when allowed to thermally diffuse into the surface at appropriate temperatures. The use of nitrogen for this function has been often termed ’nitrogen doping’ and is being applied in the LCLS-II and LCLS-II HE projects. We report characterization studies of the distribution of nitrogen into the exposed niobium surface and how such distribution is affected by the quality of the vacuum furnace environment in which the doping takes place, and the complexity of nitride crystal growth on different grain orientations of surface niobium. Using state-of-the-art quantification methods by dynamic secondary ion mass spectrometry (SIMS) depth profiling in niobium, we identify several phenomena involving furnace-sourced contamination. We also highlight a potential issue with N₂ flow constraints from the flange ’caps’ used during heat treatments.

Reece, Charles↗

Preserving Superconvergence of Spectral Elements for Curved Domains via $h$ and $p$-Geometric Refinement

Spectral element methods (SEM), extensions of finite element methods (FEM), have emerged as significant techniques for solving partial differential equations in physics and engineering. SEM can potentially deliver superior accuracy due to the potential superconvergence in nodal solutions for well-shaped tensor-product elements. However, the accuracy of SEM often degrades in complex geometries due to geometric inaccuracies near curved boundaries and the loss of superconvergence with simplicial or non-tensor-product elements. To overcome the first issue, we propose using h- and p-geometric refinement, which refines the mesh near high-curvature regions and increases the degree of geometric basis functions, respectively. We show that when using mixed-element meshes with tensor-product elements in the interior of the domain, curvature-based geometric refinement near boundaries can improve the accuracy of the interior elements by reducing pollution errors and preserving the superconvergence in nodal solutions. To address the second issue, we introduce a post-processing technique using the adaptive extended stencil finite element method (AES-FEM) to recover the accuracy near the curved boundaries. The combination of curvature-based geometric refinement and accurate post-processing offers an effective and easier-to-implement alternative to methods reliant on exact geometries. We demonstrate our techniques by solving the convection-diffusion equation in 2D and show up to two orders of magnitude of improvement in the solution accuracy, even when the elements are poorly shaped near boundaries.

97 MATHEMATICS AND COMPUTING↗

Preserving Superconvergence of Spectral Elements for Curved Domains

Spectral element methods (SEM), extensions of finite element methods (FEM), have emerged as significant techniques for solving partial differential equations in physics and engineering. SEM can potentially deliver superior accuracy due to the potential superconvergence in nodal solutions for well-shaped tensor-product elements. However, the accuracy of SEM often degrades in complex geometries due to geometric inaccuracies near curved boundaries and the loss of superconvergence with simplicial or non-tensor-product elements. To overcome the first issue, we propose using geometric refinement, which both refines the mesh near high-curvature regions and increases the degree of geometric basis functions. We show that when using mixed-element meshes with tensor-product elements in the interior of the domain, curvature-based geometric refinement near boundaries can improve the accuracy of the interior elements by reducing pollution errors and preserving the superconvergence in nodal solutions. To address the second issue, we introduce ApSEM, a post-processing technique using the adaptive extended stencil finite element method (AES-FEM) to recover the accuracy near the curved boundaries. The combination of curvature-based geometric refinement and accurate post-processing offers an effective and easier-to-implement alternative to methods reliant on exact geometries. We demonstrate our techniques by solving the convection-diffusion equation in 2D and 3D and show up to two orders of magnitude of improvement in the solution accuracy, even when the elements are poorly shaped near boundaries. We also show the efficiency of ApSEM as it can recover superconvergence in nodal solutions without drastically increasing the computational cost.

97 MATHEMATICS AND COMPUTING↗

Predictive Models and Novel Accelerated Tests for the Reliability of Cell Metallization in Photovoltaic Modules (Final Report)

Studies of metallization corrosion m photovoltaics have mainly been limited to comparisons of modules placed in accelerated chambers to fielded modules [1]. Damp Heat accelerated tests and phenomenological equations [2] are used to assess metallization corrosion without understanding the effect of UV light and temperature and humidity cycles on encapsulant adhesion degradation. The roles of encapsulant in-and out-diffusions of moisture and encapsulant impurities are important. Furthermore, few photovoltaic metallization corrosion studies included the role of bias and leakage currents, which are crucial in the electrochemical reaction of metallization. Leakage currents can highly accelerate the corrosion mechanism and are important to include in the studies of corrosion. In our research plan, we will address the following gaps in the PV community's understanding of metallization corrosion: (1) metallization corrosion with bias, humidity, and impurities in the encapsulant or metallization; (2) humidity diffusion through fresh and degraded encapsulants; and (3) comparison of model predictions with outdoor field modules and SunPower's extensive data for its back-contact and front-contact fleets [2] along with NREL's store of >20 year old modules. Our goal is to build models and accelerated tests to predict long term degradation of metallization corrosion of photovoltaic modules in the field. Our studies will include metals used in c-Si solar cells (Cu, Ag, and Al) and commonly used encapsulants (EV A (ethylene vinyl acetate), TPO (thermoplastic olefin), and silicone).

14 SOLAR ENERGY↗