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At least 217 records · Page 12

A Decentralized Approach for Modeling Organized Convection Based on Thermal Populations on Microgrids

Abstract In this study, a spectral model for convective transport is coupled to a thermal population model on a two‐dimensional horizontal “microgrid,” covering the typical gridbox size of general circulation models. The goal is to explore new ways of representing impacts of spatial organization in cumulus cloud fields. The thermals are considered the smallest building block of convection, with thermal life cycle and movement represented through binomial functions. Thermals interact through two simple rules, reflecting pulsating growth and environmental deformation. Long‐lived thermal clusters thus form on the microgrid, exhibiting scale growth and spacing that represent simple forms of spatial organization and memory. Size distributions of cluster number are diagnosed from the microgrid through an online clustering algorithm, and provided as input to a spectral multiplume eddy‐diffusivity mass flux scheme. This yields a decentralized transport system, in that the thermal clusters acting as independent but interacting nodes that carry information about spatial structure. The main objectives of this study are (a) to seek proof of concept of this approach, and (b) to gain insight into impacts of spatial organization on convective transport. Single‐column model experiments demonstrate satisfactory skill in reproducing two observed cases of continental shallow convection. Metrics expressing self‐organization and spatial organization match well with large‐eddy simulation results. We find that in this coupled system, spatial organization impacts convective transport primarily through the scale break in the size distribution of cluster number. The rooting of saturated plumes in the subcloud mixed layer plays a key role in this process.

54 ENVIRONMENTAL SCIENCES↗

Towards universal unfolding of detector effects in high-energy physics using denoising diffusion probabilistic models

Correcting for detector effects in experimental data, particularly through unfolding, is critical for enabling precision measurements in high-energy physics. However, traditional unfolding methods face challenges in scalability, flexibility, and dependence on simulations. We introduce a novel approach to multidimensional object-wise unfolding using conditional Denoising Diffusion Probabilistic Models (cDDPM). Our method utilizes the cDDPM for a non-iterative, flexible posterior sampling approach, incorporating distribution moments as conditioning information, which exhibits a strong inductive bias that allows it to generalize to unseen physics processes without explicitly assuming the underlying distribution. Our results highlight the potential of this method as a step towards a "universal" unfolding tool that reduces dependence on truth-level assumptions, while enabling the unfolding of a wide range of measured distributions with improved adaptability and accuracy.

71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗

Round 3 Update of Stress Testing Results for Organic Light-Emitting Diode Panels and Luminaires

Organic light-emitting diode (OLED) sources are a potential solid-state lighting technology for use in indoor lighting applications. Some of the advantages offered by OLEDs include thin profiles, low glare, diffuse lighting, and unique form factors. The U.S. Department of Energy (DOE) has released six technical reports focused on OLED technologies to provide information and analysis to the lighting industry. These reports include the evaluation of two different field deployment sites, a market analysis, a tear-down analysis, and two independent assessments of the performance of select commercially available OLED products. This report builds on earlier DOE efforts with OLED technology by updating information about previously benchmarked commercial OLED products. Specifically, this report provides updated findings about the robustness and reliability of commercial OLED products.

42 ENGINEERING↗

Sorption kinetics and stability of conventional adsorbents for mercury remediation

In-situ remediation of mercury at numerous contaminated sites worldwide is a challenging and costly endeavor due to the persistency of this contaminant. In this study, we evaluated eight commercially available sorbent media ranging from carbon-, clays- and silica-based materials (PBC– Biochar, eSorb – Sorbster, nsPAC – Powdered Activated Carbon, fsPAC – Powdered Activated Carbon with Mackinawite, F300 – Filtrasorb 300, Si-SH – Silica Thiol, eBind – RemBind, Q-Clay – Organoclay PM-199), for their effectiveness in sorbing mercury (Hg 2+ ) and mercury complexed with dissolved organic matter (Hg-DOM). Under the chosen experimental conditions of this study, results showed that in the absence of DOM, the kinetic rates of Hg 2+ sorption onto the evaluated sorbents were in the order of 0.31 min-1 (Si-SH) to 2.98 min -1 (nsPAC), whereas in the presence of DOM, the rates varied from 0.16 min-1 (F300) to 0.95 min -1 (nsPAC). The measured sorption capacity for Hg 2+ in the absence of DOM varied from 3.02 mg/g (Q-Clay) to 35.15 mg/g (Si-SH), whereas in the presence of DOM, calculated partition coefficient (KD) ranged from 69.7 mL/g (Q-Clay) to 41,510 mL/g (Si-SH). Furthermore, kinetic data suggest liquid film diffusion was the rate-limiting steps governing mercury sorption onto the studied media. Overall, the obtained study parameters (kinetics/isotherm) are particularly important in informing robust engineering designs for deployment of the vast majority of evaluated sorbents. Thus, sorbent-based strategies offer viable solutions for cost-effective cleanup of mercury at industrially contaminated sites.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

Measurement of gas-concentration-driven permeation for the examination of permeability, solubility, and diffusivity in varying materials

This manuscript describes the development and operation of an apparatus for the measurement of steady-state and transient gas permeation through different types of solid materials with varying geometries. It is capable of operation from 293 K to 673 K and could theoretically be used with any non-corrosive gas or a mix of gases, although only hydrogen isotopes are used in the current study. A quadrupole mass spectrometer is used to measure permeation fluxes as low as 1011 molecules/s. This unique test setup allows for the simultaneous measurement of diffusivity, solubility, and permeability. Furthermore, varying the pressure in the fore-sample volume allows for tests of Sievert’s law and can give information on surface effects.

Young, Katherine T. (ORCID:0000000285845576)↗

A computational study of the thermodynamic conditions leading to autoignition in nanosecond pulsed discharges

Nanosecond pulsed discharges have attracted the attention of engine manufacturers due to the possibility of attaining distributed ignition sites that accelerate burn rates while resulting in very little electrode erosion. Multidimensional modeling tools currently capture the electrical structure of such discharges accurately, but resolving the chemical structure remains a challenging problem owing to the disparity of time-scales in streamer propagation (nanoseconds) and ignition phenomena (microseconds). The purpose of this study is to extend multidimensional results towards resolving the chemical structure in the wake of streamers (or the afterglow) by using a batch reactor model. This can afford the use of very detailed chemical kinetic information. The full non-equilibrium nature of the electrons is taken into account, along with fast gas heating, shock wave propagation, and thermal diffusion. The results shed light on ignition phenomena brought about by such discharges.

ignition, plasma, kinetics↗

Memoirs of Mass Accretion: Probing the Edges of Intracluster Light in Simulated Galaxy Clusters

The diffuse starlight extending throughout massive galaxy clusters, known as intracluster light (ICL), has the potential to be read as a memoir of mass accretion: informative, individual, and yet imperfect. Here, we combine dark-matter-only zoom-in simulations from the Symphony suite with the Nimbus “star-tagging” model of the stellar halo to assess how much information about the mass assembly of an individual galaxy cluster can be gleaned from idealized measurements of ICL outskirts. We show that the edges of a cluster’s stellar profile—the primary (R sp⋆,1 ) and secondary (R sp⋆,2 ) stellar “splashback” radii—are sensitive to both continuous mass accretion histories (MAHs) and discrete merger events, making them potentially powerful probes of a cluster’s past. We find that R sp⋆,1 strongly correlates with the cluster’s mass ∼1 dynamical time ago, while R sp⋆,2 traces more recent MAH to a slightly lesser degree. In combination, these features can further distinguish between clusters that have and have not undergone a major merger within the past dynamical time. We use both to predict realistic cluster MAHs with the MultiCAM framework. These outer ICL features are significantly more sensitive to mass accretion and merger histories than the stellar mass gap and halo concentration, and perform comparably to the commonly used X-ray-based tracer of relaxedness, x off . While our analysis is idealized, the relevant ICL features are potentially detectable in next-generation deep imaging of nearby clusters. This work highlights the promise of ICL measurements and lays the groundwork for more detailed forecasts of their power.

79 ASTRONOMY AND ASTROPHYSICS↗

Physics-Informed Neural Network Method for Forward and Backward Advection-Dispersion Equations

Advection-dispersion equations (ADEs) are commonly used to describe transport phenomena in porous media. Even though mature discretization-based numerical methods for ADEs exist, some challenges still remain, especially when it comes to solving advection-dominated forward ADEs and diffusion-dominated backward ADEs. The latter problem usually arises in the source identification context and leads to numerically unstable grid-based solutions that require a form of regularization or should be treated as an inverse problem that is computationally more expensive because it requires solving the forward problem multiple times. In this study, we propose a discretization-free approach based on the physics-informed neural network (PINN) method for solving coupled ADE and Darcy flow equations with space-dependent hydraulic conductivity. In this approach, the hydraulic conductivity, hydraulic head, and concentration fields are approximated with deep neural networks (DNNs). We assume that the conductivity field is given by its values on a grid, and we use these values to train the conductivity DNN. The head and concentration DNNs are trained by minimizing the residuals of the flow equation and ADE and using the initial and boundary conditions as additional constraints. The PINN method is applied to one- and two-dimensional forward ADE problems, where its performance for various P\'{e}clet numbers ($Pe$) is compared with the analytical and numerical solutions. We find that the PINN method is accurate with errors of less than 1\% and outperforms some conventional discretization-based methods for $Pe$ larger that 100. Next, we demonstrate that the PINN method remains accurate for the backward ADEs, with the relative errors in most cases staying under 5\% compared to the reference concentration field. Finally, we show that when available, the concentration measurements can be easily incorporated in the PINN method and significantly improve (by more than 50\% in the considered cases) the accuracy of the PINN solution of the backward ADE.

He, Qizhi↗

CompLaB v1.0: a scalable pore-scale model for flow, biogeochemistry, microbial metabolism, and biofilm dynamics

Abstract. Microbial activity and chemical reactions in porous media depend on the local conditions at the pore scale and can involve complex feedback with fluid flow and mass transport. We present a modeling framework that quantitatively accounts for the interactions between the bio(geo)chemical and physical processes and that can integrate genome-scale microbial metabolic information into a dynamically changing, spatially explicit representation of environmental conditions. The model couples a lattice Boltzmann implementation of Navier–Stokes (flow) and advection–diffusion-reaction (mass conservation) equations. Reaction formulations can include both kinetic rate expressions and flux balance analysis, thereby integrating reactive transport modeling and systems biology. We also show that the use of surrogate models such as neural network representations of in silico cell models can speed up computations significantly, facilitating applications to complex environmental systems. Parallelization enables simulations that resolve heterogeneity at multiple scales, and a cellular automaton module provides additional capabilities to simulate biofilm dynamics. The code thus constitutes a platform suitable for a range of environmental, engineering and – potentially – medical applications, in particular ones that involve the simulation of microbial dynamics.

58 GEOSCIENCES↗

Utilization of 29Si MAS-NMR to Understand Solid State Diffusion in Energy Storage Materials

The properties of many solid-state materials arise from critical interfaces tied to the structure, morphology, and composition of the materials under study. For many materials, identifying components that may be invisible to diffraction techniques or other bulk sensitive techniques (i.e. inductively coupled plasma (ICP)), may cause important information to be overlooked. These can include grain boundary phases, nanoscale coatings, amorphous layers, or second phases that influence the materials environment. In this short review, the use of 29 Si MAS NMR as a local probe to detect silicon-containing phases in complex energy storage systems is explored with a focus is on silicon-containing materials and silicon electrodes. Examples highlighting the utility of 29 Si MAS NMR include 1) examining copper diffusion into silicon as a method to create 3 dimensional electrodes, 2) using Mg(II) electrolyte additives to create in-situ nanoscale silicide coatings to inhibit low voltage parasitic side reactions and extend calendar life, and 3) studying the lithiation reactions of passivated silicon on different time scales.

Dogan, Fulya↗

A model of spatio-temporal regulation within biomaterials using DNA reaction–diffusion waveguides

In multi-cellular organisms, cells and tissues coordinate biochemical signal propagation across length scales spanning micrometres to metres. Designing synthetic materials with similar capacities for coordinated signal propagation could allow these systems to adaptively regulate themselves across space and over time. Here, we combine ideas from cell signalling and electronic circuitry to propose a biochemical waveguide that transmits information in the form of a concentration of a DNA species on a directed path. The waveguide could be seamlessly integrated into a soft material because there is virtually no difference between the chemical or physical properties of the waveguide and the material it is embedded within. We propose the design of DNA strand displacement reactions to construct the system and, using reaction–diffusion models, identify kinetic and diffusive parameters that enable super-diffusive transport of DNA species via autocatalysis. Finally, to support experimental waveguide implementation, we propose a sink reaction and spatially inhomogeneous DNA concentrations that could mitigate the spurious amplification of an autocatalyst within the waveguide, allowing for controlled waveguide triggering. Chemical waveguides could facilitate the design of synthetic biomaterials with distributed sensing machinery integrated throughout their structure and enable coordinated self-regulating programmes triggered by changing environmental conditions.

71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗

Leveraging lifetime information to perform real-time 3D single-particle tracking in noisy environments

A microscopy platform that leverages the arrival time of individual photons to enable 3D single-particle tracking of fast-moving (translational diffusion coefficient of ≃ 3.3 µm 2 /s) particles in high-background environments is reported here. It combines a hardware-based time-gating module, which enables the rate of photon processing to be as high as 100 MHz, with a two-photon excited 3D single-particle tracking confocal microscope to enable high sample penetration depth. Proof-of-principle experiments where single quantum dots are tracked in solutions containing dye-stained cellulose are shown, with tracking performance markedly improved using the hardware-based time-gating module. Furthermore, such a microscope design is anticipated to be of use to a variety of communities who wish to track single-particles in cellular environments, which commonly have high fluorescence and scattering background.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

Physics-informed machine learning exploration of Na storage mechanisms in disordered carbon

Sodium-ion batteries are a cost-effective, sustainable alternative to lithium-ion systems for large-scale energy storage. However, optimizing sodium storage in carbon-based anodes with microstructural complexity and atomic disorder remains a major challenge. The intrinsic inhomogeneity of these materials produces diverse local environments, making it difficult for conventional methods to predict and control ion dynamics. Hard carbon (HC) anodes, composed of ranges of ordered-to-disordered graphitic and amorphous nanodomains, offer tunable ion storage and rate capacity, yet rationale design remains a challenge due to poorly understood correlation between local atomic feature and ion transport mechanism. Here, to address this challenge, we introduce a data-driven framework that integrates validated machine-learned interatomic potentials, large-scale molecular dynamics simulations, and machine learning to elucidate sodium transport mechanisms as a function of carbon and sodium loading densities. By computing per-ion structural descriptors and applying unsupervised learning, we identify distinct diffusion modes governed by microscopic features. Supervised analysis and correlation mapping then establish quantitative links between these transport regimes and processing variables such as bulk carbon density and sodium content. This physics-informed approach establishes quantitative structure–transport relationships and offers actionable design principles for engineering high-performance HC anodes.

Data-driven framework↗

Homotypic aggregates contribute to heterogeneity in B cell fates due to an intrinsic gradient of stimulant exposure

Highlights: • CD40-signaled B cells in cultures form three-dimensional homotypic aggregates. • These tight aggregates hinder the free diffusion of large molecule stimulants. • The resulting concentration gradient of stimulants leads to heterogeneous cell fates. • We describe a flow cytometric approach to quantify this positional information. Monocultures of several cell types result in the formation of robust clusters called homotypic aggregates (HAs). How this physical aggregation affects cell fates in immune cell cultures, is poorly understood. We studied anti-CD40-stimulated primary B cell cultures, where cells assembled into large three-dimensional LFA1-driven HAs by 72 h. The dense packing in these aggregates restricts the infiltration of stimulants, such as antibodies, to cells inside the clusters. This creates a concentration gradient of stimulant availability across the cross-section of HAs. We describe a method to retain this positional information even after the disruption of HAs, for analysis by flow cytometry. Comparison of stage-specific cell-surface markers showed that the extent of stimulant-binding affected multiple fates non-uniformly. While germinal center and lineage markers were moderately upregulated, immunoglobulins and markers associated with memory were more than doubled in the peripheral cells binding more anti-CD40. These cells also experienced a strong repression of the plasma cell regulator Prdm1 and an upregulation of the oncogene Myc. Thus, cells at different locations in HAs are subjected to unequal doses of stimulants, leading to a hitherto unreported source of heterogeneity in cell fates. These findings can be extrapolated to understand the dose-dependent effects of stimulants in other three-dimensional cell clusters.

60 APPLIED LIFE SCIENCES↗

Rotational memory function of SPC/E water

Memory effects are essential for the dynamics of condensed materials and are responsible for non-exponential relaxation of correlation functions of dynamic variables through the memory function. Memory functions of dipole rotations for water have never been calculated directly from molecular dynamics simulations. We present here calculations of memory functions for single-dipole rotations and for the overall dipole moment of the sample for SPC/E water. The normalized memory functions for single-particle and collective dipole dynamics turn out to be nearly identical. This result validates theories of dielectric spectroscopy in terms of single-particle time correlation functions and the connection between the collective and single-particle relaxation times through the Kirkwood factor. The dielectric function in this formalism contains no new dynamic information that does not exist in the single-dipole correlation function. A short memory time, ≲1 fs, justifies the use of the mathematics of rotational diffusion to describe the dynamics of a single molecular dipole moment in bulk water. Here, an analytical equation for the rotational memory time is derived.

Asthagiri, Dilipkumar N. [Oak Ridge National Labor↗

2021 Report - SRNL Aging and Lifetimes program tritium aging studies on structural alloys

This report documents work performed in fiscal year 2021 at SRNL in support of the Aging and Lifetimes program. This work is part of an on-going collaboration between SRNL and SNL to understand tritium embrittlement of structural metals used in Gas Transfer System reservoirs, thereby informing lifetime assessments and predictions. In this effort, test coupons are pre-charged with tritium and allowed to age in a freezer to minimize tritium diffusion and off-gassing while allowing for born-in helium levels to systematically increase. Coupons are then removed periodically and tested to develop an understanding of how mechanical properties degrade as helium levels increase. This report summarizes test results from coupons which are in various stages of aging as they were tritium pre-charged in previous years. Tests were performed on 304L that was previously tritium pre-charged and allowed to age to nominally 300 appm helium. Specimens from this study were previously tested at 100 appm nominal helium content, and this new test point expands that study. Tensile testing of these heat treated 304L tubes (and welded tubes) aged to 100 appm helium were completed which provided a unique study of a diverse set of microstructures and yield strengths ranging from 200-800 MPa. Additionally, 304L notched and smooth tensile specimens aged to 300 appm helium were tensile tested to predetermined strains to provide for a systematic microscopy investigation of aging effects on microstructural damage in partnership with SNL. Testing was performed on 304L electron beam (EB) weld coupons as well as 21-6-9 annealed coupons that were thermally pre-charged in 2020. Tests on the EB welds were completed at 100 appm helium contents, and tests on the annealed 21-6-9 material were completed at 100, 200, and 300 appm helium. Table 0-1 provides the status of the ongoing tritium coupon aging studies. The table includes the year tritium pre-charging took place, the material, and the targeted helium concentrations (appm) for testing.

12 MANAGEMENT OF RADIOACTIVE AND NON-RADIOACTIVE W↗

2022 Report - SRNL Aging and Lifetimes program tritium aging studies on structural alloys

This report documents work performed in fiscal year 2022 at SRNL in support of the Aging and Lifetimes program. This work is an enduring collaboration between SRNL and SNL to study tritium embrittlement of structural metals used in Gas Transfer System reservoirs. The measured data inform component lifetime assessments and predictions. Test coupons are thermally pre-charged with tritium and allowed to age at cryogenic temperatures to freeze out tritium diffusion and minimize off-gassing while allowing for decay helium levels to build. Coupons are removed and tested at planned intervals to measure how mechanical properties degrade as helium levels increase. This report summarizes test results from coupons which are in various stages of aging as they were tritium pre-charged in previous years, as well as documenting one new charging run.

12 MANAGEMENT OF RADIOACTIVE AND NON-RADIOACTIVE W↗