Search NASASearch

DOE OSTI · 2999173

Multipoint Correlations in Poisson Media

Abstract

Multipoint correlations in randomly heterogeneous composite media are determined by the probability that a set of points belong to specific phases. They determine a wide range of macroscopic transport properties such as conductivity, dielectric constant, diffusion coefficient, and transmittance. The Poisson model—a random tesselation of space by hyperplanes—provides realistic descriptions of heterogeneous media in, e.g., radiation-transport applications; yet, until now, it has lacked closed-form expressions for its multipoint correlations. We resolve this problem by presenting an exact solution for the multipoint correlations in the Poisson model. By comparing it to Monte Carlo simulations of four-point correlations in three dimensions, we demonstrate the accuracy of our solution. In conclusion, we visualize the multipoint correlations and discuss their features.

Explore related subjects

Keep this discovery

Explore connections, maps & timelines

BibTeXRIS

Shelley, Alec [Stanford Univ., CA (United States)] (ORCID:0009000982222363), Olson, Aaron Jeffrey [Sandia National Lab. (SNL-NM), Albuquerque, NM (United States)] (ORCID:0000000250362515), Geraci, Gianluca [Sandia National Lab. (SNL-NM), Albuquerque, NM (United States)], Tartakovsky, Daniel M. [Stanford Univ., CA (United States)] (ORCID:0000000190198935). 2025-10-09. Multipoint Correlations in Poisson Media. https://doi.org/10.1103/325k-g4dr

Cite the original work for its findings. Save a collection to share your selection of sources.

KEEP EXPLORING

Related reports

Structural Origins of High MoO 3 Solubility in Peraluminous Borosilicate Glasses

Molybdenum (Mo) imposes strict loading limits in conventional borosilicate nuclear waste glasses due to the tendency of tetrahedral molybdate [MoO 4 ] 2− species to phase-separate and crystallize as alkali molybdates. Here, we demonstrate an unprecedented 13.96 wt % (7.51 mol %) MoO 3 solubility in peraluminous sodium aluminoborosilicate glasses a ∼15× increase over their peralkaline counterparts. Using Raman spectroscopy, multinuclear and dipolarcorrelation magic angle spinning nuclear magnetic resonance (MAS NMR), electron paramagnetic resonance (EPR), and scanning transmission electron microscopy (STEM)-energy dispersive spectroscopy (EDS), we reveal that Nadeficient, low optical basicity conditions stabilize octahedral MoO 6 units, which polymerize into molybdite-like Mo−O clusters dispersed within the glass matrix. These Mo-rich clusters suppress the formation of depolymerized [MoO 4 ] 2− environments typically responsible for Na 2 MoO 4 precipitation and instead promote the formation of Na 2 Mo 2 O 7 as the saturation phase. Concurrently, Mo solubility drives the conversion of AlO 4 − to higher-coordination AlO 5 species, liberating Na + that is subsequently sequestered in molybdate-rich domains. The combined evolution of Mo coordination, modifier redistribution, and network depolymerization provides a mechanistic basis for the markedly enhanced Mo solubility in peraluminous compositions. These findings establish new structural guidelines for designing aluminoborosilicate waste forms with substantially greater capacity to incorporate Mo-rich nuclear waste streams.

Amorphous materials

Organic Acid-Assisted Thermal Dehalogenation of Halide Salt Nuclear Wastes: From Waste Salts to Borosilicate Glass

Only a handful of high-halide salt waste forms have been demonstrated for vitrification-based immobilization strategies for halide-salt nuclear waste streams (e.g., pyroprocessing wastes, molten salt reactor wastes) and they all have low waste loading potential and most have low chemical durabilities for high-alkali streams. An alternative approach to direct salt immobilization is salt partitioning prior to waste form fabrication and one option for partitioning is halide removal (called dehalogenation). Removing the halogen fraction through dehalogenation can significantly reduce the waste volume required for disposal in the primary waste form. Furthermore, when dehalogenation is performed using organic acids, the dehalogenation reagent can decompose during high-temperature vitrification, reducing waste loading limitations in the waste form. In the current work, different organic acids (i.e., oxalic, formic, acetic, oxamic, and citric) were evaluated for dehalogenation efficiency of a simple chloride salt simulant (7.19% LaCl 3 , 53.77% LiCl, and 39.04% KCl, by mole) and a more complex chloride salt simulant called ERV3 (electrorefiner version 3) at 150 °C–300 °C and using H + /Cl – molar ratios of 1:1, 2:1, and 3:1. Additionally, a borosilicate glass waste form called TARS (or the average of refined specifications) was formulated, produced, and characterized for dehalogenated ERV3.

Amorphous materials

Advanced Method Optimization with Categorical and Constrained Continuous Parameters

Traditional approaches to analytical method optimization (e.g., univariate and “guess-and-check”) can be time-consuming, costly, and often fail to identify true optima within the parameter space. Previous work defined and implemented a generalized technique for method optimization for continuous method parameters, but a knowledge gap remains for the incorporation of categorical variables into these advanced method optimization schemes. This work presents and validates a generalized optimization approach that incorporates both continuous and categorical variables while also utilizing a multivariate, multiobjective optimization scheme with Karush–Kuhn–Tucker conditions to bound the optimization space to solutions within the physical limitations of the parameter space. Method optimization from a case study using GC–MS for the analysis of 11 analytical standards with objectives to minimize peak width and maximize peak height resulted in a 3 orders of magnitude improvement in the average peak height and a 2 orders of magnitude improvement in the average peak width compared to the least optimal (but reasonable) instrumental parameters utilized in this study. This approach to optimization allows for a customizable method optimization in which users can include both continuous and categorical variables to achieve objectives specific to their analytical goals. This approach significantly reduces the labor and cost associated with traditional method development approaches and can be applied in a variety of scientific fields across a range of laboratory techniques (e.g., instrument method development, sample preparation, and extraction techniques).

Amorphous materials