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    The physics of baryons in haloes, and their subsequent influence on the total matter phase space, has a rich phenomenology and must be well understood in order to pursue a vast set of questions in both cosmology and astrophysics. We use the Cosmology and Astrophysics with MachinE Learning Simulation (Camels) suite to quantify the impact of four different galaxy formation parameters/processes (as well as two cosmological parameters) on the concentration–mass relation, cvir−Mvir. We construct a simulation-informed non-linear model for concentration as a function of halo mass, redshift, and six cosmological/astrophysical parameters. This is done for two galaxy formation models, IllustrisTNG and Simba, using 1000 simulations of each. We extract the imprints of galaxy formation across a wide range in mass $M_{\rm vir}\in [10^{11}, 10^{14.5}] \, {\rm M}_\odot \, h^{-1}$ and in redshift z ∈ [0, 6] finding many strong mass- and redshift-dependent features. Comparisons between the IllustrisTNG and Simba results show the astrophysical model choices cause significant differences in the mass and redshift dependence of these baryon imprints. Finally, we use existing observational measurements of cvir−Mvir to provide rough limits on the four astrophysical parameters. Our non-linear model is made publicly available and can be used to include Camels-based baryon imprints in any halo model-based analysis.

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  2. Free, publicly-accessible full text available August 1, 2024
  3. Abstract 
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    Free, publicly-accessible full text available April 1, 2024
  4. Permeability of binary mixtures of soils is important for several industrial and engineering applications. Previous models for predicting the permeability of a binary mixture of soils were primarily developed from Kozeny–Carman equation with an empirical approach. The permeability is predicted based on an equivalent particle size of the two species. This study is aimed to develop a model using a more fundamental approach. Instead of an equivalent particle size, the permeability is predicted based on the bimodal void sizes of the binary mixture. Because the bimodal void sizes are not available as commonly measured physical properties. We first develop an analytical method that has the capability of predicting the bimodal void sizes of a binary mixture. A permeability model is then developed based on the bimodal void sizes of the binary mixture. The developed permeability model is evaluated by comparing the predicted and experimentally measured results for binary mixtures of glass beads, crush sand, and gravel sand. The findings can contribute to a better understanding of the important influence of pore structure on the prediction of permeability. 
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    Free, publicly-accessible full text available January 1, 2024
  5. Free, publicly-accessible full text available August 1, 2024
  6. Graphene layers placed on SrTiO3 single-crystal substrates, i.e., templates for remote epitaxy of functional oxide membranes, were investigated using temperature-dependent confocal Raman spectroscopy. This approach successfully resolved distinct Raman modes of graphene that are often untraceable in conventional measurements with non-confocal optics due to the strong Raman scattering background of SrTiO3. Information on defects and strain states was obtained for a few graphene/SrTiO3 samples that were synthesized by different techniques. This confocal Raman spectroscopic approach can shed light on the investigation of not only this graphene/SrTiO3 system but also various two-dimensional layered materials whose Raman modes interfere with their substrates.

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  7. Abstract 
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  8. Abstract

    Jamming is the transition from a fluid‐like state to a solid‐like state of a packing system. Recent studies have shown that jamming transition depends upon many factors: particle shape, friction/cohesion between particles, particle size dispersity, the stress of the packing, etc. This study aims to contribute to this growing area of research by exploring the jamming density of soil with strong dispersity. In analogous to Gibbs excess energy, we introduce excess volume‐potentials for each species. We then proposed a mathematical model to quantitatively compute the jamming density based on the second law of equilibrium in thermodynamics. This approach is validated using experimental results on glass beads and on silty sand. It is hoped that this study will provide to a deeper understanding of the link between jamming density, packing dispersity and the second law of thermodynamics.

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