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Abstract We propose and unify classes of different models for information propagation over graphs. In a first class, propagation is modelled as a wave, which emanates from a set ofknownnodes at an initial time, to all otherunknownnodes at later times with an ordering determined by the arrival time of the information wave front. A second class of models is based on the notion of a travel time along paths between nodes. The time of information propagation from an initialknownset of nodes to a node is defined as the minimum of a generalised travel time over subsets of all admissible paths. A final class is given by imposing a local equation of an eikonal form at eachunknownnode, with boundary conditions at theknownnodes. The solution value of the local equation at a node is coupled to those of neighbouring nodes with lower values. We provide precise formulations of the model classes and prove equivalences between them. Finally, we apply the front propagation models on graphs to semi-supervised learning via label propagation and information propagation on trust networks. 

Abstract This study evaluates a popular density current propagation speed equation using a large, novel set of radiosonde and dropsonde observations. Data from pairs of sondes launched inside and outside of cold pools along with the theoretical density current propagation speed equation are used to calculate sonde-based propagation speeds. Radar-/satellite-based propagation speeds, assumed to be the truth, are calculated by manually tracking the propagation of cold pools and correcting for advection due to the background wind. Several results arise from the comparisons of the theoretical sonde-based speeds with the radar-/satellite-based speeds. First, sonde-based and radar-based propagation speeds are strongly correlated for U.S. High Plains cold pools, suggesting the density current propagation speed equation is appropriate for use in midlatitude continental environments. Second, cold pool Froude numbers found in this study are in agreement with previous studies. Third, sonde-based propagation speeds are insensitive to how cold pool depth is defined since the preponderance of negative buoyancy is near the surface in cold pools. Fourth, assuming an infinite channel depth and assuming an incompressible atmosphere when deriving the density current propagation speed equation can increase sonde-based propagation speeds by up to 20% and 11%, respectively. Finally, sonde-based propagation speeds can vary by ∼300% based on where and when the sondes were launched, suggesting submesoscale variability could be a major influence on cold pool propagation. 

Networks with controlled ratios of neutral and ionic dynamic crosslinks were prepared and demonstrate multiple damping modes. 

We examine the bulk electronic structure of ${\mathrm{Nd}}_3{\mathrm{Ni}}_2{\mathrm{O}}_7$using Ni $2p$core-level hard x-ray photoemission spectroscopy combined with density functional theory $+$dynamical mean-field theory. Our results reveal a large deviation of the Ni $3d$occupation from the formal ${\mathrm{Ni}}^{2.5+}$valency, highlighting the importance of the charge transfer from oxygen ligands. We find that the dominant $d^8$configuration is accompanied by nearly equal contributions from $d^7$and $d^9$states, exhibiting an unusual valence state among Ni-based oxides. Finally, we discuss the Ni $d_{x^2-y^2}$and $d_{z^2}$orbital-dependent hybridization, correlation and local spin dynamics. Published by the American Physical Society2025 

Abstract Oxide heterostructures exhibit a vast variety of unique physical properties. Examples are unconventional superconductivity in layered nickelates and topological polar order in (PbTiO₃)_n/(SrTiO₃)_nsuperlattices. Although it is clear that variations in oxygen content are crucial for the electronic correlation phenomena in oxides, it remains a major challenge to quantify their impact. Here, we measure the chemical composition in multiferroic (LuFeO₃)₉/(LuFe₂O₄)₁superlattices, mapping correlations between the distribution of oxygen vacancies and the electric and magnetic properties. Using atom probe tomography, we observe oxygen vacancies arranging in a layered three-dimensional structure with a local density on the order of 10¹⁴cm⁻², congruent with the formula-unit-thick ferrimagnetic LuFe₂O₄layers. The vacancy order is promoted by the locally reduced formation energy and plays a key role in stabilizing the ferroelectric domains and ferrimagnetism in the LuFeO₃and LuFe₂O₄layers, respectively. The results demonstrate pronounced interactions between oxygen vacancies and the multiferroic order in this system and establish an approach for quantifying the oxygen defects with atomic-scale precision in 3D, giving new opportunities for deterministic defect-enabled property control in oxide heterostructures. 

Sensitive, accurate, and early detection of biomarkers is essential for prompt response to medical decisions for saving lives. Some infectious diseases are deadly even in small quantities and require early detection for patients and public health. The scarcity of these biomarkers necessitates signal amplification before diagnosis. Recently, we demonstrated single-molecule-level detection of tuberculosis biomarker, lipoarabinomannan, from patient urine using silver plasmonic gratings with thin plasma-activated alumina. While powerful, biomarker binding density was limited by the surface density of plasma-activated carbonyl groups, that degraded quickly, resulting in immediate use requirement after plasma activation. Therefore, development of stable high density binding surfaces such as high binding polystyrene is essential to improving shelf-life, reducing binding protocol complexity, and expanding to a wider range of applications. However, any layers topping the plasmonic grating must be ultra-thin (<10 nm) for the plasmonic enhancement of adjacent signals. Furthermore, fabricating thin polystyrene layers over alumina is nontrivial because of poor adhesion between polystyrene and alumina. Herein, we present the development of a stable, ultra-thin polystyrene layer on the gratings, which demonstrated 63.8 times brighter fluorescence compared to commercial polystyrene wellplates. Spike protein was examined for COVID-19 demonstrating the single-molecule counting capability of the hybrid polystyrene-plasmonic gratings. 

Voids—the nothingness—broadly exist within nanomaterials and impact properties ranging from catalysis to mechanical response. However, understanding nanovoids is challenging due to lack of imaging methods with the needed penetration depth and spatial resolution. Here, we integrate electron tomography, morphometry, graph theory and coarse-grained molecular dynamics simulation to study the formation of interconnected nanovoids in polymer films and their impacts on permeance and nanomechanical behaviour. Using polyamide membranes for molecular separation as a representative system, three-dimensional electron tomography at nanometre resolution reveals nanovoid formation from coalescence of oligomers, supported by coarse-grained molecular dynamics simulations. Void analysis provides otherwise inaccessible inputs for accurate fittings of methanol permeance for polyamide membranes. Three-dimensional structural graphs accounting for the tortuous nanovoids within, measure higher apparent moduli with polyamide membranes of higher graph rigidity. Our study elucidates the significance of nanovoids beyond the nothingness, impacting the synthesis‒morphology‒function relationships of complex nanomaterials. 

Capillary suspensions are three-phase mixtures containing a solid particulate phase, a continuous liquid phase, and a second immiscible liquid forming capillary bridges between particles. Capillary suspensions are encountered in a wide array of applications including 3D printing, porous materials, and food formulations, but despite recent progress, the micromechanics of particle clusters in flow is not fully understood. In this work, we study the dynamics of meniscus-bound particle clusters in planar extensional flow using a Stokes trap, which is an automated flow control technique that allows for precise manipulation of freely suspended particles or particle clusters in flow. Focusing on the case of a two-particle doublet, we use a combination of experiments and analytical modeling to understand how particle clusters rearrange, deform, and ultimately break up in extensional flow. The time required for cluster breakup is quantified as a function of capillary number Ca and meniscus volume V. Importantly, a critical capillary number Cacrit for cluster breakup is determined using a combination of experiments and modeling. Cluster relaxation experiments are also performed by deforming particle clusters in flow, followed by flow cessation prior to breakup and observing cluster relaxation dynamics under zero-flow conditions. In all cases, experiments are complemented by an analytical model that accounts for capillary forces, lubrication forces, hydrodynamic drag forces, and hydrodynamic interactions acting on the particles. Results from the analytical models are found to be in good agreement with experiments. Overall, this work provides a new quantitative understanding of the deformation dynamics of capillary clusters in extensional flow.