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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. 

Redox-active colloids (RACs) represent a novel class of energy carriers that exchange electrical energy upon contact. Understanding contact-mediated electron transfer dynamics in RACs offers insights into physical contact events in colloidal suspensions and enables quantification of electrical energy transport in nonconjugated polymers. Redox-based electron transport was directly observed in monolayers of micron-sized RACs containing ethyl-viologen side groups via fluorescence microscopy through an unexpected nonlinear electrofluorochromism that is quantitatively coupled to the redox state of the colloid. Via imaging studies, using this electrofluorochromism, the apparent charge transfer diffusion coefficientD_CTof the RAC was easily determined. The visualization of energy transport within suspensions of redox-active colloids was also demonstrated. Our work elucidates fundamental mechanisms of energy transport in colloidal systems, informs the development of next-generation redox flow batteries, and may inspire new designs of smart active soft matter including conductive polymers for applications ranging from electrochemical sensors and organic electronics to colloidal robotics. 

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.