We study the diffusion dynamics, the diffusion mechanisms, and the adsorption energetics of Ag, Au, Cu, and Pd dimers, as well as of Ag trimers on single-layer graphene (SLG) by means of ab initio molecular dynamics (AIMD) simulations and density-functional theory (DFT) calculations. The simulations show that Ag, Cu, and Au clusters exhibit a super-diffusive pattern characterized by long jumps, which can be explained by the flat potential energy landscape (PEL) (corrugation of a few tens of meV) encountered by those clusters on SLG. Pd dimers, instead, diffuse in a pattern that is reminiscent of conventional random walk, which is consistent with a significantly rougher PEL of the order of 100 meV. Moreover, our data show that all clusters exhibit diffusion mechanisms that include both concerted translation and rotation. The overall results of the present study provide key insights for modeling the growth of metal layers and nanostructures on graphene and other van der Waals materials, which is a prerequisite for the directed growth of multifunctional metal contacts in a broad range of enabling devices.
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http://dx.doi.org/10.1039/d1cp00522g | DOI Listing |
Understanding cellular responses to external stimuli is critical for parsing biological mechanisms and advancing therapeutic development. High-content image-based assays provide a cost-effective approach to examine cellular phenotypes induced by diverse interventions, which offers valuable insights into biological processes and cellular states. In this paper, we introduce MorphoDiff, a generative pipeline to predict high-resolution cell morphological responses under different conditions based on perturbation encoding.
View Article and Find Full Text PDFMicrobes of nearly every species can form biofilms, communities of cells bound together by a self-produced matrix. It is not understood how variation at the cellular level impacts putatively beneficial, colony-level behaviors, such as cell-to-cell signaling. Here we investigate this problem with an agent-based computational model of metabolically driven electrochemical signaling in Bacillus subtilis biofilms.
View Article and Find Full Text PDFPregnancy is a period of profound biological transformation. However, we know remarkably little about pregnancy-related brain changes. To address this gap, we chart longitudinal changes in brain structure during pregnancy and explore potential mechanisms driving these changes.
View Article and Find Full Text PDFBrain Commun
January 2025
Normandie Univ, UNICAEN, INSERM, U1237, PhIND 'Physiopathology and Imaging of Neurological Disorders', Institut Blood and Brain @ Caen-Normandie, Cyceron, 14000 Caen, France.
Four important imaging biomarkers of Alzheimer's disease, namely grey matter atrophy, glucose hypometabolism and amyloid-β and tau deposition, follow stereotypical spatial distributions shaped by the brain network of structural and functional connections. In this case-control study, we combined several predictors reflecting various possible mechanisms of spreading through structural and functional pathways to predict the topography of the four biomarkers in amyloid-positive patients while controlling for the effect of spatial distance along the cortex. For each biomarker, we quantified the relative contribution of each predictor to the variance explained by the model.
View Article and Find Full Text PDFVisual attribution in medical imaging seeks to make evident the diagnostically-relevant components of a medical image, in contrast to the more common detection of diseased tissue deployed in standard machine vision pipelines (which are less straightforwardly interpretable/explainable to clinicians). We here present a novel generative visual attribution technique, one that leverages latent diffusion models in combination with domain-specific large language models, in order to generate normal counterparts of abnormal images. The discrepancy between the two hence gives rise to a mapping indicating the diagnostically-relevant image components.
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