Mechanism Regulating Self-Intercalation in Layered Materials

Recent experimental breakthrough demonstrated a powerful synthesis approach for intercalating the van der Waals gap of layered materials to achieve property modulation, thereby opening an avenue for exploring new physics and devising novel applications, but the mechanism governing intercalant assembly patterns and properties remains unclear. Based on extensive structural search and energetics analysis by ab initio calculations, we reveal a Sabatier-like principle that dictates spatial arrangement of self-intercalated atoms in transition metal dichalcogenides. We further construct a robust descriptor quantifying that strong intercalant-host interactions favor a monodispersing phase of intercalated atoms that may exhibit ferromagnetism, while weak interactions lead to a trimer phase with attenuated or quenched magnetism, which further evolves into tetramer and hexagonal phases at increasing intercalant density. These findings elucidate the mechanism underpinning experimental observations and paves the way for rational design and precise control of self-intercalation in layered materials

Deep-Learning-Enhanced Diffusion Imaging Assay for Resolving Local-Density Effects on Membrane Receptors

G-protein-coupled receptor (GPCR) density at the cell surface is thought to regulate receptor function. Spatially resolved measurements of local-density effects on GPCRs are needed but technically limited by density heterogeneity and mobility of membrane receptors. We now develop a deep-learning (DL)-enhanced diffusion imaging assay that can measure local-density effects on ligand–receptor interactions in the plasma membrane of live cells. In this method, the DL algorithm allows the transformation of 100 ms exposure images to density maps that report receptor numbers over any specified region with ∼95% accuracy by 1 s exposure images as ground truth. With the density maps, a diffusion assay is further established for spatially resolved measurements of receptor diffusion coefficient as well as to express relationships between receptor diffusivity and local density. By this assay, we scrutinize local-density effects on chemokine receptor CXCR4 interactions with various ligands, which reveals that an agonist prefers to act with CXCR4 at low density while an inverse agonist dominates at high density. This work suggests a new insight into density-dependent receptor regulation as well as provides an unprecedented assay that can be applicable to a wide variety of receptors in live cells

Deep-Learning-Enhanced Diffusion Imaging Assay for Resolving Local-Density Effects on Membrane Receptors

G-protein-coupled receptor (GPCR) density at the cell surface is thought to regulate receptor function. Spatially resolved measurements of local-density effects on GPCRs are needed but technically limited by density heterogeneity and mobility of membrane receptors. We now develop a deep-learning (DL)-enhanced diffusion imaging assay that can measure local-density effects on ligand–receptor interactions in the plasma membrane of live cells. In this method, the DL algorithm allows the transformation of 100 ms exposure images to density maps that report receptor numbers over any specified region with ∼95% accuracy by 1 s exposure images as ground truth. With the density maps, a diffusion assay is further established for spatially resolved measurements of receptor diffusion coefficient as well as to express relationships between receptor diffusivity and local density. By this assay, we scrutinize local-density effects on chemokine receptor CXCR4 interactions with various ligands, which reveals that an agonist prefers to act with CXCR4 at low density while an inverse agonist dominates at high density. This work suggests a new insight into density-dependent receptor regulation as well as provides an unprecedented assay that can be applicable to a wide variety of receptors in live cells