The galaxy size - halo mass scaling relations and clustering properties of central and satellite galaxies

In this work, we combine size and stellar mass measurements from the Sloan Digital Sky Server (SDSS) with the group finder algorithm of Rodriguez \& Merch\'an in order to determine the stellar and halo mass -- size relations of central and satellite galaxies separately. We show that, while central and satellite galaxies display similar stellar mass -- size relations, their halo mass -- size relations differ significantly. As expected, more massive haloes tend to host larger central galaxies. However, the size of satellite galaxies depends only slightly on halo virial mass. We show that these results are compatible with a remarkably simple model in which the size of central and satellite galaxies scales as the cubic root of their host halo mass, with the normalization for satellites being $\sim$ 30 \% smaller than that for central galaxies, which can be attributed to tidal stripping. We further check that our measurements are in excellent agreement with predictions from the IllustrisTNG hydrodynamical simulation. In the second part of this paper, we analyse how the clustering properties of central and satellite galaxies depend on their size. We demonstrate that, independently of the stellar mass threshold adopted, smaller galaxies are more tightly clustered than larger galaxies when either the entire sample or only satellites are considered. The opposite trend is observed on large scales when the size split is performed for the central galaxies alone. Our results place significant constraints for halo-galaxy connection models that link galaxy size with the properties of their hosting haloes.Comment: 15 pages, 12 figures. Accepted for publication in MNRA

Twisted graphene in graphite: Impact on surface potential and chemical stability

Abstract Highly-oriented pyrolytic graphite (HOPG), i.e., the 3D stack of sp2-hybridized carbon sheets, is an attractive material thanks to its high electrical conductivity, chemical inertness, thermal stability, atomic-scale flatness, and ease of exfoliation. Despite an apparently ideal and uniform material, freshly cleaved HOPG shows domains in Kelvin probe force microscopy (KPFM) with surface potential contrast over 30 mV. We systematically investigated these domains using an integrated approach, including time-dependent KPFM and hyperspectral Raman imaging. The observed time-evolving domains are attributed to locally different hydrocarbon adsorption from the environment, driven by structural defects likely related to rotational mismatch, i.e., twisted layers. These defects affect the interlayer coupling between topmost graphene and the underlying layers. Our hypothesis was supported by Raman spectroscopy results, showing domains with G peak shifts and 2D line shape compatible with bilayer graphene. We attribute the selective sensitivity of our Raman spectroscopy results to the top graphene layers as resonances due to van Hove singularities. Our results show that the chemical and electrical properties of HOPG are far more complex than what is generally believed due to the broken symmetry at the top surface, giving rise to graphene bilayer-like behavior

Beyond Tissue replacement: The Emerging role of smart implants in healthcare

Smart implants are increasingly used to treat various diseases, track patient status, and restore tissue and organ function. These devices support internal organs, actively stimulate nerves, and monitor essential functions. With continuous monitoring or stimulation, patient observation quality and subsequent treatment can be improved. Additionally, using biodegradable and entirely excreted implant materials eliminates the need for surgical removal, providing a patient-friendly solution. In this review, we classify smart implants and discuss the latest prototypes, materials, and technologies employed in their creation. Our focus lies in exploring medical devices beyond replacing an organ or tissue and incorporating new functionality through sensors and electronic circuits. We also examine the advantages, opportunities, and challenges of creating implantable devices that preserve all critical functions. By presenting an in-depth overview of the current state-of-the-art smart implants, we shed light on persistent issues and limitations while discussing potential avenues for future advancements in materials used for these devices

Surface- and tip-enhanced Raman spectroscopy reveals spin-waves in iron oxide nanoparticles

Nanomaterials have the remarkable characteristic of displaying physical properties different from their bulk counterparts. An additional degree of complexity and functionality arises when oxide nanoparticles interact with metallic nanostructures. In this context the Raman spectra due to plasmonic enhancement of iron oxide nanocrystals are here reported showing the activation of spin-waves. Iron oxide nanoparticles on gold and silver tips are found to display a band around 1584 cm−1 attributed to a spin-wave magnon mode. This magnon mode is not observed for nanoparticles deposited on silicon (111) or on glass substrates. Metal–nanoparticle interaction and the strongly localized electromagnetic field contribute to the appearance of this mode. The localized excitation that generates this mode is confirmed by tip-enhanced Raman spectroscopy (TERS). The appearance of the spin-waves only when the TERS tip is in close proximity to a nanocrystal edge suggests that the coupling of a localized plasmon with spin-waves arises due to broken symmetry at the nanoparticle border and the additional electric field confinement. Beyond phonon confinement effects previously reported in similar systems, this work offers significant insights on the plasmon-assisted generation and detection of spin-waves optically induced

Counterfactual Explanations via Locally-guided Sequential Algorithmic Recourse

Counterfactuals operationalised through algorithmic recourse have become a powerful tool to make artificial intelligence systems explainable. Conceptually, given an individual classified as y -- the factual -- we seek actions such that their prediction becomes the desired class y' -- the counterfactual. This process offers algorithmic recourse that is (1) easy to customise and interpret, and (2) directly aligned with the goals of each individual. However, the properties of a "good" counterfactual are still largely debated; it remains an open challenge to effectively locate a counterfactual along with its corresponding recourse. Some strategies use gradient-driven methods, but these offer no guarantees on the feasibility of the recourse and are open to adversarial attacks on carefully created manifolds. This can lead to unfairness and lack of robustness. Other methods are data-driven, which mostly addresses the feasibility problem at the expense of privacy, security and secrecy as they require access to the entire training data set. Here, we introduce LocalFACE, a model-agnostic technique that composes feasible and actionable counterfactual explanations using locally-acquired information at each step of the algorithmic recourse. Our explainer preserves the privacy of users by only leveraging data that it specifically requires to construct actionable algorithmic recourse, and protects the model by offering transparency solely in the regions deemed necessary for the intervention.Comment: 7 pages, 5 figures, 3 appendix page

Polymer brushes on graphitic carbon nitride for patterning and as a SERS active sensing layer via incorporated nanoparticles

Graphitic carbon nitride (gCN) has a broad range of promising applications, from energy harvesting and storage to sensing. However, most of the applications are still restricted due to gCN poor dispersibility and limited functional groups. Herein, a direct photografting of gCN using various polymer brushes with tailorable functionalities via UV photopolymerization at ambient conditions is demonstrated. The systematic study of polymer brush-functionalized gCN reveals that the polymerization did not alter the inherent structure of gCN. Compared to the pristine gCN, the gCN-polymer composites show good dispersibility in various solvents such as water, ethanol, and tetrahydrofuran (THF). Patterned polymer brushes on gCN can be realized by employing photomask and microcontact printing technology. The polymer brushes with incorporated silver nanoparticles (AgNPs) on gCN can act as a multifunctional recyclable active sensing layer for surface-enhanced Raman spectroscopy (SERS) detection and photocatalysis. This multifunctionality is shown in consecutive cycles of SERS and photocatalytic degradation processes that can be applied to in situ monitor pollutants, such as dyes or pharmaceutical waste, with high chemical sensitivity as well as to water remediation. This dual functionality provides a significant advantage to our AgNPs/polymer-gCN with regard to state-of-the-art systems reported so far that only allow SERS pollutant detection but not their decomposition. These results may provide a new methodology for the covalent functionalization of gCN and may enable new applications in the field of catalysis, biosensors, and, most interestingly, environmental remediation