AI Article Synopsis
- The synthesis of covalent organic nanosheets on reactive metal surfaces can hide their true properties due to strong adsorption.
- Post-synthetic exposure to iodine vapor can create an iodine layer between the organic networks and metal surfaces, helping to reduce electronic coupling.
- This iodine intercalation leads to changes in the nanosheets that make their geometric and electronic properties more similar to those of free-standing networks, as confirmed by experiments and DFT simulations.
Article Abstract
The on-surface synthesis of covalent organic nanosheets driven by reactive metal surfaces leads to strongly adsorbed organic nanostructures, which conceals their intrinsic properties. Hence, reducing the electronic coupling between the organic networks and commonly used metal surfaces is an important step towards characterization of the true material. We demonstrate that post-synthetic exposure to iodine vapor leads to the intercalation of an iodine monolayer between covalent polyphenylene networks and Ag(111) surfaces. The experimentally observed changes from surface-bound to detached nanosheets are reproduced by DFT simulations. These findings suggest that the intercalation of iodine provides a material that shows geometric and electronic properties substantially closer to those of the freestanding network.
Download full-text PDF |
Source |
|---|---|
| http://dx.doi.org/10.1002/anie.201600684 | DOI Listing |
Publication Analysis
Top Keywords
Similar Publications
Spontaneous Catalytic Reaction of a Surfactant in the Interfacial Microenvironment of Colloidal Gold Nanoparticles.
J Am Chem Soc
January 2025
State Key Laboratory of Marine Environmental Science, Fujian Provincial Key Laboratory for Coastal Ecology and Environmental Studies, Center for Marine Environmental Chemistry and Toxicology, College of the Environment and Ecology, Xiamen University, Xiamen 361102, China.
The performance of nanomaterials is significantly determined by the interfacial microenvironment, in which a surfactant plays an essential role as the adsorbent, but its involvement in the interfacial reaction is often overlooked. Here, it was discovered that citrate and ascorbic acid, the two primarily used surfactants for colloidal gold nanoparticles (Au NPs), can spontaneously undergo catalytic reaction with trace-level nitrogenous residue under ambient environment to form oxime, which is subsequently cleaved to generate CN or a compound containing the -CN group. Such a catalytic reaction shows wide universality in both reactants, including various carbonaceous and nitrogenous sources, and metal catalysts, including Au, Ag, Fe, Cu, Ni, Pt, and Pd NPs.
View Article and Find Full Text PDFMimicking Nature: Effect of Architectural Design Inspired by Cancellous Bone on the Biological Response of hMSC Cultured on Titanium Scaffolds Fabricated by Laser Beam Powder Bed Fusion.
J Biomed Mater Res A
January 2025
Faculty of Materials Science and Engineering, Warsaw University of Technology, Warsaw, Poland.
Bone tissue regeneration can be affected by various architectonical features of 3D porous scaffold, for example, pore size and shape, strut size, curvature, or porosity. However, the design of additively manufactured structures studied so far was based on uniform geometrical figures and unit cell structures, which often do not resemble the natural architecture of cancellous bone. Therefore, the aim of this study was to investigate the effect of architectonical features of additively manufactured (aka 3D printed) titanium scaffolds designed based on microtomographic scans of fragments of human femurs of individuals of different ages on in vitro response of human bone-derived mesenchymal stem cells (hMSC).
View Article and Find Full Text PDFLiquid-Metal-Based Multichannel Strain Sensor for Sign Language Gesture Classification Using Machine Learning.
ACS Appl Mater Interfaces
January 2025
Centre for Robotics and Automation, Department of Biomedical Engineering, City University of Hong Kong, Hong Kong 999077, China.
Liquid metals are highly conductive like metallic materials and have excellent deformability due to their liquid state, making them rather promising for flexible and stretchable wearable sensors. However, patterning liquid metals on soft substrates has been a challenge due to high surface tension. In this paper, a new method is proposed to overcome the difficulties in fabricating liquid-state strain sensors.
View Article and Find Full Text PDFTailoring rhodium-based metal-organic layers for parahydrogen-induced polarization: achieving 20% polarization of H in liquid phase.
Natl Sci Rev
January 2025
State Key Laboratory of Physical Chemistry of Solid Surfaces, School of Electronic Science and Engineering, Department of Chemistry, College of Chemistry and Chemical Engineering, Xiamen University, Xiamen 361005, China.
Heterogeneous catalysts for parahydrogen-induced polarization (HET-PHIP) would be useful for producing highly sensitive contrasting agents for magnetic resonance imaging (MRI) in the liquid phase, as they can be removed by simple filtration. Although homogeneous hydrogenation catalysts are highly efficient for PHIP, their sensitivity decreases when anchored on porous supports due to slow substrate diffusion to the active sites and rapid depolarization within the channels. To address this challenge, we explored 2D metal-organic layers (MOLs) as supports for active Rh complexes with diverse phosphine ligands and tunable hydrogenation activities, taking advantage of the accessible active sites and chemical adaptability of the MOLs.
View Article and Find Full Text PDFMetal-organic frameworks (MOFs) are porous, crystalline materials with high surface area, adjustable porosity, and structural tunability, making them ideal for diverse applications. However, traditional experimental and computational methods have limited scalability and interpretability, hindering effective exploration of MOF structure-property relationships. To address these challenges, we introduce, for the first time, a category-specific topological learning (CSTL), which combines algebraic topology with chemical insights for robust property prediction.
View Article and Find Full Text PDFWant AI Summaries of new PubMed Abstracts delivered to your In-box?
Enter search terms and have AI summaries delivered each week - change queries or unsubscribe any time!