MOFGalaxyNet: a social network analysis for predicting guest accessibility in metal–organic frameworks utilizing graph convolutional networks

Metal–organic frameworks (MOFs), are porous crystalline structures comprising of metal ions or clusters intricately linked with organic entities, displaying topological diversity and effortless chemical flexibility. These characteristics render them apt for multifarious applications such as adsorption, separation, sensing, and catalysis. Predominantly, the distinctive properties and prospective utility of MOFs are discerned post-manufacture or extrapolation from theoretically conceived models. For empirical researchers unfamiliar with hypothetical structure development, the meticulous crystal engineering of a high-performance MOF for a targeted application via a bottom-up approach resembles a gamble. For example, the precise pore limiting diameter (PLD), which determines the guest accessibility of any MOF cannot be easily inferred with mere knowledge of the metal ion and organic ligand. This limitation in bottom-up conceptual understanding of specific properties of the resultant MOF may contribute to the cautious industrial-scale adoption of MOFs. Consequently, in this study, we take a step towards circumventing this limitation by designing a new tool that predicts the guest accessibility—a MOF key performance indicator—of any given MOF from information on only the organic linkers and the metal ions. This new tool relies on clustering different MOFs in a galaxy-like social network, MOFGalaxyNet, combined with a Graphical Convolutional Network (GCN) to predict the guest accessibility of any new entry in the social network. The proposed network and GCN results provide a robust approach for screening MOFs for various host–guest interaction studies

Sensing Molecules with Metal–Organic Framework Functionalized Graphene Transistors

Graphene is inherently sensitive to vicinal dielectrics and local charge distributions, a property that can be probed by the position of the Dirac point in graphene field-effect transistors. Exploiting this as a useful sensing principle requires selectivity; however, graphene itself exhibits no molecule-specific interaction. Complementarily, metal–organic frameworks can be tailored to selective adsorption of specific molecular species. Here, a selective ethanol sensor is demonstrated by growing a surface-mounted metal–organic framework (SURMOF) directly onto graphene field-effect transistors (GFETs). Unprecedented shifts of the Dirac point, as large as 15 V, are observed when the SURMOF/GFET is exposed to ethanol, while a vanishingly small response is observed for isopropanol, methanol, and other constituents of the air, including water. The synthesis and conditioning of the hybrid materials sensor with its functional characteristics are described and a model is proposed to explain the origin, magnitude, and direction of the Dirac point voltage shift. Tailoring multiple SURMOFs to adsorb specific gases on an array of such devices thus generates a versatile, selective, and highly sensitive platform for sensing applications

Relaxation and reconstruction on (111) surfaces of Au, Pt, and Cu

We have theoretically studied the stability and reconstruction of (111) surfaces of Au, Pt, and Cu. We have calculated the surface energy, surface stress, interatomic force constants, and other relevant quantities by ab initio electronic structure calculations using the density functional theory (DFT), in a slab geometry with periodic boundary conditions. We have estimated the stability towards a quasi-one-dimensional reconstruction by using the calculated quantities as parameters in a one-dimensional Frenkel-Kontorova model. On all surfaces we have found an intrinsic tensile stress. This stress is large enough on Au and Pt surfaces to lead to a reconstruction in which a denser surface layer is formed, in agreement with experiment. The experimentally observed differences between the dense reconstruction pattern on Au(111) and a sparse structure of stripes on Pt(111) are attributed to the details of the interaction potential between the first layer of atoms and the substrate.Comment: 8 pages, 3 figures, submitted to Physical Review

DLS setup for in-situ measurements of photo-induced size changes of microgel-based hybrid particles

Photoinduced size changes in microgel particles loaded with gold nanoparticles (AuNPs) were investigated with an extended multiangle dynamic light scattering (DLS) setup. The DLS setup was equipped with a conventional laser (λ = 633 nm) to determine the microgel particle size. Additionally, a laser (λ = 532 nm) is installed to study the photoresponsive behavior of the AuNP–microgel hybrids. The wavelength of 532 nm is close to the absorption maximum of the plasmon resonance of the AuNPs used in the present study (i.e. spherical AuNPs with a diameter of 14 nm). The extended DLS setup enables us to follow in situ the change in microgel size during irradiation. The light stimulus is directly correlated with the size changes of the hybrid particles and the photothermal effect depends on the intensity of the excitation laser. The increase in excitation laser intensity results in a size reduction of hybrid particles because of the ability of AuNPs to partially transform the absorbed photon energy into heat which is emitted into the surrounding microgel network

Adsorbate-induced lifting of substrate relaxation is a general mechanism governing titania surface chemistry

Under ambient conditions, almost all metals are coated by an oxide. These coatings, the result of a chemical reaction, are not passive. Many of them bind, activate and modify adsorbed molecules, processes that are exploited, for example, in heterogeneous catalysis and photochemistry. Here we report an effect of general importance that governs the bonding, structure formation and dissociation of molecules on oxidic substrates. For a specific example, methanol adsorbed on the rutile TiO2(110) single crystal surface, we demonstrate by using a combination of experimental and theoretical techniques that strongly bonding adsorbates can lift surface relaxations beyond their adsorption site, which leads to a significant substrate-mediated interaction between adsorbates. The result is a complex superstructure consisting of pairs of methanol molecules and unoccupied adsorption sites. Infrared spectroscopy reveals that the paired methanol molecules remain intact and do not deprotonate on the defect-free terraces of the rutile TiO2(110) surface

Atomically precise semiconductor-graphene and hBN interfaces by Ge intercalation

The full exploration of the potential, which graphene offers to nanoelectronics requires its integration into semiconductor technology. So far the real-world applications are limited by the ability to concomitantly achieve large single-crystalline domains on dielectrics and semiconductors and to tailor the interfaces between them. Here we show a new direct bottom-up method for the fabrication of high-quality atomically precise interfaces between 2D materials, like graphene and hexagonal boron nitride (hBN), and classical semiconductor via Ge intercalation. Using angle-resolved photoemission spectroscopy and complementary DFT modelling we observed for the first time that epitaxially grown graphene with the Ge monolayer underneath demonstrates Dirac Fermions unaffected by the substrate as well as an unperturbed electronic band structure of hBN. This approach provides the intrinsic relativistic 2D electron gas towards integration in semiconductor technology. Hence, these new interfaces are a promising path for the integration of graphene and hBN into state-of-the-art semiconductor technology