Abstract: Periodic mesoporous organosilicas provide the best of two worlds: the strength and porosity of an inorganic framework combined with the infinite possibilities created by the organic bridging unit. In this work we focus on post-synthetical modification of benzene bridged PMO, in order to create bromobenzene PMO. In the past, this proved to be very challenging due to unwanted structural deterioration. However, now we have found a way to brominate this material whilst keeping the structure intact. In-depth structural analysis by solid state NMR and XPS shows both vast progress over previous attempts as well as potential for improvement.

Abstract: Plasma medicine has attracted tremendous interest in a variety of medical conditions, ranging from wound healing to antimicrobial applications, even in cancer treatment, through the interactions of cold atmospheric plasma (CAP) and various biological tissues directly or indirectly. The underlying mechanisms of CAP treatment are still poorly understood although the oxidative effects of CAP with amino acids, peptides, and proteins have been explored experimentally. In this study, machine learning (ML) technology is introduced to efficiently unveil the interaction mechanisms of amino acids and reactive oxygen species (ROS) in seconds based on the data obtained from the reactive molecular dynamics (MD) simulations, which are performed to probe the interaction of five types of amino acids with various ROS on the timescale of hundreds of picoseconds but with the huge computational load of several days. The oxidative reactions typically start with H-abstraction, and the details of the breaking and formation of chemical bonds are revealed; the modification types, such as nitrosylation, hydroxylation, and carbonylation, can be observed. The dose effects of ROS are also investigated by varying the number of ROS in the simulation box, indicating agreement with the experimental observation. To overcome the limits of timescales and the size of molecular systems in reactive MD simulations, a deep neural network (DNN) with five hidden layers is constructed according to the reaction data and employed to predict the type of oxidative modification and the probability of occurrence only in seconds as the dose of ROS varies. The well-trained DNN can effectively and accurately predict the oxidative processes and productions, which greatly improves the computational efficiency by almost ten orders of magnitude compared with the reactive MD simulation. This study shows the great potential of ML technology to efficiently unveil the underpinning mechanisms in plasma medicine based on the data from reactive MD simulations or experimental measurements. In this study, since reactive molecular dynamics simulation can currently only describe interactions between a few hundred atoms in a few hundred picoseconds, deep neural networks (DNN) are introduced to enhance the simulation results by predicting more data efficiently. image

Abstract: Following an extensive investigation of various monolayer transition metal dichalcogenides (MX2), research interest has expanded to include multilayer systems. In bilayer MX2, the stacking order strongly impacts the local band structure as it dictates the local confinement and symmetry. Determination of stacking order in multilayer MX(2)domains usually relies on prior knowledge of in-plane orientations of constituent layers. This is only feasible in case of growth resulting in well-defined triangular domains and not useful in-case of closed layers with hexagonal or irregularly shaped islands. Stacking order can be discerned in the reciprocal space by measuring changes in diffraction peak intensities. Advances in detector technology allow fast acquisition of high-quality four-dimensional datasets which can later be processed to extract useful information such as thickness, orientation, twist and strain. Here, we use 4D scanning transmission electron microscopy combined with multislice diffraction simulations to unravel stacking order in epitaxially grown bilayer MoS2. Machine learning based data segmentation is employed to obtain useful statistics on grain orientation of monolayer and stacking in bilayer MoS2.

Abstract: We present KITE, a general purpose open-source tight-binding software for accurate real-space simulations of electronic structure and quantum transport properties of large-scale molecular and condensed systems with tens of billions of atomic orbitals (N similar to 10(10)). KITE's core is written in C++, with a versatile Python-based interface, and is fully optimized for shared memory multi-node CPU architectures, thus scalable, efficient and fast. At the core of KITE is a seamless spectral expansion of lattice Green's functions, which enables large-scale calculations of generic target functions with uniform convergence and fine control over energy resolution. Several functionalities are demonstrated, ranging from simulations of local density of states and photo-emission spectroscopy of disordered materials to large-scale computations of optical conductivity tensors and real-space wave-packet propagation in the presence of magneto-static fields and spin-orbit coupling. On-the-fly calculations of real-space Green's functions are carried out with an efficient domain decomposition technique, allowing KITE to achieve nearly ideal linear scaling in its multi-threading performance. Crystalline defects and disorder, including vacancies, adsorbates and charged impurity centres, can be easily set up with KITE's intuitive interface, paving the way to user-friendly large-scale quantum simulations of equilibrium and non-equilibrium properties of molecules, disordered crystals and heterostructures subject to a variety of perturbations and external conditions.

Abstract: The dithiol functionalized UiO-66-(SH)(2) is developed as an efficient adsorbent for the removal of mercury in aqueous media. Important parameters for the application of MOFs in real-life circumstances include: stability and recyclability of the adsorbents, selectivity for the targeted Hg species in the presence of much higher concentrations of interfering species, and ability to purify wastewater below international environmental limits within a short time. We show that UiO-66-(SH)(2) meets all these criteria.

Abstract: We present a model that describes the effect of elastic constraint on the thermodynamics of hydrogen absorption and desorption in biphasic core-shell nanoparticles, where the core is a hydride forming metal. In particular, the change of the hydride formation enthalpy and of the equilibrium pressure for the metal/hydride transformation are described as a function of nanoparticles radius, shell thickness, and elastic properties of both core and shell. To test the model, the hydrogen sorption isotherms of Mg-MgO core-shell nanoparticles, synthesized by inert gas condensation, were measured by means of optical hydrogenography. The model's predictions are in good agreement with the experimentally determined plateau pressure of hydrogen absorption. The features that a core-shell systems should exhibit in view of practical hydrogen storage applications are discussed with reference to the model and the experimental results. Copyright (C) 2013, Hydrogen Energy Publications, LLC. Published by Elsevier Ltd. All rights reserved.

Abstract: We present a combined study of experimental and computational work for a dielectric barrier discharge (DBD) used for CH4 conversion into H2. More specifically, we investigated the influence of N2 as an impurity (150,000 ppm) and as additive gas (199%) on the CH4 conversion and H2 yield. For this purpose, a zero-dimensional chemical kinetics model is applied to study the plasma chemistry. The calculated conversions and yields for various gas mixing ratios are compared to the obtained experimental values, and good agreement is achieved. The study reveals the significance of the View the MathML source and View the MathML source metastable states for the CH4 conversion into H2, based on a kinetic analysis of the reaction chemistry.

Abstract: We present the in situ synthesis of Pt nanoparticles within MIL-101-Cr (MIL = Materials Institute Lavoisier) by means of atomic layer deposition (ALD). The obtained Pt@MIL-101 materials were characterized by means of N2 adsorption and X-ray powder diffraction (XRPD) measurements, showing that the structure of the metal organic framework was well preserved during the ALD deposition. X-ray fluorescence (XRF) and transmission electron microscopy (TEM) analysis confirmed the deposition of highly dispersed Pt nanoparticles with sizes determined by the MIL-101-Cr pore sizes and with an increased Pt loading for an increasing number of ALD cycles. The Pt@MIL-101 material was examined as catalyst in the hydrogenation of different linear and cyclic olefins at room temperature, showing full conversion for each substrate. Moreover, even under solvent free conditions, full conversion of the substrate was observed. A high concentration test has been performed showing that the Pt@MIL-101 is stable for a long reaction time without loss of activity, crystallinity and with very low Pt leaching.

Abstract: To obtain a nanocrystalline SnO2 matrix and mono- and bimetallic nanocomposites SnO2/Pd, SnO2/Pt, and SnO2/PtPd, a flame spray pyrolysis with subsequent impregnation was used. The materials were characterized using X-ray diffraction (XRD), a single-point BET method, transmission electron microscopy (TEM), and high angle annular dark field scanning transmission electron microscopy (HAADF-STEM) with energy dispersive X-ray (EDX) mapping. The electronic state of the metals in mono- and bimetallic clusters was determined using X-ray photoelectron spectroscopy (XPS). The active surface sites were investigated using the Fourier Transform infrared spectroscopy (FTIR) and thermo-programmed reduction with hydrogen (TPR-H-2) methods. The sensor response of blank SnO2 and nanocomposites had a carbon monoxide (CO) level of 6.7 ppm and was determined in the temperature range 60-300 degrees C in dry (Relative Humidity (RH) = 0%) and humid (RH = 20%) air. The sensor properties of the mono- and bimetallic nanocomposites were analyzed on the basis of information on the electronic state, the distribution of modifiers in SnO2 matrix, and active surface centers. For SnO2/PtPd, the combined effect of the modifiers on the electrophysical properties of SnO2 explained the inversion of sensor response from n- to p-types observed in dry conditions.

Abstract: We report morpho-structural properties and charge conduction mechanisms of a foamy “graphene sponge ”, having a density as low as & AP;0.07 kg/m3 and a carbon to oxygen ratio C:O & SIME; 13:1. The spongy texture analysed by scanning electron microscopy is made of irregularly-shaped millimetres-sized small flakes, containing small crystallites with a typical size of & SIME;16.3 nm. A defect density as high as & SIME;2.6 x 1011 cm-2 has been estimated by the Raman intensity of D and G peaks, dominating the spectrum from room temperature down to & SIME;153 K. Despite the high C:O ratio, the graphene sponge exhibits an insulating electrical behavior, with a raise of the resistance value at & SIME;6 K up to 5 orders of magnitude with respect to the room temperature value. A variable range hopping (VRH) conduction, with a strong 2D character, dominates the charge carriers transport, from 300 K down to 20 K. At T < 20 K, graphene sponge resistance tends to saturate, suggesting a temperature-independent quantum tunnelling. The 2D-VRH conduction originates from structural disorder and is consistent with hopping of charge carriers between sp2 defects in the plane, where sp3 clusters related to oxygen functional groups act as potential barriers.</p>

Abstract: The vibrational properties of 2H-TaSe_2-xS_x (0≤x≤2) single crystals were probed using Raman spectroscopy and density functional theory calculations. The end members revealed two out of four symmetry-predicted Raman active modes, together with the pronounced two-phonon structure, attributable to the enhanced electron-phonon coupling. Additional peaks become observable due to crystallographic disorder for the doped samples. The evolution of the E₂g² mode Fano parameter reveals that the disorder has a weak impact on electron-phonon coupling, which is also supported by the persistence of two-phonon structure in doped samples. As such, this research provides thorough insights into the lattice properties, the effects of crystallographic disorder on Raman spectra, and the interplay of this disorder with the electron-phonon coupling in 2H-TaSe_2-xS_x compounds.

Abstract: Motivated by the potential of atomically thin magnets towards achieving tunable high-frequency magnonics, we detail the spin-wave dispersion of bilayer CrI3. We demonstrate that the magnonic behavior of the bilayer strongly depends on its stacking configuration and the interlayer magnetic ordering, where a topological band gap opens in the dispersion caused by the Dzyaloshinskii-Moriya and Kitaev interactions, classifying bilayer CrI3 as a topological magnon insulator. We further reveal that both the size and the topology of the band gap in a CrI3 bilayer with an antiferromagnetic interlayer ordering are tunable by an external magnetic field.

Abstract: Research efforts on the description of the low-temperature magnetic order and electronic properties of U3O8 have been inconclusive so far. Reinterpreting neutron scattering results, we use group representation theory to show that the ground state presents collinear out-of-plane magnetic moments, with antiferromagnetic coupling both in-layer and between layers. Charge order relieves the initial geometric frustration, generating a slightly distorted honeycomb sublattice with Néel-type order. The precise knowledge of the characteristics of this magnetic ground state is then used to explain the fine features of the band gap. In this system, spin-orbit coupling (SOC) is of critical importance, as it strongly affects the electronic structure, narrowing the gap by ∼38%, compared to calculations neglecting SOC. The predicted electronic structure actually explains the salient features of recent optical absorption measurements, further demonstrating the excellent agreement between the calculated ground state properties and experiment.

Abstract: Hydrogen production through photocatalytic water splitting is being developed swiftly to address the ongoing energy crisis. Over the past decade, with the rise of graphene and other two-dimensional (2D) materials, an increasing number of computational and experimental studies have focused on relevant van der Waals (vdW) semiconductor heterostructures for photocatalytic water splitting. In this review, the fundamental mechanism and distinctive performance of type-II and Z-scheme vdW heterostructure photocatalysts are presented. Accordingly, we have conducted a systematic review of recent studies focusing on candidates for photocatalysts, specifically vdW heterostructures involving 2D transition metal disulfides (TMDs), 2D Janus TMDs, and phosphorenes. The photocatalytic performance of these heterostructures and their suitability in theoretical scenarios are discussed based on their electronic and optoelectronic properties, particularly in terms of band structures, photoexcited carrier dynamics, and light absorption. In addition, various approaches for tuning the performance of these potential photocatalysts are illustrated. This strategic framework for constructing and modulating 2D heterostructure photocatalysts is expected to provide inspiration for addressing possible challenges in future studies.