Abstract: We detail the effects of Cl and S functionalization on the superconducting properties of layered (bulk) and monolayer niobium carbide (Nb2C) MXene crystals, based on first-principles calculations combined with Eliashberg theory. For bulk layered Nb2CCl2, the calculated superconducting transition temperature (T-c) is in very good agreement with the recently measured value of 6 K. We show that T-c is enhanced to 10 K for monolayer Nb2CCl2, due to an increase in the density of states at the Fermi level, and the corresponding electron-phonon coupling. We further demonstrate feasible gate- and strain-induced enhancements of T-c for both bulk-layered and monolayer Nb2CCl2 crystals, resulting in T-c values of around 38 K. In the S-functionalized Nb2CCl2 crystals, our calculations reveal the importance of phonon softening in understanding their superconducting properties. Finally, we predict that Nb3C2S2 in bulk-layered and monolayer forms is also superconducting, with a T-c of around 28 K. Considering that Nb2C is not superconducting in pristine form, our findings promote functionalization as a pathway towards robust superconductivity in MXenes.

Abstract: We developed a novel in situ (i.e. inside plasma and during operation) IR dielectric barrier discharge cell allowing investigation of plasma catalysis in transmission mode, atmospheric pressure, flow conditions (WHSV similar to 0-50 000 mL g(-1) h(-1)), at relevant discharge voltages (similar to 0-50 kV) and frequencies (similar to 0-5 kHz). We applied it to study the IR-active surface species formed on a SiO2 support and on a 3 wt% Ru/SiO2 catalyst, which can help to reveal the important surface reaction mechanisms during the plasma-catalytic dry reforming of methane (DRM). Moreover, we present a technique for the challenging task of estimating the temperature of a catalyst sample in a plasma-catalytic system in situ and during plasma operation. We found that during the reaction, water is immediately formed at the SiO2 surface, and physisorbed formic acid is formed with a delay. As Ru/SiO2 is subject to greater plasma-induced heating than SiO2 (with a surface temperature increase in the range of 70-120 degrees C, with peaks up to 150 degrees C), we observe lower amounts of physisorbed water on Ru/SiO2, and less physisorbed formic acid formation. Importantly, the formation of surface species on the catalyst sample in our plasma-catalytic setup, as well as the observed conversions and selectivities in plasma conditions, can not be explained by plasma-induced heating of the catalyst surface, but must be attributed to other plasma effects, such as the adsorption of plasma-generated radicals and molecules, or the occurrence of Eley-Rideal reactions.

Abstract: We evaluate the importance of quantum effects on the sticking of H2 on Al(110) for conditions that are close to those of molecular beam experiments that have been done on this system. Calculations with the quasi-classical trajectory (QCT) method and with quantum dynamics (QD) are performed using a model in which only motion in the six molecular degrees of freedom is allowed. The potential energy surface used has a minimum barrier height close to the value recently obtained with the quantum Monte Carlo method. Monte Carlo averaging over the initial rovibrational states allowed the QD calculations to be done with an order of magnitude smaller computational expense. The sticking probability curve computed with QD is shifted to lower energies relative to the QCT curve by 0.21 to 0.05 kcal/mol, with the highest shift obtained for the lowest incidence energy. Quantum effects are therefore expected to play a small role in calculations that would evaluate the accuracy of electronic structure methods for determining the minimum barrier height to dissociative chemisorption for H2 + Al(110) on the basis of the standard procedure for comparing results of theory with molecular beam experiments.

Abstract: We generalize the Gielis Superformula by extending the R. Chacon approach, but avoiding the use of Jacobi elliptic functions. The obtained results are extended to the three-dimensional case. Several new shapes are derived by using the computer algebra system Mathematica(C).

Abstract: We introduce a facile approach to transfer thin films and other mechanically sensitive TEM samples inside a FIB with minimal introduction of stress and bending. The method is making use of a pre-synthetized flexible freestanding Ag nanowire attached to the tip of a typical tungsten micromanipulator inside the FIB. The main advantages of this approach are the significantly reduced stress-induced bending during transfer and attachment of the TEM sample, the very short time required to attach and cut the nanowire, the operation at very low dose and ion current, and only using the e-beam for Pt deposition during the transfer of sensitive TEM samples. This results in a reduced sample preparation time and reduced exposure to the ion beam or e-beam for Pt deposition during the sample preparation and thus also reduced contamination and beam damage. The method was applied to a number of thin films and different TEM samples in order to illustrate the advantageous benefits of the concept. In particular, the technique has been successfully tested for the transfer of a thin film onto a MEMS heating chip for in situ TEM experiments.

Abstract: We introduce LPMLE3, a new 1-D approach to quantify vertical water flow components at streambeds using temperature data collected in different depths. LPMLE3 solves the partial differential equation for coupled water flow and heat transport in the frequency domain. Unlike other 1-D approaches it does not assume a semi-infinite halfspace with the location of the lower boundary condition approaching infinity. Instead, it uses local upper and lower boundary conditions. As such, the streambed can be divided into finite subdomains bound at the top and bottom by a temperature-time series. Information from a third temperature sensor within each subdomain is then used for parameter estimation. LPMLE3 applies a low order local polynomial to separate periodic and transient parts (including the noise contributions) of a temperature-time series and calculates the frequency response of each subdomain to a known temperature input at the streambed top. A maximum-likelihood estimator is used to estimate the vertical component of water flow, thermal diffusivity, and their uncertainties for each streambed subdomain and provides information regarding model quality. We tested the method on synthetic temperature data generated with the numerical model STRIVE and demonstrate how the vertical flow component can be quantified for field data collected in a Belgian stream. We show that by using the results in additional analyses, nonvertical flow components could be identified and by making certain assumptions they could be quantified for each subdomain. LPMLE3 performed well on both simulated and field data and can be considered a valuable addition to the existing 1-D methods.

Abstract: We investigate a Josephson junction in an electron-hole superfluid in a double-layer transition metal dichalco-genide heterostructure. The observation of a critical tunneling current is a clear signature of superfluidity. In addition, we find the BCS-BEC crossover physics in the narrow barrier region controls the critical current across the entire system. The corresponding critical velocity, which is measurable in this system, has a maximum when the excitations pass from bosonic to fermionic. Remarkably, this occurs for the density at the boundary of the BEC to BCS-BEC crossover regime determined from the condensate fraction. This provides, in a semiconductor system, an experimental way to determine the position of this boundary.

Abstract: We investigate discharge contraction in a microwave plasma at sub-atmospheric pressure, operating in CO2 and CO2/CH4 mixtures. The rise of the electron number density with plasma contraction intensifies the gas heating in the core of the plasma. This, in turn, initiates fast core-periphery transport and defines the rate of thermal chemistry over plasma chemistry. In this context, power concentration describes the overall mechanism including plasma contraction and chemical kinetics. In a complex chemistry such as dry reforming of methane, transport of reactive species is essential to define the performance of the reactor and achieve the desired outputs. Thus, we couple experimental observations and thermodynamic calculations for model validation and understanding of reactor performance. Adding CH4 alters the thermodynamic properties of the mixture, especially the reactive component of the heat conductivity. The increase in reactive heat conductivity increases the pressure at which plasma contraction occurs, because higher rates of gas heating are required to reach the same temperature. In addition, we suggest that the predominance of heat conduction over convection is a key condition to observe the effect of heat conductivity on gas temperature.

Abstract: We investigate the ground-state and dynamical properties of nonuniform two-dimensional (2D) clusters of long-range interacting particles. We demonstrate that, when the confining external potential is designed to produce an approximate 1/ r 2 density profile, the particles crystallize into highly ordered structures featuring spiral crystalline lines. Despite the strong inhomogeneity of the observed configurations, most of them are characterized by small density of topological defects, typical of conformal crystals, and the net topological charge induced by the simply-connected geometry of the system is concentrated near the cluster center. These crystals are shown to be robust with respect to thermal fluctuations up to a certain threshold temperature, above which the net charge is progressively redistributed from the center to the rest of the system and the topological order is lost. The crystals are also resilient to the shear stress produced by a small nonuniform azimuthal force field, rotating as a rigid body (RB). For larger forces, topological defects proliferate and the RB rotation gives place to plastic flow.

Abstract: We investigate the self-assembly of vortices in a type-II superconducting disk subjected to highly nonuniform confining potentials produced by inhomogeneous magnetic textures. Using a series of numerical experiments performed within the Ginzburg–Landau theory, we show that vortices can arrange spontaneously in highly nonuniform, defect-free crystals, reminiscent of conformal lattices, even though the strict conditions for the conformal crystal are not fulfilled. These results contradict continuum-limit theory, which predicts that the order of a nonuniform crystal is unavoidably frustrated by the presence of topological defects. By testing different cooling routes of the superconductor, we observed several different self-assembled configurations, each of which corresponding to one in a set of allowed conformal transformations, which depends on the magnetic and thermal histories of the system.

Abstract: We model transport through two-dimensional topological insulator (TI) nanoribbons. To model the quantum transport, we employ the non-equilibrium Green's function approach. With the presented approach, we study the effect of lattice imperfections on the carrier transport. We observe that the topologically protected edge states of TIs are robust against a high percentage (2%) of vacancy defects. We also investigate tunneling of the edge states in two decoupled TI nanoribbons.

Abstract: We present a computational imaging mode for large scale electron microscopy data, which retrieves a complex wave from noisy/sparse intensity recordings using a deep learning approach and subsequently reconstructs an image of the specimen from the Convolutional Neural Network (CNN) predicted exit waves. We demonstrate that an appropriate forward model in combination with open data frameworks can be used to generate large synthetic datasets for training. In combination with augmenting the data with Poisson noise corresponding to varying dose-values, we effectively eliminate overfitting issues. The U-NET[1] based architecture of the CNN is adapted to the task at hand and performs well while maintaining a relatively small size and fast performance. The validity of the approach is confirmed by comparing the reconstruction to well-established methods using simulated, as well as real electron microscopy data. The proposed method is shown to be effective particularly in the low dose range, evident by strong suppression of noise, good spatial resolution, and sensitivity to different atom types, enabling the simultaneous visualisation of light and heavy elements and making different atomic species distinguishable. Since the method acts on a very local scale and is comparatively fast it bears the potential to be used for near-real-time reconstruction during data acquisition.

Abstract: We present a computational model to model the magnetic structure of two-dimensional (2D) dilute-magnetic-semiconductors (DMS) both the monolayers and multilayers using first-principles density functional theory (DFT), as well as their magnetic phase transition as a function of temperature using Monte-Carlo simulations. Using our method, we model the magnetic structure of bulk, bilayer, and monolayer MoS2 substitutionally doped with Fe atoms. We find that the out-of-plane interaction in bilayer MoS2 is weakly ferromagnetic, whereas in bulk MoS2 it is strongly anti-ferromagnetic. Finally, we show that the magnetic order is more robust in bilayer Fe-doped MoS2 compared to the monolayer and results in a room-temperature FM at an atomic substitution of 14-16%.

Abstract: We present a large dataset containing simulated core-loss electron energy loss spectroscopy (EELS) spectra with the elemental content as ground-truth labels. Additionally we present some neural networks trained on this data for element identification.  The simulated dataset contains zero padded core-loss spectra from 0 to 3072 eV, which represents 107 core-loss edges through all 80 elements from Be up to Bi. The core-loss edges are calculated from the generalised oscillator strength (GOS) database presented by Zhang et al.[1] Generic fine structures using lifetime broadened peaks are used to imitate fine structure due to solid-state effects in experimental spectra. Generic low-loss regions are used to imitate the effect of multiple scattering. Each spectrum contains at least one edge of a given query element and possibly additional edges depending on samples drawn from The Materials Project [2]. The dataset contains for each of the 80 elements: 7000 training spectra, 1500 test spectra, 600 validation spectra and 100 spectra representing only the query element. This results in a total 736 000 labeled spectra. Code on how to  – read the simulated data – transform HDF5 format to TFRecord format – train and evaluate neural networks using the simulated data – use the trained networks for automated element identification is available on GitHub at arnoannys/EELS_ID A full report on the simulation of the dataset and the training and evaluation of the neural networks can be found at:                    Annys, A., Jannis, D. & Verbeeck, J. Deep learning for automated materials characterisation in core-loss electron energy loss spectroscopy. Sci Rep 13, 13724 (2023). https://doi.org/10.1038/s41598-023-40943-7 [1] Zezhong Zhang, Ivan Lobato, Daen Jannis, Johan Verbeeck, Sandra Van Aert, & Peter Nellist. (2023). Generalised oscillator strength for core-shell electron excitation by fast electrons based on Dirac solutions (1.0) [Data set]. Zenodo. https://doi.org/10.5281/zenodo.7729585 [2] Anubhav Jain, Shyue Ping Ong, Geoffroy Hautier, Wei Chen, William Davidson Richards, Stephen Dacek, Shreyas Cholia, Dan Gunter, David Skinner, Gerbrand Ceder, Kristin A. Persson; Commentary: The Materials Project: A materials genome approach to accelerating materials innovation. APL Mater 1 July 2013; 1 (1): 011002. [https://doi.org/10.1063/1.4812323](https://doi.org/10.1063/1.4812323)

Abstract: We present here a new interatomic potential parameter set to predict the thermal conductivity of zirconium trisulfide monolayers. The generated Tersoff-type force field is parameterized using data collected with first-principles calculations. We use non-equilibrium molecular dynamics simulations to predict the thermal conductivity. The generated parameters result in very good agreement in structural, mechanical, and dynamical parameters. The room temperature lattice thermal conductivity ( kappa) of the considered crystal is predicted to be kappa x x = 25.69Wm – 1K – 1 and kappa y y = 42.38Wm – 1K – 1, which both agree well with their corresponding first-principles values with a discrepancy of less than 5%. Moreover, the calculated kappa variation with temperature (200 and 400 K) are comparable within the framework of the accuracy of both first-principles and molecular dynamics simulations.