Gas adsorption and dynamics in Pillared Graphene Frameworks

We thank prof. Marco Frasconi for advice on the kind of moieties to be used as pillars. N.M.P. is supported by the European Research Council PoC 2015 “Silkene” No. 693670, by the European Commission H2020 under the Graphene Flagship Core 1 No. 696656 (WP14 “Polymer Nanocomposites”) and under the Fet Proactive “Neurofibres” No. 732344. S.T and G.G. acknowledge funding from previous WP14 “Polymer Nanocomposites” grant. Access to computing and storage facilities owned by parties and projects contributing to the Czech National Grid Infrastructure MetaCentrum provided under the programme “Projects of Large Research, Development, and Innovations Infrastructures” (CESNET LM2015042), is greatly appreciated (https://www.metacentrum.cz/en/)

Functionalization of Indium Oxide for Empowered Detection of CO2 over an Extra-Wide Range of Concentrations

Carbon capture, storage, and utilization have becomefamiliar termswhen discussing climate change mitigation actions. Such endeavorsdemand the availability of smart and inexpensive devices for CO2 monitoring. To date, CO2 detection relies on opticalproperties and there is a lack of devices based on solid-state gassensors, which can be miniaturized and easily made compatible withInternet of Things platforms. With this purpose, we present an innovativesemiconductor as a functional material for CO2 detection.A nanostructured In2O3 film, functionalizedby Na, proves to enhance the surface reactivity of pristine oxideand promote the chemisorption of even rather an inert molecule asCO(2). An advanced operando equipment basedon surface-sensitive diffuse infrared Fourier transform is used toinvestigate its improved surface reactivity. The role of sodium isto increase the concentration of active sites such as oxygen vacanciesand, in turn, to strengthen CO2 adsorption and reactionat the surface. It results in a change in film conductivity, i.e.,in transduction of a concentration of CO2. The films exhibitexcellent sensitivity and selectivity to CO2 over an extra-widerange of concentrations (250-5000 ppm), which covers most indoorand outdoor applications due to the marginal influence by environmentalhumidity

Electronic excitation spectra of cerium oxides: from ab initio dielectric response functions to Monte Carlo electron transport simulations

Nanomaterials made of the cerium oxides CeO$_2$ and Ce$_2$O$_3$ have a broad range of applications, from catalysts in automotive, industrial or energy operations to promising materials to enhance hadrontherapy effectiveness in oncological treatments. To elucidate the physico-chemical mechanisms involved in these processes, it is of paramount importance to know the electronic excitation spectra of these oxides, which are obtained here through high-accuracy linear-response time-dependent density functional theory calculations. In particular, the macroscopic dielectric response functions $\bar\epsilon$ of both bulk CeO$_2$ and Ce$_2$O$_3$ are derived, which compare remarkably well with the available experimental data. These results stress the importance of appropriately accounting for local field effects to model the dielectric function of metal oxides. Furthermore, we reckon the materials energy loss functions \mbox{Im} (-1/\bar{\epsilon}), including the accurate evaluation of the momentum transfer dispersion from first-principles. In this respect, by using a Mermin-type parametrization we are able to model the contribution of different electronic excitations to the dielectric loss function. Finally, from the knowledge of the electron inelastic mean free path, together with the elastic mean free path provided by the relativistic Mott theory, we carry out statistical Monte Carlo (MC) charge transport simulations to reproduce the major features of the reported experimental reflection electron energy loss (REEL) spectra of cerium oxides. The good agreement with REEL experimental data strongly supports our approach based on MC modelling informed by ab initio calculated electronic excitation spectra in a broad range of momentum and energy transfers.Comment: 21 pages, 19 figure

A novel combined experimental and multiscale theoretical approach to unravel the structure of SiC/SiOx core/shell nanowires for their optimal design

In this work we propose a realistic model of nanometer-thick SiC/SiOxcore/shell nanowires (NWs) using a combined first-principles and experimental approach. SiC/SiOxcore/shell NWs were first synthesised by a low-cost carbothermal method and their chemical-physical experimental analysis was accomplished by recording X-ray absorption near-edge spectra. In particular, the K-edge absorption lineshapes of C, O, and Si are used to validate our computational model of the SiC/SiOxcore/shell NW architectures, obtained by a multiscale approach, including molecular dynamics, tight-binding and density functional simulations. Moreover, we present ab initio calculations of the electronic structure of hydrogenated SiC and SiC/SiOxcore/shell NWs, studying the modification induced by several different substitutional defects and impurities into both the surface and the interfacial region between the SiC core and the SiOxshell. We find that on the one hand the electron quantum confinement results in a broadening of the band gap, while hydroxyl surface terminations decrease it. This computational investigation shows that our model of SiC/SiOxcore/shell NWs is capable to deliver an accurate interpretation of the recorded X-ray absorption near-edge spectra and proves to be a valuable tool towards the optimal design and application of these nanosystems in actual devices

Nanomechanics of individual aerographite tetrapods

R.A., O.L. and K.S. would like to thank the German Research Foundation (DFG) for the financial support under schemes AD 183/17-1 and SFB 986-TP-B1, respectively, and the Graphene FET Flagship. R.M. and D.E. would like to thank for financial support from Latvian Council of Science, no. 549/2012. N.M.P. is supported by the European Research Council (ERC PoC 2015 SILKENE no. 693670) and by the European Commission H2020 under the Graphene Flagship (WP14 ‘Polymer Composites’, no. 696656) and under the FET Proactive (‘Neurofibres’ no. 732344). S.S. acknowledges support from SILKENE

Mathematical programming formulation for approximate simulation of closed-loop systems

Closed-loops systems have been analyzed by means of Markov theory, discrete event simulation models, renewal theory and random walks. The dynamics of discrete event systems (DES) has been recently addressed with the mathematical programming technique. In particular, DESs are mapped into a mixed integer linear programming (MILP) formulation, the optimal solution of which represents the trajectory of the DES itself, i.e., the output of a standard simulation. This paper proposes approximate linear programming–based models to simulate and optimize the closed–loop system behavior. The approximation has been obtained by relaxing the constraints that keep the number of parts circulating in the system constant. In the relaxed model, the fixed population aspect, which characterizes the system, is indirectly modeled by means of continuous time variables that limit the entering (leaving) of parts into (from) the system. The main advantage of the proposed approximate simulation model is that it preserves its linearity even when used for optimization. Numerical experiments show the accuracy of the proposed models for the optimal pallet allocation problem

Design and control of manufacturing systems: a discrete event optimisation methodology

Simulation optimisation has gained a great attention due to its success in the design of complex manufacturing systems. In this paper, we look at manufacturing as a special class of queueing systems and propose the Discrete Event Optimisation (DEO) methodology, which provides a formal way to develop integrated mathematical models for the simultaneous simulation and optimisation. In the case, the obtained model is a mixed integer linear programming model; the methodology provides a formal way to generate approximations of them. The analytical properties of DEO models are analysed for the first time in the framework of sample path optimisation and mathematical programming. The methodology represents a reference for the use of mathematical programming as a way to model simulation optimisation for queueing systems. The applicability of the DEO methodology to complex problems is showed using the task and buffer allocation problem in a production line

A simulation based cut generation approach to improve deo efficiency: The buffer allocation case

The stochastic Buffer Allocation Problem (BAP) is well known in several fields and it has been characterized as NP-Hard. It deals with the optimal allocation of buffer spaces among stages of a system. Simulation Optimization is a possible way to approximately solve the problem. In particular, we refer to the Discrete Event Optimization (DEO). According to this approach, BAP simulation optimization can be modeled as a Mixed Integer Programming model. Despite the advantages deriving from having a single model for both simulation and optimization, its solution can be extremely demanding. In this work, we propose a Benders decomposition approach to efficiently solve large DEO of BAP, in which cuts are generated by simulation. Numerical experiment shows that the computation time can be significantly reduced by using this approach. Pedrielli, Matta, and Alfieri (2015) proposed a general DEO framework to model and optimize queueing systems. The approach relies on the Event Relationship Graph Lite (ERG Lite) formalism to formulate integrated simulation optimization mathematical programming models. ERG Lite is an extension of the Event Relationship Graphs. The authors showed that the BAP can be solved by DEO (Matta 2008) models that contain both simulation and optimization aspects. The simulation components control the event times, by means of constraints dealing with the system dynamics. The optimization components, instead, correspond to the binary variables and related constraints used for the capacity selection and minimization of total buffer space. © 2016 IEEE