Abstract: We calculate the contact resistance for an edge- and top-contacted 2D semiconductor. The contact region consists of a metal contacting a monolayer of MoS2 which is otherwise surrounded by SiO2. We use the quantum transmitting boundary method to compute the contact resistance as a function of the 2D semiconductor doping concentration. An effective mass Hamiltonian is used to describe the properties of the various materials. The electrostatic potentials are obtained by solving the Poisson equation numerically. We incorporate the effects of the image-force barrier lowering on the Schottky barrier and examine the impact on the contact resistance. At low doping concentrations, the contact resistance of the top contact is lower compared to edge contact, while at high doping concentrations, the edge contact exhibits lower resistance.

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: In environmental assessments, the characterization of urban soils relies heavily on invasive investigation, which is often insufficient to capture their full spatial heterogeneity. Non-invasive geophysical techniques enable rapid collection of high-resolution data and provide a cost-effective alternative to investigate soil in a spatially comprehensive way. This paper presents the results of combining multi-receiver electromagnetic induction and stepped-frequency ground penetrating radar to characterize a former garage site contaminated with petroleum hydrocarbons. The sensor combination showed the ability to identify and accurately locate building remains and a high-density soil layer, thus demonstrating the high potential to investigate anthropogenic disturbances of physical nature. In addition, a correspondence was found between an area of lower electrical conductivity and elevated concentrations of petroleum hydrocarbons, suggesting the potential to detect specific chemical disturbances. We conclude that the sensor combination provides valuable information for preliminary assessment of urban soils.

Abstract: The effects on river water quality of sewer overflows are not well known. Since the duration of the overflow is in the order of magnitude of minutes to hours, continuous measurements of water quality are needed and traditional grab sampling is unable to quantify the pollution loads. The objective of this paper was to demonstrate the applicability of high frequency measurements for assessing the impacts of waste water treatment plants on the water quality of the receiving surface water. In our in situ water quality monitoring setup, two types of multiparameter sensors mounted on a floating fixed platform were used to determine the dynamics of dissolved oxygen, specific conductivity, ammonium-N, nitrate-N and dissolved organic carbon downstream of a waste water treatment plant (WWTP), in combination with data on rainfall, river discharge and WWTP overflow discharge. The monitoring data for water quantity and water quality were used to estimate the pollution load from waste water overflow events and to assess the impact of waste water overflows on the river water quality. The effect of sewer overflow on a small river in terms of N load was shown to be significant. The WWTP overflow events accounted for about 1/3 of the river discharge. The NH4-N loads during overflow events contributed 29% and 21% to the August 2010 and June 2011 load, respectively, in only 8% and 3% of the monthly time span. The results indicate that continuous monitoring is needed to accurately represent the effects of sewer overflows in river systems.

Abstract: Bilayers of carbon, consisting of a layer of natural carbon and a second layer highly enriched in 13C, were investigated with the LAMMA 500-® instrument. When such a bilayer is perforated by the laser beam, comparable amounts of 12C and 13C are evaporated and partly ionized so that geometry effects and recombination reactions during laser-induced ionization can straightforwardly be studied.

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: The catalytic oxidative dehydrogenation of hydrocarbons is an industrially important process, in which selectivity is a key issue. We here investigate the conversion of methanol to formaldehyde on a vanadia surface employing long timescale simulations, reaching a time scale of seconds. In particular, we compare the thermal process to the case where an additional external electric field is applied, as would be the case in a direct plasma-catalysis setup. We find that the electric field influences the retention time of the molecules at the catalyst surface. These simulations provide an atomic scale insight in the thermal catalytic oxidative dehydrogenation process, and in how an external electric field may affect this process.

Abstract: In this review paper, we present several examples of reactive molecular dynamics simulations, which contribute to a better understanding of the underlying mechanisms in plasma medicine on the atomic scale. This includes the interaction of important reactive oxygen plasma species with the outer cell wall of both gram-positive and gram-negative bacteria, and with lipids present in human skin. Moreover, as most biomolecules are surrounded by a liquid biofilm, the behavior of these plasma species in a liquid (water) layer is presented as well. Finally, a perspective for future atomic scale modeling studies is given, in the field of plasma medicine in general, and for cancer treatment in particular.

Abstract: PECVD of a nanoscale SiO2 capping layer using low pressure SiCl4/O-2/Ar plasmas is numerically investigated. The purpose of this capping layer is to restore photoresist profiles with improved line edge roughness. A 2D plasma and Monte Carlo feature profile model are applied for this purpose. The deposited films are calculated for various operating conditions to obtain a layer with desired shape. An increase in pressure results in more isotropic deposition with a higher deposition rate, while a higher power creates a more anisotropic process. Dilution of the gas mixture with Ar does not result in an identical capping layer shape with a thickness linearly correlated to the dilution. Finally, a substrate bias seems to allow proper control of the vertical deposition rate versus sidewall deposition as desired.

Abstract: A numerical model for NxOy remediation in humid air plasma produced with a dielectric barrier discharge at atmospheric pressure is presented. Special emphasis is given to NO2 and N2O reduction with the decrease of O2 content in the feedstock gas. A detailed reaction mechanism including electronic and ionic processes, as well as the contribution of radicals and excited atomic/molecular species is proposed. The temporal evolution of the densities of NO, NO2 and N2O species, and some other by-products, is analyzed, and the major pathways for the NxOy remediation are discussed for one pulse. Subsequently, simulations are presented for a multi-pulses case, where three O2 contents are tested for optimization of the remediation process. It is found that when the gas mixture O2/N2/H2O/NOx has no initial O2 content, the best NOx and N2O remediation is achieved.

Abstract: Modeling results are presented to gain a better insight in the properties of a SiH4/O2/Ar inductively coupled plasma (ICP) and how it interacts with a silicon substrate (wafer), as applied in the microelectronics industry for the fabrication of electronic devices. The SiH4/O2/Ar ICP is used for the filling of microtrenches with isolating material (SiO2), as applied in shallow trench isolation (STI). In this article, a detailed reaction set that describes the plasma chemistry of SiH4/O2/Ar discharges as well as surface processes, such as sputtering, oxidation, and deposition, is presented. Results are presented on the plasma properties during the plasma enhanced chemical vapor deposition process (PECVD) for different gas ratios, as well as on the shape of the filled trenches and the surface compositions of the deposited layers. For the operating conditions under study it is found that the most important species accounting for deposition are SiH2, SiH3O, SiH3 and SiH2O, while SiH+2, SiH+3, O+2 and Ar+ are the dominant species for sputtering of the surface. By diluting the precursor gas (SiH4) in the mixture, the deposition rate versus sputtering rate can be controlled for a desired trench filling process. From the calculation results it is clear that a high deposition rate will result in undesired void formation during the trench filling, while a small deposition rate will result in undesired trench bottom and mask damage by sputtering. By varying the SiH4/O2 ratio, the chemical composition of the deposited layer will be influenced. However, even at the highest SiH4/O2 ratio investigated (i.e., 3.2:1; low oxygen content), the bulk deposited layer consists mainly of SiO2, suggesting that low-volatile silane species deposit first and subsequently become oxidized instead of being oxidized first in the plasma before deposition. Finally, it was found that the top surface of the deposited layer contained less oxygen due to preferential sputtering of O atoms, making the top layer more Si-rich. However, this effect is negligible at a SiH4/O2 ratio of 2:1 or lower.

Abstract: In this article, surface processes occurring during the etching of Si with a Cl2/O2/Ar plasma are investigated by means of experiments and modeling. Cl2-based plasmas are commonly used to etch silicon, while a small fraction of O2 is added to protect the sidewalls from lateral etching during the shallow trench isolation process. When the oxygen fraction exceeds a critical value, the wafer surface process changes from an etching regime to a deposition regime, drastically reducing the etch rate. This effect is commonly referred to as the etch stop phenomenon. To gain better understanding of this mechanism, the oxygen fraction is varied in the gas mixture and special attention is paid to the effects of oxygen and of the redeposition of non-volatile etched species on the overall etch/deposition process. It is found that, when the O2 flow is increased, the etch process changes from successful etching to the formation of a rough surface, and eventually to the actual growth of an oxide layer which completely blocks the etching of the underlying Si. The size of this etch stop island was found to increase as a function of oxygen flow, while its thickness was dependent on the amount of Si etched. This suggests that the growth of the oxide layer mainly depends on the redeposition of non-volatile etch products. The abrupt change in the etch rate as a function of oxygen fraction was not found back in the oxygen content of the plasma, suggesting the competitive nature between oxidation and chlorination at the wafer. Finally, the wafer and reactor wall compositions were investigated by modeling and it was found that the surface rapidly consisted mainly of SiO2 when the O2 flow was increased above about 15 sccm.