Abstract: Broad area as well as buried heterostructure lasers based on In0.72Ga0.28As0.62P0.38/InP and emitting at 1.3 mum are grown by liquid phase epitaxy and are studied in detail by means of transmission electron microscopy, X-ray diffraction, secondary ion mass-spectrometry, and electroluminescence. The InGaAsP epilayer is found to be well lattice-matched and of good structural quality. A tentative explanation is presented for the spinodal decomposition observed in the InGaAsP alloy. We also report on the high performance characteristics of the infrared lasers.

Abstract: The amorphous oxide semiconductor Indium-Gallium-Zinc-Oxide (a-IGZO) has gained a large technological relevance as a semiconductor for thin-film transistors in active-matrix displays. Yet, major questions remain unanswered regarding the atomic origin of threshold voltage control, doping level, hysteresis, negative bias stress (NBS), and negative bias illumination stress (NBIS). We undertake a systematic study of the effects of oxygen vacancies on the properties of a-IGZO by relating experimental observations to microscopic insights gained from first-principle simulations. It is found that the amorphous nature of the semiconductor allows unusually large atomic relaxations. In some cases, oxygen vacancies are found to behave as perfect shallow donors without the formation of structural defects. Once structural defects are formed, their transition states can vary upon charge and discharge cycles. We associate this phenomenon to a possible presence of hysteresis in the transfer curve of the devices. Under NBS, the creation of oxygen vacancies becomes energetically very stable, hence thermodynamically very likely. This generation process is correlated with the occurrence of the negative bias stress instabilities observed in a-IGZO transistors. While oxygen vacancies can therefore be related to NBS and hysteresis, it appears unlikely from our results that they are direct causes of NBIS, contrary to common belief.

Abstract: In this article, we report on the synthesis of thin, epitaxial films of the transparent conductive oxide Al:ZnO on (0001)-oriented synthetic sapphire substrates by DC sputtering from targets with a nominal 1 at.% Al substitution. The deposition was carried out at an unusually low substrate temperature of only 250 °C in argonoxygen mixtures as well as in pure argon. The impact of the processgas composition on the morphology was analysed by transmission electron microscopy, revealing epitaxial growth in all the cases with a minor impact of the process parameters on the resulting grain sizes. The transport properties resistivity, Hall effect and magnetoresistance were studied in the range from 10 to 300 K in DC and pulsed magnetic fields up to 45 T. While the carrier density and mobility are widely temperature independent, we identified a low fieldlow temperature regime in which the magnetoresistance shows an anomalous, negative behaviour. At higher fields and temperatures, the magnetoresistance exhibits a more conventional, positive curvature with increasing field strength. As a possible explanation, we propose carrier scattering at localised magnetic trace impurities and magnetic correlations.

Abstract: The depth strain profile in silicon from the Si (001) substrate to the surface of a 2 nm thick Si/12 nm thick SiGe/bulk Si heterostructure has been determined by medium energy ion scattering (MEIS). It shows with sub-nanometer resolution and high strain sensitivity that the thin Si cap presents residual compressive strain caused by Ge diffusion coming from the fully strained SiGe layer underneath. The strain state of the SiGe buffer have been checked by X-ray diffraction (XRD) and nano-beam electron diffraction (NBED) measurements.

Abstract: Sample holders for transmission electron microscopy (TEM) based on micro-electro-mechanical systems (MEMS) have recently become popular for investigating the behavior of nanomaterials under in situ or environmental conditions. The accuracy and reproducibility of these in situ holders are essential to ensure the reliability of experimental results. In addition, the uniformity of an applied temperature trigger across the MEMS chip is a crucial parameter. In this work, it is measured the temperature homogeneity of MEMS-based heating sample supports by locally analyzing the dynamics of heat-induced alloying of Au@Ag nanoparticles located in different regions of the support through quantitative fast high-angle annular dark-field scanning TEM tomography. These results demonstrate the superior temperature homogeneity of a microheater design based on a heating element shaped as a circular spiral with a width decreasing outwards compared to a double spiral-shaped designed microheater. The proposed approach to measure the local temperature homogeneity based on the thermal properties of bimetallic nanoparticles will support the future development of MEMS-based heating supports with improved thermal properties and in situ studies where high precision in the temperature at a certain position is required. This schematic delineates an approach to quantifying potential localized temperature deviation within a nanochip. Employing two comparable nanoparticles as thermal probes in discrete nanochip regions, the alloying kinetics of these nanoparticles are monitorable using in situ quantitative high-angle annular dark-field scanning transmission electron microscopy (HAADF-STEM) tomography, thus enabling the precise estimation of local temperature deviations.image

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.