Abstract: Resistive Random Access Memories are among the most promising candidates for the next generation of non-volatile memory. Transition metal oxides such as HfOx and TaOx attracted a lot of attention due to their CMOS compatibility. Furthermore, these materials do not require the inclusion of extrinsic conducting defects since their operation is based on intrinsic ones (oxygen vacancies). Using Density Functional Theory, we evaluated the thermodynamics of the defects formation and the kinetics of diffusion of the conducting species active in transition metal oxide RRAM materials. The gained insights based on the thermodynamics in the Top Electrode, Insulating Matrix and Bottom Electrode and at the interfaces are used to design a proper defect reservoir, which is needed for a low-energy reliable switching device. The defect reservoir has also a direct impact on the retention of the Low Resistance State due to the resulting thermodynamic driving forces. The kinetics of the diffusing conducting defects in the Insulating Matrix determine the switching dynamics and resistance retention. The interface at the Bottom Electrode has a significant impact on the low-current operation and long endurance of the memory cell. Our first-principles findings are confirmed by experimental measurements on fabricated RRAM devices. Published by AIP Publishing.

Abstract: The effects of hole injection in amorphous indium-gallium-zinc-oxide (a-IGZO) are analyzed by means of first-principles calculations. The injection of holes in the valence band tail states leads to their capture as a polaron, with high self-trapping energies (from 0.44 to 1.15 eV). Once formed, they mediate the formation of peroxides and remain localized close to the hole injection source due to the presence of a large diffusion energy barrier (of at least 0.6 eV). Their diffusion mechanism can be mediated by the presence of hydrogen. The capture of these holes is correlated with the low off-current observed for a-IGZO transistors, as well as with the difficulty to obtain a p-type conductivity. The results further support the formation of peroxides as being the root cause of Negative Bias Illumination Stress (NBIS). The strong self-trapping substantially reduces the injection of holes from the contact and limits the creation of peroxides from a direct hole injection. In the presence of light, the concentration of holes substantially rises and mediates the creation of peroxides, responsible for NBIS. Published by AIP Publishing.

Abstract: The E centers (dopant-vacancy pairs) play a significant role in dopant deactivation in semiconductors. In order to gain insight into dopant-defect interactions during epitaxial growth of in situ phosphorus doped Ge, positron annihilation spectroscopy, which is sensitive to open-volume defects, was performed on Ge layers grown by chemical vapor deposition with different concentrations of phosphorus (similar to 1 x 10(18)-1 x 10(20) cm(-3)). Experimental results supported by first-principles calculations based on the two component density-functional theory gave evidence for the existence of mono-vacancies decorated by several phosphorus atoms as the dominant defect type in the epitaxial Ge. The concentration of vacancies increases with the amount of P-doping. The number of P atoms around the vacancy also increases, depending on the P concentration. The evolution of P-n-V clusters in Ge contributes significantly to the dopant deactivation. Published under license by AIP Publishing.

Abstract: Positron annihilation spectroscopy in the Doppler and coincidence Doppler mode was applied on Ge1 xSnx epitaxial layers, grown by chemical vapor deposition with different total As concentrations (1019-1021 cm3), high active As concentrations (1019 cm3), and similar Sn concentrations (5.9%-6.4%). Positron traps are identified as mono-vacancy complexes. Vacancy-As complexes, V-Asi, formed during the growth were studied to deepen the understanding of the electrical passivation of the Ge1 xSnx:As epilayers. Larger monovacancy complexes, V-Asi (i 2), are formed as the As doping increases. The total As concentration shows a significant impact on the saturation of the number of As atoms (i 1/4 4) around the vacancies in the sample epilayers. The presence of V-Asi complexes decreases the dopant activation in the Ge1 xSnx:As epilayers. Furthermore, the presence of Sn failed to hinder the formation of larger V-Asi complexes and thus failed to reduce the donor-deactivation.

Abstract: Based on the current knowledge, a plasma–liquid interface looks and behaves very differently from its counterpart at a solid surface. Local processes characteristic to most liquids include a stronger evaporation, surface deformations, droplet ejection, possibly distinct mechanisms behind secondary electron emission, the formation of an electric double layer, and an ion drift-mediated liquid resistivity. All of them can strongly influence the interfacial charge distribution. Accordingly, the plasma sheath at a liquid surface is most likely unique in its own way, both with respect to its structure and behavior. However, insights into these properties are still rather scarce or uncertain, and more studies are required to further disclose them. In this Perspective, we argue why more research on the plasma sheath is not only recommended but also crucial to an accurate understanding of the plasma–liquid interaction. First, we analyze how the sheath regulates various elementary processes at the plasma–liquid interface, in terms of the electrical coupling, the bidirectional mass transport, and the chemistry between plasma and liquid phase. Next, these three regulatory functions of the sheath are illustrated for concrete applications. Regarding the electrical coupling, a great deal of attention is paid to the penetration of fields into biological systems due to their relevance for plasma medicine, plasma agriculture, and food processing. Furthermore, we illuminate the role of the sheath in nuclear fusion, nanomaterial synthesis, and chemical applications. As such, we hope to motivate the plasma community for more fundamental research on plasma sheaths at liquid surfaces.

Abstract: Binding of the SARS-CoV-2 S-glycoprotein to cell receptors is vital for the entry of the virus into cells and subsequent infection. ACE2 is the main cell receptor for SARS-CoV-2, which can attach to the C-terminal receptor-binding domain (RBD) of the SARS-CoV-2 S-glycoprotein. The GRP78 receptor plays an anchoring role, which attaches to the RBD and increases the chance of other RBDs binding to ACE2. Although high levels of reactive oxygen and nitrogen species (RONS) are produced during viral infections, it is not clear how they affect the RBD structure and its binding to ACE2 and GRP78. In this research, we apply molecular dynamics simulations to study the effect of oxidation of the highly reactive cysteine (Cys) amino acids of the RBD on its binding to ACE2 and GRP78. The interaction energy of both ACE2 and GRP78 with the whole RBD, as well as with the RBD main regions, is compared in both the native and oxidized RBDs. Our results show that the interaction energy between the oxidized RBD and ACE2 is strengthened by 155 kJ/mol, increasing the binding of the RBD to ACE2 after oxidation. In addition, the interaction energy between the RBD and GRP78 is slightly increased by 8 kJ/mol after oxidation, but this difference is not significant. Overall, these findings highlight the role of RONS in the binding of the SARS-CoV-2 S-glycoprotein to host cell receptors and suggest an alternative mechanism by which RONS could modulate the entrance of viral particles into the cells.

Abstract: Atomistic simulation methods for the quantification of free energies are in wide use. These methods operate by sampling the probability density of a system along a small set of suitable collective variables (CVs), which is, in turn, expressed in the form of a free energy surface (FES). This definition of the FES can capture the relative stability of metastable states but not that of the transition state because the barrier height is not invariant to the choice of CVs. Free energy barriers therefore cannot be consistently computed from the FES. Here, we present a simple approach to calculate the gauge correction necessary to eliminate this inconsistency. Using our procedure, the standard FES as well as its gauge-corrected counterpart can be obtained by reweighing the same simulated trajectory at little additional cost. We apply the method to a number of systems—a particle solvated in a Lennard-Jones fluid, a Diels–Alder reaction, and crystallization of liquid sodium—to demonstrate its ability to produce consistent free energy barriers that correctly capture the kinetics of chemical or physical transformations, and discuss the additional demands it puts on the chosen CVs. Because the FES can be converged at relatively short (sub-ns) time scales, a free energy-based description of reaction kinetics is a particularly attractive option to study chemical processes at more expensive quantum mechanical levels of theory.

Abstract: The evaluation of nucleation rates from molecular dynamics trajectories is hampered by the slow nucleation time scale and impact of finite size effects. Here, we show that accurate nucleation rates can be obtained in a very general fashion relying only on the free energy barrier, transition state theory, and a simple dynamical correction for diffusive recrossing. In this setup, the time scale problem is overcome by using enhanced sampling methods, in casu metadynamics, whereas the impact of finite size effects can be naturally circumvented by reconstructing the free energy surface from an appropriate ensemble. Approximations from classical nucleation theory are avoided. We demonstrate the accuracy of the approach by calculating macroscopic rates of droplet nucleation from argon vapor, spanning 16 orders of magnitude and in excellent agreement with literature results, all from simulations of very small (512 atom) systems.

Abstract: The hyperdynamics method is a powerful tool to simulate slow processes at the atomic level. However, the construction of an optimal hyperdynamics potential is a task that is far from trivial. Here, we propose a generally applicable implementation of the hyperdynamics algorithm, borrowing two concepts from metadynamics. First, the use of a collective variable (CV) to represent the accelerated dynamics gives the method a very large flexibility and simplicity. Second, a metadynamics procedure can be used to construct a suitable history-dependent bias potential on-the-fly, effectively turning the algorithm into a self-learning accelerated molecular dynamics method. This collective variable-driven hyperdynamics (CVHD) method has a modular design: both the local system properties on which the bias is based, as well as the characteristics of the biasing method itself, can be chosen to match the needs of the considered system. As a result, system-specific details are abstracted from the biasing algorithm itself, making it extremely versatile and transparent. The method is tested on three model systems: diffusion on the Cu(001) surface and nickel-catalyzed methane decomposition, as examples of reactive processes with a bond-length-based CV, and the folding of a long polymer-like chain, using a set of dihedral angles as a CV. Boost factors up to 109, corresponding to a time scale of seconds, could be obtained while still accurately reproducing correct dynamics.

Abstract: The conversion of CO2 and CH4 into value-added chemicals is studied in a new geometry of a dielectric barrier discharge (DBD) with multi-electrodes, dedicated to the treatment of high gas flow rates. Gas chromatography is used to define the CO2 and CH4 conversion as well as the yields of the products of decomposition (CO, O2 and H2) and of recombination (C2H4, C2H6 and CH2O). The influence of three parameters is investigated on the conversion: the CO2 and CH4 flow rates, the plasma power and the nature of the carrier gas (argon or helium). The energy efficiency of the CO2 conversion is estimated and compared with those of similar atmospheric plasma sources. Our DBD reactor shows a good compromise between a good energy efficiency and the treatment of a large CO2 flow rate.

Abstract: Plasma technology is gaining increasing interest for CO2 conversion, but to maximize the energy efficiency, it is important to track the different energy transfers taking place in the plasma. In this paper, we study these mechanisms by a 0D chemical kinetics model, including the vibrational kinetics, for different conditions of reduced electric field, gas temperature and ionization degree, at a pressure of 100 mbar. Our model predicts a maximum conversion and energy efficiency of 32% and 47%, respectively, at conditions that are particularly beneficial for energy efficient CO2 conversion, i.e. a low reduced electric field (10 Td) and a low gas temperature (300 K). We study the effect of the efficiency by which the vibrational energy is used to dissociate CO2, as well as of the activation energy of the reaction CO2+O→CO+O2, to elucidate the theoretical limitations to the energy
efficiency. Our model reveals that these parameters are mainly responsible for the limitations in the energy efficiency. By varying these parameters, we can reach a maximum conversion and energy efficiency of 86%. Finally, we derive an empirical formula to estimate the maximum possible energy efficiency that can be reached under the assumptions of the model.