Abstract: Cold atmospheric plasma (CAP) has great potential for sterilization in the food industry, by deactivation of thermophilic bacteria, but the underlying mechanisms are largely unknown. Therefore, we investigate here whether CAP is able to denature/modify protein from thermophilic bacteria. We focus on MTH1880 (MTH) from Methanobacterium thermoautotrophicum as model protein, which we treated with dielectric barrier discharge (DBD) plasma operating in air for 10, 15 and 20 mins. We analysed the structural changes of MTH using circular dichroism, fluorescence and NMR spectroscopy, as well as the thermal and chemical denaturation, upon CAP treatment. Additionally, we performed molecular dynamics (MD) simulations to determine the stability, flexibility and solvent accessible surface area (SASA) of both the native and oxidised protein.

Abstract: NADPH oxidases 1 (NOX1) derived reactive oxygen species (ROS) play an important role in the progression of cancer through signaling pathways. Therefore, in this paper, we demonstrate the effect of cold atmospheric plasma (CAP) on the structural changes of Noxa1 SH3 protein, one of the regulatory subunits of NOX1. For this purpose, firstly we purified the Noxa1 SH3 protein and analyzed the structure using X-ray crystallography, and subsequently, we treated the protein with two types of CAP reactors such as pulsed dielectric barrier discharge (DBD) and Soft Jet for different time intervals. The structural deformation of Noxa1 SH3 protein was analyzed by various experimental methods (circular dichroism, fluorescence, and NMR spectroscopy) and by MD simulations. Additionally, we demonstrate the effect of CAP (DBD and Soft Jet) on the viability and expression of NOX1 in A375 cancer cells. Our results are useful to understand the structural modification/oxidation occur in protein due to reactive oxygen and nitrogen (RONS) species generated by CAP.

Abstract: Purified water supply for human use, agriculture and industry is the major global priority nowadays. The advanced oxidation process based on atmospheric pressure non-thermal plasma (NTP) has been used for purification of wastewater, although the underlying mechanisms of degradation of organic pollutants are still unknown. In this study we employ two needle-type atmospheric pressure non-thermal plasma jets, i.e., indirect (ID-APPJ) and direct (D-APPJ) jets operating at Ar feed gas, for the treatment of methylene blue, methyl orange and congo red dyes, for two different times (i.e., 20 min and 30 min). Specifically, we study the decolorization/degradation of all three dyes using the above mentioned plasma sources, by means of UV-Vis spectroscopy, HPLC and a density meter. We also employ mass spectroscopy to verify whether only decolorization or also degradation takes place after treatment of the dyes by the NTP jets. Additionally, we analyze the interaction of OH radicals with all three dyes using reactive molecular dynamics simulations, based on the density functional-tight binding method. This investigation represents the first report on the degradation of these three different dyes by two types of NTP setups, analyzed by various methods, and based on both experimental and computational studies.

Abstract: Hydrogen–graphite interactions are relevant to a wide variety of applications, ranging from astrophysics to fusion devices and nano-electronics. In order to shed light on these interactions, atomistic simulation using Molecular Dynamics (MD) has been shown to be an invaluable tool. It suffers, however, from severe timescale
limitations. In this work we apply the recently developed Collective Variable-Driven Hyperdynamics (CVHD) method to hydrogen etching of graphite for varying inter-impact times up to a realistic value of 1 ms, which corresponds to a flux of
1020 m2 s1. The results show that the erosion yield, hydrogen surface coverage and species distribution are significantly affected by the time between impacts. This can be explained by the higher probability of C–C bond breaking due to the prolonged exposure to thermal stress and the subsequent transition from ion- to thermal-induced etching. This latter regime of thermal-induced etching – chemical erosion – is here accessed for the first time using atomistic simulations. In conclusion, this study demonstrates that accounting for long time-scales significantly affects ion bombardment simulations and should not be neglected in a wide range of conditions, in contrast to what is typically assumed.

Abstract: A study of ns-laser ablation is presented, which focuses on the transient behavior of the physical processes that act in and above a copper sample. A dimensionless multiphase collisional radiative model describes the interplay between the ablation, collisional, and radiative mechanisms. Calculations are done for a 6 ns-Nd:YAG laser pulse operating at 532 nm and fluences up to 15 J/cm2. Temporal intensity profiles as well as transmissivities are in good agreement with experimental results. It is found that volumetric ablation mechanisms and photo-processes both play an essential role in the onset of ns-laser induced breakdown.

Abstract: This paper presents the computational study of the metal-organic (MO) CVD of titanium dioxide (TiO2) films grown using titanium tetraisopropoxide (TTIP) as a precursor and nitrogen as a carrier gas. The TiO2 films are deposited under atmospheric pressure. The effects of the precursor concentration, the substrate temperature, and the hydrolysis reaction on the deposition process are investigated. It is found that hydrolysis of the TTIP decreases the onset temperature of the gas-phase thermal decomposition, and that the deposition rate increases with the precursor concentration and with the decrease of substrate temperature. Concerning the mechanism responsible for the film growth, the model shows that at the lowest precursor concentration, the direct adsorption of the precursor is dominant, while at higher precursor concentrations, the monomer deposition becomes more important.

Abstract: We introduce a simple enhanced sampling approach for the calculation of free energy differences and barriers along a one-dimensional reaction coordinate. First, a small number of short nonequilibrium simulations are carried out along the reaction coordinate, and the Jarzynski equality is used to learn an approximate free energy surface from the nonequilibrium work distribution. This free energy estimate is represented in a compact form as an artificial neural network and used as an external bias potential to accelerate rare events in a subsequent molecular dynamics simulation. The final free energy estimate is then obtained by reweighting the equilibrium probability distribution of the reaction coordinate sampled under the influence of the external bias. We apply our reweighted Jarzynski sampling recipe to four processes of varying scales and complexities.spanning chemical reaction in the gas phase, pair association in solution, and droplet nucleation in supersaturated vapor. In all cases, we find reweighted Jarzynski sampling to be a very efficient strategy, resulting in rapid convergence of the free energy to high precision.

Abstract: The conformational and configurational preferences of Me2PNSNPMe2 (3) and Me2PNSNAsMe2 (4) have been identified using quantum chemical calculations at the DFT/B3LYP/6-311+G* level of theory. An approach in which energetic, structural (geometries and bond orders), electronic (analysis of the electron density) and spectroscopic properties are combined leads to the conclusion that these sulfur-nitrogen-pnictogen chains share many of the properties of their chalcogen-nitrogen analogues but that the through-space intramolecular interactions favouring the Z,Z configuration are even weaker than in these latter compounds. The results of this analysis also lead to an unambiguous assignment of the variable-temperature 31P and 15N NMR spectra of these compounds and their structures both in solution and in the solid state.

Abstract: Understanding the nature and effect of the multitude of plasma–surface interactions in plasma catalysis is a crucial requirement for further process development and improvement. A particularly intriguing and rather unique property of a plasma-catalytic setup is the ability of the plasma to modify the electronic structure, and hence chemical properties, of the catalyst through charging, i.e. the absorption of excess electrons. In this work, we develop a quantum chemical model based on density functional theory to study excess negative surface charges in a heterogeneous catalyst exposed to a plasma. This method is specifically applied to investigate plasma-catalytic CO2 activation on supported M/Al2O3 (M=Ti, Ni, Cu) single atom catalysts. We find that (1) the presence of a negative surface charge dramatically improves the reductive power of the catalyst, strongly promoting the splitting of CO2 to CO and oxygen, and (2) the relative activity of the investigated transition metals is also changed upon charging, suggesting that controlled surface charging is a powerful additional parameter to tune catalyst activity and selectivity. These results strongly point to plasma-induced surface charging of the catalyst as an important factor contributing to the plasma-catalyst synergistic effects frequently reported for plasma catalysis.

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.