Abstract: The structural stability of 2D transition metal dichalcogenide (TMD) formations is of particular importance for their reliable device performance in nano-electronics and opto-electronics. Recent observations show that the CVD-grown TMD monolayers are likely to encounter stability problems such as cracking or fracturing when they are kept under ambient conditions. Here, two different growth configurations are investigated and a favorable growth geometry is proposed, which also sheds light onto the growth mechanism and provides a solution for the stability and fracture formation issues for TMDs specifically for MoS2 monolayers. It is shown that 18 months naturally and thermally aged MoS2 monolayer flakes grown using specifically developed conditions, retain their stability. To understand the mechanism of the structural deterioration, two possible effective mechanisms, S vacancy defects and growth-induced tensile stress, are assessed by the first principle calculations where the role of S vacancy defects in obtaining oxidation resistant MoS2 monolayer flakes is revealed to be rather more critical. Hence, these simulations, time-dependent observations and thermal aging experiments show that durability and stability of 2D MoS2 flakes can be controlled by CVD growth configuration.

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 control of damage to individual environmental particles by a laser beam during Raman spectroscopy carried out in ambient air is generally well understood. The nature and control of damage under vacuum conditions (e.g. in the scanning electron microscopy with energy X-ray detection combined with micro-Raman spectroscopyinterfaced SEM-EDX/MRS) are more complex and less well comprehended. The physical and chemical processes that affect the damage caused to small particles by lasers still remain somewhat unclear, but certainly the atmosphere (vacuum/air) and the beam intensity have very significant influences. Furthermore, it has been determined that some particles (e.g. haematite), although stable under an electron beam, are damaged by the laser beam, hampering their analysis. Additionally, when simultaneous analyses by SEM/EDX and MRS are considered, the correct choice of the collection surface plays a crucial role. As a result, the following collection substrates were tested to determine their influence on the laser beam damage process to the particle: silver and aluminium foils and silicon wafers. A test study was performed using artificial examples of haematite (Fe2O3) particles. Exposure of Fe2O3 particles in vacuum to 514- and 785-nm laser radiation often leads to their melting, transformation and evaporation. The dependence of the damage caused by the laser beam on the particle structure is reported here. Molecular and crystallographic changes have also been revealed. Formation of magnetite (as an effect of re-crystallisation) and Raman inactive structures was detected.

Abstract: Toxicological research of novel nanomaterials is a major developmental step of their clinical approval. Since iron oxide magnetic nanoparticles have a great potential in cancer treatment and diagnostics, the investigation of their toxic properties is very topical. In this paper we synthesized bovine serum albumin-coated iron oxide nanoparticles with different sizes and their polyethylene glycol derivative. To prove high biocompatibility of obtained nanoparticles the number of in vitro toxicological tests on human fibroblasts and U251 glioblastoma cells was performed. It was shown that albumin nanoparticles' coating provides a stable and biocompatible shell and prevents cytotoxicity of magnetite core. On long exposure times (48 hours), cytotoxicity of iron oxide nanoparticles takes place due to free radical production, but this toxic effect may be neutralized by using polyethylene glycol modification.

Abstract: Mannosylerythritol lipids (MELs) are a promising group of biosurfactants due to their high fermentation yield, selfassembly and biological activity. During fermentation by Pseudozyma aphidis, a mixture of MELs with different levels of acylation is formed, of which the fully deacetylated form is the most valuable. In order to reduce the environmental impact of deacetylation, an enzymatic process using natural deep eutectic solvents (NADES) has been developed. We tested the deacetylation of a purified MELs mixture with immobilized Candida antarctica lipase B enzyme and 2-ethylhexanol as co-substrate in 140 h reactions with different NADES. We identified hydrophobic NADES systems with similar yields and kinetics as in pure 2-ethylhexanol solvent. Our results indicate that deacetylation of MELs mixtures in NADES as a solvent is possible with yields comparable to pure co-substrate and that hydrophobic NADES without carboxylic acid compounds facilitate the reaction to the greatest extent.

Abstract: A portable and highly sensitive sensor was designed for the specific detection of 3,4-methyl-enedioxy-methamphetamine (MDMA), in a range of field-testing situations. The sensor can detect MDMA in street samples, even when other controlled substances drugs, or adulterants are present. In this work, we report for the first time a sensor using electroactive molecularly imprinted polymer nanoparticles computationally designed to recognize MDMA and then produced using solid phase synthesis. A composite comprising chitosan, reduced graphene oxide, and molecularly imprinted polymer nanoparticles synthesized for MDMA for the first time was immobilized on screen-printed carbon electrodes. The sensors displayed a satisfactory sensitivity (106.8 nA x mu M-1), limit of detection (1.6 nM; 0.31 ng/mL), and recoveries (92-99%). The accuracy of the results was confirmed through validation using Ultra-High Performance Liquid Chromatography coupled with tandem Mass Spectrometry (UPLC-MS/MS). This technology could be used in forensic analysis and make it possible to selectively detect MDMA in street samples. A highly sensitive and portable sensor has been developed to detect MDMA in street samples. It uses electroactive molecularly imprinted polymer nanoparticles computationally designed to recognize MDMA, which were immobilized on screen-printed carbon electrodes with chitosan and graphene. The sensor showed good sensitivity and satisfactory recoveries (92-99%), confirmed with UPLC-MS/MS validation. This technology has the potential to be used in forensic analysis.image

Abstract: Mass spectrometry identifies the atomic mass of molecules and fragments in the gas phase. The spectrometer ionizes the molecules that then pass through an electric or magnetic field towards a detector. The field modifies the molecule's trajectory and we infer mass from its direction and velocity in a static field or from the stability of its path in a dynamic field. The electric current is amplified and a mass spectrum is generated from the location or timing of the signal from the detector, translated into a plot of the intensity as a function of the mass‐over‐charge ratio. It is field deployable, measures concentrations in real time with a temporal resolution better than 100 ms, and detection limits of fg. However, the signal drifts with time so we have to calibrate it as frequently as every hour. Calibrating requires multiple mixtures with varying concentrations to map the non‐linear response. The Web of Science Core Collection indexed over 60 000 articles that refer to MS (2016 and 2017) with applications ranging from permanent gas analysis, to identifying protein, forensic science, and natural products. The bibliometric software VOSViewer(2010) identified four clusters of research related to MS: (1) proteomics, proteins, plasma, and metabolomics; (2) solid phase extraction together with gas chromatography; (3) tandem mass spectrometry and liquid chromatography; and (4) waste water and toxicity. We expect that the technique will continue to evolve with increased sensitivity, lower drift, and greater specificity. Miniaturization efforts should also continue in order to develop faster field deployable instruments.

Abstract: Laser microprobe mass analysis was applied to study the chemical composition of spheroliths in the Bowman's membrane of patients suffering from primary atypical bandkeratopathy. The inclusions appear to consist mainly of calcium phosphate.

Abstract: The characteristics and analytical utility of laser microprobe mass analysis (LAMMA) are described and evaluated, and a short history of this recent microanalytical technique is presented. A review of the areas of application of LAMMA and related laser microprobes is presented with special emphasis on applications in the life sciences.

Abstract: The analytical methods which are often used for the determination of cocaine in complex biological matrices are a prescreening immunoassay and confirmation by chromatography combined with mass spectrometry. We suggest an ultra-high-pressure liquid chromatography combined with a potentiometric detector, as a fast and practical method to detect and quantify cocaine in biological samples. An adsorption/desorption model was used to investigate the usefulness of the potentiometric detector to determine cocaine in complex matrices. Detection limits of 6.3ngmL(-1) were obtained in plasma and urine, which is below the maximum residue limit (MRL) of 25ngmL(-1). A set of seven plasma samples and 10 urine samples were classified identically by both methods as exceeding the MRL or being inferior to it. The results obtained with the UPLC/potentiometric detection method were compared with the results obtained with the UPLC/MS method for samples spiked with varying cocaine concentrations. The intraclass correlation coefficient was 0.997 for serum (n =7) and 0.977 for urine (n =8). As liquid chromatography is an established technique, and as potentiometry is very simple and cost-effective in terms of equipment, we believe that this method is potentially easy, inexpensive, fast and reliable. Copyright (c) 2014 John Wiley & Sons, Ltd.

Abstract: In this work, the electroporation phenomenon induced by pulsed electric field on different nucleated biological cells is studied. A nonlinear, non-local, dispersive, and space-time multiphysics model based on Maxwell's and asymptotic Smoluchowski's equations has been developed to calculate the transmembrane voltage and pore density on both plasma and nuclear membrane perimeters. The irregular cell shape has been modeled by incorporating in the numerical algorithm the analytical functions pertaining to Gielis curves. The dielectric dispersion of the cell media has been modeled considering the multi-relaxation Debye-based relationship. Two different irregular nucleated cells have been investigated and their response has been studied applying both the dispersive and non-dispersive models. By a comparison of the obtained results, differences can be highlighted confirming the need to make use of the dispersive model to effectively investigate the cell response in terms of transmembrane voltages, pore densities, and electroporation opening angle, especially when irregular cell shapes and short electric pulses are considered. Bioelectromagnetics. 2019;40:331-342. (c) 2019 Wiley Periodicals, Inc.