Synthesis and Assessment of Two Malonyl Dihydrazide Derivatives as Corrosion Inhibitors for Carbon Steel in Acidic Media: Experimental and Theoretical Studies

Despite the extensive use of carbon steel in all industrial sectors, particularly in the petroleum industry, its low corrosion resistance is an ongoing problem for these industries. In the current work, two malonyl dihydrazide derivatives, namely 2,2’-malonylbis (N-phenylhydrazine-1-carbothiamide (MBC) and N’1, N’3-bis(-2-hydroxybenzylidene) malonohydrazide (HBM), were examined as inhibitors for the carbon steel corrosion in 1.0 M HCl. Both MBC and HBM were characterised using thin-layer chromatography, elemental analysis, infrared spectroscopy, and nuclear magnetic resonance techniques. The corrosion tests were performed using mass loss measurements, polarisation curves, and electrochemical impedance spectroscopy. It is obtained from the mass loss studies that the optimal concentration for both inhibitors is 2.0 × 10⁻⁵ mol/L, and the inhibition efficiencies reached up to 90.7% and 84.5% for MBC and HBM, respectively. Electrochemical impedance spectroscopy (EIS) and potentiodynamic polarisation (PDP) indicate an increased impedance in the presence of both MBC and HBM and mixed-type inhibitors, respectively. Both inhibitors can mitigate corrosion in the range of 298–328 K. Values of free energy changes obtained from the Langmuir model suggest that the inhibitors suppress the corrosion process principally by chemisorption. The computational investigations were conducted to identify the factors connected with the anti-corrosive properties of the examined inhibitors.     

Investigating the Disordered and Membrane-Active Peptide A-Cage-C Using Conformational Ensembles

The driving forces and conformational pathways leading to amphitropic protein-membrane binding and in some cases also to protein misfolding and aggregation is the subject of intensive research. In this study, a chimeric polypeptide, A-Cage-C, derived from α-Lactalbumin is investigated with the aim of elucidating conformational changes promoting interaction with bilayers. From previous studies, it is known that A-Cage-C causes membrane leakages associated with the sporadic formation of amorphous aggregates on solid-supported bilayers. Here we express and purify double-labelled A-Cage-C and prepare partially deuterated bicelles as a membrane mimicking system. We investigate A-Cage-C in the presence and absence of these bicelles at non-binding (pH 7.0) and binding (pH 4.5) conditions. Using in silico analyses, NMR, conformational clustering, and Molecular Dynamics, we provide tentative insights into the conformations of bound and unbound A-Cage-C. The conformation of each state is dynamic and samples a large amount of overlapping conformational space. We identify one of the clusters as likely representing the binding conformation and conclude tentatively that the unfolding around the central W23 segment and its reorientation may be necessary for full intercalation at binding conditions (pH 4.5). We also see evidence for an overall elongation of A-Cage-C in the presence of model bilayers.     

General expression of the calibration curve for the CR-39 radon track detectors

The CR-39 detectors are widely used as passive radon dosimeters, as well as in physics laboratories or for industrial applications. For what concerns radon monitoring, the calibration curve which is usually adopted corresponds to a linear relation between the actual etched track density and the track density counted by an automatic acquisition system. This linear calibration provides very accurate radon exposure assessments in a restricted range of etched track density, however it neglects the effect of the tracks overlapping that becomes as relevant as the track density increases. In the present work the mathematical expression of the area covered by a set of uniformly distributed tracks is deduced. This result allows then to infer the probability that the system acquires the right track density, providing a general calibration curve for a solid state radon track detector. The process of track production and reading routine is also simulated adopting a Monte Carlo approach, showing that the obtained results are in agreement with the function proposed as calibration curve. Moreover, a linear dependence between the track average area and the rate parameter of the calibration curve has been observed. Finally a semi-empirical correlation based on the previous results is proposed.     

Some insights in superdiffusive transport

In a wide range of systems, the relaxation in response to an initial pulse has been experimentally found to follow a nonlinear relationship for the mean squared displacement, of the kind 〈x²(t)〉∝t^α$〈x^2(t)〉\propto t^{\alpha }$, where α$\alpha$ may be greater or smaller than 1. Such phenomena have been described under the generic term of anomalous diffusion. “Lévy flights” stochastic processes lead to superdiffusive behaviour (1<α<2)$(1<\alpha <2)$ and have been recently proposed to model—among the others—the subsurface contaminant spread in highly heterogeneous media under the effects of water flow. In this paper, within the continuous-time random walk (CTRW) approach to anomalous diffusion, we compare the analytical solution of the approximated fractional diffusion equation (FDE) with the Monte Carlo one, obtained by simulating the superdiffusive behaviour of an ensemble of particle in a medium. We show that the two are neatly different as the process approaches the standard diffusive behaviour. We argue that this is due to a truncation in the Fourier space expansion introduced by the FDE approach. We propose a second-order correction to this expansion and numerically solve the CTRW model under this hypothesis: the accuracy of the results thus obtained is validated through Monte Carlo simulation over all the superdiffusive range. The same kind of discrepancy is shown to occur also in the derivation of the fractional moments of the distribution: analogous corrections are proposed and validated through the Monte Carlo approach.     

Quantitative Time-Resolved Fluorescence Spectrum of the Cortical Sarcoma and the Adjacent Normal Tissue

The difference in time-resolved fluorescence spectrum between the cortical sarcoma and the adjacent normal tissue was studied in both experimental and theoretical ways. The Clinical data were obtained in vivo using a time-resolved fluorescence spectrometer employing a single fiber-optic probe for excitation and detection. Tissue was modeled as s-180 sarcoma tumor surrounded with normal muscle and was mediated by the Palladium-porphyrin photosensitizer (Pd-TCPP). The emitted fluorescence was considered as arising from the tumor tissue or the normal muscle, due to the presence of the photosensitizer. A computational code which could simulating time-resolved fluorescence emission was presented and applied to comparing fluorescence decay of photosensitizer in different stages of tumor growth. In this code the different stages of the tumor was modeled through changing the time τ, the delay of the fluorescence photon emission and z _max, the thickness of the tumor. It was found in the in vivo experiment that the fluorescence from tumor tissue decayed more quickly than from the adjacent normal muscle. For the ten rats in the first experiment day, the mean decay constant of tumor T _s and normal tissue T _n were 554 and 526 μs, respectively. And T _s increased with the tumor growth, from 554 μs in the first day to 634 μs in the eighth day while T _s kept steady. It was believed that the more adequate oxygen supplied by the normal tissue can more effectively quench the fluorescence and in the normal tissue the photosensitizer lifetime is smaller. As a result the simulated time-resolved fluorescence spectrum of normal tissue showed more quickly decay. And the thickness of the tumor can also delay the fluorescence decay. Both the experimental and simulated results indicated that the germination of the tumor would increase the decay constant of the time-resolved fluorescence spectrum. So decay constant of the tumor tissue spectrum should be larger than that of adjacent normal tissue for the reason of hypoxia and overgrouth. This fact could be of use in the tumor diagnoses.     

Reliable radical stabilization energies from diffusion Monte Carlo calculations

We assess the performance of variational (VMC) and diffusion (DMC) quantum Monte Carlo methods for calculating the radical stabilization energies of a set of 43 carbon-centered radical species. Even using simple single-determinant trial wavefunctions, both methods perform exceptionally well, with mean absolute deviations from reference values well under the chemical accuracy standard of 1 kcal/mol. In addition, the use of DMC results in a highly concentrated spread of errors, with all 43 results within chemical accuracy at the 95% confidence level. These results indicate that DMC is an extremely reliable method for calculating radical stabilization energies and could be used as a benchmark method for larger systems in future.     

Theoretical Modeling of the Surface-Guided Self-Assembly of Functional Molecules

Directing the self-assembly of organic building blocks with 2D templates has been a promising method to create molecular superstructures having unique physicochemical properties. In this work the on-surface self-assembly of simple ditopic functional molecules confined inside periodic nanotemplates was modeled by means of the lattice Monte Carlo simulation method. Two types of confinement, that is honeycomb porous networks and parallel grooves of controlled diameter and width were used in the calculations. Additionally, the effect of (pro)chirality of the adsorbing molecules on the outcome of the templated self-assembly was examined. To that end, enantiopure and racemic assemblies were studied and the resulting structures were identified and classified. The obtained findings demonstrated that suitable tuning of the structural parameters of the templates enables directing the self-assembly towards linear and cyclic aggregates with controlled size. Moreover, chiral resolution of the molecular conformers using honeycomb networks with adjusted pore size was found possible. Our theoretical predictions can be helpful in designing structured surfaces to direct self-assembly and polymerization of organic functional building blocks.     

长程差分吸收光谱技术气体浓度反演误差的定量估计

长程差分吸收光谱法(LP-DOAS)是基于最小二乘原理来反演大气痕量气体浓度的。LP-DOAS能对痕量气体进行高灵敏的测量,但是还没有统计的方法定量确定LP-DOAS反演误差。痕量气体的吸收通常很弱,外来影响因素决定了检测限和测量精度,其被误当做真正的吸收,增加了没有统计特性的噪声到残差中,导致最小二乘拟合误差(err(LSQ))有一个明显的误估计。研究采用蒙特卡罗方法,通过残差的循环移位定量确定差分吸收光谱法反演气体浓度的误差。实验结果表明,蒙特卡罗方法可以定量估计差分吸收光谱法反演误差,误估计因子为1.13,而err(LSQ)为3.12。