Determination of trace amounts of uranium in plutonium oxide by wavelength dispersive X-ray fluorescence spectrometry

Journal of Radioanalytical and Nuclear Chemistry - 149Tb, 152Tb, 155Tb and 161Tb can cover all the modalities of diagnostic and therapeutic purposes of nuclear medicine. The production cross...     

Conceptualization and Synthesis of the First Inosito-Inositol (Decahydroxydecalin,DHD): In silico Binding to β-Amyloid Protein

Previously unknown entities in the form of 1,2,3,4,5,6,7,8,9,10-decahydroxydecalins (DHDs) have been conceptualized and the first member of this class, an inosito-inositol, has been synthesized from aromatic hydrocarbon naphthalene following a flexible strategy that is amenable to diversity creation. The DHD accessed here has been subjected to preliminary in silico evaluation with Aβ and may hold some promise in Alzheimer's disease therapeutics.     

Framing the novel aspects of irreversibilty in MHD flow of Williamson nanomaterial with thermal radiation near stagnation point

Journal of Thermal Analysis and Calorimetry - Here, MHD stagnation point flow of non-Newtonian fluid over a stretchable surface is considered. Process of modeling is characterized for basic...     

Solvent Effects in the Homogeneous Catalytic Reduction of Propionaldehyde with Aluminium Isopropoxide Catalyst: New Insights from PFG NMR and NMR Relaxation Studies

Solvent effects in homogeneous catalysis are known to affect catalytic activity. Whilst these effects are often described using qualitative features, such as Kamlet-Taft parameters, experimental tools able to quantify and reveal in more depth such effects have remained unexplored. In this work, PFG NMR diffusion and T₁ relaxation measurements have been carried out to probe solvent effects in the homogeneous catalytic reduction of propionaldehyde to 1-propanol in the presence of aluminium isopropoxide catalyst. Using data on diffusion coefficients it was possible to estimate trends in aggregation of different solvents. The results show that solvents with a high hydrogen-bond accepting ability, such as ethers, tend to form larger aggregates, which slow down the molecular dynamics of aldehyde molecules, as also suggested by T₁ measurements, and preventing their access to the catalytic sites, which results in the observed decrease of catalytic activity. Conversely, weakly interacting solvents, such as alkanes, do not lead to the formation of such aggregates, hence allowing easy access of the aldehyde molecules to the catalytic sites, resulting in higher catalytic activity. The work reported here is a clear example on how combining traditional catalyst screening in homogeneous catalysis with NMR diffusion and relaxation time measurements can lead to new physico-chemical insights into such systems by providing data able to quantify aggregation phenomena and molecular dynamics.     

Creation of Laser-Induced Long Ionized Channels in Air Suspension

Russian Physics Journal - The paper deals with the propagation of the powerful laser beam in gas-dispersion systems and atmospheric aerosol background, which is accompanied by a wide spectrum of...     

Electrical Conductivity in a Laser Beam Channel

Russian Physics Journal - Electrical conductivity in a laser beam channel has been investigated. Oscillations of the conductivity caused by the oscillation motion of electrons in laser-induced...     

Rapid Learning-Based and Geologically Consistent History Matching

Various types of data become available at different stages of a reservoir’s life. The production data are integrated into the flow simulation models through a process referred to as history matching. The history-matching process is iterative, and it usually involves a large number of simulation runs. Hence, this process requires significant computational time. In most history-matching methods, the initial geological assumptions in the reservoir model are destroyed or significantly altered in the process. Furthermore, they do not account for the information obtained during the previous trials, and lack learning from the previous failures. In this paper, we introduce a new methodology that maintains the geological realism. The candidate realizations are selected through a learning-based history-matching (LHM) algorithm by which all the previously successful patterns are preserved and used to assist the construction of the next realizations. The various pieces of matching regions are assembled together to make a pool of the successful candidates. Such regions are then utilized for making an auxiliary dataset in a multiscale framework by which the next model is generated. To prevent from trapping in local minima, ideas from the genetic algorithm is adapted. The LHM algorithm can be applied to both categorical and continuous distributions. The LHM provides a conditional map by which the new production data are immediately incorporated into the existing reservoir models. We apply the LHM algorithm to various 2D and 3D examples with very complex binary and continuous properties. The algorithm is shown to produce history-matched models with significantly smaller CPU times.     

Numerical simulation of unsteady 3D magneto-Sisko fluid flow with nonlinear thermal radiation and homogeneous–heterogeneous chemical reactions

In this paper, we study the qualitative behaviour of satellite systems using bifurcation diagrams, Poincaré section, Lyapunov exponents, dissipation, equilibrium points, Kaplan–Yorke dimension etc. Bifurcation diagrams with respect to the known parameters of satellite systems are analysed. Poincaré sections with different sowing axes of the satellite are drawn. Eigenvalues of Jacobian matrices for the satellite system at different equilibrium points are calculated to justify the unstable regions. Lyapunov exponents are estimated. From these studies, chaos in satellite system has been established. Solution of equations of motion of the satellite system are drawn in the form of three-dimensional, two-dimensional and time series phase portraits. Phase portraits and time series display the chaotic nature of the considered system.     

Bentonite-modified electrochemical sensors: a brief overview of features and applications

Bentonites are promising materials for electrochemical sensing because of their unique physicochemical properties. They have relatively high surface area, good adsorption and ion-exchange ability, highly tunable surface and interlayer composition, non-toxic nature, and excellent biocompatibility. Moreover, they are outstanding substrates for stable immobilization of different functional moieties. The primary focus of this review article is to highlight the applications of bentonite-modified electrodes for the analysis of organic and inorganic analytes in different matrices. A brief summary on the necessity of analysis of different compounds is provided. For the first time, features and applications of bentonite-modified electrodes are critically appraised. The key features of bentonite-modified electrodes that enhance their electrocatalytic activity toward detection of certain target analytes are highlighted. At the end, an account of current status of bentonite-modified electrodes along with future research directions is provided.