Selective Recovery of Cadmium,Cobalt, and Nickel from Spent Ni–Cd Batteries Using Adogen® 464 and Mesoporous Silica Derivatives

Spent Ni–Cd batteries are now considered an important source for many valuable metals. The recovery of cadmium, cobalt, and nickel from spent Ni–Cd Batteries has been performed in this study. The optimum leaching process was achieved using 20% H₂SO₄, solid/liquid (S/L) 1/5 at 80 °C for 6 h. The leaching efficiency of Fe, Cd, and Co was nearly 100%, whereas the leaching efficiency of Ni was 95%. The recovery of the concerned elements was attained using successive different separation techniques. Cd(II) ions were extracted by a solvent, namely, Adogen^® 464, and precipitated as CdS with 0.5% Na₂S solution at pH of 1.25 and room temperature. The extraction process corresponded to pseudo-2nd-order. The prepared PTU-MS silica was applied for adsorption of Co(II) ions from aqueous solution, while the desorption process was performed using 0.3 M H₂SO₄. Cobalt was precipitated at pH 9.0 as Co(OH)₂ using NH₄OH. The kinetic and thermodynamic parameters were also investigated. Nickel was directly precipitated at pH 8.25 using a 10% NaOH solution at ambient temperature. FTIR, SEM, and EDX confirm the structure of the products.     

A Multistage In Silico Study of Natural Potential Inhibitors Targeting SARS-CoV-2 Main Protease

Among a group of 310 natural antiviral natural metabolites, our team identified three compounds as the most potent natural inhibitors against the SARS-CoV-2 main protease (PDB ID: 5R84), M^pro. The identified compounds are sattazolin and caprolactin A and B. A validated multistage in silico study was conducted using several techniques. First, the molecular structures of the selected metabolites were compared with that of GWS, the co-crystallized ligand of M^pro, in a structural similarity study. The aim of this study was to determine the thirty most similar metabolites (10%) that may bind to the M^pro similar to GWS. Then, molecular docking against M^pro and pharmacophore studies led to the choice of five metabolites that exhibited good binding modes against the M^pro and good fit values against the generated pharmacophore model. Among them, three metabolites were chosen according to ADMET studies. The most promising M^pro inhibitor was determined by toxicity and DFT studies to be caprolactin A (292). Finally, molecular dynamics (MD) simulation studies were performed for caprolactin A to confirm the obtained results and understand the thermodynamic characteristics of the binding. It is hoped that the accomplished results could represent a positive step in the battle against COVID-19 through further in vitro and in vivo studies on the selected compounds.     

EEG rhythm/channel selection for fuzzy rule-based alertness state characterization

The aim of the paper is to automatically select the optimal EEG rhythm/channel combinations capable of classifying human alertness states. Four alertness states were considered, namely ‘engaged’, ‘calm’, ‘drowsy’ and ‘asleep’. The features used in the automatic selection are the energies associated with the conventional rhythms, \(\delta , \theta , \alpha , \beta\) and \(\gamma\), extracted from overlapping windows of the different EEG channels. The selection process consists of two stages. In the first stage, the optimal brain regions, represented by sets of EEG channels, are selected using a simple search technique based on support vector machine (SVM), extreme learning machine (ELM) and LDA classifiers. In the second stage, a fuzzy rule-based alertness classification system (FRBACS) is used to identify, from the previously selected EEG channels, the optimal features and their supports. The IF–THEN rules used in FRBACS are constructed using a novel differential evolution-based search algorithm particularly designed for this task. Each alertness state is represented by a set of IF–THEN rules whose antecedent parts contain EEG rhythm/channel combination. The selected spatio-frequency features were found to be good indicators of the different alertness states, as judged by the classification performance of the FRBACS that was found to be comparable to those of the SVM, ELM and LDA classifiers. Moreover, the proposed classification system has the advantage of revealing simple and easy to interpret decision rules associated with each of the alertness states.

     

Investigation of wall mass transfer characteristics downstream of an orifice

Numerical simulations were performed to determine the effect of Reynolds number and orifice to pipe diameter ratio (d_o/d) on the wall mass transfer rate downstream of an orifice. The simulations were performed for d_o/d of 0.475 for Reynolds number up to 70,000. The effect of d_o/d was determined by performing simulations at a Reynolds number of 70,000 for d_o/d of 0.375, 0.475 and 0.575. The momentum and mass transport equations were solved using the Low Reynolds Number (LRN) K-? turbulence model. The Sherwood number (Sh) profile downstream of the orifice was in relatively good agreement with existing experimental results. The Sh increases sharply downstream of the orifice, reaching a maximum within 1–2 diameters downstream of the orifice, before relaxing back to the fully developed pipe flow value. The Sh number well downstream of the orifice was in good agreement with results for fully developed pipe flow estimated from the correlation of Berger and Hau (1977). The peak Sh numbers from the simulations were higher than that predicted from Tagg et al. (1979) and Coney (1980).     

Evolutionary Algorithms and Theirs Use in the Design of Sequential Logic Circuits

In this paper an approach based on an evolutionary algorithm to design synchronous sequential logic circuits with minimum number of logic gates is suggested. The proposed method consists of four main stages. The first stage is concerned with the use of genetic algorithms (GA) for the state assignment problem to compute optimal binary codes for each symbolic state and construct the state transition table of finite state machine (FSM). The second stage defines the subcircuits required to achieve the desired functionality. The third stage evaluates the subcircuits using extrinsic Evolvable Hardware (EHW). During the fourth stage, the final circuit is assembled. The obtained results compare favourably against those produced by manual methods and other methods based on heuristic techniques.     

Fabrication of transparent polymer-matrix nanocomposites with enhanced mechanical properties from chemically modified ZrO<Subscript>2</Subscript> nanoparticles

Optically transparent nanocomposites with enhanced mechanical properties were fabricated using stable dispersions of sub 10 nm ZrO₂ nanoparticles. The ZrO₂ dispersions were mixed with a commercially available bisphenol-A-based epoxy resin (RIMR 135i) and cured with a mixture of two amine-based curing agents (RIMH 134 and RIMH 137) after complete solvent removal. The colloidal dispersions of ZrO₂ nanoparticles, synthesized through a non-aqueous approach, were obtained through a chemical modification of the ZrO₂ nanoparticle surface, employing different organic ligands through simple mixing at room temperature. Successful binding of the ligands to the surface was studied utilizing ATR–FT-IR and thermogravimetric analysis. The homogeneous distribution of the nanoparticles within the matrix was proven by SAXS and the observed high optical transmittance for ZrO₂ contents of up to 8 wt%. Nanocomposites with a ZrO₂ content of only 2 wt% showed a significant enhancement of the mechanical properties, e.g., an increase of the tensile strength and Young’s modulus by up to 11.9 and 12.5%, respectively. Also the effect of different surface bound ligands on the mechanical properties is discussed.     

Synthesis and electrophoretic deposition of hydrothermally synthesized multilayer TiO2 nanotubes on conductive filters

TiO₂ nanotubes were synthesized by the decomposition of titanium isopropoxide in water and the calcination at 450 °C for 2 h to form TiO₂ nanoparticles. The synthesized TiO₂ in anatase form nanoparticles were processed hydrothermally in 10 M NaOH solution at 130 °C for 24 h to obtain multilayer TiO₂ nanotubes. TEM analysis revealed that the diameters of the tubes were around 10 nm and they are in the length of 100 nm. Subsequently, colloidal suspensions containing 1% wt. Of TiO2 nanotubes were prepared with TEA and butanol and electrophoretic deposition (EPD) experiments were conducted in order to obtain coatings on Ni and carbon filters using a deposition time of 10 min. and an applied voltage of 65 V. It is also shown that multilayer TiO₂ nanotubes having outer diameter around 10 nm and inner diameters of 4.3 nm can be produced using the described technique. EPD is also shown to be an effective technique to coat three dimensional components, such as Ni and C filters for various applications including water and air purification systems.