Acid/base and hydrogen bonding effects on the proton-coupled electron transfer of quinones and hydroquinones in acetonitrile: Mechanistic investigation by voltammetry, H NMR and computation

This report seeks to address the role of hydrogen bonding with Brønsted acids and bases in proton-coupled electron transfer (PCET) as it pertains to concerted or stepwise pathways of quinone (Q) and hydroquinone (QH₂) electrochemistry. This study was performed using a series of techniques that included cyclic voltammetry (CV), digital simulations, computational chemistry and ¹H NMR. Hydrogen bonding was inferred by a decrease in diffusion coefficient (D) values measured using a pulsed gradient echo- (PGE-) ¹H NMR technique. Changes of 40.8% and 37.9% in D values were only noted after the addition of two equivalents of acetate to 1,4-hydroquinone (1,4-QH₂) and catechol (1,2-QH₂), respectively. In contrast, the D values for the addition of selected amines (pyridine, N,N-diisopropylethylamine and triethylamine) changed only 3.2% on average. Quantum mechanical calculations were conducted to determine the pK_a of all quinoid species to serve as a starting point for the determination of equilibrium constants in voltammetric simulations. Simulations indicate that 1,4-benzoquinone undergoes stepwise electron-proton transfer upon addition of acetic acid, N-ethyldiisopropylammonium perchlorate and pyridinium nitrate and were simulated without the presence of hydrogen bonds. The QH₂ compounds show stepwise proton-electron transfers after addition of the both the conjugate amines and acetate.     

A two-channel microfluidic sensor that uses anodic electrogenerated chemiluminescence as a photonic reporter of cathodic redox reactions

This paper describes a new approach for sensing electrochemically active substrates in microfluidic systems. This two-electrode sensor relies on electrochemical detection at one electrode and electrogenerated chemiluminescent (ECL) reporting at the other. Each microfabricated indium tin oxide electrode is located in a separate microfluidic channel, but the channels are connected downstream of the electrodes to maintain a complete electrical circuit. Because of laminar flow, there is no bulk mixing of the fluids in the detecting and reporting channels. This approach allows the ECL reaction to be physically and chemically decoupled from the sensing channel of the device, which greatly expands the number of analytes that can be detected. However, because the cathode and anode are connected, electron-transfer processes occurring at the sensing electrode are electrically coupled to the ECL reaction. Charge balance permits the ECL light output to be quantitatively correlated to electrochemical reductions at the cathode. The system is used to detect Fe(CN)6(3-), Ru(NH3)6(3+), and benzyl viologen and report their presence via Ru(bpy)3(2+) (bpy = bipyridine) luminescence. Each different redox target initiates ECL at a unique potential bias related to its standard redox potential. The influence of the concentrations of Ru(bpy)3(2+) and the target analytes is discussed.     

Effect of decortication and protease treatment on the kinetics of liquefaction,saccharification, and ethanol production from sorghum

BACKGROUND: This study analyzes the effect of decortication and protease treatment on the kinetics of liquefaction, saccharification and ethanol production from sorghum kernels. In general, bioethanol yields from sorghum are lower than those from maize. This has been attributed to reduced access of starch‐degrading enzymes due to the crosslinked protein net in the sorghum kernels. RESULTS: Liquefaction is described as a zero order kinetics process, with reaction rates enhanced by protease treatment. The use of protease almost doubled the liquefaction rate in both whole and decorticated sorghum, compared with untreated kernels. During saccharification of decorticated sorghum, protease treatment significantly affected the glucose/starch yield and the glucose concentration profile over time. When compared with maize, protease treatment of decorticated sorghum resulted in superior ethanol production rates. Specific ethanol yields during fermentation were statistically comparable with those for maize. CONCLUSION: Protease treatment of decorticated sorghum kernels can impart substantial economic benefits in terms of improvement of bioethanol yield (13% over whole sorghum) and in reduced fermentation time (approximately 50% with respect to maize). Copyright © 2010 Society of Chemical Industry     

Biguanide-, imine-, and guanidine-based networks as catalysts for transesterification of vegetable oil

Polycationic systems based on poly(hexamethylene biguanide) (PHMBG), branched polyethyleneimine (PEI) and poly(N-vinylguanidine) (PVG) have been evaluated as heterogeneous catalysts for the transesterification of sunflower oil by methanol. Insoluble networks are synthesized via cross-linking of PHMBG by either 4,4′-methylenebis(N,N-diglycidylaniline) or polyisocyanate prepolymer, PEI with sebacoyl chloride, and PVG with 1,4-butanediol diglycidyl ether. PHMBG and its cross-linked networks appeared to be remarkably efficient catalysts, enabling 80–100% triglyceride conversion within 0.5 h at 70 °C. PEI-based networks catalyzed triglyceride transesterification with rates 8- to 12-fold slower than their PHMBG-based counterparts. The PVG-based networks, which were devoid of hydrophobic moieties, appeared to be inefficient catalysts due to limited accessibility of the basic guanidine groups to reactants. The PHMBG networks were shown to be recyclable by a simple centrifugal filtration. After 15 cycles of recovery and reuse, only 10–15% decline in performance was observed.     

Enhancement of immune response in mice fed with Streptococcus thermophilus and Lactobacillus acidophilus

Swiss mice, fed for 8 consecutive d with 50 micrograms/d of viable cultures of Lactobacillus acidophilus and Streptococcus thermophilus, showed significant variation in their immune system. In order to study this phenomenon assays for macrophage and lymphocyte function were carried out. Both lactic acid bacteria enhanced significantly the enzymatic and phagocytic activity of peritoneal macrophages as checked against the controls and also accelerated the phagocytic function of the reticuloendothelial system as revealed by the carbon clearance test. On the 2nd d (100 micrograms), L. acidophilus reached a peak of K = .271, which remained high. Streptococcus thermophilus was effective only on the 2nd d and then decreased. The lymphocytic activity studied by immunoglobulin secreting cells was assayed by Jerne's method of plaque-forming cells (PFC). This activity also was increased by the two microorganisms. Streptococcus thermophilus proved more effective than L. acidophilus. Lactobacillus acidophilus and S. thermophilus activated macrophages and lymphocytes and produced the same increase in the immune response of mice whether administered orally or intraperitoneally.     

An optimization method for learning statistical classifiers in structural reliability

Monte Carlo simulation is a general and robust method for structural reliability analysis, affected by the serious efficiency problem consisting in the need of computing the limit state function a very large number of times. In order to reduce this computational effort the use of several kinds of solver surrogates has been proposed in the recent past. Proposals include the Response Surface Method (RSM), Neural Networks (NN), Support Vector Machines (SVM) and several other methods developed in the burgeoning field of Statistical Learning (SL). Many of these techniques can be employed either for function approximation (regression approach) or for pattern recognition (classification approach). This paper concerns the use of these devices for discriminating samples into safe and failure classes using the classification approach, because it constitutes the core of Monte Carlo simulation as applied to reliability analysis as such. Due to the flexibility of most SL methods, a critical step in their use is the generation of the learning population, as it affects the generalization capacity of the surrogate. To this end it is first demonstrated that the optimal population from the information viewpoint lies around in the vicinity of the limit state function. Next, an optimization method assuring a small as well as highly informative learning population is proposed on this basis. It consists in generating a small initial quasi-random population using Sobol sequence for triggering a Particle Swarm Optimization (PSO) performed over an iteration-dependent cost function defined in terms of the limit state function. The method is evaluated using SVM classifiers, but it can be readily applied also to other statistical classification techniques because the distinctive feature of the SVM, i.e. the margin band, is not actively used in the algorithm. The results show that the method yields results for the probability of failure that are in very close agreement with Monte Carlo simulation performed on the original limit state function and requiring a small number of learning samples.     

Drying of industrial sludge waste in a conical spouted bed dryer. Effect of air temperature and air velocity

To determine the performance of a conical spouted bed dryer for the drying of sludge waste, an experimental study of drying in a spouted bed regime was performed under different experimental conditions. The drying performance was determined based on the time evolution of solid moisture content, and the influence of operating conditions (inlet air temperature, air flow rate, and bed mass) on the drying rate of sludge waste in spouted beds of a conical geometry was analyzed.     

Bioleaching of metal from waste stream using a native strain of Acidithiobacillus isolated from a coal mine drainage

In this study, the feasibility of using a biohydrometallurgical technique for selective metals recovery from electronic waste (e‐waste) by bacterial bioleaching was investigated. Acidithiobacillus was identified in coal mining acid mine drainage (AMD). The microorganism was studied using specific sequencing of a 16s rDNA fragment. The potential for the dissolution of copper from waste printed wire boards (PWBs) using the isolated Acidithiobacillus ferrooxidans (A. ferroxidans) was evaluated. The bioleaching experiments were performed in an orbital shaker at 30 °C and 170 rpm, with 10 % (v/v) inoculum and a pulp density of 30 g/L. The copper concentration was determined by energy dispersive x‐ray fluorescence (XRF). The result shows that copper recovery from PWBs using our A. ferrooxidans strain was 95 % after 8 days, which showed the feasibility of this process.