Catalytic Nitrene Transfer by an FeIV-Imido Complex Generated by a Comproportionation Process

Nitrene transfer reactions have emerged as one of the most powerful and versatile ways to insert an amine function to various kinds of hydrocarbon substrates. However, the mechanisms of nitrene generation have not been studied in depth albeit their formation is taken for granted in most cases without definitive evidence of their occurrence. In the present work, we compare the generation of tosylimido iron species and NTs transfer from Fe^II and Fe^III precursors where the metal is embedded in a tetracarbene macrocycle. Catalytic nitrene transfer to reference substrates (thioanisole, styrene, ethylbenzene and cyclohexane) revealed that the same active species was at play, irrespective of the ferrous versus ferric nature of the precursor. Through combination of spectroscopic (UV-visible, Mössbauer), ESI-MS and DFT studies, an Fe^IV tosylimido species was identified as the catalytically active species and was characterized spectroscopically and computationally. Whereas its formation from the Fe^II precursor was expected by a two-electron oxidative addition, its formation from an Fe^III precursor was unprecedented. Thanks to a combination of spectroscopic (UV-visible, EPR, Hyscore and Mössbauer), ESI-MS and DFT studies, we found that, when starting from the Fe^III precursor, an Fe^III tosyliodinane adduct was formed and decomposed into an Fe^V tosylimido species which generated the catalytically active Fe^IV tosylimide through a comproportionation process with the Fe^III precursor.     

Hyperparameter on-line learning of stochastic resonance based threshold networks

Aiming at training the feed-forward threshold neural network consisting of nondifferentiable activation functions, the approach of noise injection forms a stochastic resonance based threshold network that can be optimized by various gradient-based optimizers. The introduction of injected noise extends the noise level into the parameter space of the designed threshold network, but leads to a highly non-convex optimization landscape of the loss function. Thus, the hyperparameter on-line learning procedure with respective to network weights and noise levels becomes of challenge. It is shown that the Adam optimizer, as an adaptive variant of stochastic gradient descent, manifests its superior learning ability in training the stochastic resonance based threshold network effectively. Experimental results demonstrate the significant improvement of performance of the designed threshold network trained by the Adam optimizer for function approximation and image classification.     

Mechanism of BPh3-Catalyzed N-Methylation of Amines with CO2 and Phenylsilane: Cooperative Activation of Hydrosilane

BPh₃ catalyzes the N-methylation of secondary amines and the C-methylenation (methylene-bridge formation between aromatic rings) of N,N-dimethylanilines or 1-methylindoles in the presence of CO₂ and PhSiH₃; these reactions proceed at 30–40 °C under solvent-free conditions. In contrast, B(C₆F₅)₃ shows little or no activity. ¹¹B NMR spectra suggested the generation of [HBPh₃]⁻. The detailed mechanism of the BPh₃-catalyzed N-methylation of N-methylaniline ( 1 ) with CO₂ and PhSiH₃ was studied by using DFT calculations. BPh₃ promotes the conversion of two substrates (N-methylaniline and CO₂) into a zwitterionic carbamate to give three-component species [Ph(Me)(H)N⁺CO₂⁻⋅⋅⋅BPh₃]. The carbamate and BPh₃ act as the nucleophile and Lewis acid, respectively, for the activation of PhSiH₃ to generate [HBPh₃]⁻, which is used to produce key CO₂-derived species, such as silyl formate and bis(silyl)acetal, essential for the N-methylation of 1 . DFT calculations also suggested other mechanisms involving water for the generation of [HBPh₃]⁻ species.     

Optimization of Transducer Location for Novel Non-Intrusive Methodologies of Diagnosis in Diesel Engines

The health monitoring has been studied to ensure integrity of design of engine structure by detection, quantification, and prediction of damages. Early detection of faults may allow the downtime of maintenance to be rescheduled, thus preventing sudden shutdown of machines. In cylinder pressure developed, vibrations and noise emissions data provide a rich source of information about condition of engines. Monitoring of vibrations and noise emissions are novel non-intrusive methodologies for which positioning of various transducers are important issue. The presented work shows applicability of these diagnosis methodologies adopted in case of diesel engines. The effects of changing various fuel injection parameters was analyzed. Scope of using non-intrusive technique has been analyzed by changing locations of microphone. Novelty of this worklies in exploring signal processing methods for various locations around the engine test set up. Various frequency ranges of contributing noise and vibration sources were identified. Time-Frequency analysis showed the onset of various cyclic. Based on the identification of various frequency bands, it is possible to device suitable filters in order to extract more information.     

Assessment of Noise Exposure of Sawmill Workers in Southwest,Nigeria

Economic wood processing employs the use of industrial machines for cutting, shaping, milling, and sawing timber, thereby leading to the generation of high levels of noise. Published data from empirical studies have categorized noise as an environmental hazard of global significance. Furthermore, noise exposure limits for different industries and all the industrial machines available has not been formally established as it presently exists in developed nations around the world. Therefore, this study assessed the daily exposure of sawmills workers to noise in Southwestern Nigeria. Reconnaissance surveys were first carried out in Osun, Oyo, Ondo, Ekiti, Lagos, and Ogun States to select sawmills that were fully operational and fit for the study. Two fully functional sawmills in two cities of each State were eventually selected for data collection, making a total of 24 sawmills, while the Circular Machines (CM), Planer Machines (PM), and Band-saw Machines (BM) were the machines in each sawmill considered. Two machines each of CM, PM, and BM were considered in each sawmill, making a total of forty-eight (48) machines each of CM, PM, and BM. Sound data were collected between 7 am and 7 pm each day for six days (between Monday and Saturday) using Extech 407732 sound level meter and all stabilized measurements were taken three times at different intervals. The data collected were in three different periods: Machine No-work Period (NP_m), Machine Idle Period (IP_m), and Machine Working Period (WP_m). A two–way Analysis of Variance (ANOVA) was carried out at P < 0.05 to determine whether there is a significant difference in the sound level average before and after the break, for both the idle and working periods of the three machines considered. This was also done to determine whether there is a significant difference between the sound level average of the results collected during idle and working periods of the three machines. Noise Pollution Levels (L_np) ranged from 83.20 dB (PM) to 107.65 (BM) and 93.42 (CM and PM) – 116.00 (BM) respectively, while IP_m also gave the least noise pollution level of 95.79 dB and WP_m gave the highest level of 102.88 dB. The results revealed that all the machines’ L_np values in the working period are more than the 90 dB acceptable limit the recommendation value of 90 dB while 89.6% of CMs, 75% of PMs, and 89.6% of BM had their L_np above 90 dB in the idle period respectively. The minimum and the maximum noise dose levels for IP_m, WP_m and overall are 0.09 (BM) and 2.37 (CM), 0.50 (CM), and 4.77 (PM) and 0.69 (BM) and 6.64 (PM) respectively. The study found out that the fundamental contributing factors to the high noise levels in sawmills are poor machine maintenance, use of old and obsolete machines, poor housekeeping strategy, limited space, workers’ negligence, lack of PPE, and lack of occupational safety training. The study recommends that proper workplace practices such as use of personal protective equipment, new and modern machines, training, and occupational safety programmes be implemented in the considered sawmills.     

A DFT study on mechanisms of CO2 coupling with propargylic alcohols using alkali carbonates

The mechanisms of CO₂ coupling with the propargylic alcohol using alkali carbonates M₂CO₃ (M = Li, Na, K, Cs) have been investigated by means of density functional theory calculations. The calculations reveal that the target product tetronic acid (TA) is yielded through two stages: (a) the formation of the α-alkylidene cyclic carbonate (αACC) intermediate via Cs₂CO₃-mediated carboxylative cyclization of the propargylic alcohol with CO₂, and (b) the conversion of the αACC intermediate with Cs₂CO₃ to produce the cesium salt of the TA. Since the overall kinetic barriers for the two stages are comparable and affordable, the excellent chemoselectivity to the TA should be primarily originated from the high thermodynamic stability of the cesium salt of the TA. Moreover, relative to the TA, the possibility to yield the by-product acyclic carbonate can be excluded due to the both kinetics and thermodynamic inferiority. This result is different from the organic base-mediated reaction. Alternatively, our calculations predict that CsHCO₃ together generated with the cesium salt of the TA might also be an available mediating reagent for the incorporation of CO₂ with the propargylic alcohol. Compared to other alkali carbonates M₂CO₃ (M = Li, Na, K), the stronger basicity of Cs₂CO₃ and the lower ionic potential of cesium ion can raise the effective concentration of the αACC intermediate, and thus the conversion of the αACC intermediate into the cesium salt of the TA can be achieved with high yield.     

Theoretical studies on the influence of metallic cations on ring opening of propylene oxide catalyzed by metal-salen complexes

We studied the ring opening of propylene oxide (PO) by salen-M coordinated OH⁻ group [M = Al(III), Sc(III), Cr(III), Mn(III), Fe(III), Co(II), Co(III), Ni(II), Cu(II), Zn(II), Ru(III) and Rh(III)]. The results show that the ring-opening energy barriers for M(II) complexes are much lower than those with M(III) complexes in the gas phase, and the barriers correlate linearly with the negative charges on the OH⁻ group and the Fukui function condensed on the OH⁻ group. The nucleophilicity ordering in the gas phase can be rationalized by the ratio of formal positive charges/radius of M cations. Solvent effect greatly increases the barriers of M(II) complexes but slightly changes the results of M(III) ones, making the barriers similar. Analysis indicates that the reaction heats are linearly proportional to the reverse reaction barriers. The relationships established here can be used to estimate the ring-opening barriers and to screen epoxide ring-opening catalysts.     

Full counting statistics of transport electrons through a two-level quantum dot with spin–orbit coupling

We study the full counting statistics of transport electrons through a semiconductor two-level quantum dot with Rashba spin–orbit (SO) coupling, which acts as a nonabelian gauge field and thus induces the electron transition between two levels along with the spin flip. By means of the quantum master equation approach, shot noise and skewness are obtained at finite temperature with two-body Coulomb interaction. We particularly demonstrate the crucial effect of SO coupling on the super-Poissonian fluctuation of transport electrons, in terms of which the SO coupling can be probed by the zero-frequency cumulants. While the charge currents are not sensitive to the SO coupling.