Reduction of the squeal noise from an automotive water pump

Nonlinear Dynamics - This paper presents a method to reduce the squeal noise generated by an automotive water pump. The noise and vibration of the water pump were analyzed through experiments, from...     

New multifunctional heterobinuclear palladium (II) complexes based on organometallic dithiocarbazate ligands

In the research of new compounds with multifunctional applications, heterobinuclear palladium (II) complexes based on organometallic dithiocarbazates (DTCZs) have been isolated. The organometallic DTCZ ligands of the general formula [{(η⁵-C₅H₄)-CH=NNHC(S)SCH₃}]MLn [MLn = Re (CO)₃ ( 2a ); Mn (CO)₃ ( 2b ); FeCp ( 2c )] were prepared by the reaction between formyl organometallic precursors ( 1a−c ) with S-methyldithiocarbazate. Subsequently, a two-step reaction of 2a−c with: (i) K₂[PdCl₄] and (ii) PPh₃ yielded heterobinuclear complexes [Pd{MLn(η⁵-C₅H₄)-CH=NNHC(S)SCH₃}–(Cl)(PPh₃)] [MLn = Re (CO)₃ ( 3a ); Mn (CO)₃ ( 3b ); FeCp ( 3c )]. All compounds were characterized by conventional spectroscopic techniques (infrared spectroscopy, nuclear magnetic resonance spectroscopy, mass spectrometry and elemental analysis). In addition, the molecular structures of 2a , 2c and 3c were determined by single-crystal X-ray diffraction. The new palladium (II) complexes ( 3a−c ) were evaluated as antiproliferative agents against non-small cell lung cancer cells (H1299 cells). Complexes 3a and 3b containing cyrhetrenyl- and cymantrenyl-DTCZ ligands, respectively, were more active than their ferrocenyl analogue 3c . The activity was associated with the electron-withdrawing properties of the (η⁵-C₅H₄)M (CO)₃ moieties and their better lipophilicity than that of the ferrocenyl analogue. In addition, we studied the capacity of metalloligands ( 2a−c ) and palladium (II) complexes ( 3a−c ) to remove methylene blue in water under UV–visible light irradiation. The results established that the complexes showed moderate efficiency and were less active than their corresponding free ligands.     

Lignin,a biomass crosslinker,in a shape memory polycaprolactone network

This work reports a new direction of natural lignin valorization, which utilizes lignin to produce crosslinked polycaprolactone (PCL) via a straightforward synthesis. Lignin's hydroxyl groups of its multibranched phenolic structure allow lignin to serve as crosslinkers, whereas the aromatic groups serve as hard segments. The modified natural lignin containing alkene terminals is crosslinked with a thiol‐terminal PCL via Ru‐catalyzed photoredox thiol‐ene reaction. The high rate of gel contents measured for all crosslinked polymers, with the least being 84% of gel content, indicates efficient crosslinking. The prepared flat rectangular shape lignin‐crosslinked PCL sample demonstrates rapid thermal responsive shape memory behavior at 10 °C and 80 °C showing interconversion between a permanent and temporary shape. The melting temperature of the lignin‐crosslinked PCL is tunable by varying the percent weight of lignin. The 11, 21, and 30 wt % lignin demonstrated T_m of 42 °C, 35 °C, and 26 °C, respectively. The role of lignin as a crosslinker presented in this work suggests that lignin can serve as an efficient biomass‐based functional additive to polymers. © 2019 Wiley Periodicals, Inc. J. Polym. Sci., Part A: Polym. Chem. 2019, 57, 2121–2130     

Strategies Towards Capturing Nitrogenase Substrates and Intermediates via Controlled Alteration of Electron Fluxes

Nitrogenase utilizes an ATP-dependent reductase to deliver electrons to its catalytic component to enable two important reactions: the reduction of N₂ to NH₄⁺, and the reduction of CO to hydrocarbons. The two nitrogenase-based reactions parallel the industrial Haber–Bosch and Fischer–Tropsch processes, yet they occur under ambient conditions. As such, understanding the enzymatic mechanism of nitrogenase is crucial for the future development of biomimetic strategies for energy-efficient production of valuable chemical commodities. Mechanistic investigations of nitrogenase has long been hampered by the difficulty to trap substrates and intermediates relevant to the nitrogenase reactions. Recently, we have successfully captured CO on the Azotobacter vinelandii V-nitrogenase via two approaches that alter the electron fluxes in a controlled manner: one approach utilizes an artificial electron donor to trap CO on the catalytic component of V-nitrogenase in the resting state; whereas the other employs a mismatched reductase component to reduce the electron flux through the system and consequently accumulate CO on the catalytic component of V-nitrogenase. Here we summarize the major outcome of these recent studies, which not only clarified the catalytic relevance of the one-CO (lo-CO) and multi-CO (hi-CO) bound states of nitrogenase, but also pointed to a potential competition between N₂ and CO for binding to the same pair of reactive Fe sites across the sulfur belt of the cofactor. Together, these results highlight the utility of these strategies in poising the cofactor at a well-defined state for substrate- or intermediate-trapping via controlled alteration of electron fluxes, which could prove beneficial for further elucidation of the mechanistic details of nitrogenase-catalyzed reactions.     

Exploring the oxidation chemistry of diisopropyl ether: Jet-stirred reactor experiments and kinetic modeling

Diisopropyl ether (DIPE) is considered as a promising gasoline additive due to the favorable blending Reid vapor pressure and the low water solubility. To get a good understanding of the DIPE oxidation chemistry, oxidation experiments of a stoichiometric mixture of DIPE/O₂/Ar/Kr were performed in a jet-stirred reactor (JSR) at atmospheric pressure over the temperature range of 525–900 K in this work. About 30 intermediates and products were identified and quantified using a photoionization molecular-beam mass spectrometer (PI-MBMS). Furthermore, a detailed kinetic model was proposed for DIPE oxidation, which showed satisfactory performances in predicting the species concentration profiles in this work as well as those in literature. For DIPE oxidation, the fuel consumption was observed only above 750 K, even though DIPE has two tertiary hydrogen atoms that are easy to be abstracted so that low-temperature oxidation reactivity is expected. The low oxidation reactivity at low temperature is because the formed OOQOOH radical mostly dissociates back to QOOH+O₂, instead of undergoing intramolecular isomerization which leads to the low-temperature chain-branching. At higher temperature, DIPE is mainly consumed by hydrogen abstraction reactions from the carbon atoms adjacent to the oxygen atom, producing dominantly the IC₃H₇OC(CH₃)₂ fuel radical, which then decomposes rapidly via CO bond β-scission instead of combining with O₂. In contrast, the minor fuel radical IC₃H₇OCH(CH₃)CH₂ tends to go through the O₂ addition reaction and the subsequent chain branching reactions, as confirmed by the detection of cyclic ether intermediates. Propylene and acetone are the most abundant intermediates in DIPE oxidation, both of which predominantly come from the initial fuel decomposition steps. Other intermediates are mainly formed via the consumption of these two species.     

Correlation‐assisted nearest shrunken centroid classifier with applications for high dimensional spectral data

High throughput data are frequently observed in contemporary chemical studies. Classification through spectral information is an important issue in chemometrics. Linear discriminant analysis (LDA) fails in the large‐p‐small‐n situation for two main reasons: (1) the sample covariance matrix is singular when p > n and (2) there is an accumulation of noise in the estimation of the class centroid in high dimensional feature space. The Independence Rule is a class of methods used to overcome these drawbacks by ignoring the correlation information between spectral variables. However, a strong correlation is an essential characteristic of spectral data. We proposed a new correlation‐assisted nearest shrunken centroid classifier (CA‐NSC) to incorporate correlation information into the classification. CA‐NSC combines two sources of information [class centroid (mean) and correlation structure (variance)] to generate the classification. We used two real data analyses and a simulation study to verify our CA‐NSC method. In addition to NSC, we also performed a comparison with the soft independent modeling of class analogy (SIMCA) approach, which uses only correlation structure information for classification. The results show that CA‐NSC consistently improves on NSC and SIMCA. The misclassification rate of CA‐NSC is reduced by almost half compared with NSC in one of the real data analyses. Generally, correlation among variables will worsen the performance of NSC, even though the discriminatory information contained in the class centroid remains unchanged. If only correlation structure information is used (as in the case of SIMCA), the result will be satisfactory only when the correlation structure alone can provide sufficient information for classification. Copyright © 2015 John Wiley & Sons, Ltd.