Synthesis and Spectroscopic Analyses of New Polycarbonates Based on Bisphenol A-Free Components

This paper discusses a new synthesis of bisphenol A-free polycarbonates based on four aliphatic-aromatic systems. In the first stage, different types of monomers (with/without sulfur) derived from diphenylmethane were synthesized. Then, new polycarbonates were prepared in the reactions with diphenyl carbonate (DPC) by transesterification and polycondensation reactions. Three different catalysts (zinc acetate, 4-(dimethylamino)pyridine and benzyltriethylammonium chloride) were tested. The structures of the compounds were confirmed by Nuclear Molecular Resonance spectroscopy (NMR) in each stage. The chemical structures of the obtained polycarbonates were verified by means of Attenuated Total Reflectance Fourier Transform infrared spectroscopy (ATR-FTIR). The presence of a carbonyl group in the infrared spectrum confirmed polycarbonate formation. Thermal studies by differential scanning calorimetry (DSC) were carried out to determine the melting temperatures of the monomers. A gel permeation chromatography analysis (GPC) of the polycarbonates was performed in order to investigate their molar masses. Thermal analysis proved the purity of the obtained monomers; the curves showed a characteristic signal of melting. The obtained polycarbonates were characterized as having high resistance to organic solvents, including tetrahydrofuran. The GPC analysis proved their relatively large molar masses and their low dispersity.

Wireless Passive High-Temperature Sensor Readout System for Rotational-Speed Measurement

Rotational-speed measurement in harsh environments is an important topic. However, the high rotation results in rapid frequency variations in the signals of a sensor and changes in physical properties under extreme thermal circumstances cause significant difficulties in reading signals. To address this problem, we adopt wireless passive measurement methods to design a special characteristic signal circuit module that achieves precise measurement of rotational speed at high temperatures. The sensor and the readout system include a variable frequency source, a readout antenna, and a radio frequency demodulation circuit. Herein, a demodulation detector of the signal conversion circuit is designed and used in the envelope detection module of the single sideband demodulation method. In addition, a conversion circuit test platform for high-temperature environment sensor signal is developed. From the testing, the output signal demodulation of the sensor was observed under a maximum temperature of 700°C with error less than 0.12%. The new sensor and measurement method do not require physical leads and achieve wireless noncontact accurate measurement of rotational speed at high temperature.

Signaling Information Management in Entrepreneurial Firms’ Financing Acquisition

Research has identified the significant effect of new ventures’ signaling information management on their ability to secure private equity financing. This study adopts an integrated signaling and screening perspective to investigate investors’ differing perceptions of signals from ventures, across early financing stages. It proposes a three-step interpretation process. Based on an inductive multiple case study of signaler‒receiver dyads, it finds that to reach a financing decision, angel investors extract a characteristic signal as the fundamental type, orchestrate an acting signal as a supplementary type, and scrutinize the consistency between both. However, venture capital investors extract an action signal as the fundamental type, orchestrate characteristic and endorsement signals as complementary types, and scrutinize the consistency among all three types.

Gear tooth breakage analysis based on multi-order modulated sideband RMS trending method

The fault characteristic signal energy for early gear tooth breakage is relatively weak and easily drowned by other signals, which is not conducive to the study of the fault development stage. A multi-order modulated sideband RMS (Root Mean Square) trend analysis method is proposed to analyse the development trend of the broken gear fault characteristics. By using this method to analyse gear breakage faults, the multi-order modulated sideband RMS trend analysis method can effectively determine the fault deterioration and fault stabilisation stages.

Time–Frequency Domain Characteristics of Acoustic Emission Signals and Critical Fracture Precursor Signals in the Deep Granite Deformation Process

To study the crack evolution law and failure precursory characteristics of deep granite rocks in the process of deformation and failure under high confining pressure, granite samples obtained from a depth of 1150 m are tested using a TAW-2000 triaxial hydraulic servo testing machine and a PCI-II acoustic emission monitoring system. Based on the stress–strain curve and IET function, the loading process of the sample is divided into five stages: crack closure, linear elastic deformation, microcrack generation and development, macroscopic fracture generation and energy surge, and post-peak failure. The evolution trend and fracture evolution law of the acoustic emission signal event interval function in different stages are analyzed. In particular, the signals with an amplitude greater than 85 dB, a peak frequency greater than 350 kHz, and a frequency centroid greater than 275 kHz are defined as the failure precursor signals before the rock reaches the peak stress. The defined precursor signal conditions agree well with the experimental results. The time–frequency analysis and wavelet packet decomposition of the precursor signal are performed on the extracted characteristic signal of the failure precursor. The results show that the time-domain signal is in the form of a continuous waveform, and the frequency-domain waveform has multi-peak coexistence that is mainly concentrated in the high-frequency region. The energy distribution obtained by the wavelet packet decomposition of the characteristic signal is verified with the frequency-domain waveform. The energy distribution of the signal is mainly concentrated in the 343.75–375 kHz frequency band, followed by the 281.25–312.5 kHz frequency band. The energy proportion of the high-frequency signal increases with the confining pressure.

Stochastic Resonance and Self-Induced Stochastic Resonance in Bearing Fault Diagnosis

Stochastic resonance (SR) and self-induced stochastic resonance (SISR) are two kinds of important dynamical phenomena in the nonlinear system. SR occurs at the frequency of the characteristic signal. However, SISR can occur at a frequency that is included in the excitation. In present, there are volumes of literatures focusing on extracting the bearing fault characteristics from the vibration signal by SR method. However, the occurrence of SISR may result in the fault features misjudgment in SR processing. Through experimental verifications, we find that the interference of SISR is illustrated strongly in the fault characteristics identification. More importantly, the transition from SISR to SR corresponds to the evolution process of bearing state from normal to damage. Therefore, this evolutionary process can not only judge the state of bearing, but also describe the severity of bearing failure. The result is verified by processing the signals of bearing fault with different severity in noise background. They are the most important findings in this work.

Continental Hotspots Tracks from Analysis of GOCE Gravity Gradients Data

<p>Hotspots are thermal instabilities that originate in the mantle and manifest themselves on the surface by volcanism, continental breaks or "traces" observed in the oceans. Theirs effects under the continents are still debated: in addition to a phase of activity associated with surface volcanism, a residual thermal anomaly could persist durably under the lithosphere along the trajectory of the hotspot.<br>For a simple model of thermal anomaly (parallelogram aligned in a fixed direction), we compute the perturbations of the geoid, of the gravity vector and of the associated gravity gradients. We show that in a coordinate system aligned with the parallelogram, gravity gradients have a characteristic signal with an order of magnitude of a few hundred mEotvos, well above the current data detection level. Thus for four real cases: in North Africa (with the Hoggar, Tibesti, Darfur and Cameroon hotspots), in Greenland (Iceland and Jan Mayen), in Australia (Cosgrove) and in Europe (Eifel), we calculate the paleo-positions of the hotspots during the last 100 Ma in a reference frame linked to the lithospheric plates, and we build maps of gravity gradients at different altitudes filtered at the spatial scale of a few hundred kilometers (scale of the hotspot) and oriented along the direction of the trajectory.<br>We clearly find signals aligned in the direction of the movement of the plates on spatial scales of a few hundred kilometers.<br>This signal is sometimes correlated with the topography and it is difficult to separate the sources resulting from volcanic edifices and their associated isostatic crustal roots from that induced by residual thermal anomaly. These results show that gradiometric data are able to detect and follow the tracks of hotspots in the continental lithosphere, during at least a few tens of millions of years, providing new clues to constrain their trajectory and improve reference frame tied to the mantle.</p>