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A fluorescence signal has been demonstrated as an effective implement for micro/nanoscale temperature measurement which can be realized by either direct fluorescence excitation from materials or by employing nanoparticles as sensors. In this work, a steady-state electrical-heating fluorescence-sensing (SEF) technique is developed for the thermal characterization of one-dimensional (1D) materials. In this method, the sample is suspended between two electrodes and applied with steady-state Joule heating. The temperature response of the sample is monitored by collecting a simultaneous fluorescence signal from the sample itself or nanoparticles uniformly attached on it. According to the 1D heat conduction model, a linear temperature dependence of heating powers is obtained, thus the thermal conductivity of the sample can be readily determined. In this work, a standard platinum wire is selected to measure its thermal conductivity to validate this technique. Graphene quantum dots (GQDs) are employed as the fluorescence agent for temperature sensing. Parallel measurement by using the transient electro-thermal (TET) technique demonstrates that a small dose of GQDs has negligible influence on the intrinsic thermal property of platinum wire. This SEF technique can be applied in two ways: for samples with a fluorescence excitation capability, this method can be implemented directly; for others with weak or no fluorescence excitation, a very small portion of nanoparticles with excellent fluorescence excitation can be used for temperature probing and thermophysical property measurement.

With the increase in thermal power capacity, ultra supercritical units have become the mainstream of power industry. At the same time, with the improvement of the steam parameters and the lengthening of shafting, the production of steam flow excited vibration is frequent in the ultra supercritical units, which may seriously affect the reliability of the unit. This paper has taken steam flow excited vibration of a 1000MW turbine as an example in accordance with the experimental and theoretical causes of steam flow excited vibration to solve the problem of steam flow excited vibration by the proposed treatment plan. This can greatly improve the reliability of operation and the units with high load capacity.

The research results of coal characterization using the XPS method are summarized. Microsoft Visual Studio.net is utilized to build a database functional group characterization for coal, which contains over 1000 records including the kind of functional group, binding energy value, coal specie, producing area, sample preparation, and literature information. The database can be used to search and analyze XPS data for coal conveniently and is also of significance to support further coal research using XPS.

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