GH4169 is comparatively a new superalloy mainly used as turbine components because of its outstanding combination properties such as high-temperature strength, thermal stability and wear resistance. But these also make it hard to cut, and its machined surface quality and integrity are particularly sensitive to the manufacturing process employed. The existing researches on machining-induced surface integrity and machinability of hard-to-cut materials are briefly reviewed; the effects of processing parameters on surface integrity for GH4169 components are studied in detail via orthogonal-designed external grinding experiment. The single-factorial plain grinding experiment was designed to further investigate the influence of depth of cut on the surface integrity characteristics. The surface roughness, residual stress distribution, microhardness profile and microstructural alteration within the subsurface were obtained and analyzed. It was shown that the surface integrity is susceptible to the magnitude of depth of cut, and the components ground with low depth of cut are of more acceptable surface quality with less variation in residual stress and microhardness within the machining-affected layer than those obtained with high depth of cut. No severe microstructural alteration or adverse surface cracking was discerned when the depth of cut is reasonably set
Investigating the multimolecule patterns in living cells is of vital importance for clinical and biomedical studies. Herein, we reported for the first time the engineering of gold nanoflares as smart automata to implement computing-based diagnosis in living mammalian cells. Defining the logic combinations of miR122 and miR21 as the detection patterns, the corresponding OR and AND diagnostic automata were designed. The results showed that they could recognize the correct patterns rapidly and sensitively. The automata could enter cells via self-delivery and have good biocompatibility. They enabled accurate diagnosis on miRNA signatures in different cell lines and differentiation of fluctuations in the same cell line at single cell resolution. Moreover, the automata afforded an innovative diagnostic mode. It simplified the complicated process of detecting, data-collecting, computing, and evaluating. The direct diagnosing result ("1" or "0") was exported according to the embedded computation code. It highlighted the new possibility of using smart automata for intelligent diagnostics and cancer therapy at single cell resolution.
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