| 1 | A hidden precipitation scenario of theθ’-phase in Al-Cu alloys显示文摘Al-Cu binary alloys are important and interesting industry materials.Up to date,the formation mechanisms of the key strengthening precipitates,namedθ’-phase,in the alloys are still controversial.Here,we report that for non-deformed bulk Al-Cu alloys theθ’-phase actually has its own direct precursors that can form only at elevated aging temperature(>ca.200℃).These high-temperature precursors have the same plate-like morphology as theθ’-phase precipitates but rather different structures.Atomicresolution imaging reveals that they have a tetragonal structure with a=0.405 nm and c=1.213 nm,and an average composition of Al_(5-x)Cu_(1+x)(0≤x<1),being fully coherent with the Al-lattice.This precursor phase may initiate with a composition of Al5 Cu and evolve locally towards Al_(4)Cu_(2)in composition,eventually leading to a consequent structural transformation into theθ’-phase(Al4 Cu2=Al2 Cu).There are evidences that because of their genetic links in structure,such a high-temperature precursor may transform to theθ’-phase without having to change their morphology and interface structure.Our study reveals a well-defined and previously hidden precipitation scenario for theθ’-phase to form in Al-Cu alloys at an elevated aging temperature. | L.Zhou C.L.Wu P.Xie F.J.Niu W.Q.Ming K.Du J.H.Chen | 2021 | Journal of Materials Science & Technology2021，，16： | 4 |
| 2 | Electron tomography for sintered ceramic materials by a neural network algebraic reconstruction technique显示文摘The missing wedge effect in electron tomography introduces various types of artifacts in the tomograms and lowers the reconstruction resolution and quality.The artifacts produced in tomographic reconstruction of bulk materials can be very severe,particularly for sintered bulk ceramic materials in which there are often nano-pores or pore-like microstructure features.Here,we report a neural network algebraic reconstruction algorithm with no prior knowledge to perform electron tomography for a sintered SiC material with nano carbon zones.The results show that the proposed algorithm has a great suppressive effect on the missing wedge artifacts and a high tolerance for noise.The information in the missing wedge can be partly recovered by this technique.Thus,both the shape of the bulk SiC specimen and its irregular inner pore-like features are correctly retrieved in the obtained 3D image.Our study shows the effectiveness of the neural network algorithm for improving the reconstruction accuracy of electron tomography,in order to reveal sophisticated 3D microstructures generally existing in sintered ceramic materials. | R.H.Shen Y.T.He W.Q.Ming Y.Zhang X.D.Xu J.H.Chen | 2022 | Journal of Materials Science & Technology2022，，5： | 2 |
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