| 1. |
- Shen, Yong-Feng, et al.
(författare)
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Deformation mechanisms of a 20Mn TWIP steel investigated by in situ neutron diffraction and TEM
- 2013
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Ingår i: Acta Materialia. - : Elsevier. - 1359-6454 .- 1873-2453. ; 61:16, s. 6093-6106
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Tidskriftsartikel (refereegranskat)abstract
- The deformation mechanisms and associated microstructure changes during tensile loading of an annealed twinning-induced plasticity steel with chemical composition Fe-20Mn-3Si-3Al-0.045C (wt.%) were systematically investigated using in situ time-of-flight neutron diffraction in combination with post mortem transmission electron microscopy (TEM). The initial microstructure of the investigated alloy consists of equiaxed gamma grains with the initial alpha'-phase of similar to 7% in volume. In addition to dislocation slip, twinning and two types of martensitic transformations from the austenite to alpha'- and epsilon-martensites were observed as the main deformation modes during the tensile deformation. In situ neutron diffraction provides a powerful tool for establishing the deformation mode map for elucidating the role of different deformation modes in different strain regions. The critical stress is 520 MPa for the martensitic transformation from austenite to alpha'-martensite, whereas a higher stress (>600 MPa) is required for actuating the deformation twin and/or the martensitic transformation from austenite to epsilon-martensite. Both epsilon- and alpha'-martensites act as hard phases, whereas mechanical twinning contributes to both the strength and the ductility of the studied steel. TEM observations confirmed that the twinning process was facilitated by the parent grains oriented with < 1 1 1 > or < 1 1 0 > parallel to the loading direction. The nucleation and growth of twins are attributed to the pole and self-generation formation mechanisms, as well as the stair-rod cross-slip mechanism.
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| 2. |
- Jia, Xue, et al.
(författare)
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CsPb(IxBr1-x)(3) solar cells
- 2019
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Ingår i: Science Bulletin. - : ELSEVIER. - 2095-9273. ; 64:20, s. 1532-1539
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Tidskriftsartikel (refereegranskat)abstract
- Owing to its nice performance, low cost, and simple solution-processing, organic-inorganic hybrid perovskite solar cell (PSC) becomes a promising candidate for next-generation high-efficiency solar cells. The power conversion efficiency (PCE) has boosted from 3.8% to 25.2% over the past ten years. Despite the rapid progress in PCE, the device stability is a key issue that impedes the commercialization of PSCs. Recently, all-inorganic cesium lead halide perovskites have attracted much attention due to their better stability compared with their organic-inorganic counterpart. In this progress report, we summarize the properties of CsPb(IxBr1-x)(3) and their applications in solar cells. The current challenges and corresponding solutions are discussed. Finally, we share our perspectives on CsPb(IxBr1-x)(3) solar cells and outline possible directions to further improve the device performance. (C) 2019 Science China Press. Published by Elsevier B.V. and Science China Press. All rights reserved.
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| 3. |
- Zhang, Meng, et al.
(författare)
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Top ten intelligent algorithms towards smart manufacturing
- 2023
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Ingår i: Journal of manufacturing systems. - : Elsevier BV. - 0278-6125 .- 1878-6642. ; 71, s. 158-171
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Forskningsöversikt (refereegranskat)abstract
- Intelligent algorithms can empower the development of smart manufacturing, since they can provide optimal solutions for detection, analysis, prediction and optimization. In recent ten years, publications on intelligent algorithms in smart manufacturing have increased sharply, showing superior performance in solving problems such as shop-floor scheduling, equipment prognosis, product defect detection and manufacturing service composition, etc. In this context, this paper focuses on the selection of commonly used top ten algorithms by providing a sound understanding of how they contribute to improving manufacturing processes. First, it presents a comprehensive survey and bibliometric analysis according to relevant literature. On this basis, the top ten algorithms are highlighted and reviewed. Then three key issues concerning when to use these algorithms in smart manufacturing, how to use them, as well as why to use them are studied. Finally, the challenges for the ten algorithms are summarized.
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