Engineering topics
Li, Zhiming
Publications and source records attributed to Li, Zhiming.
The effects of carbon on the phase stability and mechanical properties of heat-treated FeNiMnCrAl high entropy alloys
This work systematically investigates the effect of carbon on the phase stability and room- temperature tensile performance of an annealed Fe 40.4 Ni 11.3 Mn 34.8 Al 7.5 Cr 6 (at%) high entropy alloy without (HEA) and with 1.1% carbon (CHEA). Four annealing conditions were investigated: 773 K for 13 d and 42 d, 973 K for 20 d, and 1073 K and 1423 K for 24 h. The resulting microstructures were analyzed using a combination of scanning electron microscopy (SEM), transmission electron microscopy (TEM), energy dispersive spectroscopy (EDS), and atom probe tomography (APT). Vickers hardness testing and room- temperature tensile testing were used to determine the mechanical properties of the annealed HEA and the CHEA. APT composition profiles revealed fine Ni,Mn,Al-enriched matrix precipitates in the CHEA annealed at 773 K for 13 d. After ageing at 773 K for 42 d, colonies of (Ni,Fe) 2 MnAl- enriched Heusler phase lamellae were observed at the grain boundaries (GBs) and in the matrix for the HEA, while GB lamellar colonies of Mn,Cr-enriched M 23 C 6 carbides were observed for the CHEA. Due to the presence of the GB carbides, the resulting room-temperature elongation to fracture for the CHEA annealed at 773 K for 42 d was ~1% compared to ~11% for the HEA given the same anneal. At higher annealing temperatures, the microstructure contains Ni,Al-rich and Mn,Cr,C-rich precipitates that alternate along the GBs and appear to be associated with each other in the matrix. Electron diffraction analysis indicates the aforementioned Ni,Al-precipitates and Mn,Cr-carbides have b.c.c. and f.c.c. crystal structures, respectively. Once again, a low elongation to fracture (2%) was seen for the carbon-containing material compared to its un-doped counterpart (23%) which solely contained Ni,Al-rich b.c.c. precipitates.
Global stability of a diffusive and delayed virus infection model with general incidence function and adaptive immune response
In this paper, the dynamical behaviors for a five-dimensional virus infection model with diffusion and two delays which describes the interactions of antibody, cytotoxic T-lymphocyte (CTL) immune responses and a general incidence function are investigated. The reproduction numbers for virus infection, antibody immune response, CTL immune response, CTL immune competition and antibody immune competition, respectively, are calculated. By using the Lyapunov functionals and linearization methods, the threshold conditions on the global stability of the equilibria for infection-free, immune-free, antibody response, CTL response and antibody and CTL responses, respectively, are established if the space is assumed as homogeneous. When the space is inhomogeneous, the effects of diffusion, intracellular delay and production delay are obtained by the numerical simulations.
Multiscale Persistent Functions for Biomolecular Structure Characterization
Here in this paper, we introduce multiscale persistent functions for biomolecular structure characterization. The essential idea is to combine our multiscale rigidity functions (MRFs) with persistent homology analysis, so as to construct a series of multiscale persistent functions, particularly multiscale persistent entropies, for structure characterization. To clarify the fundamental idea of our method, the multiscale persistent entropy (MPE) model is discussed in great detail. Mathematically, unlike the previous persistent entropy (Chintakunta et al. in Pattern Recognit 48(2):391–401, 2015; Merelli et al. in Entropy 17(10):6872–6892, 2015; Rucco et al. in: Proceedings of ECCS 2014, Springer, pp 117–128, 2016), a special resolution parameter is incorporated into our model. Various scales can be achieved by tuning its value. Physically, our MPE can be used in conformational entropy evaluation. More specifically, it is found that our method incorporates in it a natural classification scheme. This is achieved through a density filtration of an MRF built from angular distributions. To further validate our model, a systematical comparison with the traditional entropy evaluation model is done. Additionally, it is found that our model is able to preserve the intrinsic topological features of biomolecular data much better than traditional approaches, particularly for resolutions in the intermediate range. Moreover, by comparing with traditional entropies from various grid sizes, bond angle-based methods and a persistent homology-based support vector machine method (Cang et al. in Mol Based Math Biol 3:140–162, 2015), we find that our MPE method gives the best results in terms of average true positive rate in a classic protein structure classification test. More interestingly, all-alpha and all-beta protein classes can be clearly separated from each other with zero error only in our model. Finally, a special protein structure index (PSI) is proposed, for the first time, to describe the “regularity” of protein structures. Basically, a protein structure is deemed as regular if it has a consistent and orderly configuration. Our PSI model is tested on a database of 110 proteins; we find that structures with larger portions of loops and intrinsically disorder regions are always associated with larger PSI, meaning an irregular configuration, while proteins with larger portions of secondary structures, i.e., alpha-helix or beta-sheet, have smaller PSI. Essentially, PSI can be used to describe the “regularity” information in any systems.