Institution
University of Science and Technology Beijing
Education•Beijing, China•
About: University of Science and Technology Beijing is a education organization based out in Beijing, China. It is known for research contribution in the topics: Microstructure & Alloy. The organization has 41558 authors who have published 44473 publications receiving 623229 citations. The organization is also known as: Beijing Steel and Iron Institute.
Topics: Microstructure, Alloy, Corrosion, Austenite, Ultimate tensile strength
Papers published on a yearly basis
Papers
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TL;DR: In this article, a sequentially activated multistage strain hardening (SMSH) mechanism was proposed for strong ultrafine-grained eutectic high-entropy alloy (EHEA), which enables the sequential activation of stress-dependent multiple hardening mechanisms.
150 citations
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TL;DR: The dielectric constant ε of the solvent is found to be a powerful predictor for the polar contribution to the free energy in implicit models; however, the Onsager relation may not hold for realistic solvent, as suggested by explicit solvent and SMD calculations.
Abstract: Quantitative prediction of physical properties of liquids is important for many applications. Computational methods based on either explicit or implicit solvent models can be used to approximate thermodynamics properties of liquids. Here, we evaluate the predictive power of implicit solvent models for solvation free energy of organic molecules in organic solvents. We compared the results calculated with four generalized Born (GB) models (GBStill, GBHCT, GBOBCI, and GBOBCII), the Poisson–Boltzmann (PB) model, and the density-based solvent model SMD with previous solvation free energy calculations (Zhang et al. J. Chem. Inf. Model. 2015, 55, 1192–1201) and experimental data. The comparison indicates that both PB and GB give poor agreement with explicit solvent calculations and even worse agreement with experiments (root-mean-square deviation ≈ 15 kJ/mol). The main problem seems to be the prediction of the apolar contribution, which should include the solvent entropy. The quantum mechanical-based SMD model g...
150 citations
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TL;DR: A waveguide-based retrieval method for measuring complex permittivity and permeability tensors of metamaterials is presented and shows its effectiveness in the effective parameters extraction.
Abstract: A waveguide-based retrieval method for measuring complex permittivity and permeability tensors of metamaterials is presented. In the proposed scheme, multiple independent sets of scattering data for the material under test with different orientations are measured in the frequency range corresponding to the dominant TE(10) mode. The method is applied to various metamaterials and shows its effectiveness in the effective parameters extraction.
149 citations
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TL;DR: In this article, the authors review the most recent research momentum regarding the formation mechanisms (elemental segregation, dislocation cell and oxide inclusion), the kinetics of the size and morphology, the growth orientation and the thermodynamic stability of these cellular structures by taking AM austenitic stainless steel as an exemplary material.
Abstract: The quick-emerging paradigm of additive manufacturing technology has revealed salient advantages in enabling the tailored-design of structural components with more exceptional performances over ordinary subtractive processing routines. As a peculiar feature, sub-micro cellular structures widely exist in additively manufactured (AM) metallic materials. This phenomenon primarily appears with high-density dislocations and segregated elements or precipitates at the cellular boundaries. The discovery of novel metastable substructures in various alloys through numerous investigations has proven their substantial effects on the engineering properties of AM components. This paper reviews the most recent research momentum regarding the formation mechanisms (elemental segregation, dislocation cell and oxide inclusion), the kinetics of the size and morphology, the growth orientation and the thermodynamic stability of these cellular structures by taking AM austenitic stainless steel as an exemplary material. Another topic of concern here is the inherent correlation between the unique cellular microstructure and the corresponding mechanical properties (strength, ductility, fatigue, etc.) and corrosion responses (passivity, irradiation damage, hydrogen embrittlement, etc.) for this category of AM materials. The design, control, and optimization of cellular structures for additive manufacturing techniques are expected to inspire new strategies for advancing high-performance structural alloy development.
149 citations
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TL;DR: Two types of fuzzy boundary controllers are proposed to ensure the exponential stability of the resulting closed-loop system and the advantages and effectiveness of the proposed control methodology are demonstrated by the simulation results of two examples.
Abstract: This paper deals with the problem of fuzzy boundary control design for a class of nonlinear distributed parameter systems which are described by semilinear parabolic partial differential equations (PDEs). Both distributed measurement form and collocated boundary measurement form are considered. A Takagi–Sugeno (T–S) fuzzy PDE model is first applied to accurately represent the semilinear parabolic PDE system. Based on the T–S fuzzy PDE model, two types of fuzzy boundary controllers, which are easily implemented since only boundary actuators are used, are proposed to ensure the exponential stability of the resulting closed-loop system. Sufficient conditions of exponential stabilization are established by employing the Lyapunov direct method and the vector-valued Wirtinger's inequality and presented in terms of standard linear matrix inequalities. Finally, the advantages and effectiveness of the proposed control methodology are demonstrated by the simulation results of two examples.
149 citations
Authors
Showing all 41904 results
Name | H-index | Papers | Citations |
---|---|---|---|
Zhong Lin Wang | 245 | 2529 | 259003 |
Yang Yang | 171 | 2644 | 153049 |
Jun Chen | 136 | 1856 | 77368 |
Jun Lu | 135 | 1526 | 99767 |
Jie Liu | 131 | 1531 | 68891 |
Shuai Liu | 129 | 1095 | 80823 |
Jian Zhou | 128 | 3007 | 91402 |
Chao Zhang | 127 | 3119 | 84711 |
Shaobin Wang | 126 | 872 | 52463 |
Tao Zhang | 123 | 2772 | 83866 |
Jian Liu | 117 | 2090 | 73156 |
Xin Li | 114 | 2778 | 71389 |
Jianhui Hou | 110 | 429 | 53265 |
Hong Wang | 110 | 1633 | 51811 |
Baoshan Xing | 109 | 823 | 48944 |