Author
Chaofang Dong
Other affiliations: University of Calgary, Chinese Ministry of Education, University of California, Berkeley
Bio: Chaofang Dong is an academic researcher from University of Science and Technology Beijing. The author has contributed to research in topics: Corrosion & Materials science. The author has an hindex of 39, co-authored 249 publications receiving 5684 citations. Previous affiliations of Chaofang Dong include University of Calgary & Chinese Ministry of Education.
Papers published on a yearly basis
Papers
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TL;DR: To prevent disasters, Xiaogang Li and colleagues call for open data infrastructures to collate information on materials failures as discussed by the authors, which can be used to detect and prevent disasters.
Abstract: To prevent disasters, Xiaogang Li and colleagues call for open data infrastructures to collate information on materials failures.
482 citations
TL;DR: In this article, the electrochemical behavior of duplex stainless steel in alkaline solutions with different pH values in the presence of NaCl was evaluated by different techniques: potentiodynamic measurements, electrochemical impedance spectroscopy and capacitance measurements (Mott-Schottky approach).
299 citations
TL;DR: The passivity of 316L stainless steel in borate buffer solution has been investigated by Mott-Schottky, atomic absorption spectrometry (AAS) and X-ray photoelectron spectroscopy (XPS) as mentioned in this paper.
293 citations
TL;DR: In this paper, the authors investigated the hydrogen-induced cracking behavior of X100 pipeline steel by a combination of tensile test, electrochemical hydrogen permeation measurement and surface characterization techniques.
261 citations
TL;DR: In this paper, the authors investigated the effects of heat treatment on the microstructural, mechanical and corrosion properties of 316 L stainless steel fabricated by selective laser melting, and they found that the passive film thickness and corrosion potential of the SLMed 316
234 citations
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01 May 1993
TL;DR: Comparing the results to the fastest reported vectorized Cray Y-MP and C90 algorithm shows that the current generation of parallel machines is competitive with conventional vector supercomputers even for small problems.
Abstract: Three parallel algorithms for classical molecular dynamics are presented. The first assigns each processor a fixed subset of atoms; the second assigns each a fixed subset of inter-atomic forces to compute; the third assigns each a fixed spatial region. The algorithms are suitable for molecular dynamics models which can be difficult to parallelize efficiently—those with short-range forces where the neighbors of each atom change rapidly. They can be implemented on any distributed-memory parallel machine which allows for message-passing of data between independently executing processors. The algorithms are tested on a standard Lennard-Jones benchmark problem for system sizes ranging from 500 to 100,000,000 atoms on several parallel supercomputers--the nCUBE 2, Intel iPSC/860 and Paragon, and Cray T3D. Comparing the results to the fastest reported vectorized Cray Y-MP and C90 algorithm shows that the current generation of parallel machines is competitive with conventional vector supercomputers even for small problems. For large problems, the spatial algorithm achieves parallel efficiencies of 90% and a 1840-node Intel Paragon performs up to 165 faster than a single Cray C9O processor. Trade-offs between the three algorithms and guidelines for adapting them to more complex molecular dynamics simulations are also discussed.
29,323 citations
Journal Article•
28,685 citations
TL;DR: There remains growing interest in magnesium (Mg) and its alloys, as they are the lightest structural metallic materials Mg alloys have the potential to enable design of lighter engineered systems, including positive implications for reduced energy consumption as mentioned in this paper.
1,173 citations