Pengtao Li

Bio: Pengtao Li is an academic researcher from Northwestern Polytechnical University. The author has contributed to research in topics: Microstructure & Ultimate tensile strength. The author has an hindex of 9, co-authored 17 publications receiving 144 citations.

Nano-precipitates strengthened non-equiatomic medium-entropy alloy with outstanding tensile properties

Abstract: In this work, a novel non-equiamotic Ni46Cr23Co23Al4Ti4 medium-entropy alloy (MEA) strengthened by nanoscale coherent γ′ particles with L12 superlattice was successfully synthesized, then its microstructure, mechanical properties, strengthening and deformation mechanism were systemically investigated. Our experimental results demonstrated that this precipitation strengthened MEA exhibited outstanding strength-ductility synergy, combination a high yield strength of ~920 MPa, an ultimate tensile strength of ~1320 MPa and an excellent ductility of ~36%. The nanosized γ′ particles bought out effective precipitation strengthening in this non-equiamotic MEA, contributing a majority yield strength enhancement of ~600 MPa. For this γ′-strengthened MEA, the dominant deformation model was the stacking-faults controlled mode rather than the mechanical twin dominated mode in single-phase face-centered-cubic structure Ni50Cr25Co25 MEA. Our work provides a further understanding of precipitate strengthening in non-equiamotic high-entropy alloys (HEAs)/MEAs.

Molecular dynamic simulation of nanocrystal formation and tensile deformation of TiAl alloy

Abstract: The formation of nanocrystals from undercooling TiAl melt and deformation behavior of nanocrystalline TiAl alloy under tensile loading conditions are investigated by molecular dynamics simulation. The effects of quenching rate related to the solidification structure evolution during rapid quenching are described by internal energy, radial distribution functions, and common neighbor analysis. The simulation results indicate that the accumulation of atoms with icosahedral configuration and transformation into atomic cluster with BCC configuration in the undercooling melt are the key in crystalline nucleation growth, and eventually liquid TiAl alloy completely crystallizes at the quenching rate of 0.02 K ps−1. In the tensile deformation, grain boundaries sliding and lamellar domain increasing are the two main deformation mechanisms during plastic deformation, and cracks form due to the nucleation, growth and coalescence of void along the grain boundaries, which results in subsequent failure in nanocrystalline TiAl alloy. This paper provides fundamental understanding of the nanocrystalline formation of undercooling TiAl melt and the deformation mechanisms in the nanocrystalline TiAl at the atomic scale.

Fast parallel algorithms for short-range molecular dynamics

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.

A structure zone diagram including plasma based deposition and ion etching - eScholarship

Abstract: An extended structure zone diagram is proposed that includes energetic deposition, characterized by a large flux of ions typical for deposition by filtered cathodic arcs and high power impulse magnetron sputtering. The axes are comprised of a generalized homologous temperature, the normalized kinetic energy flux, and the net film thickness, which can be negative due to ion etching. It is stressed that the number of primary physical parameters affecting growth by far exceeds the number of available axes in such a diagram and therefore it can only provide an approximate and simplified illustration of the growth condition?structure relationships.

Machine learning assisted design of γ′-strengthened Co-base superalloys with multi-performance optimization

Abstract: Designing a material with multiple desired properties is a great challenge, especially in a complex material system. Here, we propose a material design strategy to simultaneously optimize multiple targeted properties of multi-component Co-base superalloys via machine learning. The microstructural stability, γ′ solvus temperature, γ′ volume fraction, density, processing window, freezing range, and oxidation resistance were simultaneously optimized. A series of novel Co-base superalloys were successfully selected and experimentally synthesized from >210,000 candidates. The best performer, Co-36Ni-12Al-2Ti-4Ta-1W-2Cr, possesses the highest γ′ solvus temperature of 1266.5 °C without the precipitation of any deleterious phases, a γ′ volume fraction of 74.5% after aging for 1000 h at 1000 °C, a density of 8.68 g cm−3 and good high-temperature oxidation resistance at 1000 °C due to the formation of a protective alumina layer. Our approach paves a new way to rapidly design multi-component materials with desired multi-performance functionality.