Oleg N. Senkov

Bio: Oleg N. Senkov is an academic researcher from Air Force Research Laboratory. The author has contributed to research in topics: Microstructure & Alloy. The author has an hindex of 60, co-authored 200 publications receiving 16970 citations. Previous affiliations of Oleg N. Senkov include Wright-Patterson Air Force Base & Ohio State University.

Development and exploration of refractory high entropy alloys—A review

Abstract: Open literature publications, in the period from 2010 to the end of January 2018, on refractory high entropy alloys (RHEAs) and refractory complex concentrated alloys (RCCAs) are reviewed. While RHEAs, by original definition, are alloys consisting of five or more principal elements with the concentration of each of these elements between 5 and 35 at.%, RCCAs can contain three or more principal elements and the element concentration can be greater than 35%. The 151 reported RHEAs/RCCAs are analyzed based on their composition, processing methods, microstructures, and phases. Mechanical properties, strengthening and deformation mechanisms, oxidation, and corrosion behavior, as well as tribology, of RHEA/RCCAs are summarized. Unique properties of some of these alloys make them promising candidates for high temperature applications beyond Ni-based superalloys and/or conventional refractory alloys. Methods of development and exploration, future directions of research and development, and potential applications of RHEAs are discussed.

I and i

Abstract: There is, I think, something ethereal about i —the square root of minus one. I remember first hearing about it at school. It seemed an odd beast at that time—an intruder hovering on the edge of reality. Usually familiarity dulls this sense of the bizarre, but in the case of i it was the reverse: over the years the sense of its surreal nature intensified. It seemed that it was impossible to write mathematics that described the real world in …

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.