Xu Zhang

Bio: Xu Zhang is an academic researcher from Chinese Academy of Sciences. The author has contributed to research in topics: Medicine & Biology. The author has an hindex of 30, co-authored 464 publications receiving 4557 citations. Previous affiliations of Xu Zhang include Xi'an Jiaotong University & Northeastern University.

Identification and Genotyping of Enterocytozoon bieneusi in China

Abstract: In this study, the prevalence of Enterocytozoon bieneusi in China was investigated. Twelve genotypes of E. bieneusi were identified, of which 10 were novel genotypes. Further, 41.6% of the genotypes were found in both humans and animals. This is the first report of E. bieneusi in China.

Giant magnetocaloric effect in isostructural MnNiGe-CoNiGe system by establishing a Curie-temperature window

Abstract: An effective scheme of isostructural alloying was applied to establish a Curie-temperature window in isostructural MnNiGe-CoNiGe system. With the simultaneous accomplishment of decreasing structural-transition temperature and converting antiferromagnetic martensite to ferromagnetic state, a 200 K Curie-temperature window was established between Curie temperatures of austenite and martensite phases. In the window, a first-order magnetostructural transition between paramagnetic austenite and ferromagnetic martensite occurs with a sharp jump in magnetization, showing a magnetic entropy change as large as −40 J kg−1 K−1 in a 50 kOe field change. This giant magnetocaloric effect enables Mn1−xCoxNiGe to become a potential magnetic refrigerant.

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.