Jun Lu

Bio: Jun Lu is an academic researcher from Chinese Academy of Sciences. The author has contributed to research in topics: Medicine & Materials science. The author has an hindex of 135, co-authored 1526 publications receiving 99767 citations. Previous affiliations of Jun Lu include Drexel University & Argonne National Laboratory.

Insight into Reversible Conversion Reactions in SnO2 -Based Anodes for Lithium Storage: A Review.

Abstract: Various anode materials have been widely studied to pursue higher performance for next generation lithium ion batteries (LIBs). Metal oxides hold the promise for high energy density of LIBs through conversion reactions. Among these, tin dioxide (SnO2 ) has been typically investigated after the reversible lithium storage of tin-based oxides is reported by Idota and co-workers in 1997. Numerous in/ex situ studies suggest that SnO2 stores Li+ through a conversion reaction and an alloying reaction. The difficulty of reversible conversion between Li2 O and SnO2 is a great obstacle limiting the utilization of SnO2 with high theoretical capacity of 1494 mA h g-1 . Thus, enhancing the reversibility of the conversion reaction has become the research emphasis in recent years. Here, taking SnO2 as a typical representative, the recent progress is summarized and insight into the reverse conversion reaction is elaborated. Promoting Li2 O decomposition and maintaining high Sn/Li2 O interface density are two effective approaches, which also provide implications for designing other metal oxide anodes. In addition, some in/ex situ characterizations focusing on the conversion reaction are emphatically introduced. This review, from the viewpoint of material design and advanced characterizations, aims to provide a comprehensive understanding and shed light on the development of reversible metal oxide electrodes.

Thermally induced substitutional reaction of Fe into Mo2GaC thin films

Abstract: The first Fe-based MAX phase is realized by solid-state substitution reaction of an Fe/Au/Mo2GaC thin-film diffusion couple, as determined by X-ray diffraction and scanning transmission electron mi...

The cationic small molecule GW4869 is cytotoxic to high phosphatidylserine-expressing myeloma cells

Abstract: We have discovered that a small cationic molecule, GW4869, is cytotoxic to a subset of myeloma cell lines and primary myeloma plasma cells. Biochemical analysis revealed that GW4869 binds to anionic phospholipids such as phosphatidylserine - a lipid normally confined to the intracellular side of the cell membrane. However, interestingly, phosphatidylserine was expressed on the surface of all myeloma cell lines tested (n = 12) and 9/15 primary myeloma samples. Notably, the level of phosphatidylserine expression correlated well with sensitivity to GW4869. Inhibition of cell surface phosphatidylserine exposure with brefeldin A resulted in resistance to GW4869. Finally, GW4869 was shown to delay the growth of phosphatidylserine-high myeloma cells in vivo. To the best of our knowledge, this is the first example of using a small molecule to target phosphatidylserine on malignant cells. This study may provide the rationale for the development of phosphatidylserine-targeting small molecules for the treatment of surface phosphatidylserine-expressing cancers.

Gene set enrichment analysis: A knowledge-based approach for interpreting genome-wide expression profiles

Abstract: Although genomewide RNA expression analysis has become a routine tool in biomedical research, extracting biological insight from such information remains a major challenge. Here, we describe a powerful analytical method called Gene Set Enrichment Analysis (GSEA) for interpreting gene expression data. The method derives its power by focusing on gene sets, that is, groups of genes that share common biological function, chromosomal location, or regulation. We demonstrate how GSEA yields insights into several cancer-related data sets, including leukemia and lung cancer. Notably, where single-gene analysis finds little similarity between two independent studies of patient survival in lung cancer, GSEA reveals many biological pathways in common. The GSEA method is embodied in a freely available software package, together with an initial database of 1,325 biologically defined gene sets.

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.