Author
Jun Lu
Other affiliations: Drexel University, Argonne National Laboratory, Tsinghua University ...read more
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.
Topics: Medicine, Materials science, Computer science, Thin film, Biology
Papers published on a yearly basis
Papers
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TL;DR: In this article, single-crystal and poly-crystalline TiN/Cu stacks were prepared by unbalanced DC magnetron sputter deposition at a substrate temperature of 700°C and a pulsed bias potential of −100 V.
Abstract: Dense single-crystal and polycrystalline TiN/Cu stacks were prepared by unbalanced DC magnetron sputter deposition at a substrate temperature of 700 °C and a pulsed bias potential of −100 V. The microstructural variation was achieved by using two different substrate materials, MgO(001) and thermally oxidized Si(001), respectively. Subsequently, the stacks were subjected to isothermal annealing treatments at 900 °C for 1 h in high vacuum to induce the diffusion of Cu into the TiN. The performance of the TiN diffusion barrier layers was evaluated by cross-sectional transmission electron microscopy in combination with energy-dispersive X-ray spectrometry mapping and atom probe tomography. No Cu penetration was evident in the single-crystal stack up to annealing temperatures of 900 °C, due to the low density of line and planar defects in single-crystal TiN. However, at higher annealing temperatures when diffusion becomes more prominent, density-functional theory calculations predict a stoichiometry-dependent ...
38 citations
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TL;DR: Results indicate that PX domains contain a combination of conserved and variable features that allow them to have a common function and at the same time exhibit distinct specificities, mechanisms of regulation, or modes of interaction with effector molecules.
Abstract: PX domains have been recently found to act as phosphoinositide binding modules. In the yeast SNARE protein Vam7p, the PX domain binds to PtdIns(3)P and is required for vacuolar targeting. To gain i...
38 citations
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TL;DR: It is found that unilateral DBS in the GPe in rats significantly increased both non-rapid eye movement and rapid eye movement sleep compared to sham DBS stimulation, and the G Pe is potentially a better site for DBS to treat both insomnia and motor disorders caused by basal ganglia dysfunction.
38 citations
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TL;DR: In this article, the authors presented the visualization of dynamic nucleation and growth processes of gold nanoparticles on ultrathin MoS2 nanoflakes by in situ liquid-cell transmission electron microscopy (TEM).
Abstract: Two-dimensional (2D) substrates decorated with metal nanoparticles offer new opportunities to achieve high-performance catalytic behavior. However, little is known on how the substrates control the nucleation and growth processes of the nanoparticles. This paper presents the visualization of dynamic nucleation and growth processes of gold nanoparticles on ultrathin MoS2 nanoflakes by in situ liquid-cell transmission electron microscopy (TEM). The galvanic displacement resulting in Au nuclei formation on MoS2 was observed in real time inside the liquid cell. We found that the growth mechanism of Au particles on pristine MoS2 is in between diffusion-limited and reaction-limited, possibly due to the presence of electrochemical Ostwald ripening. A larger size distribution and more orientation variation is observed for the Au particles along the MoS2 edge than on the interior. Differing from pristine MoS2, sulfur vacancies on MoS2 induce Au particle diffusion and coalescence during the growth process. Density functional theory (DFT) calculations show that the size difference is because the exposed molybdenum atoms at the edge with dangling bonds can strongly interact with Au atoms, whereas sulfur atoms on the MoS2 interior have no dangling bonds and weakly interact with gold atoms. In addition, S vacancies on MoS2 generate strong nucleation centers that can promote diffusion and coalescence of Au nanoparticles. The present work provides key insights into the role of 2D materials in controlling the size and orientation of noble metal nanoparticles vital to the design of next generation catalysts.
38 citations
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TL;DR: In this article, low-temperature x-ray diffraction, susceptibility, specific heat, and thermal conductivity results both on single crystal and polycrystalline samples were presented.
Abstract: We present low-temperature x-ray diffraction, susceptibility, specific heat, and thermal conductivity results both on single crystal and polycrystalline $\mathrm{Mn}{\mathrm{V}}_{2}{\mathrm{O}}_{4}$ The single crystal sample exhibits two transitions: a spin ordering (ferrimagnetic) transition at ${T}_{\mathrm{SO}}=56\phantom{\rule{03em}{0ex}}\mathrm{K}$ and an orbital ordering transition at ${T}_{\mathrm{OO}}=52\phantom{\rule{03em}{0ex}}\mathrm{K}$ The structural change and phase separation at ${T}_{\mathrm{OO}}$ suggest that the transition is first order With applied magnetic fields, both ${T}_{\mathrm{SO}}$ and ${T}_{\mathrm{OO}}$ increase and ${T}_{\mathrm{OO}}$ disappears with $H\ensuremath{\geqslant}05\phantom{\rule{03em}{0ex}}\mathrm{T}$ The polycrystalline sample just exhibits one transition at $55\phantom{\rule{03em}{0ex}}\mathrm{K}$ The difference between the single crystal and polycrystalline samples is due to the nonstoichiometric polycrystalline sample
38 citations
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TL;DR: Recognition of the widespread applicability of these concepts will increasingly affect the development of new means to treat human cancer.
51,099 citations
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TL;DR: The Gene Set Enrichment Analysis (GSEA) method as discussed by the authors focuses on gene sets, that is, groups of genes that share common biological function, chromosomal location, or regulation.
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.
34,830 citations
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TL;DR: There is, I think, something ethereal about i —the square root of minus one, which seems an odd beast at that time—an intruder hovering on the edge of reality.
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 …
33,785 citations
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
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28,685 citations