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.

Electrically robust ultralong nanowires of NiSi, Ni2Si and Ni31Si12

Abstract: Mass fabrication of directly accessible, ultralong, uniform Si nanowires is realized by employing a controllable and reproducible method based on standard Si technology. High-conductivity polycrystalline Ni-silicide nanowires around 30 nm by 30 nm in cross section, able to support extremely high currents at ∼108A∕cm2, are obtained by means of solid-state reaction of the Si nanowires with subsequently deposited Ni films. By properly adjusting the Ni film thickness, NiSi, Ni2Si, and Ni31Si12 nanowires characterized with distinct resistivity and temperature coefficient of resistance are obtained. Upon annealing, the electrical continuity of the nanowires breaks at temperatures about 0.7 times the melting points of the silicides.

Response to Comment on "Differential Rescue of Light- and Food-Entrainable Circadian Rhythms"

Abstract: The points raised by Mistlberger et al . arise from a shortcoming in their approach, namely, that they measure the response to food restriction by using food-seeking behavior, which is confounded by homeostatic inputs. We used unrelated circadian-driven physiological responses, and we stand by our finding that the dorsomedial nucleus of the hypothalamus contains a food-entrainable oscillator that is sufficient for entrainment of circadian rhythms of body temperature and locomotor activity.

A Non‐aqueous H 3 PO 4 Electrolyte Enables Stable Cycling of Proton Electrodes

Abstract: A non-aqueous proton electrolyte is devised by dissolving H3 PO4 into acetonitrile. The electrolyte exhibits unique vibrational signatures from stimulated Raman spectroscopy. Such an electrolyte exhibits unique characteristics compared to aqueous acidic electrolytes: 1) higher (de)protonation potential for a lower desolvation energy of protons, 2) better cycling stability by dissolution suppression, and 3) higher Coulombic efficiency owing to the lack of oxygen evolution reaction. Two non-aqueous proton full cells exhibit better cycling stability, higher Coulombic efficiency, and less self-discharge compared to the aqueous counterpart.

Performance Fluctuation of FinFETs With Schottky Barrier Source/Drain

Abstract: A considerable performance fluctuation of FinFETs featuring PtSi-based Schottky barrier source/drain is found. The Fin-channels measure 27-nm tall and 35-nm wide. Investigation of similarly processed transistors of broad gate-widths reveals a large variation in the position of the PtSi/Si interface with reference to the gate edge along the gate width. This variation suggests an uneven underlap between the PtSi and the gate from device to device for the FinFETs, since essentially only one silicide grain would be in contact with each Fin-channel at the PtSi/Si interface. The size of the underlap is expected to sensitively affect the performance of the FinFETs.

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.