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.

Experimental and theoretical characterization of ordered MAX phases Mo2TiAlC2 and Mo2Ti2AlC3

Abstract: Herein, we report on the phase stabilities and crystal structures of two newly discovered ordered, quaternary MAX phases—Mo2TiAlC2 and Mo2Ti2AlC3—synthesized by mixing and heating different elemental powder mixtures of mMo:(3-m)Ti:1.1Al:2C with 1.5 ≤ m ≤ 2.2 and 2Mo: 2Ti:1.1Al:2.7C to 1600 °C for 4 h under Ar flow. In general, for m ≥ 2 an ordered 312 phase, (Mo2Ti)AlC2, was the majority phase; for m < 2, an ordered 413 phase (Mo2Ti2)AlC3, was the major product. The actual chemistries determined from X-ray photoelectron spectroscopy (XPS) are Mo2TiAlC1.7 and Mo2Ti1.9Al0.9C2.5, respectively. High resolution scanning transmission microscopy, XPS and Rietveld analysis of powder X-ray diffraction confirmed the general ordered stacking sequence to be Mo-Ti-Mo-Al-Mo-Ti-Mo for Mo2TiAlC2 and Mo-Ti-Ti-Mo-Al-Mo-Ti-Ti-Mo for Mo2Ti2AlC3, with the carbon atoms occupying the octahedral sites between the transition metal layers. Consistent with the experimental results, the theoretical calculations clearly show that M l...

Role of endogenous sleep-wake and analgesic systems in anesthesia.

Abstract: Classical anesthetics of the gamma-aminobutyric acid type A receptor (GABA(A))-enhancing class (e.g., pentobarbital, chloral hydrate, muscimol, and ethanol) produce analgesia and unconsciousness (sedation). Dissociative anesthetics that antagonize the N-methyl-D-aspartate (NMDA) receptor (e.g., ketamine, MK-801, dextromethorphan, and phencyclidine) produce analgesia but do not induce complete loss of consciousness. To understand the mechanisms underlying loss of consciousness and analgesia induced by general anesthetics, we examined the patterns of expression of c-Fos protein in the brain and correlated these with physiological effects of systemically administering GABAergic agents and ketamine at dosages used clinically for anesthesia in rats. We found that GABAergic agents produced predominantly delta activity in the electroencephalogram (EEG) and sedation. In contrast, anesthetic doses of ketamine induced sedation, followed by active arousal behaviors, and produced a faster EEG in the theta range. Consistent with its behavioral effects, ketamine induced Fos expression in cholinergic, monoaminergic, and orexinergic arousal systems and completely suppressed Fos immunoreactivity in the sleep-promoting ventrolateral preoptic nucleus (VLPO). In contrast, GABAergic agents suppressed Fos in the same arousal-promoting systems but increased the number of Fos-immunoreactive neurons in the VLPO compared with waking control animals. All anesthetics tested induced Fos in the spinally projecting noradrenergic A5-7 groups. 6-hydroxydopamine lesions of the A5-7 groups or ibotenic acid lesions of the ventrolateral periaqueductal gray matter (vlPAG) attenuated antinociceptive responses to noxious thermal stimulation (tail-flick test) by both types of anesthetics. We hypothesize that neural substrates of sleep-wake behavior are engaged by low-dose sedative anesthetics and that the mesopontine descending noradrenergic cell groups contribute to the analgesic effects of both NMDA receptor antagonists and GABA(A) receptor-enhancing anesthetics.

Surface regulation enables high stability of single-crystal lithium-ion cathodes at high voltage.

Abstract: Single-crystal cathode materials for lithium-ion batteries have attracted increasing interest in providing greater capacity retention than their polycrystalline counterparts. However, after being cycled at high voltages, these single-crystal materials exhibit severe structural instability and capacity fade. Understanding how the surface structural changes determine the performance degradation over cycling is crucial, but remains elusive. Here, we investigate the correlation of the surface structure, internal strain, and capacity deterioration by using operando X-ray spectroscopy imaging and nano-tomography. We directly observe a close correlation between surface chemistry and phase distribution from homogeneity to heterogeneity, which induces heterogeneous internal strain within the particle and the resulting structural/performance degradation during cycling. We also discover that surface chemistry can significantly enhance the cyclic performance. Our modified process effectively regulates the performance fade issue of single-crystal cathode and provides new insights for improved design of high-capacity battery materials.

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.