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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.


Papers
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TL;DR: In this paper, a robust, scalable PtSix process is developed, which consists of two consecutive annealing steps in a single run; the first is silicidation of Pt films on Si substrates carried out in N-2.
Abstract: A robust, scalable PtSix process is developed. The process consists of two consecutive annealing steps in a single run; the first is silicidation of Pt films on Si substrates carried out in N-2, wh ...

30 citations

Journal ArticleDOI
Mingjun Xia1, Shipeng Shen1, Jun Lu1, Young Sun1, Rukang Li1 
TL;DR: A new gadolinium-rich orthoborate K3 Li3 Gd7 (BO3 )9 (1) is grew as a promising cryogenic magnetic coolant that exhibits a complicated three dimensional framework constructed from BO3 groups and gadolinia-oxygen chains.
Abstract: Magnetic cooling technology based on magnetocaloric effect (MCE) has attracted great interest in obtaining extremely low temperatures, for example, for space exploration. Here, we grew a new gadolinium-rich orthoborate K3 Li3 Gd7 (BO3 )9 (1) as a promising cryogenic magnetic coolant. It exhibits a complicated three dimensional framework constructed from BO3 groups and gadolinium-oxygen chains. The Gd-O chain consists of two types of clusters of Gd3 O20 and Gd3 O19 interconnection by Gd(4)O8 polyhydron. Due to its high gadolinium concentration, a large -ΔSm of 56.6 J kg-1 K-1 for 1 was obtained at 2 K and ΔH=7 T, much larger than that of the commercial benchmark Gd3 Ga5 O12 (GGG) crystal (38.4 J kg-1 K-1 ), suggesting it to be an excellent MCE material.

30 citations

Journal ArticleDOI
23 Apr 2020
TL;DR: The ability to reverse the inherent tendency of noble metals to grow in an uncontrolled threedimensional (3D) fashion on weakly interacting substrates, including two-dimensional (2D) materials and...
Abstract: The ability to reverse the inherent tendency of noble metals to grow in an uncontrolled three-dimensional (3D) fashion on weakly interacting substrates, including two-dimensional (2D) materials and ...

30 citations

Journal ArticleDOI
TL;DR: The present data show that α-BiFeO3 crystallizes in space group P1 with magnetic modulation vector in reciprocal space q = 0.0045a* - 0.00045b*, which is the magnetic structure model proposed by I. Sosnowska (1) applied to the new P1 crystal symmetry of α- biFeO2.
Abstract: Polycrystalline and monocrystalline alpha-BiFeO3 crystals have been synthesized by solid state reaction and flux growth method, respectively. X-ray, neutron, and electron diffraction techniques are used to study the crystallographic and magnetic structure of alpha-BiFeO3. The present data show that alpha-BiFeO3 crystallizes in space group PI with a = 0.563 17(1) nm, b = 0.563 84(1) nm, c = 0.563 70(1) nm, alpha = 59.33(1)degrees, beta = 59.35(1)degrees, gamma = 59.38(1)degrees, and the magnetic structure of alpha-BiFeO3 can be described by space group PI with magnetic modulation vector in reciprocal space q = 0.0045a* - 0.0045b*, which is the magnetic structure model proposed by I. Sosnowska(1) applied to the new PI crystal symmetry of alpha-BiFeO3

30 citations

Journal ArticleDOI
TL;DR: Findings are consistent with the hypothesis that MAT could play a significant role in the molecular mechanism by which TETA extracts CuII from the systemic compartment in diabetic subjects.
Abstract: Triethylenetetramine (TETA), a selective Cu(II)-chelator used in the treatment of Wilson's disease, is now undergoing clinical trials for the treatment of heart failure in diabetes. Despite decades of clinical use, knowledge of its pharmacology in human subjects remains incomplete. Here, we first used liquid chromatography-mass spectrometry (LC-MS) to detect and identify major metabolites of TETA in human plasma and urine, and then used this method to measure concentrations of TETA and its metabolites in the urine of healthy and diabetic subjects who were administered increasing doses (300, 600, 1200, and 2400 mg) of TETA orally. Twenty-four-hour urine collections were performed before and after dosing participants. Two major metabolites of TETA were detected in human urine, N(1)-acetyltriethylenetetramine (MAT) and N(1),N(10)-diacetyltriethylenetetramine, the latter being novel. Both metabolites were verified with synthetic standards by LC-MS. The proportion of unchanged TETA excreted as a fraction of total urinary drug-derived molecules was significantly higher in healthy than in matched diabetic subjects, consistent with a higher rate of TETA metabolism in the latter. TETA-evoked increases in urinary Cu excretion in nondiabetic subjects were more closely correlated with parent drug concentrations than in diabetic subjects, whereas, by contrast, urinary Cu was more closely associated with the sum of TETA and MAT. These findings are consistent with the hypothesis that MAT could play a significant role in the molecular mechanism by which TETA extracts Cu(II) from the systemic compartment in diabetic subjects.

30 citations


Cited by
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04 Mar 2011-Cell
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

Journal ArticleDOI
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

Journal ArticleDOI

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08 Dec 2001-BMJ
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