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.

High Nickel and No Cobalt─The Pursuit of Next-Generation Layered Oxide Cathodes.

Abstract: The prosperity of the electric vehicle industry is driving the research and development of lithium-ion batteries. As one of the core components in the entire battery system, cathode materials are currently facing major challenges in pushing a higher capacity up to the materials' theoretical limits and transitioning away from unaffordable metals. The search for next-generation cathode materials has shifted to high-nickel and cobalt-free cathodes to meet these requirements. In this review, we distinctly point out the shortcomings of cobalt in stabilizing layered structures and systematically summarize the recent efforts to eliminate cobalt and achieve higher nickel content in layered cathode materials. Finally, a reasonable prospect is put forward for further development of layered cathode materials and other promising candidates, which is likely to spur a wave of efforts toward developing high-performance and low-cost Li-ion batteries.

Fabrication and properties of Cf/(Ti0.2Zr0.2Hf0.2Nb0.2Ta0.2)C-SiC high-entropy ceramic matrix composites via precursor infiltration and pyrolysis

Abstract: In this work, Cf/(Ti0.2Zr0.2Hf0.2Nb0.2Ta0.2)C-SiC high-entropy ceramic matrix composites were reported for the first time. Based on the systematic study of the pyrolysis and solid-solution mechanisms of (Ti0.2Zr0.2Hf0.2Nb0.2Ta0.2)C precursor by Fourier transform infrared spectroscopy, TG-MS and XRD, Cf/(Ti0.2Zr0.2Hf0.2Nb0.2Ta0.2)C-SiC with uniform phase and element distribution were successfully fabricated by precursor infiltration and pyrolysis. The as-fabricated composites have a density and open porosity of 2.40 g/cm3 and 13.32 vol% respectively, with outstanding bending strength (322 MPa) and fracture toughness (8.24 MPa m1/2). The Cf/(Ti0.2Zr0.2Hf0.2Nb0.2Ta0.2)C-SiC composites also present excellent ablation resistant property at a heat flux density of 5 MW/m2, with linear and mass recession rates of 2.89 μm/s and 2.60 mg/s respectively. The excellent combinations of mechanical and ablation resistant properties make the Cf/(Ti0.2Zr0.2Hf0.2Nb0.2Ta0.2)C-SiC composites a new generation of reliable ultra-high temperature materials.

Mass and charge transport relevant to the formation of toroidal lithium peroxide nanoparticles in an aprotic lithium-oxygen battery: An experimental and theoretical modeling study

Abstract: The discharge and charge mechanisms of rechargeable Li-O2 batteries have been the subject of extensive investigation recently. However, they are not fully understood yet. Here we report a systematic study of the morphological transition of Li2O2 from a single crystalline structure to a toroid like particle during the discharge–charge cycle, with the help of a theoretical model to explain the evolution of the Li2O2 at different stages of this process. The model suggests that the transition starts in the first monolayer of Li2O2, and is subsequently followed by a transition from particle growth to film growth if the applied current exceeds the exchange current for the oxygen reduction reaction in a Li-O2 cell. Furthermore, a sustainable mass transport of the diffusive active species (e.g., O2 and Li+) and evolution of the underlying interfaces are critical to dictate desirable oxygen reduction (discharge) and evolution (charge) reactions in the porous carbon electrode of a Li-O2 cell.

Microbial Community Structures and Dynamics in the O3/bac Drinking Water Treatment Process

Abstract: Effectiveness of drinking water treatment, in particular pathogen control during the water treatment process, is always a major public health concern. In this investigation, the application of PCR-DGGE technology to the analysis of microbial community structures and dynamics in the drinking water treatment process revealed several dominant microbial populations including: α-Proteobacteria, β-Proteobacteria, γ-Proteobacteria, Bacteroidetes, Actinobacteria Firmicutes and Cyanobacteria. α-Proteobacteria and β-Proteobacteria were the dominant bacteria during the whole process. Bacteroidetes and Firmicutes were the dominant bacteria before and after treatment, respectively. Firmicutes showed season-dependent changes in population dynamics. Importantly, γ-Proteobacteria, which is a class of medically important bacteria, was well controlled by the O3/biological activated carbon (BAC) treatment, resulting in improved effluent water bio-safety.

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.