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纳米晶Ni_3 Fe和Fe_(75) Al_(12.5) Ge_(12.5)的软磁性能

上海钢研 2001年第3期 63-66页

作者： H.N.Frase r.d.shull L.- B.Hong T.A.Stephens Z. -Q.Gao B.Fultz 张延忠

测量了不同晶粒尺寸的纳米晶Ni_3Fe和Fe_(75)Al(12.5)Ge_(12.5)的磁化曲线。这些材料是通过高能球磨接着在不同温度下退火制成。之所以选择这两种成份,是因为它们的大块材料具有低的磁致伸缩。这意味着样品中的应变对磁性的影响很小。利... 详细信息

测量了不同晶粒尺寸的纳米晶Ni_3Fe和Fe_(75)Al(12.5)Ge_(12.5)的磁化曲线。这些材料是通过高能球磨接着在不同温度下退火制成。之所以选择这两种成份,是因为它们的大块材料具有低的磁致伸缩。这意味着样品中的应变对磁性的影响很小。利用M-H磁化曲线得到矫顽力、最大磁导率和饱和磁化强度。这些磁性能的差异和晶粒尺寸及均方根(rMS)内应变(平均有效应变)的变化有关。尽管这两种大块材料的磁致伸缩小,内应力还是控制着矫顽力。但是,磁导率的变化并不象从晶粒尺寸变化趋势所预料的那样。我们提出的看法是,粉末的形态在决定这两种纳米晶合金的软磁性能中起重要作用。

关键词：软磁合金纳米晶合金软磁性能

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Nanocrystalline and Nanocomposite Magnetic Materials and Their Applications

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Journal of Iron and Steel research International 2007年第4期14卷 69-74页

作者： robert d shull Magnetic Materials Group National Institute of Standards and TechnologyGaithersburg MD 20899MarylandUSA

Nanocrystalline materials can possess bulk properties quite different from those commonly associated with conventional large-grained materials. Nanocomposites, a subset of nanocrystalline materials, in addition have been found to possess magnetic properties which are similar to, but different from, the properties of the individual constituents. New magnetic phenomena, unusual property combinations, and both enhanced and diminished magnetic property values are just some of the changes observed in magnetic nanocomposites from conventional magnetic materials. Here, a description will be presented of some of the exciting new properties discovered in nanomaterials and the magnetic applications envisioned for them.

关键词： nanocomposite ferromagnet magnetoresistance magnetic refrigeration domain imaging

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Identification of Global dNA Methylation Signatures in Glioblastoma-derived Cancer Stem Cells

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Journal of Genetics and Genomics 2015年第7期42卷 355-371页

作者： Eun-Joon Lee Prakash rath Jimei Liu dungsung ryu Lirong Pei Satish K.Noonepalle Austin Y.shull Qi Feng N.Scott Litofsky douglas C.Miller douglas C.Anthony Mark d.Kirk John Laterra Libin deng Hong-Bo Xin Xinguo Wang Jeong-Hyeon Choi Huidong Shi GrU Cancer Center Georgia Regents University department of Biology College of Art and SciencesUniversity of Missouri Office of In Vitro diagnostics and radiological Health Center for Devices and Radiological HealthFood and Drug Administration department of Biochemistry and Molecular Biology Georgia Regents University division of Neurological Surgery University of Missouri School of Medicine department of Pathology and Anatomical Sciences University of Missouri School of Medicine department of Pathology and Laboratory Medicine Brown University and Lifespan Academic Medical Center department of Neurology The Hugo W.Moser Research Institute at Kennedy Krieger Inc.and The Johns Hopkins University School of Medicine Institute of Translational Medicine Nanchang University david H.Murdock research Institute department of Biostatistics and Epidemiology Georgia Regents University

Glioblastoma （GBM） is the most common and most aggressive primary brain tumor in adults. The existence of a small population of stem-like tumor cells that efficiently propagate tumors and resist cytotoxic therapy is one proposed mechanism leading to the resilient behavior of tumor cells and poor prognosis. In this study, we performed an in-depth analysis of the dNA methylation landscape in GBM- derived cancer stem ceils （GSCs）. Parallel comparisons of primary tumors and GSC lines derived from these tumors with normal controls （a neural stem cell （NSC） line and normal brain tissue） identified groups of hyper- and hypomethylated genes that display a trend of either increasing or decreasing methylation levels in the order of controls, primary GBMs, and their counterpart GSC lines, respectively. Interestingly, concurrent promoter hypermethylation and gene body hypomethylation were observed in a subset of genes including MGMT, AJAP1 and PTPrN2. These unique dNA methylation signatures were also found in primary GBM-derived xenograft tumors indicating that they are not tissue culture-related epigenetic changes. Integration of GSC-specific epigenetic signatures with gene expression analysis further identified candidate tumor suppressor genes that are frequently down-regulated in GBMs such as SPINT2, NEFM and PENK. Forced re-expression of SPINT2 reduced glioma cell proliferative capacity, anchorage independent growth, cell motility, and tumor sphere formation in vitro. The results from this study demonstrate that GSCs possess unique epigenetic signatures that may play important roles in the pathogenesis of GBM.

关键词： Glioblastoma Cancer stem cells dNA methylation SPINT2

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Machine learning assisted derivation of minimal low-energy models for metallic magnets

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npj Computational Materials 2023年第1期9卷 353-364页

作者： Vikram Sharma Zhentao Wang Cristian d.Batista department of Physics and Astronomy The University of TennesseeKnoxvilleTN 37996USA School of Physics and Astronomy University of MinnesotaMinneapolisMN 55455USA Quantum Condensed Matter division and shull-Wollan Center Oak Ridge National LaboratoryOak RidgeTN 37831USA Present address:Center for Correlated Matter and School of Physics Zhejiang UniversityHangzhou 310058China

We consider the problem of extracting a low-energy spin Hamiltonian from a triangular Kondo Lattice Model(KLM).The non-analytic dependence of the effective spin-spin interactions on the Kondo exchange excludes the use of perturbation theory beyond the second *** then introduce a Machine Learning(ML)assisted protocol to extract effective two-and four-spin *** resulting spin model reproduces the phase diagram of the original KLM as a function of magnetic field and single-ion anisotropy and reveals the effective four-spin interactions that stabilize the field-induced skyrmion crystal ***,this model enables the computation of static and dynamical properties with a much lower numerical cost relative to the original KLM.A comparison of the dynamical spin structure factor in the fully polarized phase computed with both models reveals a good agreement for the magnon dispersion even though this information was not included in the training data set.

关键词： Kondo dynamical derivation

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