The effects of CNTs and/or Si additions on the structure and magnetic properties of SmCo7-based alloys

Sun, Ji-Bing; Bu, Shaojing; Ding, He-Wei; Cui, Chunxiang; Yang, Wei; Zhang, Li

doi:10.1016/j.jallcom.2013.02.103

Cited by 11 publications

(4 citation statements)

References 28 publications

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“…From the abovementioned MGI database of Sm-Co materials, a data set of saturation magnetization was extracted (which is provided in Section S1 in the Supporting Information), and it contains data of 214 kinds of materials from various resources published in 40 years from 1978 to 2018. ,,,,− The information related to saturation magnetization includes the Sm-Co matrix with a certain atomic ratio ( x matrix = ( x Co + x M )/ x Sm ), doping element (denoted as “M”), doping concentration ( x doping = x M / x Co ), processing of material ( C proc ), form of the material for testing ( C form ), grain size ( d ), and so on. It is known that, for a data set, machine learning can generate a predictive model, which can be applied to design new materials.…”

Section: Resultsmentioning

confidence: 99%

“…In this respect, we spent over 10 years building up a specific database for Sm-Co systems, which contains both experimental and computational data for ∼1050 alloys published in the literature for decades, and some of them are used as references in this work. − ,,,− More importantly, we embedded in the database the related information search regarding composition, processing, microstructure, properties, and references of the material, which is unique from other material databases. The above specialized database may be considered as a “Materials Genome Initiative (MGI) , database of Sm-Co materials” according to its characteristics.…”

Section: Introductionmentioning

confidence: 99%

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Selecting Doping Elements by Data Mining for Advanced Magnets

et al. 2019

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Compared with other material performances, magnetic properties are more closely related to the electronic structure and sensitive to the material composition. To date, no unified approach has been reported to understand the complicated influence of composition on a material’s magnetic properties. As one of the two most representative permanent magnetic systems, Sm-Co-based materials have been developed in terms of composition design mainly by empirical exploration. Taking advantage of a unique home-built Materials Genome Initiative database of Sm-Co systems, this work reports a data-driven material development that aims at high saturation magnetization, along with excellent comprehensive magnetic performance. A novel method using a unified “indicator” capable of precisely evaluating effects of doping elements on saturation magnetization was developed, and the priority of possible elements was predicted by extending the screening of elements to the periodic table, from which some elements that have never been tried in magnetic materials are discovered. By this approach, a top level of saturation magnetization was achieved in a series of prepared stoichiometric Sm-Co-based alloys, which also have high coercivity and high remanence in the same system. The strategy proposed here will be applicable on doping element selections for a large variety of material property modulations.

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Section: Resultsmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

Selecting Doping Elements by Data Mining for Advanced Magnets

et al. 2019

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“…These samples exhibited excellent soft magnetic properties. As is well known, the saturation magnetization (M s ) is insensitive to the microstructure and mainly could be determined by the chemical composition and crystal structure [12]. Hysteresis loops indicate that by adding CNTs, the M s decreased from 52.4 emu/g for Ni to 45.1 and 30.7 emu/ g for Ni-10%CNTs and Ni-30%CNTs, respectively.…”

Section: Resultsmentioning

confidence: 99%

“…Hysteresis loops indicate that by adding CNTs, the M s decreased from 52.4 emu/g for Ni to 45.1 and 30.7 emu/ g for Ni-10%CNTs and Ni-30%CNTs, respectively. Ni is a ferromagnetic material and the ferromagnetism of CNTs is an open subject and it is reported that CNTs can display weak ferromagnetism [12]. The M s of the nanocomposites decreased with the increase of CNTs amounts.…”

Section: Resultsmentioning

confidence: 99%

Characterization of Ni-CNTs Nanocomposites Produced by Mechanical Alloying

Gharegozloo

Abdizadeh

Ataie

2013

AMR

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The interest in using CNTs as the reinforcement of metal matrix nanocomposites has been growing considerably due to their enhanced properties. In the present work, nickel was reinforced by carbon nanotubes (CNTs) via high energy mechanical milling method. The effects of various amounts of CNTs (5%, 10%, 20% and 30%) and different milling times (1, 5, 10 and 15 hours) were investigated. X-ray diffraction (XRD), field emission scanning electron microscopy (FESEM) and vibrating sample magnetometer (VSM) analysis were used for evaluation of phase composition, morphology and magnetic properties of the samples, respectively. The results showed a homogeneous dispersion of CNTs into the nickel matrix phase by mechanical milling. It was observed that the increase in the milling time, for a particular amount of CNTs, caused a decrease of mean crystallite size from 56 nm to 35 nm. The increase of CNTs amount also resulted in the powder particle refinement. VSM analysis showed that with the increase of CNTs from 0% to 30%, the magnetization of the samples decreases from 52.36 to 30.74 emu/g, and the coercivity of the nanocomposites increases from 61.45 to 114 Oe.

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