Selection Of Magnetic Materials Research Articles

Magnetic Technologies and Green Solvents in Extraction and Separation of Bioactive Molecules Together with Biochemical Objects: Current Opportunities and Challenges

Currently, magnetic technology and green solvents are widely used in chemical engineering, environmental engineering and other fields as they are environmentally friendly, easy to operate and highly efficient. Moreover, a magnetic field has positive effect on many physicochemical processes. However, related new methods, materials, strategies and applications in separation science still need to be developed. In this review, a series of meaningful explorations of magnetic technologies for the separation of natural products and biologic objects, including magnetic ionic liquids and other magnetic solvents and fluids, magnetic nanoparticles and magnetic fields, and the development of magnetic separators were reviewed. Furthermore, the difficulties in the application and development of magnetic separation technology were discussed on the basis of comparison and data analysis, especially for the selection of magnetic materials and magnetic field sources. Finally, the progress in the development of magnetic separators was also elaborated for researchers, mainly including that of the new high-efficiency magnetic separator through multi-technology integration and the optimization of traditional magnetic separators, which help current techniques break through their bottleneck as a powerful driving force.

Comprehensive comparison and selection of magnetic materials for powertrain DC–DC converters

In power powertrain, DC–DC converters, the selection of suitable magnetic core materials is a critical design consideration. It ensures weight and volume reduction and performance enhancement of such types of converters. This study provides a comprehensive comparison of magnetic core materials and a simplified cobweb chart that aids in the initial selection of magnetic core materials for powertrain DC–DC converters. The weighted property method (WPM) is used to systematically select and rank the suitability of the magnetic core materials, and a multi-attribute decision-making analytical hierarchy processes is used to calculate the relative weight of different properties. Based on the peculiar requirements of powertrain DC–DC converters, the most suitable magnetic core materials are identified and ranked with the help of the cobweb chart and the WPM. This study aims at providing a quick reference for designers to ease the selection of suitable magnetic core material for powertrain DC–DC converters.

Evaluation of magnetic chitosan beads for adsorption of heavy metal ions

Although many magnetic chitosan materials have been prepared for adsorption of metal ions, there is no standard method for comprehensive evaluation of material performance. The common practice simply compares either adsorption capacity (Q) or saturation magnetization (Ms) of interested materials; however, these two important parameters often work in opposite way. This study aims to establish two methods for evaluation of the overall performance of magnetic materials. The proposed methods consider both heavy metal ion adsorption capacity and magnetic recovery of the material after use. The first method introduces adsorption recovery index (ARI, ARI=Qt), which is calculated using Q and recovery time (t) needed for achieving 98% material recovery. Higher ARI value shows better performance of a magnetic material. The second method uses effort-vector data visualization, in which the position of a magnetic material is shown on a coordinate depicted using normalized Q and Ms value. The distance of the data point to the target (ideal Q and Ms value) indicates the performance of the material. The shorter the distance, the better the overall performance is. Two series of MCBs with different Fe3O4 chitosan mass ratios were prepared by using embedding method and chemical co-precipitation method respectively. They were used as model compounds for investigation of the feasibility of the proposed evaluation methods through adsorption of various metal ions (Ag+, Cu2+, Hg2+, Cr3+ and Cr6+) and MCBs recovery test. The best performers were able to be identified by using both methods and the results agreed with each other. Compared with ARI, the effort-vector data visualization was more straightforward and easier to use. This method was successfully applied to evaluate a wide selection of magnetic materials, including those prepared in this work and reported from literatures, for their overall performance.

New approach to select materials using MADM tools

Revolutionary attitude of researchers to invent and develop decision-making support tools has been increased for years. Effective methods and models are created to fulfil experts, engineers and managers skill for better and distinct solution. This paper proposes two new multi-attribute decisionmaking methods to indicate applicability and performance of them in area of design and material. Factor relationship (FARE) is introduced for first time in material evaluation field to elaborate weights of material criteria. This method resolves the problem of pairwise comparison judgement which naturally happens for decision makers and addresses more accurate rate of decision criteria. In order to assess materials and sort them according their performance and technical properties, weighted aggregated sum product assessment (WASPAS) method is acquired. The proposed approach is applied in hard magnetic material selection. In the final part of the paper, some tests (e.g., using normalisation tool and correlation coefficient) are handled to conform and validate obtained results.

New approach to select materials using MADM tools

Revolutionary attitude of researchers to invent and develop decision-making support tools has been increased for years. Effective methods and models are created to fulfil experts, engineers and managers skill for better and distinct solution. This paper proposes two new multi-attribute decisionmaking methods to indicate applicability and performance of them in area of design and material. Factor relationship (FARE) is introduced for first time in material evaluation field to elaborate weights of material criteria. This method resolves the problem of pairwise comparison judgement which naturally happens for decision makers and addresses more accurate rate of decision criteria. In order to assess materials and sort them according their performance and technical properties, weighted aggregated sum product assessment (WASPAS) method is acquired. The proposed approach is applied in hard magnetic material selection. In the final part of the paper, some tests (e.g., using normalisation tool and correlation coefficient) are handled to conform and validate obtained results.

New magnetic rails with double-layer Halbach structure by employing NdFeB and ferrite magnets for HTS maglev

In the high temperature superconducting (HTS) maglev system, the magnetic rail as an essential infrastructure is needed all along the route to carry passengers and goods to the destinations. Thus, large amount of rare earth magnetic materials are required in the magnetic rail construction. In order to decrease the dependence of magnetic rails on rare earth elements, the ferrite magnet is employed to replace part of the NdFeB magnets containing rare earth elements. Consequently, a new type rail with double-layer Halbach structure is presented, which is consisted of NdFeB and ferrite magnets. In this paper, we designed and fabricated the proposed rail, and further measured its magnetic flux density distribution and electromagnetic force interacting with HTS bulks. Experimental results indicate that, this new type rail, in double-layer Halbach structure, can achieve an equivalent distribution of magnetic flux density and levitation performance as the pure NdFeB Halbach rail, while a 10% reduction in NdFeB magnet consumption can be realized at the same time. In addition this work explores another magnetic material selection for HTS maglev applications. The dependence on rare earth element and the cost of magnetic rails can be further reduced, as the coercive force of ferrite magnets improved.

Design Methodology for High-Speed Permanent Magnet Synchronous Machines

In this paper, a design methodology for surface permanent magnet (PM) synchronous machines, with special application to the case of high-speed machines, will be presented. Following a discussion of the principle and assumptions inherent in the methodology, the analytical model used in the study will be presented. This model will then be implemented to solve the problem of maximizing the power-to-volume ratio from an analytical perspective. It will be shown how this formulation serves to establish design rules, in addition to setting criteria values for the selection of magnetic materials (i.e., silicon steel sheet versus a soft magnetic material). At last, the paper will present a data test bench made of two PM machines designed since the methodology presented herein.

Magnetic Loading of Soft Magnetic Material Selection Implications for Embedded Machines in More Electric Engines

This paper presents the analysis of different soft magnetic materials for high-speed, high-temperature applications, such as embedded electrical machines for aircraft gas turbine. The aim is to provide a comparison of their electromagnetic and thermal impacts, for varying alloy content and lamination thickness. The comparative study is carried out among different lamination material choices based on iron loss, thermal impact, and power density using a finite element analysis tool. Through this simulation study, cobalt-iron alloys appear to be the optimum choice for their combination of high thermal capability with high strength and high saturation magnetization. Furthermore, it is suggested that alloys with thin laminations will limit high iron losses.

Selection of Magnetic Materials for Bearingless High-Speed Mobile Flywheel Energy Storage Systems

Beside a higher amount of reactive power and a lower power to weight ratio compared with other machine types, the switched reluctance motor (SRM) features robustness, low cost, failure tolerance, and a wide operation temperature range. With additional power electronics and construction effort, the SRM can be operated as a bearingless drive. This is important to increase the lifetime of bearings in vacuum since their lubrication is difficult. In this paper, the technical potential of this particular motor topology to produce torque and radial force is evaluated based on finite element simulations. Additionally, the estimated hysteresis and eddy current losses during the normal and bearingless drive operation depending on the selected soft magnetic materials are evaluated.

Insights into Ultrafast Demagnetization in Pseudogap Half-Metals

A series of experiments on a judicious selection of magnetic materials using ultrafast laser pulses demonstrate successful control of spin polarization and ultrafast spin dynamics in the materials through their electronic structures.

Magnetic material selection using multiple attribute decision making approach

A large number of magnetic materials have been fabricated and found to be promising for their technological applications. However, it is difficult to select an optimal material (for technological application) because of the conflicting tradeoffs between their properties. In this context, the screening of magnetic materials is an important task. In this article, an attempt has been made to select the soft and hard magnetic materials using Multiple Attribute Decision Making (MADM) approach. VlseKriterijumska Optimizacija I Kompromisno Resenje (VIKOR) and Technique for order preference by similarity to ideal solution (TOPSIS) methods (MADM techniques) are employed to evaluate the relative ranking of these materials understudy. The relative weights for the different attributes (properties) are calculated using Shannon’s entropy method. It is found that (Supermalloy, Magnifer 7904) (79Ni–15Fe–5Mo–0.5Mn) and Ferrite 4 (sintered) (SrO–6Fe2O3) are the optimal materials among studied soft and hard magnetic materials, respectively. Hierarchical clustering is used to classify magnetic materials under study. Pearson correlation coefficients are calculated between the attributes under study.

Megaspeed Drive Systems: Pushing Beyond 1 Million r/min

The latest research in mesoscale drive systems is targeting rotational speeds toward 1 million r/min for a power range of 1-1 kW. Emerging applications for megaspeed drives (MegaNdrives) are to be found in future turbo compressor systems for fuel cells and heat pumps, generators/starters for portable nanoscale gas turbines, printed circuit board drilling and machining spindles, and electric power generation from pressurized gas flow. The selection of the machine type and the challenges involved in designing a machine for megaspeed operation such as the winding concepts, a mechanical rotor design capable of 1 000 000 r/min, the selection of magnetic materials for the stator, and the optimization concerning high-frequency losses and torque density are presented. Furthermore, a review of the advantageous inverter topologies, taking into account the extremely low stator inductance and possible high-speed bearing types such as ball bearings, air bearings, foil bearings, and magnetic bearings, are given. Finally, prototypes and experimental results originating from MegaNdrive research at Swiss Federal Institute of Technology Zurich are discussed and extreme temperature operation and power microelectricalmechanical system are identified as targets for future research.

Application of neural network algorithm to CAD of magnetic systems

Magnetic systems comprise some of the most useful devices in the world, e.g. magnets for magnetic resonance images (MRI), nuclear magnetic resonance (NMR), and linear motors and accelerators. Generally, their constituent magnetic-elements have a strongly nonlinear and finite magnetic permeability, and their magnetic materials are hard and difficult to cut, in addition to being expensive. For determination of the best shape of magnetic systems and the best selection of magnetic materials, it is useful to investigate CAD (computer-aided design) systems based on electromagnetic theory using the material relations (magnetic flux density-magnetization (B-M) curves). Our aims are to construct general CAD systems appropriate for macro- to nano-machines, but in the present paper we focus our attention on the shape design of a simple permanent magnet as an example. Our CAD system is constructed with two parts to determine (1) the self-consistent distribution of magnetization under a certain shape and (2) the best shape which gives the minimum volume. We show that in both cases a neural network algorithm (which we developed) can play a powerful role.

Selection of magnetic materials for an active magnetic regenerative refrigerator

High efficiencies of active magnetic regenerative refrigerators (AMRR) are strongly dependent on the correct selection of the magnetic regenerator working material. The selection process involves the thermodynamic analysis of the AMRR cycle to determine the adiabatic temperature change profile (ΔT versus T) over the temperature span of interest for an ideal material, and then the matching of real materials whose magnetocaloric effect (MCE) as a function of absolute temperature best fits this profile. This paper develops the calculation of the ideal magnetic material ΔT versus T profile for a real AMRR operating between 110 and 300 K and with 1 kW of cooling power. The ideal profile was a function of the constant entropy flux from the cold end heat load, the irreversible regenerator entropy production, and other real effects. To accommodate the large temperature span, several magnetic materials were chosen and layered in the regenerator from the cold to the hot end by increasing the Curie temperature. The resultant ΔT versus T curve of the combined material provided only a rough approximation of the calculated ideal material curve. To improve this approximation, physical mixing of magnetic refrigerants was investigated. This procedure diluted the magnetic moment, thereby reducing magnetic entropy available for the cycle. Further, under adiabatic conditions, mixing produced an intolerable amount of entropy during cycle execution. Simple segmentation of the regenerator with more magnetic materials that better match the ideal profile is an easier way to approximate the ideal ΔT versus T curve with real materials. Optimum segmentation will be determined by regenerator complexity.