The process parameters optimization in laser powder bed fusion (LPBF) technique have been studied extensively by using the volumetric energy input (E=P/(v.t.h)) equation, which includes the major build parameters; laser power (P), scan speed (v), layer thickness (t) and hatch spacing (h) [1-3]. Even though utilizing laser energy density to predict final properties of a specified materials is a good way to start, only considering this is not enough [4]. Researchers have generally focused on the effect of laser power and scan speed on the final properties [5-8]. This study indicates how major process parameters influence the physical and magnetic properties of LPBF-processed Fe-based amorphous/nanocrystalline composites ((Fe87.38Si6.85B2.54Cr2.46C0.77 (mass%)). The figure illustrates the magnetization (M)-magnetic field (H) loops corresponding sample microstructures fabricated by using same E (=60 J/mm3) and v (=1000 mm/s) and varying P, h and t (left corner). It is obvious that despite being printed with same energy density, changing h and t (Sample 1 and 2) or changing P and h (Sample 2, 3 and 4) led to the quite different results. It was found that bulk density improves as P increases, v, t and h decreases, i.e., high E is necessary, however, greater than 80 J/mm3 (due to the keyhole effect) and less than 45 J/mm3 (because of the insufficient energy input to the powder bed) causes either failing parts or large and high number of pores. Owing to the laser scanning nature, the microstructure evolves as molten pool (MP) and heat affected zones (HAZ) due to the high thermal gradient occurred between laser tracks [9]. MP form around the scans, having Fe2B nanograins mainly, whereas HAZ generally contains α-Fe(Si) and Fe3Si nanocrystalline clusters. The sizes and quantities of those nanocrystallites determine the magnetic properties. With same E (60 J/mm3), v (1000 mm/s) and t (50 µm), only changing P and h caused samples to have different saturation magnetization; 206 emu/gr (P: 90 W and h: 30 µm) and 150 emu/gr (P: 150 W and h: 50 µm) (Figure). 
**References:** [1] H. Gong, K. Rafi and H. Gu, Materials and Design, Vol. 86, p. 545-554 (2015). 
[2] S. Liu, H. Li and C. Qin, Materials and Design, Vol. 191, ID: 108642 (2020). 
[3] H. Gong, K. Rafi and H. Gu, Additive Manufacturing, Vol. 1, p. 87-98 (2014). 
[4] K. Prashanth, S. Scudino and T. Maity, Materials Research Letters, Vol. 5, p. 386-390 (2017). 
[5] S. Alleg, R. Drablia and N. Fenineche, Journal of Superconductivity and Novel Magnetism, Vol. 31, p. 3565-3577 (2018). 
[6] H. Jung, S. Choi and K. Prashanth, Materials and Design, Vol. 86, p. 703-708 (2015). 
[7] Y. Nam, B. Koo and M. Chang, Materials Letters, Vol. 261, ID: 127068 (2020). 
[8] D. Ouyang, W. Xing and N. Li, Additive Manufacturing, Vol. 23, p. 246-252 (2018). 
[9] C. Zhang, D. Ouyang and S. Pauly, Material Science and Engineering R, Vol. 145, ID: 100625 (2021). 

![](https://s3.eu-west-1.amazonaws.com/underline.prod/uploads/markdown_image/1/image/8a303fbd2fb2b87b8ef323cee9b2c17f.png) 
Figure: M-H loops and micrographs of the samples LPBF-processed with same E (=60 J/mm3) and v (=1000 mm/s).

Optimizing Laser Additive Manufacturing for Fe based Amorphous Magnetostrictive Materials

The high cost of CoFe alloys has prevented their widespread use regardless of their promising properties: high magnetisation, high Curie temperature, as soft magnetic materials for high temperature applications. Our research has shown that the additional of AlMn can be used to create CoFeMnAl alloys, which have reduced Co content but similar saturation magnetisation as CoFe alloys, therefore providing a more economical alternative to pure CoFe soft magnets. The research studied how the addition of Al to CoFeMn0.5 changed the alloy phases and hence the magnetic properties. The CoFeMn0.5Alx alloys (0 < x <0.75) were fabricated using arc-melting, and characterised using X-ray diffraction (phases present), scanning electron microscope (composition) and SQUID magnetometry (magnetic properties as a function of magnetic field and temperature). It was found that for Al content of x < 0.2, there existed mixed FCC and BCC phases, while with further addition of Al, the BCC phase was stabilised (Figure 1a.). This lead to an increase in the saturation magnetisation and a decrease in the coercive field (Figure 1b). The alloy CoFeMn0.5Al0.25 was determined to have a competitive saturation magnetisation compared to CoFe, but with the reduction of Co concentration in the alloy should also be cheaper to produce. 
**References:** 

![](https://s3.eu-west-1.amazonaws.com/underline.prod/uploads/markdown_image/1/image/e63d51817e925cf4cb35b336e4ed1f51.png) 
Figure 1a. XRD of the CoFeMn0.5Alx alloys. 1b Saturation magnetisation and coercive field as a function of Al concentration.

CoFeMn0.5Alx: High magnetization CoFe based soft alloys with reduced Co content

Reservoir computing (RC) is a machine learning paradigm where computational power is obtained from the intrinsic memory and nonlinearity of a dynamic system. Traditionally, the dynamic system is provided by a recurrent neural network, though many recent studies show this network can be substituted with a physical system. Within the field of magnetism, many systems have been proposed as candidates for RC, such as magnetic tunnel junctions (MTJs) [1], skyrmion textures [2], superparamagnetic arrays [3], and even single domain walls [4]. However, aside from MTJs, few of these proposed systems have been experimentally realised. Recently, we showed that single-layer arrays of interconnected permalloy nanorings exhibit emergent domain wall dynamics suitable for computation [5]. Here, we demonstrate RC in materio using a device containing the aforementioned arrays. Data is encoded to the array by modulating the amplitude of a rotating magnetic field. Using two-point resistance measurements, we show that we can extract information on the state of the array through anisotropic magnetoresistance (AMR). These measurements exhibit nonlinearities between applied field and the measured magnetic state of the system, as well as hysteretic memory. Next, we show how we can control the system’s dynamics through scaling of the applied magnetic field, allowing a range of different transfer functions between input and measured magnetic state. These different transfer functions can be exploited to provide improved computational performance on signal, speech, and writing processing tasks. Through optimised scaling of the applied fields, the different computational demands of each task are met on a single device. We believe that the computational versatility, relative simplicity of manufacture, as well as the wide range of available parameter space to further explore makes the ring arrays an exciting platform for neuromorphic computation.

![](https://assets.underline.io/uploads/markdown_image/1/image/2dd48ac941e88dbd5d2d7ca08ddcf6a4.jpg)

Measured AMR response for 4 rotations of 30 Oe applied field, followed by 4 rotations of 20 Oe applied field, showing both nonlinear and hysteretic behaviour.

![](https://assets.underline.io/uploads/markdown_image/1/image/7848690af170509ddac1fd479d8a859f.jpg)

Micrograph of patterned nanoring array and electric contacts taken from RAITH Voyager electron beam lithography system.

Experimental Demonstration of Reservoir Computation using Emergent Domain Wall Dynamics in a Patterned Magnetic Substrate

The aerospace industry has become increasingly reliant on carbon fibre composite (CFC) as a structural component in aircraft, due to its strength to weight ratio. One of the disadvantages of CFC are their vulnerability to impact damage and external environment changes during flight, which causes barely visible damage to the structure. One solution to this is structural health monitoring (SHM), which monitors the composite structure to provide early detection for damage. Previous work has found that magnetostrictive ribbons [1] and inkjet printed copper coils used as actuator-sensor pairs have good resolution to detect damage to CFC [2]. This research has focused on inkjet printing magnetic sensors, which can be directly attached to the surface of the composite. JetLab IV (by MicroFab) with piezoelectric print head (60um diameter orifice) was used. The sensor designs were printed using Magnetite (20% in DMF, IPA and water) and nickel (2% in NMP and water) nanoparticle dispersion inks, manufactured by Nanoshel LLC on photo paper (25x25mm) (fig 1). A MPMS3-SQUID magnetometer was used to characterise the ink’s magnetisation (fig 2). Magnetite and nickel has saturation magnetisation values of 78 and 27 emu/g respectively. Different designs and printer parameters were explored and their magnetic performance evaluated the magnetic performance of the printed designs using simple mechanical testing such as 3-point bending test and impact testing.

![](https://assets.underline.io/uploads/markdown_image/1/image/93225e2ded45120b9d7b64a6504b9660.jpg)

Fig 1. Magnetite printed design on photo paper

![](https://assets.underline.io/uploads/markdown_image/1/image/b678abbf59eac3de5f65db1d82d9bf3b.jpg)

Fig.2 Hysteresis loop of magnetite and nickel ink

Printing magnetostrictive materials for structural health monitoring of carbon fibre composite

The aerospace industry has become increasingly reliant on carbon fibre composite (CFC) as a structural component in aircraft, due to his strength to weight ratio. One of the disadvantages of CFC are their vulnerability to impact damage and external environment changes during flight, which causes barely visible damage to the structure. One solution to this is structural health monitoring (SHM), which monitors the composite structure to provide early detection for damage. Previous work has found that magnetostriction ribbons used as sensors have good resolution to detect damage but are time consuming to attach to the composite surface [1]. To solve this issue, research has focused on additive layer manufacturing to produce 3D printed sensors, which can be directly attached to the surface of the composite. To evaluate the magnetic performance of the 3D printed sensors, this project focused on the design and development of 3D printed magnetostrictive materials using computer simulations in parallel with experimental research to measure the magnetic and mechanical performance. The design of the magnetostrictive sensors was simulated using COMSOL multiphysics, to determine how design parameters such as thickness, track length and gap changed the magnetic response with and without applied force. A desktop bound metal deposition printer at the Royce Translational Centre, was then used to print the metal with a polymer binder (polypropylene) to create the chosen 3D structures (Fig 1). The magnetic material chosen for this work was stainless steel 17/4ph. The initial work assessed the current performance of the printer at each stage. The designed structure goes through two stages of printing and heat treatment processes. The development of the feedstock to the heat treated structure could affect the final performance of the magnetostrictive material. For example, after printing the printed part (green body) goes through a debinder and a sintering stage which ultimately changes the microstructure and allows grain growth, which could affect the saturation magnetisation magnitude and direction. Using a MPMS3-SQUID magnetometer, in-plane magnetisation hysteresis loops were measured of different track lengths taken from structures at the different processing stages (green body and sintering). The results show that there is an increase in saturation magnetisation from green body to sintered sample. The sintered sample showed isotropic magnetisation within the track while the green body showed an anisotropic magnetisation. This may be due to the homogenous grain growth. To evaluate the grid design performance as a strain sensor, a weight was applied to the sintered structure and the change in magnetic flux density was measured. The COMSOL simulations were used to validate the results by using the in-built magnetostriction module. Both simulations and experimental works show comparable results (Fig 2). Demonstrating the larger the track gap the larger the response to an applied force. Future work will explore a range of printable magnetostrictive materials such as nickel and magnetite. The work will explore different designs based on COMSOL simulations including mechanical and magnetic performance. Acknowledgements: We wish to acknowledge the Henry Royce Institute for Advanced Materials, funded through EPSRC grants EP/R00661X/1, EP/S019367/1, EP/P02470X/1 and EP/P025285/1, for the financial support and the Desktop Metal Studio+ system and MPMS3-SQUID access at The University of Sheffield.

**References:**

[1] Z. Leong, W. Holmes, J. Clarke, A. Padki, S. Hayes, and N. A. Morley, IEEE Trans. Magn., 55, 7, 1–6, 2019.

**Images:**

![](https://assets.underline.io/uploads/markdown_image/1/image/623f74f02e43c68a9449a77427f35558.jpg)
Fig 1. Additive manufacture sintered samples with track gap of 1.5mm, 3mm and 5mm (left to right)

![](https://assets.underline.io/uploads/markdown_image/1/image/d026f6ebdbd80cd984b1658195b9c6b0.jpg)
Fig 2. Comparison of COMSOL model and experimental data

 Modelling magnetostrictive materials for structural health monitoring of carbon fibre composite

The typical timescale for material discovery is remarkably long, taking between 10 – 20 years to propagate through idea conception, experimentation, optimisation, and deployment1. Existing global challenges such as the climate emergency require rapid development of new materials on timescales that are incompatible with the traditional linear material discovery approach. High-throughput approaches can be applied as a parallel material discovery methodology, for which a single sample contains a library of different material compositions that can be rapidly screened for the realisation of new magnetic materials. We apply the high-throughput material discovery approach to the new class of materials known as High Entropy Alloys (HEAs). HEAs often consist of five or more constituent elements mixed in near equal quantities. The name is owed to the resulting high configurational entropy of the alloy, which contributes to suppressing the formation of intermetallic phases and stabilises simple FCC and BCC solid solutions. HEAs occupy the unexplored central regions of phase diagrams, and as such, have potential to provide disruptive materials. Already HEAs have exhibited promising soft magnetic properties such as high saturation magnetisation alongside high electrical resistivity, as well as obtaining nanocrystalline textures2,3. However, the number of constituent elements and the various chemical compositions mean HEAs can be found in a very broad parameter space making it difficult to localise the search for useful compositions. This work has used combinatorial sputtering, to fabricate sample libraries containing composition variations of up to 35 at.% on a single Silicon wafer (Figure 1a). We investigate the (CoFeNi)1-x-yAxBy series, where A and B are 3d/4d transition metals (with the addition of Si and Al). Systems studied include CoFeNiMnAl, CoFeNiMnSi, and CoFeNiMnV. We implement a program to model the composition variation across a 3” Silicon wafer with three sputter sources at different incidence angles with concurrent deposition (Figure 1b). The resulting sample library is characterised using a high-throughput magneto-optical Kerr effect (MOKE) magnetometer which has been developed to automatically map the Kerr voltage (which is proportional to the magnetic moment) and coercive field across this sample library as function of HEA composition (Figure 1c). These can then be combined to achieve magnetic property mapping within the chemical composition space (Figure 1d). Following this, XRD, SQUID magnetometry, FMR and magneto-transport are used to generate a complete structural and functional property description of selected compositions. The resulting methodology not only provides a scalable process for magnetic HEA fabrication and characterisation, but can also be paired with data driven machine learning material discovery strategies such as Materials 4.04. The large datasets necessary for machine learning are costly to procure and so far lacking in functional magnetic properties (e.g. Ms, Hc) for which these high-throughput methods could provide.

**References:**

1. Y. Liu, T. Zhao, W. Ju and S. Shi, J. Materiomics 3, 159–177 (2017). 2. Y. Zhang, T. Zuo, Y. Cheng and P. K. Liaw, Sci. Rep. 3, 1455 (2013). 3. T. Zuo et al., Acta Mater. 130, 10–18 (2017). 4. R. Jose and S. Ramakrishna, Appl. Mater. Today 10, 127–132 (2018).

**Images:**

![](https://assets.underline.io/uploads/markdown_image/1/image/646e3021d243cac1b425ee3cb6de2f04.jpg)
Schematic representation of the high-throughput thin film methodology applied to magnetic material discovery, including (a) combinatorial sputtering, (b) modelling the composition across the wafer, (c) a measured Kerr Voltage map, and (d) mapping of magnetic properties as a function of chemical composition.

 High-throughput studies of magnetic High Entropy Alloys

Alloy systems of the past tend towards single principal component alloy systems. In present research, the stoichiometry of alloy systems with large number of alloying components (&gt;4) can be adjusted to stabilise near-ideal solid solution phases (termed High-entropy alloys, HEAs due to their high configurational entropy), or to possess some mixture of ordered intermetallic phases and the near-ideal solid solution phase (termed Complex Concentrated Alloys, CCAs). HEA and CCA possess many design degree-of-freedoms. Precise control over stoichiometry and thermomechanical history lead to exciting magnetic properties; e.g. through the formation of nanocomposite microstructures [1] in CCAs can achieve good magnetic softness by allowing exchange averaging of the magnetic anisotropy. A major challenge to general application is the vast compositional design space; if ignoring stoichiometry: restricting the number of elements to 1) 3d transition metals, and 2) Si and B, there are 10C5 = 792 [RRR1] possible equimolar combinations. Millions more are possible if stoichiometry is relaxed. Appropriate strategies to filter out good candidate compositional families for study are thus essential. Alloy design can be generalised to two approaches: data-driven discovery (DDD) and functionality-driven discovery (FDD). For DDD experimental data obtained from exploratory and characterisation frameworks are extrapolated for design and prediction; in FDD search and optimisation methods are used to achieve targeted properties. Prediction models (e.g. ab-initio) are used in conjunction with FDD to determine microscopic parameters that govern material properties. FDD is useful in exploring materials with large numbers of degree-of-freedoms such as HEA/CCA systems as extrapolation from experimental data is not a good predictor of quantum mechanical behaviour (i.e. electronic structure interactions). Ab-initio models can calculate potential properties of new compositions, iterating over shedloads[RRR2] of stoichiometries using search and optimisation methods. Although computationally efficient, significant computational power is still required. Applying reasonably accurate low-fidelity pre-filters derived from quantum principles reduces the computational resources required. This work uses two such low-fidelity pre-filters using a parametric semi-empirical approach for determining the saturation magnetisation and mean Curie temperature of HEA/CCA systems. The Curie temperature can be expressed as a function alloyed system (i.e. the number of impurity atoms). At the electronic level these changes are due to 1) Variations of the local moments, and/or 2) Changes in interaction strength between moments represented by the molecular field coefficient (dependent on interatomic distances and local environment effects) [2]. Since the uniaxial pressure experienced by the valence electrons upon interatomic distance changes leads to electronic density compression [3], the rectangular band model [4] can be used to explore the onset of ferromagnetism by evaluating the bulk modulus, B with respect to the Stoner criterion. From this, the ratio B/EF (where the Fermi energy EF is approximated by the Mulliken electronegativity, XM) is used to predict the Curie temperature in HEAs and CCAs (cf. Fig. 1). The predictions are validated through synthesised as-cast HEA/CCA compositions that are characterised on a SQUID-VSM and are found to be dependent on the amount of antiferromagnetic Cr alloying in the system. The Bethe-Slater curve forms part of the early understanding of magnetism and the electronic-structure-driven magnetic ordering of 3d transition metals. Slater Rules [5] are used to evaluate the 4s:3d orbital radius ratio to reconstruct the Bethe-Slater curve (cf. Fig. 2a) using synthesised HEA/CCA compositions from literature, predictions, and our own experiments. Deviations in the 3d Bethe-Slater curve due to electronic interactions lead to curve shifts and model multiplicities, making predictions non-trivial. Orbital radius changes and valence symmetry-breaking are thus evaluated in a parametric function derived from rule-of-mixtures XM and valence electron values as a supplement to the modified Beth-Slater curve. Plotted using the same dataset, this function in Fig. 2b shows good parameterisation of MS with no model multiplicities making it suitable for design predictions. Both models show reasonable accuracies when compared to the experimental data and data from literature. One benefit of both models is that they are derived from common parameters (Bulk modulus, Mulliken electronegativity, atomic number, and d-electron count). This means that the predictive calculations can be obtained by using the rule-of-averages to determine the weighted mean of these parameters for various alloy systems. In order to further test the validity of these models, the models are used with an evolutionary algorithm to design a HEA/CCA with targeted Curie temperature and saturation magnetisation. The results of this prediction are synthesised and characterised through x-ray diffraction and SQUID-VSM and will be presented here.

**References:**

[1] N.A. Morley, B. Lim, J. Xi, A. Quintana-Nedelcos, Z. Leong, Sci. Rep., Vol. 10, 14506 (2020). [2] J.P. Gavigan, D. Givord, H.S. Li, , in: Concert. Eur. Action Magn. CEAM, p.163–173 (1989). [3] S.A. Serebrinsky, J.L. Gervasoni, J.P. Abriata, V.H. Ponce, J. Mater. Sci., Vol. 33, 167–171 (1998) [4] D.G. Pettifor, Bonding and structure of molecules and solids (1995). [5] J.C. Slater, Phys. Rev., Vol 36, p.57–64 (1930).

**Images:**

![](https://assets.underline.io/uploads/markdown_image/1/image/32b4c926a5a2171a4d869a6d4bfa2874.jpg)
Fig. 1. Plot of a dimensionless number, B/XM against the Curie temperature for experimental values as well as values taken from literature. The lines represent a guide to the eye for the various amounts of Cr addition to the composition.

![](https://assets.underline.io/uploads/markdown_image/1/image/94cdfef7de161c197ef79ff1235b2407.jpg)
Fig. 2. Saturation magnetisation plotted against the 4s:3d ratio calculated using Slater Rules. *New results presented here **Experimental results from literature, ***Simulated results from literature.

 Parametric Semi-Empirical Design of Magnetic Properties in Complex Concentrated Alloys: Curie Temperature and Saturation Magnetisation

The search for new functional magnetic materials has led to the exploration into multi-component alloys (MCAs), which contain four or more elements with percentages between 12.5 % and 33 %. These include the sub-class of high entropy alloys (HEAs) which often exhibit single phases, thought to be stabilised by the high entropy of mixing of these compounds amongst other competing thermodynamic contributions. The resulting alloys often have interesting functional properties, which are linked to their structure. This work has explored a number of different compositions (CoFeNi0.5Cr0.5Alx, CoFeNi0.5CrxAl CoFeNiCryCux) in both bulk form, to understand how the phases present in the alloys influence the magnetic properties. The work has also used semi-empirical models to predict the different phases within the compositions and machine learning has been used to predict the saturation magnetisation. For example, in bulk CoFeNi0.5Cr0.5Al it was found that Fe-Cr nanoparticles formed in a weakly magnetic CoNiAl matrix [1]. This formation of round nanoparticles increased the magnetisation of the CoFeNi0.5Cr0.5Al alloy by a factor 4 at room temperature. For all the CoFeNi0.5Cr0.5Alx samples, the coercive field was small and the saturation magnetisation comparable with NiFe. While for the bulk CoFeNi0.5CrxAl samples, nanoparticles formed in all the samples containing Cr, with the CoFeNi0.5Cr1.0Al sample having square nanoparticles. Thus the amount of Cr in CoFeNi0.5Al dominates the geometry of the FeCr nanoparticles that form. Plus encapsulating the Cr in Fe-Cr nanoparticles meant that the Curie Temperatures for all the alloys containing Cr and Al were above 300 K (Fig. 1a). While for bulk CoFeNiCryCux (x = 0.0 - 1.5 and y = 0.0 - 1.0) samples, it was found that the addition of Cu could be used to tune the Curie Temperature over a 100 K range, with less than a 30 % reduction in the saturation magnetisation at 10 K, while the addition of Cr changed the Curie Temperature by 700 K and reduced the saturation magnetisation by 60 % at 10 K. By tuning the Cu to Cr ratio it is possible to achieve a Curie temperature around room temperature. The magnetocaloric effect (MCE) was studied in these materials, as the compositions tend to involve cheaper, more widely available elements, plus careful tuning of the composition will allow for the Curie Temperature to be around 300 K. It was found that the refrigeration capacity for the CoFeNiCryCux alloys was ~ 70 J/kg and for the CoFeNi0.5Cr0.5Alx alloys was ~ 75 J/kg at 2 T (Fig. 1b) [2]. Although these are smaller than existing materials such as LaFeSi, these HEAs still have advantages due to the presence of second order transitions, and having a wider operational temperature range for the MCE. In conclusion, the MCAs studied have promising functional magnetic properties, with small coercive fields, and reasonable saturation magnetisations. The phases present can be tuned via the composition, allowing for two-magnetic phase systems to be fabricated, that improve the magnetic properties compared to a single solid solution. The research carried out is only the tip of the iceberg, but these alloys are showing encouraging results.

**References:**

[1] N. A. Morley, C. R. B. Lim, J. Xi, A. Quintana-Nedelcos, and Z. Leong, Scientific Reports, 10, 14506, (2020) [2] A. Quintana-Nedelcos, Z. Leong, and N.A. Morley, Materials Today Energy, (accepted 2021)

**Images:**

![](https://assets.underline.io/uploads/markdown_image/1/image/279780d9001aefe47b6797a2a7923640.jpg)
Figure 1a. Curie Temperature for CoFeNi0.5Cr0.5Alx, CoFeNi0.5CrxAl and CoFeNiCryCux alloys. 1b. Refrigeration capacity at 2 T for CoFeNi0.5Cr0.5Alx, CoFeNi0.5CrxAl and CoFeNiCryCux alloys. Shaded area useful temperature range.

 High Entropy Alloys: The next big thing in functional magnetic alloys

Fe-Co alloys have been ideal materials for various applications where high saturation magnetization (Ms), high permeability (µ) and low coercivity (Hc) are needed, especially for the applications where the minimization of mass and volume is a design parameter, such as aerospace industries [1-6]. In addition, their high Curie temperature makes them competitive candidates for high temperature applications [4]. In this study, in order to fully understand the compositional effect of Fe-Co alloys on their magnetic behaviour, Fe25Co75, Fe50Co50 and Fe75Co25 alloys were produced by using arc melting technique and characterized with the help of X-ray diffraction (XRD) analysis and superconducting quantum interference magnetometer (SQUID). XRD analysis indicated that all the samples were single phase (BCC), proving that oxidation did not occur during the manufacturing process. Furthermore, from their hysteresis loops, their magnetic saturations, remnant magnetizations and coercivities were found in the ranges 253-280 emu/gr, 2.06-6.15 emu/gr and 8.67-40.24 Oe, [4] respectively (Fig. 1). It was observed that as the % Co (wt.) content increases, saturation and remnant magnetization decreases, thus the Fe-rich alloys have higher magnetic properties. Also, after arc melting, stress-relief annealing was employed at 1073 K for 1 hr, resulting in reduction of the magnetic saturation (220-272 emu/gr), remnant magnetization (1.08-3.8 emu/gr) and coercivity (4.73-13.28 Oe) [5] due to the microstructural refinement, as it can be seen clearly in Fig.1. This study confirms that arc melting helps to improve the magnetic properties of Fe-Co alloys, because their magnetic properties is higher than the magnetic properties of those fabricated by mechanical alloying (Ms: 150-225 emu/gr, Hc: 25-70 Oe) [4] and cold rolling (Ms: 217.8 emu/gr, Hc: 87.7 Oe) [3]. Curie temperatures of the as-cast samples (1097-1181 K), are slightly lower than the values in the literature [5], also decreased slightly to the value range of 1071-1107 K after the heat treatment. By looking at Fig. 2, for the high temperature magnetic performances of as cast and annealed specimens, it can be seen that the annealed samples have a higher saturation magnetisation as a function of temperature. Further study has been undertaken to design and develop a new Fe-based amorphous alloy, with similar properties to Fe-Co alloys. The alloy of Fe45Co15B28Al10B2 was arc-melted followed by stress-relief annealing at 573 K for 1 hr to achieve the desired magnetic properties and amorphous morphology. Using DCS and temperature dependence magnetisation measurements up to 1000 K, the temperature dependence structural and magnetic behaviour was studied. DSC analysis indicates that the sample has glassy phase with the melting point of 1200 K and glass transition temperature of 800 K. Moreover, its Curie temperature was found as 940 K. Thus, this composition has promising results as a new soft magnetic material for high temperature applications.

**References:**

[1] S. Bergheul, A. Haddad, H. Tafat and M. Azzaz, “Magnetic , Microwave and Absorbing Properties Fe-Co of Alloy Synthesized by Mechnanical Alloying Process,” in Application of Contemporary Non-Destructive Testing in Engineering, Portoroz, Slovenia, 2005. [2] R. Fingers and G. Kozlowski, “Microstructure and magnetic properties of Fe–Co alloys,” Journal of Applied Physics, vol. 81, no. 8, pp. 4110-4111, 1997. [3] S. Honjo, S. Kikuchi, A. Sakuma, S. Ishio and J. Balachandran, “Preparation of magnetic Fe-Co alloy using texture controlled technique,” Journal of Magnetism and Magnetic Materials, vol. 465, pp. 64-69, 2018. [4] F. Sanchez-De Jesus, A. Bolarin-Miro, C. Cortes Escobedo, G. Torres-Villasenor and P. Vera-Serna, “Structural Analysis and Magnetic Properties of FeCo Alloys Obtained by Mechanical Alloying,” Journal of Metallurgy, vol. 2016, p. 8347063, 2016. [5] R. Sundar and S. Deevi, “Soft magnetic FeCo alloys: alloy development, processing, and properties,” International Materials Reviews, vol. 50, no. 3, pp. 157-192, 2005. [6] Y. Zhang, R. Ma, S. Feng, L. Cheng, P. Davies and P. Yu, “Microstructures and magnetic properties of Fe-35%Co alloy fabricated bymetal injection molding,” Journal of Magnetism and Magnetic Materials, vol. 497, p. 165982, 2020.

**Images:**

![](https://assets.underline.io/uploads/markdown_image/1/image/b10699c413116d6f4d080b35248523dd.jpg)

![](https://assets.underline.io/uploads/markdown_image/1/image/a2da2cf697ccf1f003fbfd7cb478a821.jpg)

 Heat treatment investigations of Fe-based alloys

Multi-component alloys contain more than 4 elements in percentages between 12 to 35%, this can lead to single or dual phase alloys. These dual phase alloys have been shown to have promising magnetic properties [1,2], therefore further investigation is required. Two studies were carried out on the CoFeNi0.5AlCrx alloy to investigate how the structural and magnetic properties change as a function of Cr concentration and post-synthesis heat treatment. The addition of Cr to CoFeNi0.5Al changed the alloy from single phase BCC to dual phase BCC, due to the formation of nanoparticles within a matrix (Fig 1a). The Cr also reduced the saturation magnetisation at 300K. The dual phases gave rise to 2 different magnetic phases: i. high Curie temperature (Tc) almost independent of Cr, ii. low Tc decreasing with increasing Cr (Fig 1b). For CoFeNi0.5Cr0.5Al, four post heat treatments were investigated, these were either heated at 1423K for 5 or 10hrs, then either furnace cooled or water quenched. All the samples were BCC, with the water quenched 10hrs (WQ10) and furnace cooled 5 and 10hrs (FC5 and FC10) alloys all having nanoparticles within a matrix, while the water quenched 5hrs (WQ5) alloy had no clear separation of phases. These differences were observed in the Tc, as for WQ10, FC5 and FC10 alloys there were 2 distinct transition in the M-T curves (Fig 1c), while for WQ5 the transition appear as one broad change. The magnetocaloric properties were studied for all the CoFeNi0.5AlCrx alloys. It was found that Cr decreased the change in entropy (ΔS) for both Tc (Fig 1d). For all alloys, the low Tc had a smaller ΔS compared to the high Tc but a larger refrigerant capacity due to a wider temperature transition. For CoFeNi0.5AlCr0.25, the two Tc were within 100K of each other, such that the ΔS curves overlapped giving a wider temperature range, and a refrigerant capacity of 150J/K. Thus tuning the two transitions to be &lt;100K of each other increases the refrigerant capacity.

![](https://assets.underline.io/uploads/markdown_image/1/image/585620410c5d908d21de5098c3a453fc.jpg)


Figure 1a. SEM images of CoFeNi0.5AlCrx, Magnetisation as a function of temperature at 20 kA/m for 1b. CoFeNi0.5AlCrx and 1c. CoFeNi0.5AlCr0.5 and 1d. Change in entropy as a function of Cr concentration (open shapes = low Tc, and solid shapes = high Tc)

Investigating the structural and magnetic properties of CoFeNi0.5AlCrx

JOA: Amorphous and Nanocrystalline Soft Magnets I

technical paper

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JOC: Soft Magnetic Crystalline Alloys I

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IT: Non-destructive Evaluation & Other Sensors II

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JB: Crystalline Soft Magnets

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JX: Soft Magnetic Alloys and Oxides

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Presentations

Optimizing Laser Additive Manufacturing for Fe based Amorphous Magnetostrictive Materials

CoFeMn0.5Alx: High magnetization CoFe based soft alloys with reduced Co content

Experimental Demonstration of Reservoir Computation using Emergent Domain Wall Dynamics in a Patterned Magnetic Substrate

Printing magnetostrictive materials for structural health monitoring of carbon fibre composite

Modelling magnetostrictive materials for structural health monitoring of carbon fibre composite

High-throughput studies of magnetic High Entropy Alloys

Parametric Semi-Empirical Design of Magnetic Properties in Complex Concentrated Alloys: Curie Temperature and Saturation Magnetisation

High Entropy Alloys: The next big thing in functional magnetic alloys

Heat treatment investigations of Fe-based alloys

Investigating the structural and magnetic properties of CoFeNi0.5AlCrx

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