**Alloy Development through Rapid Solidification for Soft Magnetic Application**

Rajat K. Roy, Ashis K. Panda and Amitava Mitra

Additional information is available at the end of the chapter

http://dx.doi.org/0.5772/60772

#### **Abstract**

This chapter describes different rapidly solidified processing routes of soft magnetic alloys and their properties and applications in different areas. Section-2 explains the details of process mechanism. The functions of different alloying elements are discussed with the alloy design of soft magnetic alloys in section-3. The structureproperty correlation is described in section-4. Section-5 highlights different types of rapidly solidified soft magnetic alloys, like high permeability alloys, high induction alloys, Fe-6.5 wt% Si steel and GMI alloys. In the last section-6, the applications of different types of soft magnetic alloys are mentioned.

**Keywords:** Rapid solidification, soft magnetism, alloy design, saturation induction, Fe-6.5 wt% Si steel, GMI alloys

### **1. Introduction**

In recent years, amorphous and nanostructured soft magnetic alloys have gained considerable interest owing to their superior properties. Consequently, it catered to a broad area of applications such as transformer cores, magnetic field sensors, sensors for non-destructive evaluation of materials, motors, electric vehicles, etc. The bulk use of rapidly solidified ironbased magnetic materials is in distribution transformers due to its low core loss as compared to cold rolled grain orient (CRGO) Si steel. However, the use of amorphous alloy is limited only to low power transformers as the saturation induction of such alloy is low (~1.6T) as compared to CRGO Si steel (~ 2.1T). To overcome this problem the current trend is to work on

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high induction alloy so that the materials can be used for high frequency power transformers. Beside the distribution transformer, the high permeability amorphous or nanostructured magnetic alloys are used in switched mode power supply, switchgear, etc. In nanostructured alloys or nanocomposites which typically comprise nanocrystallites dispersed in amorphous matrix, the magnetic properties are controlled by the exchange of magnetic coupling between nanocrystallites through intergranular amorphous matrix. In these nanostructured materials, the extrinsic properties like coercivity and permeability are controlled through crystallite size and their distribution, whereas the intrinsic properties, like saturation magnetic induction (BS) and Curie temperatures (TC), are the functions of alloy chemistry of amorphous and nano‐ crystallite phases. The ultimate advancement of alloys is determined by the optimization of these intrinsic and extrinsic properties. Therefore, both designing of alloy composition and processing of alloys are equivalently important for attaining the ultimate goal of applications. In this chapter, the processing of different soft magnetic alloys through rapid solidification has been discussed, and the alloys are categorized according to their properties and applications.

### **2. Rapid solidification processing routes**

#### **2.1. Melt spinning technique**

Amongst different rapid solidification processing routes, melt spinning is the most common technique for yielding soft magnetic metallic ribbons in large quantity. Sometimes this technique is also described as chill block melt spinning (CBMS). Basically, the ribbons are synthesized as the stream of molten alloy from a quartz crucible is purged through argon gas pressure on a rapidly rotating wheel made from the metals like pure Cu, Cu-Be alloy and stainless steel (Fig. 1). As shown in Fig. 1, the ribbon is typically maintaining a contact of sticking distance (dt1<dt2<dt3) with the wheel surface before flying out of the wheel surface by centrifugal force. The adhesion time of ribbon at wheel surface is important for the ribbon preparation and depends on the process parameters and alloys used. It is observed that sticking distance of Fe40Ni40B20 is less than that of Fe81.5B14.5Si4 amorphous alloy on the Cu wheel [1]. Moreover, the ribbon thickness is quite important for controlling the ribbon properties, which is basically controlled by the rotating wheel speed, ejection pressure, nozzle slot size and crucible-wheel gap.

Huang et al. described the ribbon thickness effect on the core loss and excitation for straight and toroidal samples [2]. The optimum ribbon thickness of 30 µm has been found the most suitable for low core loss as well as low excitation (Fig. 2). For thin ribbon (<30 µm), both straight and toroidal samples show similar core loss and excitation, but for thick ribbons (>30 µm), core loss and excitation in toroidal samples are higher than the other. The magnetic domain structure is also responsible for better soft magnetic properties for the ribbons having thickness 25–30 µm as in such cases magnetic domains become parallel to ribbon thickness, whereas the ribbon with lower and higher thickness than above leads to transverse domain structure.

**Figure 1.** Schematic diagram showing ribbon preparation by single roller melt spinning technique and ribbon-wheel sticking distance at adhesion times t1, t2 and t3 [1].

**Figure 2.** Ribbon thickness dependence of core loss and excitation for straight ribbons and 7.5 cm toroids, annealed at 345°C/2h, B = 1.4T [2].

#### **2.2. In-rotating water quenching technique**

high induction alloy so that the materials can be used for high frequency power transformers. Beside the distribution transformer, the high permeability amorphous or nanostructured magnetic alloys are used in switched mode power supply, switchgear, etc. In nanostructured alloys or nanocomposites which typically comprise nanocrystallites dispersed in amorphous matrix, the magnetic properties are controlled by the exchange of magnetic coupling between nanocrystallites through intergranular amorphous matrix. In these nanostructured materials, the extrinsic properties like coercivity and permeability are controlled through crystallite size and their distribution, whereas the intrinsic properties, like saturation magnetic induction (BS) and Curie temperatures (TC), are the functions of alloy chemistry of amorphous and nano‐ crystallite phases. The ultimate advancement of alloys is determined by the optimization of these intrinsic and extrinsic properties. Therefore, both designing of alloy composition and processing of alloys are equivalently important for attaining the ultimate goal of applications. In this chapter, the processing of different soft magnetic alloys through rapid solidification has been discussed, and the alloys are categorized according to their properties and applications.

Amongst different rapid solidification processing routes, melt spinning is the most common technique for yielding soft magnetic metallic ribbons in large quantity. Sometimes this technique is also described as chill block melt spinning (CBMS). Basically, the ribbons are synthesized as the stream of molten alloy from a quartz crucible is purged through argon gas pressure on a rapidly rotating wheel made from the metals like pure Cu, Cu-Be alloy and stainless steel (Fig. 1). As shown in Fig. 1, the ribbon is typically maintaining a contact of sticking distance (dt1<dt2<dt3) with the wheel surface before flying out of the wheel surface by centrifugal force. The adhesion time of ribbon at wheel surface is important for the ribbon preparation and depends on the process parameters and alloys used. It is observed that sticking distance of Fe40Ni40B20 is less than that of Fe81.5B14.5Si4 amorphous alloy on the Cu wheel [1]. Moreover, the ribbon thickness is quite important for controlling the ribbon properties, which is basically controlled by the rotating wheel speed, ejection pressure, nozzle slot size and

Huang et al. described the ribbon thickness effect on the core loss and excitation for straight and toroidal samples [2]. The optimum ribbon thickness of 30 µm has been found the most suitable for low core loss as well as low excitation (Fig. 2). For thin ribbon (<30 µm), both straight and toroidal samples show similar core loss and excitation, but for thick ribbons (>30 µm), core loss and excitation in toroidal samples are higher than the other. The magnetic domain structure is also responsible for better soft magnetic properties for the ribbons having thickness 25–30 µm as in such cases magnetic domains become parallel to ribbon thickness, whereas the ribbon with lower and higher thickness than above leads to transverse domain

**2. Rapid solidification processing routes**

40 New Trends in Alloy Development, Characterization and Application

**2.1. Melt spinning technique**

crucible-wheel gap.

structure.

Another way of preparing rapidly solidified materials is the processing of microwires (~100 µm diameter) by in-rotating water quenching technique. Unlike melt spinning, the amorphous wire preparation through in-rotating water quenching technique involves rapid quenching of molten material inside the water of a rotating drum (Fig. 3). This processing route involves a stable melt impingement and minimum melt stream break into water surface and suitably carried along with the water's centrifugal velocity to acquire continuous wires. Therefore, in addition to the glass forming ability of alloys, the molten jet stability prior to quenching and high stability of water surface layer are prerequisite conditions for obtaining defect-free, continuous wires. Heyder et al. has reported that a non-viscous fluid jet may break into different steps like dropping, varicose breakup, sinuous breakup and atomization during the wire processing [3] and causes the powder formation in the quenching water. The increasing jet velocity can result in the rapid jet disintegration. The ratio between melt jet velocity (Vj ) and cooling water velocity (Vw) is an important parameter to achieve straight wire. The ratio (Vj /Vw) has been found to be 0.9 for Fe75Si10B15 metallic wires [3]. However, Olofinjana et al. have reported that the optimized ratio is in the range of 1.14–1.20 for the same aforementioned alloy and 1.16–1.18 for Fe77.5Si7.5B15 alloy for continuous wire formation [4]. Therefore, a little difference in alloy composition and processing route may change the optimum ratio for achieving continuous wires. Additionally, other parameters, such as crucible nozzle to water level separation (NW), melt ejection angle (θ), casting temperature, ejection pressure and nozzle orifice diameter (ND), have similar importance in maintaining the stability of melt jet and solidification rate of the wire and, subsequently, in obtaining good quality wires [5]. The crucible of large orifice diameter (ND) tends to produce powders due to destabilized melt jet with lower jet velocity impinging into the water. In contrast, the lower limit of ND is related to higher pressure which is required to overcome the surface tension for the melt ejection. The melt jet is more likely to resist, through surface tension forces, being flattened by the dynamic pressure or drag force of the cooling water. The low melting point alloy is instantaneously solidified on ejecting the melt alloy because of the proximity of cooling water. Thus it is observed empirically that an optimal dwell time before casting is essential to avoid stream disturbance at high temperature melt and nozzle blockage at low temperature melt [5].

**Figure 3.** Schematic presentation of in-rotating-water quenching instrument (D: diameter of drum; NW: separation be‐ tween nozzle and water surface; d: depth of water level; :ejection angle of the melt) [5].

### **3. Design of alloy composition**

wire preparation through in-rotating water quenching technique involves rapid quenching of molten material inside the water of a rotating drum (Fig. 3). This processing route involves a stable melt impingement and minimum melt stream break into water surface and suitably carried along with the water's centrifugal velocity to acquire continuous wires. Therefore, in addition to the glass forming ability of alloys, the molten jet stability prior to quenching and high stability of water surface layer are prerequisite conditions for obtaining defect-free, continuous wires. Heyder et al. has reported that a non-viscous fluid jet may break into different steps like dropping, varicose breakup, sinuous breakup and atomization during the wire processing [3] and causes the powder formation in the quenching water. The increasing jet velocity can result in the rapid jet disintegration. The ratio between melt jet velocity (Vj

42 New Trends in Alloy Development, Characterization and Application

and cooling water velocity (Vw) is an important parameter to achieve straight wire. The ratio

**Figure 3.** Schematic presentation of in-rotating-water quenching instrument (D: diameter of drum; NW: separation be‐

tween nozzle and water surface; d: depth of water level; :ejection angle of the melt) [5].

/Vw) has been found to be 0.9 for Fe75Si10B15 metallic wires [3]. However, Olofinjana et al. have reported that the optimized ratio is in the range of 1.14–1.20 for the same aforementioned alloy and 1.16–1.18 for Fe77.5Si7.5B15 alloy for continuous wire formation [4]. Therefore, a little difference in alloy composition and processing route may change the optimum ratio for achieving continuous wires. Additionally, other parameters, such as crucible nozzle to water level separation (NW), melt ejection angle (θ), casting temperature, ejection pressure and nozzle orifice diameter (ND), have similar importance in maintaining the stability of melt jet and solidification rate of the wire and, subsequently, in obtaining good quality wires [5]. The crucible of large orifice diameter (ND) tends to produce powders due to destabilized melt jet with lower jet velocity impinging into the water. In contrast, the lower limit of ND is related to higher pressure which is required to overcome the surface tension for the melt ejection. The melt jet is more likely to resist, through surface tension forces, being flattened by the dynamic pressure or drag force of the cooling water. The low melting point alloy is instantaneously solidified on ejecting the melt alloy because of the proximity of cooling water. Thus it is observed empirically that an optimal dwell time before casting is essential to avoid stream disturbance at high temperature melt and nozzle blockage at low temperature melt [5].

(Vj

)

Nanostructured soft magnetic alloys are designed on the basis of refinement of grain size to tailor intrinsic and/or extrinsic magnetic properties. The intrinsic magnetic properties (mag‐ netic flux density, Curie temperature, magnetocrystalline anisotropy, magnetostrictive coefficient) are dependent on alloy chemistry, whereas extrinsic magnetic properties (coerciv‐ ity, permeability) are influenced by the microstructures. Accordingly, a nanostructured soft magnetic alloy is basically designed with one ferromagnetic and three different non-ferro‐ magnetic elements which are categorized as glass formers, grain growth inhibitors and nucleating agents, as explained schematically in Fig. 4. The stoichiometric variation between these elements lead to a competition between amorphization and crystallinity for obtaining critical ribbon thickness in glassy alloy systems like Fe-Si-B and Co-Si-B (Fig. 5) [6]. It is noteworthy to mention that smaller amount metalloids are required for achieving amorphi‐ zation and smaller thickness ribbons in Co-based system compared to Fe-based system.

**Figure 4.** Schematic diagram showing alloy design of soft magnetic alloys (circle diameter representing approximate elemental percentage in alloy).

Fig. 5 Compositional dependence of amorphization and crystallinity in (a) Fe-Si-B **Figure 5.** Compositional dependence of amorphization and crystallinity in (a) Fe-Si-B and (b) Co-Si-B systems [6].

Although the elemental composition of nanocrystalline and amorphous alloys may

vary within wide ranges, a typical chemical formula may be explained as FxMy, where F = ferromagnetic elements (e.g., Fe, Co, Ni), M = non-ferromagnetic elements (e.g., B, Si, P, Nb, Mo, Zr, Cu, etc.), x = 70–90 at% and y = 10–30 at%. According to the compositional ranges of ferromagnetic elements and consequent property developed, nanostructured alloys may be classified as FINEMET (Fe-M-Nb-Cu, where M = B, Si), NANOPERM (Fe-B-Zr-Cu) and HITPERM (Fe-Co-B-Zr-Cu). The composition and magnetic properties of these alloys are explained in Table 1. Therefore, the intrinsic magnetic properties of these alloys are basically the function of ferromagnetic elements, and the extrinsic properties depend on the non-ferromagnetic elements along with the effect of nanocrystallinity. Accordingly, there are three factors to be emphasized during alloy design which are (i) desired magnetic properties, (ii) high thermal stability and (iii) good glass forming ability. Thus, controlled chemistry of nanostructured alloys can cater to different soft magnetic applications pertaining to either ultralow coercivity or high

and (b) Co-Si-B systems [6].

permeability or high Curie temperature or high induction.

Although the elemental composition of nanocrystalline and amorphous alloys may vary within wide ranges, a typical chemical formula may be explained as FxMy, where F = ferro‐ magnetic elements (e.g., Fe, Co, Ni), M = non-ferromagnetic elements (e.g., B, Si, P, Nb, Mo, Zr, Cu, etc.), x = 70–90 at% and y = 10–30 at%. According to the compositional ranges of ferromagnetic elements and consequent property developed, nanostructured alloys may be classified as FINEMET (Fe-M-Nb-Cu, where M = B, Si), NANOPERM (Fe-B-Zr-Cu) and HITPERM (Fe-Co-B-Zr-Cu). The composition and magnetic properties of these alloys are explained in Table 1. Therefore, the intrinsic magnetic properties of these alloys are basically the function of ferromagnetic elements, and the extrinsic properties depend on the nonferromagnetic elements along with the effect of nanocrystallinity. Accordingly, there are three factors to be emphasized during alloy design which are (i) desired magnetic properties, (ii) high thermal stability and (iii) good glass forming ability. Thus, controlled chemistry of nanostructured alloys can cater to different soft magnetic applications pertaining to either ultralow coercivity or high permeability or high Curie temperature or high induction.


**Table 1.** Compositions and magnetic properties of three types of amorphous alloys [7]

### **4. Structure-property correlation**

Saturation magnetization and Curie temperature are the intrinsic magnetic properties, depending on alloy chemistry and crystal structure, whereas soft magnetic properties like coercivity and permeability are extrinsic properties, relating to nanocrystallinity of alloys and preferred arrangement of magnetic domains. The soft magnetism of any material is monitored through the coercivity (Hc) and/or permeability (µ), which are inversely related to each other. The excellent soft magnetism is achieved with the tailoring of alloy chemistry and optimizing the microstructure [7].

According to Herzer diagram [8], the relation of soft magnetism with grain size can be divided into two segments, (i) nanocrystalline and (ii) polycrystalline (Fig. 6). For large grain size (D> 0.1–1µm), such as polycrystalline alloys, the coercivity is inversely proportional to D, i.e., Hc 1/D. So, in the segment II, the soft magnetism increases towards right side. In other words, for polycrystalline alloys, the magnetic hardness of fine grained material is larger than that of coarse grained materials. For small grain size (segment-I, D<100nm), such as amorphous and nanostructured alloys, the coercivity rapidly decreases with grain size, and it follows the relation Hc D6 .

In nanostructured materials, the fine (~15 nm diameter) ferromagnetic nanocrystallites are impregnated in the amorphous matrix, and thus magnetic coupling of nanocrystallites exchanges through intergranular amorphous matrix. In other words, the grain sizes in the order of 10–15 nm lowers the magnetocrystalline anisotropy proportionally, resulting in superior soft magnetic properties [8]. Due to higher Curie temperature of nanocrystallites than that of amorphous matrix, the intergranular coupling rapidly decreases while the measuring temperature approaches Curie temperature of amorphous matrix [9]. Since the soft magnetic properties are related to intergranular exchange interaction, Curie temperature of amorphous matrix also plays a dominant role in controlling soft magnetic properties in nanocomposites. If the alloy is designed in such a way that the amorphous matrix has high Curie temperature, the alloy can be used for high temperature applications. Thus a new series of nanostructured alloy named HITPERM was developed which contain equal at% of Fe and Co along with glass former B, nucleating element Cu and the grain growth inhibitor Zr.

Although the elemental composition of nanocrystalline and amorphous alloys may vary within wide ranges, a typical chemical formula may be explained as FxMy, where F = ferro‐ magnetic elements (e.g., Fe, Co, Ni), M = non-ferromagnetic elements (e.g., B, Si, P, Nb, Mo, Zr, Cu, etc.), x = 70–90 at% and y = 10–30 at%. According to the compositional ranges of ferromagnetic elements and consequent property developed, nanostructured alloys may be classified as FINEMET (Fe-M-Nb-Cu, where M = B, Si), NANOPERM (Fe-B-Zr-Cu) and HITPERM (Fe-Co-B-Zr-Cu). The composition and magnetic properties of these alloys are explained in Table 1. Therefore, the intrinsic magnetic properties of these alloys are basically the function of ferromagnetic elements, and the extrinsic properties depend on the nonferromagnetic elements along with the effect of nanocrystallinity. Accordingly, there are three factors to be emphasized during alloy design which are (i) desired magnetic properties, (ii) high thermal stability and (iii) good glass forming ability. Thus, controlled chemistry of nanostructured alloys can cater to different soft magnetic applications pertaining to either ultralow coercivity or high permeability or high Curie temperature or high induction.

> **Saturation Magnetization (T)**

**Table 1.** Compositions and magnetic properties of three types of amorphous alloys [7]

FINEMET Fe73.5Si13.5B9Nb3Cu1 1.24 0.53 105 370 NANOPERM Fe88Zr7B4Cu1 1.64 4.5 3.4X104 770 HITPERM Fe44Co44Zr7B4Cu1 1.6-2.1 - - >965

Saturation magnetization and Curie temperature are the intrinsic magnetic properties, depending on alloy chemistry and crystal structure, whereas soft magnetic properties like coercivity and permeability are extrinsic properties, relating to nanocrystallinity of alloys and preferred arrangement of magnetic domains. The soft magnetism of any material is monitored through the coercivity (Hc) and/or permeability (µ), which are inversely related to each other. The excellent soft magnetism is achieved with the tailoring of alloy chemistry and optimizing

According to Herzer diagram [8], the relation of soft magnetism with grain size can be divided into two segments, (i) nanocrystalline and (ii) polycrystalline (Fig. 6). For large grain size (D> 0.1–1µm), such as polycrystalline alloys, the coercivity is inversely proportional to D, i.e., Hc 1/D. So, in the segment II, the soft magnetism increases towards right side. In other words, for polycrystalline alloys, the magnetic hardness of fine grained material is larger than that of coarse grained materials. For small grain size (segment-I, D<100nm), such as amorphous and nanostructured alloys, the coercivity rapidly decreases with grain size, and it follows the

**Coercivity**

**(A/m) Permeability Curie Temp. (Tc), °C**

**Alloy Name Typical Composition**

44 New Trends in Alloy Development, Characterization and Application

**4. Structure-property correlation**

the microstructure [7].

relation Hc D6

.

**Figure 6.** Relationship between coercivity and grain size in soft magnetic alloys as proposed by G.Herzer [8].

In case of HITPERM alloys, the composition variation in amorphous matrix during the nanocrystallization process is a complex function of the enrichment in B, and Nb and increase in the Co/(Fe+Co) ratio. The magnetic properties are thus correlated with nanocrystallites formation in amorphous matrix [10]. Although the Co concentration is homogeneous through‐ out the amorphous matrix and nanocrystals, Fe is relatively enriched in the amorphous matrix and expels Nb and B to the matrix during crystallization process [11]. The enrichment of matrix with Nb and B stabilizes the residual amorphous phase. Moreover, due to low diffusivity and solubility of Nb in Fe(Co) phases, Nb acts as a diffusion barrier located at the primary nanocrystal/ amorphous matrix interface. The thickness of the diffusion barrier increases with increasing Nb percentage for fixed B containing alloys. Consequently, it hinders primary nanocrystal grain growth and also restricts Fe enrichment in Fe(Co) phases, resulting into an increase in Fe content in the amorphous matrix and retaining its higher Curie temperature.

### **5. Different soft magnetic alloys and their properties**

Rapid solidification reduces the magnetocrystalline anisotropy, increases the solubility of alloying element and also produces the materials in the form of thin sheet, and hence rolling and forging process can be avoided for many brittle materials. Composition of the materials also plays a vital role in developing soft magnetic materials. A small variation in composition can change intrinsic magnetic property like magnetostriction which in turn alters the magne‐ toelastic anisotropy of the system and thus, modifies the soft magnetic behaviour of alloys. Alloy compositions have also a strong influence on the crystallization behaviour of rapidly solidified materials. This section will be discussed on the influence of alloy composition for the soft magnetic properties.

#### **5.1. High permeability alloys**

The high permeability amorphous alloys may be categorized as FINEMET type alloys with a nominal composition of Fe76.5-xSi13.5B9MxCu1 (where M = Nb, Ta, Mo, W, V, Cr and x = 0–3 at%) [12–16]. Many attempts have been made for the modifications of FINEMET alloys, as explained in Table 2. The primary crystallization onset of these alloys approximately 435–500°C, varying with alloy composition. Upon annealing within 50o above primary crystallization tempera‐ tures, the α-Fe(Si) nanocrystallites of 10–15 nm grain size are embedded in a residual amor‐ phous matrix, which may be called as nanocomposites. Annealing near or above 600°C leads to the precipitation of boride compounds (Fe2B or Fe3B) [17] which is detrimental for soft magnetism of nanostructured materials. The Curie temperature and saturation induction of α-Fe nanocrystallites are about twice than that of amorphous phase for Fe-Si-B-Nb-Cu alloys [18]. However, both magnetic properties decrease with Si percentage in Fe96-zSixBz-xNb3Cu1. Panda et al. have examined the effect of Si/B ratio on magnetic properties for high temperature annealed alloys Fe73.5Nb3Cu1Si22.5-XBX (X = 5, 9, 10, 11.25, 19) [19]. The magnetic softening has been found maximum at Si/B ratio of 1.5, that is, for the alloy Fe73.5Nb3Cu1Si13.5B9, with a coercivity of 1.56A/m and susceptibility of 1.35×105 while the alloys is annealed at 527°C. For other Si/B ratio, the magnetic softening is deteriorated before 470°C annealing. In Co added FINEMET alloys, Si has a detrimental effect on saturation magnetization due to the formation of (Fe,Co)3Si phase than that of (Fe,Co) phase in Si-free alloy, causing less localized moment between Fe and Co atoms in former alloy [20]. On the other hand, Co-based amorphous alloys with small additions of Fe reveal nearly zero λs, resulting in good soft magnetic behaviour. Their application is limited due to the fact that their saturation induction is considerably lower compared to that of Fe-based alloys [17].


**Table 2.** Thermal and magnetic properties of some FINEMET alloys

(Tx1 = Primary crystallization temperature onset, Tx2 = secondary crystallization temperature onset, Bs = saturation induction, Hc = coercivity and µ = permeability)

#### **5.2. High induction alloys**

increasing Nb percentage for fixed B containing alloys. Consequently, it hinders primary nanocrystal grain growth and also restricts Fe enrichment in Fe(Co) phases, resulting into an increase in Fe content in the amorphous matrix and retaining its higher Curie temperature.

Rapid solidification reduces the magnetocrystalline anisotropy, increases the solubility of alloying element and also produces the materials in the form of thin sheet, and hence rolling and forging process can be avoided for many brittle materials. Composition of the materials also plays a vital role in developing soft magnetic materials. A small variation in composition can change intrinsic magnetic property like magnetostriction which in turn alters the magne‐ toelastic anisotropy of the system and thus, modifies the soft magnetic behaviour of alloys. Alloy compositions have also a strong influence on the crystallization behaviour of rapidly solidified materials. This section will be discussed on the influence of alloy composition for

The high permeability amorphous alloys may be categorized as FINEMET type alloys with a nominal composition of Fe76.5-xSi13.5B9MxCu1 (where M = Nb, Ta, Mo, W, V, Cr and x = 0–3 at%) [12–16]. Many attempts have been made for the modifications of FINEMET alloys, as explained in Table 2. The primary crystallization onset of these alloys approximately 435–500°C, varying

tures, the α-Fe(Si) nanocrystallites of 10–15 nm grain size are embedded in a residual amor‐ phous matrix, which may be called as nanocomposites. Annealing near or above 600°C leads to the precipitation of boride compounds (Fe2B or Fe3B) [17] which is detrimental for soft magnetism of nanostructured materials. The Curie temperature and saturation induction of α-Fe nanocrystallites are about twice than that of amorphous phase for Fe-Si-B-Nb-Cu alloys [18]. However, both magnetic properties decrease with Si percentage in Fe96-zSixBz-xNb3Cu1. Panda et al. have examined the effect of Si/B ratio on magnetic properties for high temperature annealed alloys Fe73.5Nb3Cu1Si22.5-XBX (X = 5, 9, 10, 11.25, 19) [19]. The magnetic softening has been found maximum at Si/B ratio of 1.5, that is, for the alloy Fe73.5Nb3Cu1Si13.5B9, with a coercivity of 1.56A/m and susceptibility of 1.35×105 while the alloys is annealed at 527°C. For other Si/B ratio, the magnetic softening is deteriorated before 470°C annealing. In Co added FINEMET alloys, Si has a detrimental effect on saturation magnetization due to the formation of (Fe,Co)3Si phase than that of (Fe,Co) phase in Si-free alloy, causing less localized moment between Fe and Co atoms in former alloy [20]. On the other hand, Co-based amorphous alloys with small additions of Fe reveal nearly zero λs, resulting in good soft magnetic behaviour. Their application is limited due to the fact that their saturation induction is considerably lower

above primary crystallization tempera‐

**5. Different soft magnetic alloys and their properties**

46 New Trends in Alloy Development, Characterization and Application

the soft magnetic properties.

**5.1. High permeability alloys**

with alloy composition. Upon annealing within 50o

compared to that of Fe-based alloys [17].

In high permeability alloys, the distribution of fine nanocrystallites in amorphous precursor is a key factor for the improvement of soft magnetism. This is attributed to the presence of high (>20 at%) metalloids by replacing ferromagnetic elements, like Fe, Co, Ni, etc. As a result, alloys like FINEMET have superior soft magnetic properties, but the saturation induction of these alloys is lower than that of Si steel. To fill up this dearth, many high (>1.24T) induction alloys have been developed in recent years (Table 3).


**Table 3.** Saturation induction (Bs), coercivity (Hc) and permeability (µ) of some amorphous alloys

The design of high induction alloys may be based on Slater-Pauling curve [42], which explains the high magnetic induction achievable in Fe-Co alloys compared to either Fe- or Co- based alloys (Fig. 7). The Curie temperature is also high in these alloys than Fe-rich alloys. The crystalline alloys of Fe65-70Co35-30 exhibit maximum saturation induction and Curie temperature of 2.4T and 1000°C, respectively [39]. These values are deteriorated in amorphous or nano‐ crystalline alloys due to the additions of metalloids and other elements. However, many Febased alloys have been explored with a saturation of 1.85T rather than Fe-Co based alloys (Table 3). Although the Curie temperature of former alloys may be lower than later alloys. The minimum magnetocrystalline anisotropy is investigated at concentration of x = 0.5 for Fe1 xCox system [39]. The magnetostriction coefficient (λs) is also significant in equiatomic com‐ position of this alloy system. Since Fe is positively magnetostrictive, addition of negatively magnetostrictive Co to Fe reduces the overall magnetostriction λs of Fe80-xCoxB20 system [39]. Similarly addition of Co to Fe raises the saturation induction as depicted in Slater Pauling curve with the maximum saturation magnetization value reported for Fe70Co10B20 alloy [41].

**Figure 7.** Slater-Pauling curve of late transition elements [42].

#### **5.3. Fe-6.5 wt% Si steel**

The development of high silicon (Si) steels bears technological as well as commercial impor‐ tance not only due to their superior soft magnetic properties but also due to low cost. The 3.5 wt% Si steel has a major application in distribution transformers owing to their excellent soft magnetic properties and low core losses [43]. This material is being produced in the form of cold rolled grain oriented (CRGO) or non-grain oriented (CRNO) Si steel. Increasing Si content beyond 3.5% in iron enhances the electrical resistivity of the alloy, resulting in low eddy current component. Si also decreases the magnetostriction constant which becomes minimum at 6.5 wt%, leading to improved soft magnetic properties and low core losses [43]. However, the workability of alloy deteriorates with enhancement in Si content due to the formation of some ordered phases B2 and DO3 (see Fig. 8), coarse grains and impurities on grain boundary, etc. [44, 45]. Therefore, the fabrication of strips with high ~6.5 wt% silicon through conventional rolling process is difficult owing to inherent brittleness of the material [47]. The brittleness is due to the formation of ordered phases, coarser grains and impurities on grain boundary, etc. A breakthrough in the improvement of ductility by suppression of ordered phases may be was achieved while processing the alloy through several rapid solidification techniques like chemical vapour deposition (CVD), gas atomization, splat quenching and melt spinning [48– 50]. The products of these processes are subjected to various annealing treatments to control the grain sizes and ordered phases for achieving superior soft magnetic properties [51]. Amongst these methods, the development of 6.5 wt% Si steel ribbons by melt spinning technique has drawn an intense research interest due to its potential for production in bulk quantities demand as a high-efficiency material for magnetic components [52, 53].

The design of high induction alloys may be based on Slater-Pauling curve [42], which explains the high magnetic induction achievable in Fe-Co alloys compared to either Fe- or Co- based alloys (Fig. 7). The Curie temperature is also high in these alloys than Fe-rich alloys. The crystalline alloys of Fe65-70Co35-30 exhibit maximum saturation induction and Curie temperature of 2.4T and 1000°C, respectively [39]. These values are deteriorated in amorphous or nano‐ crystalline alloys due to the additions of metalloids and other elements. However, many Febased alloys have been explored with a saturation of 1.85T rather than Fe-Co based alloys (Table 3). Although the Curie temperature of former alloys may be lower than later alloys. The minimum magnetocrystalline anisotropy is investigated at concentration of x = 0.5 for Fe1 xCox system [39]. The magnetostriction coefficient (λs) is also significant in equiatomic com‐ position of this alloy system. Since Fe is positively magnetostrictive, addition of negatively magnetostrictive Co to Fe reduces the overall magnetostriction λs of Fe80-xCoxB20 system [39]. Similarly addition of Co to Fe raises the saturation induction as depicted in Slater Pauling curve

48 New Trends in Alloy Development, Characterization and Application

with the maximum saturation magnetization value reported for Fe70Co10B20 alloy [41].

The development of high silicon (Si) steels bears technological as well as commercial impor‐ tance not only due to their superior soft magnetic properties but also due to low cost. The 3.5

**Figure 7.** Slater-Pauling curve of late transition elements [42].

**5.3. Fe-6.5 wt% Si steel**

In the Fe-Si alloys, mainly one disordered structure A2 and two types of ordered phases, viz., B2 (FeSi type) and DO3 (Fe3Si type) structures are observed within 5.5 to 10 wt% Si contents [54]. The ordered phases B2 and DO3 are superstructures of A2. They form from A2 phase by unlike-atom pairing of first and second nearest neighbor place in BCC lattice, respectively [53]. It is observed that melt spun ribbons comprise mainly A2 disordered phases owing to the suppression of ordered phases [52]. Subsequent heat treatment can bring about second order transformation of A2 to B2 phase, as shown in the Fe-Si phase diagram (Fig. 8). However, B2 to DO3 transformation which is of first order can take place simultaneously, leading to the co-existence of both these phases [55]. The grain size becomes finer and the ductility is also improved in the rapidly solidified ribbons. Therefore, the rapid solidification route emerges as a potential technique for the fabrication of Fe-6.5 wt % Si alloys [50, 55]. During the course of annealing treatment, the ordered phases B2 and DO3 form and affect the magnetic properties.

It is reported that the as-cast 6.5 wt% Si steel ribbon shows low permeability (µm ~ 1.13×10-3) and high coercivity (Hc ~150A/m) owing to large internal stress and grain refinement caused by rapid solidification (Fig. 9) [56]. With progress of annealing, the maximum permeability continuously increases with annealing temperature and gets saturate after 800ºC. Conversely, the coercivity decreases linearly with the annealing temperature and gets the lowest value after annealing at 850ºC. Therefore, the soft magnetic properties are quite improved by controlling the distribution and size of ordered phases [58]. In this regard, the post annealing treatment has an influential effect on the morphologies of ordered phases [59].

**Figure 8.** Fe-Si Phase diagram [54]

**Figure 9.** Variation of maximum permeability and coercivity as a function of annealing temperature [57].

#### **5.4. Alloys with giant magnetoimpedance properties**

An interesting phenomenon called giant magneto-impedance (GMI) where large magnetic field dependence of electrical impedance (Z) is observed in ferromagnetic wire prepared by in-rotating water quenching technique (discussed in section-2.2). Unlike the well-known phenomena of GMR where large change in material resistance takes place upon application of magnetic field, complex impedance suffers drastic changes as a function of external magnetic field in GMI materials within the frequency range of 100 kHz to few MHz. GMI behaviour is also observed in ribbon-shaped materials, but the value in wire-shaped material exhibits much higher value. The influence of external magnetic field on the skin depth is the major cause for large change in magnetoimpedance of rapidly solidified wire. The skin depth of the materials is expressed as

$$\delta = \frac{c}{\sqrt{4\pi^2 f \sigma \mu}} \text{ /} $$

where µ is the material permeability, c is the speed of light, σ is the electrical conductivity and is frequency of the ac current used for measuring GMI voltage.

The circular permeability is a function of external magnetic field, temperature and also stress. Thus the impedance in rapidly solidified wire changes not only with the external magnetic field but also with temperature and stress. Hence, the GMI materials have potential application as field, temperature and stress sensors. Anisotropy in rapidly solidified materials is predom‐ inantly magnetoelastic in origin. Thus the value of saturation magnetostriction constant plays major roll in controlling the circular permeability and hence the skin depth. The materials with low magnetostriction constant exhibit higher response in impedance under the influence of applied magnetic field. Thus the materials should be designed in such a way that their saturation magnetostriction constant should be very low. Usually, Co-based amorphous alloys have negative magnetostriction (*λs* ~ -3×10-6), whereas Fe-based alloys have positive magne‐ tostriction value (*λs* ~ 25×10-6). An alloy with the combination of Fe and Co will provide low saturation magnetostriction and expected to be the better GMI materials.

**Figure 8.** Fe-Si Phase diagram [54]

50 New Trends in Alloy Development, Characterization and Application

**Figure 9.** Variation of maximum permeability and coercivity as a function of annealing temperature [57].

An interesting phenomenon called giant magneto-impedance (GMI) where large magnetic field dependence of electrical impedance (Z) is observed in ferromagnetic wire prepared by in-rotating water quenching technique (discussed in section-2.2). Unlike the well-known phenomena of GMR where large change in material resistance takes place upon application of magnetic field, complex impedance suffers drastic changes as a function of external

**5.4. Alloys with giant magnetoimpedance properties**

The GMI materials are characterized by GMI ratio (Z/Z) which is the normalized value of magnetoimpedance with respect to high magnetic field and expressed as:

$$\frac{\Delta Z}{Z} \text{(\%)} \text{=} \frac{Z \text{(H)} \cdot Z \text{(H}\_{\text{MAX}})}{Z \text{(H}\_{\text{MAX}})} \text{\*} 100\%$$

where Z(H) is the impedance of the material with the applied magnetic field H and Z(Hmax) is magnetic field saturating the impedance [60].

Moreover, the Fe-, Co- and FeCo-based alloys reveal different GMI properties depending on the core–shell domain structure of the wires [60]. The Fe-based microwires (e.g., Fe-Si-B) possess cylindrical domain with longitudinal magnetization and radially closure domains. Such domain patterns attribute to a large Barkhausen effect (LBE) in the wire [61]. The LBE causes a square loop in positively magnetostrictive FeSiB systems, leading to a perspective use in switching devices [62, 63]. On the other hand, the Co-based wires (e.g., Co-Si-B) have bamboo shaped circular domains in the wire outer surface, resulting in large Barkhausen effect (LBE) and axial pattern in inner core. Such differences in domain pattern in Fe-based and Cobased alloys arise due to their positive and negative magnetostriction, respectively. Garcia et

al. has reported a large GMI ratio of 1200% at 14.2 MHz for the zero magnetostrictive amor‐ phous microwire Co68Fe4.35Si12.5B15 [64]. However, other researchers have reported a lower (600%) GMI ratio for the same composition [65, 66]. Recently, the Cr addition has revealed the improvement of GMI effect as well as field sensitivity in amorphous wires with nominal composition of (Co0.5Fe0.5)78-xCrxSi8B14 (X = 0 to 12 at%), where saturation magnetostriction of the materials changes with the Cr [67]. Fig. 10 shows the change of GMI ratio with the saturation magnetostriction at driving current (Iac) = 10mA and the driving frequency 400 kHz. The variation of maximum GMI ratio (GMImax) with Cr for as-quenched and annealed wires is shown in Fig. 11. mum<\$%&?>GMI<\$%&?>ratio<\$%&?>(GMImax)<\$%&?>with<\$%&?>Cr<\$%&?>for<\$%&?>asquenched<\$%&?>and<\$%&?>annealed<\$%&?>wires<\$%&?>is<\$%&?>shown<\$%&?>in<\$%&?>Fig.<\$%&?>11.

mum<\$%&?>GMI<\$%&?>ratio<\$%&?>(GMImax)<\$%&?>with<\$%&?>Cr<\$%&?>for<\$%&?>as-

Figure 10. GMI<\$%&?>plots<\$%&?>of<\$%&?>Cr-0,<\$%&?>Cr-4,<\$%&?>Cr-7<\$%&?>for<\$%&?>asquenched<\$%&?>wires<\$%&?>showing<\$%&?>variation<\$%&?>of<\$%&?>GMI<\$%&?>ratio<\$%&?>with<\$%&?>the<\$%&?>saturation< **Figure 10.** GMI plots of Cr-0, Cr-4, Cr-7 for as-quenched wires showing variation of GMI ratio with the saturation mag‐ netostriction constant of the materials (Co0.5Fe0.5)78-xCrxSi8B14 (X = 0, 4, 7 at%) quenched<\$%&?>wires<\$%&?>showing<\$%&?>variation<\$%&?>of<\$%&?>GMI<\$%&?>ratio<\$%&?>with<\$%&?>the<\$%&?>saturation< \$%&?>magnetostriction<\$%&?>constant<\$%&?>of<\$%&?>the<\$%&?>materials<\$%&?>(Co0.5Fe0.5)78 xCrxSi8B14<\$%&?>(X<\$%&?>=<\$%&?>0<\$%&?>,<\$%&?>4,<\$%&?>7<\$%&?>at%)

xCrxSi8B14<\$%&?>(X<\$%&?>=<\$%&?>0<\$%&?>,<\$%&?>4,<\$%&?>7<\$%&?>at%)

\$%&?>magnetostriction<\$%&?>constant<\$%&?>of<\$%&?>the<\$%&?>materials<\$%&?>(Co0.5Fe0.5)78-

Figure 10. GMI<\$%&?>plots<\$%&?>of<\$%&?>Cr-0,<\$%&?>Cr-4,<\$%&?>Cr-7<\$%&?>for<\$%&?>as-

0 2 4 6 8 10 12

Cr (at %)

5)78\_xCrxSi8B14<\$%&?>(x<\$%&?>=<\$%&?>0<\$%&?>to<\$%&?>12<\$%&?>at%)<\$%&?>wires

Figure 11. Effect<\$%&?>of<\$%&?>annealing<\$%&?>on<\$%&?>GMImax<\$%&?>with<\$%&?>Cr<\$%&?>content<\$%&?>in<\$%&?>(Co0.5Fe0.

The<\$%&?>uniqueness<\$%&?>of<\$%&?>rapidly<\$%&?>solidified<\$%&?>amorphous<\$%&?>and<\$%&?>nanocrystalline <\$%&?>materials<\$%&?>is<\$%&?>that<\$%&?>the<\$%&?>structural<\$%&?>correlation<\$%&?>(grain<\$%&?>size)<\$%&? >is<\$%&?>much<\$%&?>smaller<\$%&?>than<\$%&?>the<\$%&?>ferromagnetic<\$%&?>correlation<\$%&?>length<\$%&?>( domain<\$%&?>wall<\$%&?>with)<\$%&?>[17].<\$%&?>It<\$%&?>causes<\$%&?>the<\$%&?>lowering<\$%&?>of<\$%&?>mag netocrystalline<\$%&?>anisotropy,<\$%&?>and<\$%&?>there<\$%&?>is<\$%&?>a<\$%&?>tendency<\$%&?>of<\$%&?>vanishi

The<\$%&?>uniqueness<\$%&?>of<\$%&?>rapidly<\$%&?>solidified<\$%&?>amorphous<\$%&?>and<\$%&?>nanocrystalline <\$%&?>materials<\$%&?>is<\$%&?>that<\$%&?>the<\$%&?>structural<\$%&?>correlation<\$%&?>(grain<\$%&?>size)<\$%&? >is<\$%&?>much<\$%&?>smaller<\$%&?>than<\$%&?>the<\$%&?>ferromagnetic<\$%&?>correlation<\$%&?>length<\$%&?>( domain<\$%&?>wall<\$%&?>with)<\$%&?>[17].<\$%&?>It<\$%&?>causes<\$%&?>the<\$%&?>lowering<\$%&?>of<\$%&?>mag netocrystalline<\$%&?>anisotropy,<\$%&?>and<\$%&?>there<\$%&?>is<\$%&?>a<\$%&?>tendency<\$%&?>of<\$%&?>vanishi

Figure 11. Effect<\$%&?>of<\$%&?>annealing<\$%&?>on<\$%&?>GMImax<\$%&?>with<\$%&?>Cr<\$%&?>content<\$%&?>in<\$%&?>(Co0.5Fe0. 5)78\_xCrxSi8B14<\$%&?>(x<\$%&?>=<\$%&?>0<\$%&?>to<\$%&?>12<\$%&?>at%)<\$%&?>wires **Figure 11.** Effect of annealing on GMImax with Cr content in (Co0.5Fe0.5)78\_xCrxSi8B14 (x = 0 to 12 at%) wires

80

**6. Applications**

**6. Applications**

120

GMImax Ratio (%)

160

200

### **6. Applications**

al. has reported a large GMI ratio of 1200% at 14.2 MHz for the zero magnetostrictive amor‐ phous microwire Co68Fe4.35Si12.5B15 [64]. However, other researchers have reported a lower (600%) GMI ratio for the same composition [65, 66]. Recently, the Cr addition has revealed the improvement of GMI effect as well as field sensitivity in amorphous wires with nominal composition of (Co0.5Fe0.5)78-xCrxSi8B14 (X = 0 to 12 at%), where saturation magnetostriction of the materials changes with the Cr [67]. Fig. 10 shows the change of GMI ratio with the saturation magnetostriction at driving current (Iac) = 10mA and the driving frequency 400 kHz. The variation of maximum GMI ratio (GMImax) with Cr for as-quenched and annealed wires is

mum<\$%&?>GMI<\$%&?>ratio<\$%&?>(GMImax)<\$%&?>with<\$%&?>Cr<\$%&?>for<\$%&?>as-

mum<\$%&?>GMI<\$%&?>ratio<\$%&?>(GMImax)<\$%&?>with<\$%&?>Cr<\$%&?>for<\$%&?>as-


xCrxSi8B14<\$%&?>(X<\$%&?>=<\$%&?>0<\$%&?>,<\$%&?>4,<\$%&?>7<\$%&?>at%)

**Figure 10.** GMI plots of Cr-0, Cr-4, Cr-7 for as-quenched wires showing variation of GMI ratio with the saturation mag‐

xCrxSi8B14<\$%&?>(X<\$%&?>=<\$%&?>0<\$%&?>,<\$%&?>4,<\$%&?>7<\$%&?>at%)

0 2 4 6 8 10 12

**Figure 11.** Effect of annealing on GMImax with Cr content in (Co0.5Fe0.5)78\_xCrxSi8B14 (x = 0 to 12 at%) wires

Cr (at %)

5)78\_xCrxSi8B14<\$%&?>(x<\$%&?>=<\$%&?>0<\$%&?>to<\$%&?>12<\$%&?>at%)<\$%&?>wires

Hdc (A/m)


Hdc (A/m)

Figure 10. GMI<\$%&?>plots<\$%&?>of<\$%&?>Cr-0,<\$%&?>Cr-4,<\$%&?>Cr-7<\$%&?>for<\$%&?>as-

Figure 10. GMI<\$%&?>plots<\$%&?>of<\$%&?>Cr-0,<\$%&?>Cr-4,<\$%&?>Cr-7<\$%&?>for<\$%&?>as-

\$%&?>magnetostriction<\$%&?>constant<\$%&?>of<\$%&?>the<\$%&?>materials<\$%&?>(Co0.5Fe0.5)78-

\$%&?>magnetostriction<\$%&?>constant<\$%&?>of<\$%&?>the<\$%&?>materials<\$%&?>(Co0.5Fe0.5)78-

As-quenched

As-quenched

0 2 4 6 8 10 12

Cr (at %)

5)78\_xCrxSi8B14<\$%&?>(x<\$%&?>=<\$%&?>0<\$%&?>to<\$%&?>12<\$%&?>at%)<\$%&?>wires

Annealed : 725K/15 min.

Annealed : 725K/15 min.

0

netostriction constant of the materials (Co0.5Fe0.5)78-xCrxSi8B14 (X = 0, 4, 7 at%)

80

**6. Applications**

120

GMImax Ratio (%)

160

200

0

25

50

75

GMI Ratio (%)

100

125

150

80

**6. Applications**

120

GMImax Ratio (%)

160

200

25

50

75

GMI Ratio (%)

100

125

150

52 New Trends in Alloy Development, Characterization and Application

As-quenched wire Frequency : 400 kHz Drving current: 10 mA

As-quenched wire Frequency : 400 kHz Drving current: 10 mA

quenched<\$%&?>and<\$%&?>annealed<\$%&?>wires<\$%&?>is<\$%&?>shown<\$%&?>in<\$%&?>Fig.<\$%&?>11.

quenched<\$%&?>and<\$%&?>annealed<\$%&?>wires<\$%&?>is<\$%&?>shown<\$%&?>in<\$%&?>Fig.<\$%&?>11.

 s

 s <sup>=</sup> <sup>8</sup> . <sup>5</sup> <sup>x</sup> <sup>1</sup> <sup>0</sup>-6

 s

 s <sup>=</sup> <sup>5</sup> . <sup>2</sup> <sup>x</sup> <sup>1</sup> <sup>0</sup>-6

 s

> s

> > <sup>=</sup> <sup>8</sup> . <sup>5</sup> <sup>x</sup> <sup>1</sup> <sup>0</sup>-6

quenched<\$%&?>wires<\$%&?>showing<\$%&?>variation<\$%&?>of<\$%&?>GMI<\$%&?>ratio<\$%&?>with<\$%&?>the<\$%&?>saturation<

quenched<\$%&?>wires<\$%&?>showing<\$%&?>variation<\$%&?>of<\$%&?>GMI<\$%&?>ratio<\$%&?>with<\$%&?>the<\$%&?>saturation<

Figure 11. Effect<\$%&?>of<\$%&?>annealing<\$%&?>on<\$%&?>GMImax<\$%&?>with<\$%&?>Cr<\$%&?>content<\$%&?>in<\$%&?>(Co0.5Fe0.

Figure 11. Effect<\$%&?>of<\$%&?>annealing<\$%&?>on<\$%&?>GMImax<\$%&?>with<\$%&?>Cr<\$%&?>content<\$%&?>in<\$%&?>(Co0.5Fe0.

The<\$%&?>uniqueness<\$%&?>of<\$%&?>rapidly<\$%&?>solidified<\$%&?>amorphous<\$%&?>and<\$%&?>nanocrystalline <\$%&?>materials<\$%&?>is<\$%&?>that<\$%&?>the<\$%&?>structural<\$%&?>correlation<\$%&?>(grain<\$%&?>size)<\$%&? >is<\$%&?>much<\$%&?>smaller<\$%&?>than<\$%&?>the<\$%&?>ferromagnetic<\$%&?>correlation<\$%&?>length<\$%&?>( domain<\$%&?>wall<\$%&?>with)<\$%&?>[17].<\$%&?>It<\$%&?>causes<\$%&?>the<\$%&?>lowering<\$%&?>of<\$%&?>mag netocrystalline<\$%&?>anisotropy,<\$%&?>and<\$%&?>there<\$%&?>is<\$%&?>a<\$%&?>tendency<\$%&?>of<\$%&?>vanishi

The<\$%&?>uniqueness<\$%&?>of<\$%&?>rapidly<\$%&?>solidified<\$%&?>amorphous<\$%&?>and<\$%&?>nanocrystalline <\$%&?>materials<\$%&?>is<\$%&?>that<\$%&?>the<\$%&?>structural<\$%&?>correlation<\$%&?>(grain<\$%&?>size)<\$%&? >is<\$%&?>much<\$%&?>smaller<\$%&?>than<\$%&?>the<\$%&?>ferromagnetic<\$%&?>correlation<\$%&?>length<\$%&?>( domain<\$%&?>wall<\$%&?>with)<\$%&?>[17].<\$%&?>It<\$%&?>causes<\$%&?>the<\$%&?>lowering<\$%&?>of<\$%&?>mag netocrystalline<\$%&?>anisotropy,<\$%&?>and<\$%&?>there<\$%&?>is<\$%&?>a<\$%&?>tendency<\$%&?>of<\$%&?>vanishi

<sup>=</sup> <sup>5</sup> . <sup>2</sup> <sup>x</sup> <sup>1</sup> <sup>0</sup>-6

 Cr=0 at% Cr=2 at% Cr=4 at%

<sup>=</sup> <sup>0</sup> . <sup>9</sup> <sup>5</sup> <sup>x</sup> <sup>1</sup> <sup>0</sup>-6

 Cr=0 at% Cr=2 at% Cr=4 at%

<sup>=</sup> <sup>0</sup> . <sup>9</sup> <sup>5</sup> <sup>x</sup> <sup>1</sup> <sup>0</sup>-6

shown in Fig. 11.

The uniqueness of rapidly solidified amorphous and nanocrystalline materials is that the structural correlation (grain size) is much smaller than the ferromagnetic correlation length (domain wall with) [17]. It causes the lowering of magnetocrystalline anisotropy, and there is a tendency of vanishing magnetostriction for certain alloy compositions. As a consequence, nanocrystalline alloys achieve superior soft magnetic properties. Moreover, the improved other magnetic properties, such as higher saturation induction, Curie temperature, thermal stability of some FeCo-based amorphous and nanocrystalline alloys (HITPERM) envisage the reduction in size and weight of magnetic components, and therefore, it can be affective for the versatile applications of these alloys.

Accordingly, the nanocrystalline soft magnetic alloys may be applicable in the following field such as


The performance of magnetic choke coil made using FINEMET alloys is improved than that of Mn-Zn ferrite based choke coil [12–13]. The NANOPERM choke coil is also effective to prevent signal distortion in reactor elements of the phase modifying equipment [68]. Owing to high saturation induction, good thermal stability and low core loss, the NANOPERM alloys can also be applicable as a core material for high frequency power transformer [35]. Some FeCobased amorphous alloys (HITPERM) have a demand as core materials and winding wires for audio and radio frequency transformers in space power system [7]. These materials may also be applicable as a rotor assembly in More-Electric Aircraft Integrated Power Unit (MEA-IPU).

Beside the applications in the field of transformer, rapidly solidified materials are widely used as core materials for sensors and transducers. A wide range of magnetic sensors, such as induction sensors, fluxgate sensors (FGS), Hall Effect sensors, giant magnetoresistive sensors and superconducting quantum interference device (SQUID) gradiometers are available. A magnetic sensor directly converts the magnetic field into some measurable parameters and the field sensitivity of the sensor plays a key role in determining its operating regime and potential applications. High permeability of amorphous and nanostructured materials are rapidly replacing their crystalline counterpart to achieve better performance of the sensing device.

The GMI effect has attracted considerable scientific and technological interest especially because of its applicability in magnetic field sensing and as an additional tool to investigate soft magnetic properties of other materials, for example, ferritic steel. Magnetic sensors based upon the GMI effect offer several advantages over conventional magnetic sensors. Amorphous metallic materials cast in the form of wire having diameter of the order of 100 µm are generally used as the core of this type of magnetic sensors. These materials have their superior mechan‐ ical, electrical and magnetic properties which originate from the absence of long range order. The formation of amorphous state depends on the alloy composition as well as on the processing condition. The microwires with large and positive magnetostriction, exhibit bistable behaviour with magnetization reversal through a giant Barkhausen jump originating in the propagation of a single-domain wall. On the other hand, microwires with very low or vanishing magnetostriction show excellent GMI effect. Both the types show natural ferromag‐ netic resonance (NFMR) at microwave frequencies.

The GMI materials can be used as the magnetic field and current sensors because GMI changes as a function of external dc magnetic field or applied dc/ac currents, respectively. The sensing elements of GMI sensors are in the form of amorphous wires [69], thin films [70] or ribbons [71]. The Aichi Steel Corporation of Japan has designed and developed a variety of GMI sensors using amorphous wires for a wide range of technological applications [72]. Since GMI effect is dependent on the applied stress, it is possible to design and develop stress and magnetoe‐ lastic sensors using Co-based amorphous ribbons and wires, respectively [73, 74]. Recently, GMI sensors have been projected for structural health monitoring of industrial components [75]. Additionally, many GMI sensors have been proposed for car traffic monitoring, antitheft system, electronic compass, non-destructive crack detection, detection of ferromagnetic dust inside human body, tyre pressure monitoring system, etc. [60].

GMI phenomena attracted a great attention for the sensor applications owing to the large sensitivity of the electrical impedance to the DC magnetic field of soft magnetic conductor [76]. The ultra-high sensitivity of GMI to external dc magnetic field (down to 10-4 A/m) can be used for magnetic field sensors and other sensors based on the change of a local magnetic field.

All these novel properties make amorphous magnetic microwires very attractive for excep‐ tional technological applications, and also provide opportunities for fundamental micromag‐ netic studies mainly due to their unique magnetic domain structure. The sensitivity of GMI sensors is found to be high and have improved characteristics among the micromagnetic sensor families (Table 4) [77, 78].


**Table 4.** Micromagnetic sensor families and properties of sensor elements

Such type of magnetic field sensor can be extended for non-invasive way of monitoring the structural health of steel components which are in-service and intended to use for an extended period during which various damages can be developed such as residual stress, fatigue, creep or the formation of magnetic phase in non-magnetic steel in non-destructive way.

### **7. Conclusion**

processing condition. The microwires with large and positive magnetostriction, exhibit bistable behaviour with magnetization reversal through a giant Barkhausen jump originating in the propagation of a single-domain wall. On the other hand, microwires with very low or vanishing magnetostriction show excellent GMI effect. Both the types show natural ferromag‐

The GMI materials can be used as the magnetic field and current sensors because GMI changes as a function of external dc magnetic field or applied dc/ac currents, respectively. The sensing elements of GMI sensors are in the form of amorphous wires [69], thin films [70] or ribbons [71]. The Aichi Steel Corporation of Japan has designed and developed a variety of GMI sensors using amorphous wires for a wide range of technological applications [72]. Since GMI effect is dependent on the applied stress, it is possible to design and develop stress and magnetoe‐ lastic sensors using Co-based amorphous ribbons and wires, respectively [73, 74]. Recently, GMI sensors have been projected for structural health monitoring of industrial components [75]. Additionally, many GMI sensors have been proposed for car traffic monitoring, antitheft system, electronic compass, non-destructive crack detection, detection of ferromagnetic dust

GMI phenomena attracted a great attention for the sensor applications owing to the large sensitivity of the electrical impedance to the DC magnetic field of soft magnetic conductor [76]. The ultra-high sensitivity of GMI to external dc magnetic field (down to 10-4 A/m) can be used for magnetic field sensors and other sensors based on the change of a local magnetic field.

All these novel properties make amorphous magnetic microwires very attractive for excep‐ tional technological applications, and also provide opportunities for fundamental micromag‐ netic studies mainly due to their unique magnetic domain structure. The sensitivity of GMI sensors is found to be high and have improved characteristics among the micromagnetic sensor

**Flux gate sensor**

**Giant magnetoimpedance**

**(GMI) sensors**

coated

**(FGS)**

Ga-As Multilayer thin film Fe-Ni Amorphous wire/glass

netic resonance (NFMR) at microwave frequencies.

54 New Trends in Alloy Development, Characterization and Application

inside human body, tyre pressure monitoring system, etc. [60].

**Sensor element Hall Giant magnetoresistive**

**Table 4.** Micromagnetic sensor families and properties of sensor elements

**sensors**

Parameter Hall voltage Magnetoresistance Magnetic flux Magnetoimpedance

Frequency 0–5 kHz 0–10MHz 0 –10kHz 0.1–10MHz Head size (mm) 0.1 0.01–0.1 3–20 0.1–3 Resolution (A/m) 10-2 10-2 10-4 10-4 Sensitive axis Perpendicular Parallel Parallel Parallel Power consumption 1W 10mW 1W 10mW

0.1–2×105 10–20k 10-4–10-2 10-4–10-2

families (Table 4) [77, 78].

Materials In-Sb,

Field detection (A/m)

Rapidly solidified soft magnetic materials have been placed in special class of functional materials due to their excellent soft magnetic properties. They can be used as a transformer core or sensing element depending on composition. Due to low core loss and subsequently less heating effect, amorphous metal core transformers are slowly replacing the conventional Si steel–based distribution transformer. However, these materials are not suitable for power transformer as the saturation induction is lower than the crystalline counterpart due to the presence of non-magnetic metalloid. Extensive research is now going on to enhance the saturation induction by increasing the ferromagnetic components. The bulk production of rapidly solidified materials for transformer are mainly carried out by Hitachi Metals, Japan; Metglas, USA; Advanced Technology and Materials Co. Ltd (AT&M), China; POSCO, Korea which are the major players for large scale production of amorphous materials for transformer core where about 90 mm wide ribbons are required. Nanostructured materials are slowly replacing the core for small scale transformer like Switched Mode Power Supply (SMPS), circuit breaker and also for various types of sensor development. Nanostructured magneto‐ strictive wires are excellent element for pulse generating sensor application due to their large Barkhausen effect. Nearly zero magnetostrictive wires are excellent materials for GMI-based sensor element used for magnetic field determination.

### **Author details**

Rajat K. Roy\* , Ashis K. Panda and Amitava Mitra

\*Address all correspondence to: rajat@nmlind.org, rajatroy.k@gmail.com

MST Division, CSIR-National Metallurgical Laboratory, Jamshedpur, India

### **References**


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## **Self-Diffusion in Alloys**

Kazu-masa Yamada and Nobuaki Matsuhashi

Additional information is available at the end of the chapter

http://dx.doi.org/10.5772/60993

#### **Abstract**

It has been successfully provided that in Fe, Co, Ni, Cu, Zn, Al, Ga, Cr, and Mn, alloy has been done to obtain reliable values of diffusion coefficient particularly with Arrhenius relationship graphic plotter tool. In the presented work, the Arrhenius plots of self-diffusions and other diffusion mechanisms have been exemplified. It is an aim to summarize diffusion coefficients in Arrhenius relations that are important for physical constant values in specified materials via free-of-charge Web-based diffusion coefficient diffusion database.

**Keywords:** Diffusion coefficient, Arrhenius relation, Co, Ni, Cu, Zn, Al, Ga, Cr, Mn, Metal and alloy

### **1. Introduction**

There has been considerable important work to investigate that seems to be a reliable value of diffusion coefficient and temperature dependences of diffusivity in all around alloy and composite because it would be an essential physical constant value in specified materials and vitally useful for material development [1,2]. Particularly coefficients for self-diffusion are the most essential and have shown to be a good base element for thermal property in bulk-forming alloy. But it is difficult to measure the self-diffusivity in materials and alloys basically because the measurement is impossible other than using radioisotope tracer. In the present work, the use of a drawing tool with Arrhenius relation plots and data analysis function has been applied to determine the relations of thermal property regarding numerical activation energies and pre-exponential factors (frequency factors) and to evaluate whether it represents several Arrhenius relation platforms focusing on the developing materials [3]. Additionally, Webbased diffusion coefficient database presented the NIMS, National Institute for Materials Science, Japan, on October 10, 2014, including 8,925 diffusion data and 4,242 references which

© 2015 The Author(s). Licensee InTech. This chapter is distributed under the terms of the Creative Commons Attribution License (http://creativecommons.org/licenses/by/3.0), which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.

needed to be registered. They said that the diffusion database aims to cover all the basic diffusion data that mainly targeted metallic and inorganic materials and substantially contains information of pure metals, alloys, semiconductors, ceramics, and intermetallics [4].

The main objective of this research is to provide a diffusion data in alloys as well as a usage of Web-based diffusion database platform from all over the world to present diffusion research results and development activities in materials science. Additionally, to clarify a self-diffusion among alloys to develop for explorer thermal property using the process of plotting diffusion coefficient and temperature dependence, Arrhenius relations in alloy and composite all around the world focusing on the activation energy and pre-exponential factor discussion by using Web-based diffusion coefficient database-presented NIMS have been shown clearly in specially using freeware GP.exe plotting tool [3]. This discussion focusing on activation energy for diffusion coefficient in a relationally atomic diffusivity was able to investigate perspectives regarding discussed numerical values. Moreover, in activation energies for diffusion coeffi‐ cient within all alloys, a quantity alloy development in materials has been discussed with the use of total relationship plots in Arrhenius relations that depend on diffusion temperature.

### **2. Procedure**

Suitable for Arrhenius relation plots and data analysis, even a spreadsheet software and database relationally atomic diffusivity including the MIMS are good procedures among references of treatise for Arrhenius relation plot data and diffusion coefficients. Consequently, in the failure of searching the database, the term of an activation energy narrowing can prevent the error and be able to avoid limitation of MIMS database owing to be less than 100 results. Using freeware GP.exe plotting tool is a respectable way to discuss the activation energy and pre-exponential factor of Arrhenius relation diffusivity in alloys.

In Figure 1, the schematic diffusion coefficient tendency of 84 data alloys is related with the diffusion Web database list of MIMS, especially in Fe alloy system and with diffusant of Fe through handmade relational data-based processing by using the so-called presented work AWK-GP-PDF drawing system with GP.exe [5, 6, 7] where PDF means the Portable Document Format which the Adobe Systems Incorporated (ADBE) developed. It was found that using the AWK-GP drawing system made clear the relations between the *T*-inverse and *T*-linear value. Additionally, the *D* shows the extrapolated *D*0 strongly related among the *Q* and *T*; diffusion mechanism and thermodynamics easily show the nearly neighbored equilibrium alloy state even if it does not understand the diffusivity in objective-based alloy. The certain overall atoms in an around alloy have a rule in the tendency of this AWK-GP-PDF drawing Arrhenius plot rather than in without the extrapolated *D*0 relation. Subsequently symbol meanings are given below:

*D*: diffusion coefficient (m2 /s)

*D*0: diffusion constant (pre-exponential factor, frequency factor) (m2 /s)

*Q*: activation energy (kJ/mol), (1 eV=96.5 kJ/mol)

**Figure 1.** Schematic illustrations of Arrhenius plots for picked-up 84 data alloys between the activation energy of diffu‐ sion coefficient from 251 to 300 kJ/mol described with lower horizontal axes of temperature inversed, upper horizontal of linear temperature, left perpendicular axis of logarithm diffusion coefficient, and right perpendicular of logarithm diffusion length at time t=1 s, respectively

*R*: gas constant=8.31446 (J/mol K)

*T*: absolute temperature (K)

*t* : diffusion time (s)

needed to be registered. They said that the diffusion database aims to cover all the basic diffusion data that mainly targeted metallic and inorganic materials and substantially contains

The main objective of this research is to provide a diffusion data in alloys as well as a usage of Web-based diffusion database platform from all over the world to present diffusion research results and development activities in materials science. Additionally, to clarify a self-diffusion among alloys to develop for explorer thermal property using the process of plotting diffusion coefficient and temperature dependence, Arrhenius relations in alloy and composite all around the world focusing on the activation energy and pre-exponential factor discussion by using Web-based diffusion coefficient database-presented NIMS have been shown clearly in specially using freeware GP.exe plotting tool [3]. This discussion focusing on activation energy for diffusion coefficient in a relationally atomic diffusivity was able to investigate perspectives regarding discussed numerical values. Moreover, in activation energies for diffusion coeffi‐ cient within all alloys, a quantity alloy development in materials has been discussed with the use of total relationship plots in Arrhenius relations that depend on diffusion temperature.

Suitable for Arrhenius relation plots and data analysis, even a spreadsheet software and database relationally atomic diffusivity including the MIMS are good procedures among references of treatise for Arrhenius relation plot data and diffusion coefficients. Consequently, in the failure of searching the database, the term of an activation energy narrowing can prevent the error and be able to avoid limitation of MIMS database owing to be less than 100 results. Using freeware GP.exe plotting tool is a respectable way to discuss the activation energy and

In Figure 1, the schematic diffusion coefficient tendency of 84 data alloys is related with the diffusion Web database list of MIMS, especially in Fe alloy system and with diffusant of Fe through handmade relational data-based processing by using the so-called presented work AWK-GP-PDF drawing system with GP.exe [5, 6, 7] where PDF means the Portable Document Format which the Adobe Systems Incorporated (ADBE) developed. It was found that using the AWK-GP drawing system made clear the relations between the *T*-inverse and *T*-linear value. Additionally, the *D* shows the extrapolated *D*0 strongly related among the *Q* and *T*; diffusion mechanism and thermodynamics easily show the nearly neighbored equilibrium alloy state even if it does not understand the diffusivity in objective-based alloy. The certain overall atoms in an around alloy have a rule in the tendency of this AWK-GP-PDF drawing Arrhenius plot rather than in without the extrapolated *D*0 relation. Subsequently symbol

/s)

pre-exponential factor of Arrhenius relation diffusivity in alloys.

/s)

*Q*: activation energy (kJ/mol), (1 eV=96.5 kJ/mol)

*D*0: diffusion constant (pre-exponential factor, frequency factor) (m2

information of pure metals, alloys, semiconductors, ceramics, and intermetallics [4].

64 New Trends in Alloy Development, Characterization and Application

**2. Procedure**

meanings are given below:

*D*: diffusion coefficient (m2

And regarding Figure 1 diffusion data, in the minimum and maximum range of *T* during the diffusion process, the temperature dependence of diffusivity *D* available among references of treatise is shown below:

$$D = D\_0 \exp\left(-\frac{Q}{\mathcal{R}T}\right) \tag{1}$$

And in diffusion length [2], *L* means in general as

$$L = 2\sqrt{Dt} = 2\sqrt{D} \text{, at } t = 1 \text{s.} \tag{2}$$

In alloy development, the characteristics of the objective alloy from analysis of neighboring information of nearly alloy systems and diffusant can be predicted. Because it is difficult to obtain new experimental diffusivity, the superior study by analogy with well-known data can be modified.

It may be concluded that the AWK-GP-PDF system with NIMS diffusion database presented one of the superior level prediction processes in the world using the nearest-neighbor diffusion characteristics for user objective developing alloys.

#### **2.1. Process with AWK: An interpreted programming language**

AWK [8] which was created at Bell Labs in the 1970s is an interpreted programming language design of ASCII, abbreviated from American Standard Code for Information Interchange, for data processing and typically used as a data extraction and reporting tool. It is now presented in Unix-like operating systems, although its platform has that of Windows OS, Mac OS, and Linux OS unfluctuating on Android OS.


**Figure 2.** Schematic search tendency of 67 data alloy jointed diffusant list; relational database for alloy diffusivity using method limiter by activation energy values, e.g. material, Fe-based alloy; diffusant, Fe. Reference from NIMS database, using clipboard pasted and related with spreadsheet software, e.g., MS Excel would be highly user friendly

In Figure 2, the schematic search tendency of color-coded 67 data (only the top 21 are illustrated in Figure 2) jointed diffusant list (column 3), pre-exponential factor *D*0 (column 4), activation energy *Q* (column 5), and minimum and maximum temperature for Arrhenius relation's linear function span (columns 6 and 7), respectively. It should be rearranged in formula F1 (in Figure 2) as *D*=*D*0 exp (-*Q*/R*T*); then in MS Excel formula, "=[cell#3]\*EXP(-1\*[cell#4]\*1000/8.31429/ [cell#5]) " and "=[cell#3]\*EXP(-1\*[cell#4]\*1000/8.31429/[cell#6])," *D*min and *D*max, would be adapted, respectively.

As shown later summarized afterward AWK script make into the 3 lines of reformation CSV (comma-separated values) or space-separated value (3 lines cycled) formation for optimize into the GP.exe data format, as shown in Table 1.

The AWK, process in Figure 3, a sample AWK script for calculation and reforming suitable for GP.exe data format as filename data01.TXT is shown in Table 1. Now for adequate usage to be a reasonable AWK script, it should be named with filename ex2gp.awk and then a command line that is executable in circumstances and command as gawk –f ex2gp.awk exceldata.txt > data01.TXT should be used. For example, it is the Windows OS GNU that is a Unix-like computer operating system developed by the GNU Project tool of gawk.exe for interpreting awk script as a multi-byte version of GNU awk 3.1.5 modified for Windows OS including interactive pipe and Internet correspondence with supporting character code Shift\_JIS, EUC-JP, and UTF-8. On the other hand, in Mac OS and Linux, replacement of the only gawk name should be able to bring effect on the above command line script.

Regarding the before-mentioned "exceldata.txt," in Figure 4, a typical numerical example for copied-and-pasted text file for Arrhenius relations plots datasheet is shown. In Figure 4, [tab] means a Tab key (abbreviation of tabulator key or tabular key) on a computer keyboard. Meanwhile, on the computer screen, [tab] would be usually invisible. It is only necessary for the display of the Arrhenius relation plots of awk fields 1, 2, 3, and 4 as to be \$1, \$2, \$3, and \$4. But additionally, it would be useful for the other field of so-called code in awk \$0 that means fully one line information from the start to the end.

Additionally in Figure 5, a sample batch file script for the AWK script exaction is shown. For adequate usage to be a reasonable script, the filename should be ex2gp.bat in Windows OS. Afterthe main processing in ex2gp.bat, e.g., in the second half, a text editor Terapad.exe should be used for recognition. Other free text editors should be replaced, for example, the Emacs, etc.

### **2.2. Process with GP.exe**

It may be concluded that the AWK-GP-PDF system with NIMS diffusion database presented one of the superior level prediction processes in the world using the nearest-neighbor diffusion

AWK [8] which was created at Bell Labs in the 1970s is an interpreted programming language design of ASCII, abbreviated from American Standard Code for Information Interchange, for data processing and typically used as a data extraction and reporting tool. It is now presented in Unix-like operating systems, although its platform has that of Windows OS, Mac OS, and

**Figure 2.** Schematic search tendency of 67 data alloy jointed diffusant list; relational database for alloy diffusivity using method limiter by activation energy values, e.g. material, Fe-based alloy; diffusant, Fe. Reference from NIMS database,

In Figure 2, the schematic search tendency of color-coded 67 data (only the top 21 are illustrated in Figure 2) jointed diffusant list (column 3), pre-exponential factor *D*0 (column 4), activation energy *Q* (column 5), and minimum and maximum temperature for Arrhenius relation's linear function span (columns 6 and 7), respectively. It should be rearranged in formula F1 (in Figure

using clipboard pasted and related with spreadsheet software, e.g., MS Excel would be highly user friendly

characteristics for user objective developing alloys.

66 New Trends in Alloy Development, Characterization and Application

Linux OS unfluctuating on Android OS.

**2.1. Process with AWK: An interpreted programming language**

As AWK exploited technicalities to process the data, data01.TXT shown in Table 1 has been created. Then the next would be plotting the Arrhenius relation graph as horizontal axis of temperature *T* inverse and vertical axis of logalism diffusion coefficient *D* via diffusion mechanism for discussion infinity *T* of *D*0.

For plotting the Arrhenius relationship, the freeware in Tohoku University, by Prof. K. Edamatsu, GP.exe that was designed until 1999 to make smart graphs for publication with powerful data analysis ability such as numerical complex differentiation and comparison was used. And now it is shown that the GP.exe has been useful for genuine data processing even in the year 2015. Fortunately, GP.exe is now supported with DOS, Disk Operating System, emulator and being executed GP.exe on it. Presented tutorials show a freeware DOSBox that is DOS emulator enabled on platform of Windows OS, Mac OS, and Linux OS including Android OS. After it has been difficult in general to calculate and plot numerical *T* inverse and *D* logalism between any kinds of diffusion data and temperature, the freeware GP.exe tutorial to short-course calculation and plotting method will be provided in this session.


**Table 1.** Typical numerical example for Arrhenius relation plots and lines as the special suitable format for GP.exe as data filename data01.TXT. It is necessary for instructions to include the filename within length of 8 and 3, because of the software of legacy-type DOS. The header of 3 lines are the main title, x-axis title, and y-axis title, respectively. In addition, more than 1 blank line makes an effect of snapping regarding the continuous line of GP.exe drafting

In Figure 6, a schematic illustration of DOSBox of DOS emulator and executed GP.exe as platform on its DOSBox is shown. The left and right windows are the prompt and main frame of DOSBox emulator, respectively. GP.exe users have to add DOSBox configuration descrip‐ tions as in Figure 7 for GP.exe executable circumstances via DOSBox application menu for configurations. Additionally, GP.exe have to read firstly the initial file of INIT.GPR file as Figure 8 for easy reading the data file data01.TXT and further adding useful extra properties.

Furthermore, Figure 7 has shown the menu of "DOSBox 0.74 Options," a sample configuration script for [autoexec] area; it should be necessary to add the MOUNT and Change-Directry and then execute the GP.exe. If the user needs to use the Japanese keyboard, then the line "keyb jp" should be added and also its module. In case of English keyboard, it is not needed. In the case of GP.exe, the current directory might be C:/prog/gp/GP.exe.

### **2.3. Plot confirmation and characterization with GP.exe**

*D* logalism between any kinds of diffusion data and temperature, the freeware GP.exe tutorial

**Table 1.** Typical numerical example for Arrhenius relation plots and lines as the special suitable format for GP.exe as data filename data01.TXT. It is necessary for instructions to include the filename within length of 8 and 3, because of the software of legacy-type DOS. The header of 3 lines are the main title, x-axis title, and y-axis title, respectively. In addition, more than 1 blank line makes an effect of snapping regarding the continuous line of GP.exe drafting

In Figure 6, a schematic illustration of DOSBox of DOS emulator and executed GP.exe as platform on its DOSBox is shown. The left and right windows are the prompt and main frame of DOSBox emulator, respectively. GP.exe users have to add DOSBox configuration descrip‐ tions as in Figure 7 for GP.exe executable circumstances via DOSBox application menu for configurations. Additionally, GP.exe have to read firstly the initial file of INIT.GPR file as Figure 8 for easy reading the data file data01.TXT and further adding useful extra properties.

Furthermore, Figure 7 has shown the menu of "DOSBox 0.74 Options," a sample configuration script for [autoexec] area; it should be necessary to add the MOUNT and Change-Directry and then execute the GP.exe. If the user needs to use the Japanese keyboard, then the line "keyb

to short-course calculation and plotting method will be provided in this session.

**x-axis data y-axis data**

**A title of x-axis A title of y-axis #Comment No.01 956 3.63977E-17 1041 4.94613E-16 #Comment No.02 956 8.45635E-18 1041 1.59639E-16 #Comment No.03 800 8.75231E-22 992 2.53967E-18 #Comment No.04 1386 2.67551E-15 1528 2.07494E-14**

⋅ ⋅ ⋅ ⋅ ⋅ ⋅ ⋅ ⋅

**A main title of presented Graph**

68 New Trends in Alloy Development, Characterization and Application

If the cases that the [autoexec] area execution might be started, or in DOSBox command line "gp" followed "enter" key in to the graph plot tool GP.exe start, it would be started GP.exe opening. In Figure 8, the standard INIT.GPR file for GP.exe was shown, and one point modified description included as colored red and underlined "\*.TXT". For example, if the user needs to use a "data01.TXT" in the presented case, the user firstly should change from "\*.xy" to "\*.TXT" in the [Path and Directories] DataPath of INIT.GPR that is a good way to easy mounting data such as "data01.TXT".

Meanwhile, in Figure 9, Arrhenius relationship plot profile file is shown in detail, and descriptions of Figure 9 are explained below.

For example, on the other "data01.TXT" as shown in Table 1, 4 kinds of linear Arrhenius relations are conformed; the user can display computer graphics on graph plot tool GP.exe, finally resulting as in Figure 10 through high-resolution PostScript and PDF format.

On graph plot tool GP.exe, first of all, it is best that the user of the Arrhenius plot use not "INIT.GPR" but "ARRHEN.GPR" in the beginning as shown in Figure 9. In this figure, the use of tool extraction of freeware df.exe and schematic illustration of differences between "AR‐ RHEN.GPR" and "INIT.GPR" for executable parameters on graph plot tool GP.exe were shown. The "INIT.GPR" is completely similar as in the list in Figure 8. On the other hand, "ARRHEN.GPR" has a file of "data01.txt" that have 4 groups of data as shown in Table 1 and 4 groups of linear line in Arrhenius relationship plotting on temperature *T* inverse and legalism *D* value as shown in Figure 10.

Regarding GP.exe plot confirmation and characterization in Figure 11, GP.exe schematic illustrations for searching the plots and their points, which plots for 4 groups of linear line in Arrhenius relationship plotting on temperature inverse and legalism *D* value, are represented. That is, there are 8 edges of the right and left on the 4 linear lines. The graph plot tool GP.exe has the superior function that can show the accurate value of data as shown in Figure 11 of green-colored cross-grid. Data points from relational database for alloy diffusivity using clipboard pasted and related with spreadsheet software were concluded, and then data were delivered on GP.exe by suitable optimized processing using AWK into the GP.exe format.

### **2.4. Process with GP.exe into postscript file**

In Figure 12, schematic illustrations on the graph plot tool GP.exe, for creating the highresolution PostScript picture as shown in Figure 11, which file of 01.ps for common forms of Arrhenius plots using GP.exe. If the user wants to reproduce the similar frame of Arrhenius plots but with another diffusion data, the data should be replaced with (filename from the data01.TXT to another filename, e.g., data02.TXT) the \*.GPR graph parameter file. Meanwhile, the user can transform precisely from 01.ps to 01gw.pdf (PDF: Portable Document Format) using the freeware command line tool Ghostscript.

#### **2.5. Process with PDF graphic file**

¶(4pt)

¶(6pt)

and UTF-8

 . . . .

4 as to be \$1, \$2, \$3, and \$4

Using the freeware command line tool Ghostscript, the user can transform PS to PDF. Then the user can use another freeware, Adobe Reader or Adobe Acrobat Reader. In Figure 13, Adobe reader schematic illustrations for creating the high-resolution GIF (Graphics Inter‐ change Format) picture as all pictures shown are presented. When using those of freeware PDF reader, the user opens the PDF of 01gw.pdf, sets the magnitude to "400 %," activates "Take a Snapshot," chooses the "Select All," and finally chooses the "Copy." All through the process, the user could copy the graphic data onto the Windows OS, Mac OS, and Linux OS clipboard.

#### **2.6. Process with GIF, JPEG, PNG, etc., graphic file**

In Figure 14, it will be a pair of image processing software schematic illustrations for creating the high-resolution GIF (Graphics Interchange Format) picture as all pictures shown are presented in this paper. For example, using the freeware "IrfanView," the user opens the menu "Save Picture As" of clipboard picture data and pastes it by "Paste Ctrl+V," and the user can copy and paste through the graphic Windows OS clipboard examples. Finally, almost 94 kByte of compact-size and high-resolution GIF file was created via the software "IrfanView." This high-resolution GIF file of around 94 kByte would be user friendly for making documentation with graphic pictures. Also the other standard graphic file formats of JPEG, PNG, BMP, TIF, etc., are able to apply in a similar procedure the high-performance software "iView."

```