Open access peer-reviewed chapter

Simulation of Morphological Effects on Thermoelectric Power, Thermal and Electrical Conductivity in Multi‐Phase Thermoelectric Materials

Written By

Yaniv Gelbstein

Submitted: March 31st, 2016 Reviewed: August 4th, 2016 Published: December 21st, 2016

DOI: 10.5772/65099

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Abstract

Multi‐phase thermoelectric materials are mainly investigated these days due to their potential of lattice thermal conductivity reduction by scattering of phonons at interfaces of the involved phases, leading to the enhancement of expected thermoelectric efficiency. On the other hand, electronic effects of the involved phases on thermoelectric performance are not always being considered, while developing new multi‐phase thermoelectric materials. In this chapter, electronic effects resulting from controlling the phase distribution and morphology alignment in multi‐phase composite materials is carefully described using the general effective media (GEM) method and analytic approaches. It is shown that taking into account the specific thermoelectric properties of the involved phases might be utilized for estimating expected effective thermoelectric properties of such composite materials for any distribution and relative amount of the phases. An implementation of GEM method for the IV–VI (including SnTe and GeTe), bismuth telluride (Bi2Te3), higher manganese silicides (HMS) and half‐Heusler classes of thermoelectric materials is described in details.

Keywords

  • thermoelectric
  • GEM
  • multi‐phase

1. Thermoelectrics

Climate changes, due to fossil fuels combustion and greenhouse gases emission, cause deep concern about environmental conservation. Another pressing issue is sustainable energy production that is coupled with depletion of conventional energy resources. This concern might be tackled by converting the waste heat generated in internal‐combustion vehicles, factories, computers, etc. into electrical energy. Converting this waste heat into electricity will reduce fossil fuel consumption and emission of pollutants. This can be achieved by direct thermoelectric (TE) converters, as was successfully demonstrated by development of various highly efficient TE material classes, including Bi2Te3 [13] for temperatures, T, of up to ∼300°C, SnTe [4, 5], PbTe [6, 7] and GeTe [811], for temperatures range 300 ≤ T≤ 500°C, and higher manganese silicides (HMS) [1214], half‐Heuslers [1520], which are capable to operate at higher temperatures. Such materials require unique combination of electronic (i.e. Seebeck coefficient, α, electrical resistivity, ρ, and electronic thermal conductivity, κe) and lattice (i.e. lattice thermal conductivity, κl) properties, enabling the highest possible TE figure of merit, ZT= α2T/[ρ(κe + κl)], values, for achieving significant heat to electricity conversion efficiencies. Due to the fact, that electronic TE properties are strongly correlated, and follow opposite trends upon modifying charge carriers’ concentration, many of recently developed TE materials, were focused on nano‐structuring methods, capable of κl reduction due to lattice modifications and correspondingly increasing ZT. Such methods included alloying (for PbTe, as an example, alloying with SrTe [21, 22], MgTe [23] and CdTe [24], resulted in strained endotaxial nanostructures), applying layered structures with increased interfaces population (e.g. SnSe [25]), and thermodynamically driven phase separation reactions, generating nano‐scale modulations (e.g. GexPb1−xTe [2628] and Gex(SnyPb1−y)1−xTe [29, 30]). All of these approaches resulted in significant increase of ZTup to ∼2.5 [25] due to effective scattering of phonons by associated generated nano‐features. Nevertheless, although significant enhancement of TE properties was reported due to phonon scattering by nano‐structured phases in such multi‐phase TE materials, most of these researches did not investigate individual electronic contributions of each of the involved phases on effective TE transport properties.

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2. Multi‐phase thermoelectric materials

In the last few decades, major trend is to move from pristine single‐crystal TE compositions towards polycrystalline multi‐phase materials. One of the reasons for that is improved shear mechanical strength of polycrystalline materials compared to single crystals, exhibiting high compression, but very low transverse strengths, required to withstand high thermal and mechanical gradients applied in practical applications. Another reason is the possibility of phonon scattering by the involved interfaces as mentioned above. Most of the TE materials investigated these days are being synthesized by powder metallurgy approach under high uniaxial mechanical pressures, deforming involved grains and phases into anisotropic geometrical morphologies, which affect the electronic transport properties. Besides, a certain amount of porosity (as a second phase) is in many cases unavoidable, adversely affecting TE transport properties. Furthermore, many of currently employed TE materials (e.g. Bi2Te3 and HMS) are crystallographic anisotropic with optimal TE transport properties along preferred orientations. Some researches of such materials for TE applications do not consider crystallographic anisotropy, while assuming, that randomly oriented grains of different crystallographic planes cancel each other in polycrystalline samples. Yet, some anisotropy can exist also in such materials in case of highly anisotropic specific properties (e.g. mechanical properties), leading to textured polycrystal. For example, texture development of non‐cubic polycrystalline alloys was attributed to multiple deformation modes applied in each grain, twinning resulting in grain reorientation and strong directional grain interactions [12]. Specifically, in Bi2Te3, for example, exhibiting highly anisotropic layered crystal structure consists of 15 parallel layers stacked along crystallographic caxis, the presence of van der Waals gap in the crystal lattice, divides crystal into blocks of five mono‐atomic sheets [1]. In this case, retaining the crystallographic anisotropy is highly desired. This is due to the fact, that in transverse to crystallographic caxis, TE power factor (numerator in ZTexpression) is considerably higher, than in parallel to this direction, mainly due to higher electrical conductivity values. For powder metallurgy synthesized Bi2Te3‐based materials, it was shown that moderate powder grinding pressures, might retain some of the crystallographic anisotropy, due to the weaker van der Waals bonding of atoms located in adjacent layers along c‐axis, compared to ionic/covalent bonding between atoms located in each of the layers [31]. In this example, higher ZTvalues in transverse to powder pressing direction are expected as in single crystals. This example highlights the significance of controlling phases’ morphology for optimizing TE transport properties.

Besides of metallurgical phases, individual transport properties of two species (e.g. light and heavy holes in p‐type PbTe [32]), in materials with complicated electronic band structures might contribute dramatically to effective TE transport properties.

In this chapter, effective TE properties (Seebeck coefficient, αelectrical resistivity, ρor conductivity, σ= ρ−1 and thermal conductivity, κ) of general complex structure, consisting of at least two independent phases with any respective relative amount and geometrical alignment are derived by using the GEM method [4] and individual TE properties of each of the involved phases. This approach can be utilized for maximizing TE figure of merit of multi‐phase composite materials, for example, by intentional alignment of the involved phases along the optimal TE direction.

We consider in this chapter a simple formulation for modelling of multi‐phase TE materials, originated from materials science aspects, such as inter‐diffusion, alloying, dissolution, phase transitions, phase separation, phase segregation, precipitation, recrystallization and other phenomena, that can take place in operation conditions of TE modules, especially TE power generation modules exposed to high thermo‐mechanical stresses.

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3. TE GEM effective equations for two‐phase materials

Effective TE properties of two‐phase composites can be accurately predicted by GEM method, Eqs. (1)–(3) [4, 3335]:

αeffα2α1α2=κeffκ2σeffσ21κ1κ2σ1σ21,E1
x1(σ1)1t(σeff)1t(σ1)1t+A(σeff)1t=(1x1)(σeff)1t(σ2)1t(σ2)1t+A(σeff)1t,E2
x1(κ1)1t(κeff)1t(κ1)1t+A(κeff)1t=(1x1)(κeff)1t(κ2)1t(κ2)1t+A(κeff)1t.E3

These three GEM equations, Eqs. (1)–(3), are usually employed for calculating effective Seebeck coefficient (αeff) and effective electrical and thermal conductivities (σeff and κeff, respectively) for two‐phase materials using individual electrical (σ1 and σ2) and thermal (κ1 and κ2) conductivity, as well as, individual Seebeck coefficient (α1 and α2) values of involved phases. Morphological parameters A, tcan be derived by modelling of experimental results or from percolation equation [33, 34]. Parameter x1 is volume fraction of one of the phases. Values of Aand tare strongly affected by phase distribution and morphology. It was shown, that for homogeneously distributed second phase in continuous matrix, tvalue is equal to 1 [4] and the entire morphological alignment possibilities of the second phase related to the matrix phase are bounded by the so‐called ‘parallel’ and ‘series’ alignment of the phases (relative to electrical potential or temperature gradients). Parameter Avaries from 8 for parallel to 0 for series alignments. It can be seen, that for substituting t= 1 and A= 8in Eqs. (2) and (3), as in the case of phases distribution in parallel to electrical current direction, reduces equations to Eq. (4), while substituting of Eq. (4) in Eq. (1) leads to Eq. (5):

(σeff,κeff)=(σ1,κ1)x1+(σ2,κ2)(1x1),E4
αeff=α1σ1x1+α2σ2(1x1)σ1x1+σ2(1x1).E5

Similarly, substituting t= 1 and A= 0 in Eqs. (2) and (3), as in the case of series alignment as explained above, reduces them into Eq. (6):

(σeff,κeff)=(σ1,κ1)(σ2,κ2)(σ1,κ1)(1x1)+(σ2,κ2)x1.E6

Please note that although for the case of parallel alignment, effective electrical and thermal conductivity, Eq. (4), follow a simple rule of mixture, a more complicated dependency is apparent for series alignment, Eq. (6). Yet, as shown in Eq. (7), for this latter case, effective electrical resistivity, ρeff = σeff−1, follows the rule of mixture:

ρeff=ρ1x1+ρ2(1x1).E7

Substituting of Eq. (6) in Eq. (1), leads in this case to Eq. (8):

αeff=α1κ2x1+α2κ1(1x1)κ1(1x1)+κ2x1.E8

While investigating Eqs. (5) and (8) , for the cases of parallel and series alignment, respectively, it can be easily seen, that for both cases, effective Seebeck coefficient depends not only on individual Seebeck coefficients of the two phases, but also on other electronic transport properties, electrical conductivity of the involved phases for the case of parallel alignment, Eq. (5), and thermal conductivity of the involved phases for the case of series alignment, Eq. (8). An explanation for this observation is given in the next section.

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4. Analytical effective equations for multi‐phase materials

In order to extend GEM, Eqs. (1)–(3) listed above for two‐phase composite materials, into higher‐ordered composites with three or more coexisting phases, a simple analytical model for calculating effective TE properties of several conductors, subjected to external electrical and thermal gradients, can be applied. For this purpose, two boundary conditions explained above, can be examined; one for conductors connected in parallel to both thermal and electrical applied gradients and the other for conductors connected in series.

4.1. Thermoelectric phases in parallel

In the case of three distributed conductors oriented in parallel to external temperature, ΔT= ThTc, and electrical potentials, V, gradients, shown schematically as 1, 2 and 3 in Figure 1(a), each of them might be considered as a single phase with sample's length and perspective cross‐section area according to its relative amount (Figure 1b). For this case, electrical analogue, shown in Figure 1(c), includes three parallel branches, with power source reflecting the individual open circuit voltage developed according to Seebeck effect (V1,2,3 = α1,2,3ΔT, where α1,2,3 – Seebeck coefficients of the involved phases) under applied temperature difference, connected serially to resistor R1,2,3, reflecting internal total electrical resistance, of each of the phases. In this case, electrical currents I1,2,3, flowing through connectors are given by Eq. (9):

I1,2,3=VTcThα1,2,3dTR1,2,3.E9

Total electrical current Iin three‐phase system is given by Eq. (10):

I=I1+I2+I3=V(1R1+1R2+1R3)TcTh(α1R1+α2R2+α3R3)dT.E10

Figure 1.

Schematical description of three phases, I–III, oriented in parallel to external temperature and electrical gradients, as distributed in the sample (a) and as combined entities with sample's length and perspective cross‐section area according to their relative amount (b). The electrical analogue of this three‐phase material is given in (c).

Considering definition of Seebeck coefficient as derivative of applied voltage with respect to temperature for non‐current flowing condition, Eq. (11), a simple manipulation of Eq. (10) gives Eq. (12), which describes effective Seebeck coefficient, αeff, of parallel connected three‐phase structure:

αeffdVdT|I=0,E11
αeff=α1R1+α2R2+α3R31R1+1R2+1R3=α1R2R3+α2R1R3+α3R1R2R2R3+R1R3+R1R2.E12

Using specific parameters (resistivity ρ1,2,3 and conductivity σ1,2,3 = (ρ1,2,3)−1) instead of resistances R1,2,3, as described in Eq. (13), expression for αeff for parallel connected three‐phase structures can be derived, Eq. (14):

R1,2,3=ρ1,2,3lsampA˜1,2,3,E13
αeff=(α1ρ2ρ3A˜2A˜3+α2ρ1ρ3A˜1A˜3+α3ρ1ρ2A˜1A˜2)(ρ2ρ3A˜2A˜3+ρ1ρ3A˜1A˜3+ρ1ρ2A˜1A˜2)=α1A˜1ρ2ρ3+α2A˜2ρ1ρ3+α3A˜3ρ1ρ2A˜1ρ2ρ3+A˜2ρ1ρ3+A˜3ρ1ρ2=α1σ1A˜1+α2σ2A˜2+α3σ3A˜3σ1A˜1+σ2A˜2+σ3A˜3,E14

where, lsamp = l1 = l2 = l3 is the sample's length, A˜1,2,3is the cross‐section area transverse to electrical current flow.

While considering, volume fractions, x1,2,3 (= A˜1,2,3. lsamp/Vsamp, where Vsamp is sample's volume) of the respective phase, Eq. (15) can be easily derived:

(αeff)parallel=α1σ1x1+α2σ2x2+α3σ3x3σ1x1+σ2x2+σ3x3=αiσixiσixi.E15

From electrical analogue shown in Figure 1(c), effective electrical and thermal conductivities can also be easily derived, as expressed in Eqs. (16) and (17), respectively:

(σeff)parallel=σ1x1+σ2x2+σ3x3=σixi,E16
(κeff)parallel=κ1x1+κ2x2+κ3x3=κixi.E17

It is noteworthy that applying the same approach for higher i‐ordered multi‐phase materials will follow the general‐ordered right‐hand side expressions of Eqs. (15)–(17). Furthermore, it can be easily seen that Eqs. (15)–(17) for the case of two‐phase materials are reduced to Eqs. (5) and (4), respectively, derived from the GEM method.

4.2. Thermoelectric phases in series

Equivalent description for the case of three distributed conductors oriented in series to external temperature and electrical potentials gradients is shown in Figure 2(a).

Figure 2.

Schematical description of three phases, I–III, oriented in series to external temperature and electrical gradients, as distributed in the sample (a) and as combined entities with sample's diameter and perspective lengths according to their relative amount (b).

For this case, a similar analysis is presented, taking into account individual thermal gradients applied on each of the phases. Taking into account that the first, second and third phases are subjected to temperature differences of (ThT1), (T1T2) and (T2Tc), respectively, as shown in Figure 2(b), where T1,2 are intermediate temperatures (Th> T1 > T2 > Tc), effective Seebeck coefficient of such serially aligned three‐phase samples can be described in terms of Eq. (18):

αeff=α1(ThT1)+α2(T1T2)+α3(T2Tc)ThTc.E18

Under adiabatic heat conduction conditions, where no lateral heat losses are apparent, the heat flow, Q, through the entire sample and the individual phases can be described in terms of unidirectional Fourier heat conduction equation, Eq. (19):

Q=κ1A˜l1(ThT1)=κ2A˜l2(T1T2)=κ3A˜l3(T2Tc)=κeffA˜lsamp(ThTc),E19

where κeff is effective thermal conductivity of the three‐phase material, A˜is cross‐section area transverse to heat flow and κ1,2,3 and l1,2,3 are thermal conductivity and effective length of each of the involved phases, respectively.

Using expression (19), the numerator terms of Eq. (18) can be easily described in terms of expressions (20):

α1(ThT1)=Ql1α1κ1A˜, α2(T1T2)=Ql2α2κ2A˜, α3(T2Tc)=Ql3α3κ3A˜.E20

In the rightmost equation of expression (19), κeffA˜/lsamp represents overall thermal conductance, Keff of the three‐phase sample, which is described in Eq. (21), in terms of serially connected thermal resistances, Rth,1,2,3, specified in Eq. (22):

Keff=κeffA˜lsamp=1(Rth)1+(Rth)2+(Rth)3,E21
(Rth)1,2,3=1(κ1,2,3A˜l1,2,3).E22

Combining Eqs. (21) and (22) leads to Eq. (23):

Keff=1l1κ1A˜+l2κ2A˜+l3κ3A˜.E23

Substitution of the expression of Keff, Eq. (23) in the rightmost term of expression (19) results in the expression of ThTc, presented in Eq. (24):

Q=1l1κ1A˜+l2κ2A˜+l3κ3A˜(ThTc) or (ThTc)=Q(l1κ1A˜+l2κ2A˜+l3κ3A˜).E24

Substitution of temperature differences derived in Eqs. (20) and (24) into Eq. (18) results in the expression of αeff for serially connected three‐phase structures, Eq. (25):

(αeff)series=(Ql1α1κ1A˜+Ql2α2κ2A˜+Ql3α3κ3A˜)Q(l1κ1A˜+l2κ2A˜+l3κ3A˜)=(α1x1κ1+α2x2κ2+α3x3κ3)(x1κ1+x2κ2+x3κ3)=αixiκixiκi.E25

Applying the same considerations described above, effective electrical and thermal conductivities can also be derived, as expressed in Eqs. (26) and (27), respectively:

(σeff)series=1x1σ1+x2σ2+x3σ3=1(xiσi),E26
(κeff)series=1x1κ1+x2κ2+x3κ3=1(xiκi).E27

Similarly to the previous case of parallel‐connected phases, i‐ordered multi‐phase materials will follow general‐ordered right‐hand side expressions of Eqs. (25)–(27). Furthermore, it can be easily seen, that Eq. (25) and Eqs. (26) and (27) for the case of two‐phase materials are reduced to Eqs. (8) and (6), respectively, derived from the GEM method, highlighting validity of the analytic approach described here.

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5. Practical examples and applications

Prior to describing the full potential of the GEM concept on optimizing performance of multi‐phase TE materials, two general examples highlighting the potential of the method for monitoring the microstructure and phase morphology are described.

While analysing measured electrical and thermal conductivities of Cu following different spark plasma sintering (SPS) conditions, resulting in porosity levels in the range of 0–30%, a good agreement to GEM equations, Eqs. (2) and (3), was observed while assuming homogeneous dispersion (t= 1) and nearly spherical morphology (A= 2), as were observed by electronic microscopy, as well as σ1, κ1 values of pure Cu (the matrix phase), and σ2, κ2 equal to zero (the pores phase) [36]. This approach not just validated experimentally the GEM equations described above, but also paved a route for monitoring porosity amount during SPS consolidation process, which is widely applied in the synthesis of TE materials, as pointed out above, just by measuring electrical resistivity of the samples. For the SnTe system in the two‐phase compositional range between pure Sn and SnTe compound, a parallel morphological alignment of the phases was identified both by electronic microscopy and by measuring Seebeck coefficient values of the samples [4]. The latter was validated by comparing measured αeff to values, calculated by GEM equation, Eq. (1), with various Avalues. The best agreement was obtained for A = 8, indicating a parallel alignment of the phases. This approach validated the possibility to identify geometrical alignment of the phases just by measuring Seebeck coefficient values without any requirement of advanced electron microscopy.

Specifically, for TE materials, it was recently shown that upon introduction of MoSe2 phase into layered n‐type Bi2Te2.4Se0.6 alloy for optimizing its TE performance, the best performance was obtained for oriented samples with A= 0.3, in Eqs. (1)–(3), as shown, for example, for ρeff, in Figure 3(a) [3]. In this figure, the agreement of red experimental points with A= 0.3 curve can be clearly seen.

Figure 3.

(a) Variations of effective electrical resistivity values upon introduction of MoSe2 in Bi2Te2.4Se0.6‐MoSe2 two‐phase system [3]. (b) Room temperature GEM analysis of effective Seebeck coefficient upon homogeneous mixing (t = 1) ofc‐axis anda‐axis oriented grains of HMS for different geometrical alignment (0,series<A<∞,parallel) conditions [12]. (c) Interaction ofZTsurfaces and volumes between three phases, solution treated (ST) matrix (B), Pb‐rich (A) and Ge‐rich (C) phases of Pb0.25Sn0.25Ge0.5Te. The entire interaction volumes are bounded by ABC points, where each volume is bounded by two surfaces of series (S1‐S2‐S3) and parallel (P1‐P2‐P3) alignments [37].

A similar approach was recently applied for investigation of the morphological effects on TE properties of Ti0.3Zr0.35Hf0.35Ni1+δSn alloys following phase separation into half‐Heulser Ti0.3Zr0.35Hf0.35NiSn and Heusler Ti0.3Zr0.35Hf0.35Ni2Sn phases [15]. In this research, it was found that although phases’ orientation was aligned in intermediate level (A= 0.8) between parallel (A= 8) and spherical (A= 2) alignments, enhanced TE performance is expected in a series alignment while substituting A=0 in Eqs. (1)–(3).

Another very interesting implementation of GEM approach was recently applied to estimate effective room temperature Seebeck coefficient and electrical resistivity values of a randomly morphological oriented homogeneous mixture of (001) and (hk0) grains in anisotropic polycrystalline HMS TE samples [12]. Applying GEM analysis to homogeneous distribution of (001) and (hk0) oriented grains (t= 1), for different alignment (A) conditions, resulted in the blue curves shown in Figure 3(b). In this figure, the upper and lower blue curves represent series and parallel alignments of two configurations, respectively, points 2 and 3 represent c‐ and a‐axis‐oriented crystals, respectively, and intermediate dashed blue curve indicates a spherical distribution of two directions. Point 1 indicates 50% mixture of the directions for a spherical alignment, representing mixture of two directions, as in the case of non‐textured polycrystalline HMS powder. The black and red curves of Figure 3(b) indicate interaction between c‐ and a‐axis‐oriented grains with randomly distributed polycrystalline powder (point 1 in Figure 3b), as was calculated by GEM approach. In that case, a partial c‐axis preferred orientated powder, embedded in a homogeneous surrounding of macroscopic non‐preferred‐orientated powder is expected to exhibit αeff values that are bounded in between the series2 and parallel2 black curves of the figures. Similarly, αeff values for partial a‐axis preferred orientated powder are expected to be bounded between series3 and parallel3 red curves of the figure. The experimentally measured α, α values while considering 10% preferred orientation, as was identified by XRD, are also shown in the figure. It can be seen that experimental points lie in the interaction zone between c‐ and a‐axis‐orientated powder and a randomly distributed powder, bounded by the black and red curves, respectively. This indicates the validity of proposed calculation route to estimate electronic transport properties of textured polycrystalline materials. It can be also seen that for HMS, ∼10% preferred orientation of both of investigated directions is almost independent of the orientation of the grains, and, therefore, controlling the alignment of the grains morphology is not expected to affect the effective Seebeck coefficient.

Implementation of GEM concept in three‐phase TE materials, based on Eqs. (15)–(17) and (25)–(27), was recently shown for quasi‐ternary GeTe‐PbTe‐SnTe system [37, 38]. Specifically, it was shown that phase separation of solution‐treated (ST) Pb0.25Sn0.25Ge0.5Te composition (phase B in Figure 3c) into Pb‐rich, Pb0.33Sn0.3Ge0.37Te (phase A), and Ge‐rich, Pb0.1Sn0.17Ge0.73Te (phase C) phases is apparent in the system. In this system, prolonged thermal treatments at each temperature resulted, at the first stages, in three phases, parent B phase and two decomposed A and C phases. This stage is terminated by full decomposition into A and C, where only these phases are apparent. Furthermore, a lamellar alignment of the phases was observed at the first 24 h of thermal treatment, while prolonged treatments were resulted in spheroidization, due to reduced surface area free energy at this configuration. It was also observed that ZTvalues were increased during the first 24 h while reduced at more prolonged durations. For explaining these experimental evidences, GEM approach was applied, as shown in Figure 3(c). In this figure, triangle BDE indicates the specific interaction surface for separation of the phase B into the phases A and C, where BD side of triangle represents series (‘lamellar') alignment morphology and BE represents parallel alignment of the phases. The dashed BO line represents spherical alignment. It can be easily shown that measured ZTvalues, indicated by the blue line, indeed follow the series alignment (BD line) at the first decomposition stages, but from this point on approach the dashed BO line until a full spheroidization is occurred (at point o). From this analysis, it was concluded that any theoretical possibility for retaining the lamellar morphology in this system would result in even higher ZTvalues of up to ∼1.8 after a complete decomposition of the matrix into the two involved separation phases.

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6. Concluding remarks

In this chapter, the potential of GEM approach to optimize electronic properties of multi‐phase thermoelectric materials in terms of compositional or morphological considerations is shown in details. This approach already proved itself in monitoring of the densification rate of powder metallurgy processed materials, as well as in the determination of compositional modifications in binary systems just by measuring one of the transport properties. It is just beginning to approach the true potential to optimize thermoelectric transport properties of multi‐phase materials, such as those containing embedded nano‐features for reduction of the lattice thermal conductivity, where electronic contribution of the involved phase is usually neglected. It was shown that method does not just explain unexpected electronic trends in such materials, but might be employed for prediction of synthesis routes for optimizing thermoelectric figure of merit based on different compositions or alignment morphologies.

Based on the pointed above examples, it is obvious that for TE power generators operating at low (<300°C), intermediate (300–500°C) and high (>500°C) temperature ranges, Bi2Te3, PbTe/GeTe and HMS/half‐Heusler‐based compositions might be employed. In such systems, identifying compositions enabling phase separation or precipitation into multi‐phases, according to specific phase diagram, has a potential to reduce lattice thermal conductivity. Yet, for maximizing TE potential, optimal geometrical alignment of the phases should be identified. Using the proposed approach, based on individual TE transport properties of the involved phases, optimal geometrical alignment direction might be identified, leading to enhanced TE performance, enabling a real contribution to the society by reducing our dependence on fossil fuels and by minimizing emission of greenhouse gases.

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Acknowledgments

The work was supported by the Ministry of National Infrastructures, Energy and Water Resources grant (3/15), No. 215‐11‐050.

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Written By

Yaniv Gelbstein

Submitted: March 31st, 2016 Reviewed: August 4th, 2016 Published: December 21st, 2016