Applied Physics A

, 126:102 | Cite as

Caloric and isothermal equations of state of solids: empirical modeling with multiply broken power-law densities

  • Roman TomaschitzEmail author
  1. 1.ViennaAustria
Article

Abstract

Empirical equations of state (EoSs) are developed for solids, applicable over extended temperature and pressure ranges. The EoSs are modeled as multiply broken power laws, in closed form without the use of ascending series expansions; their general analytic structure is explained and specific examples are studied. The caloric EoS is put to test with two carbon allotropes, diamond and graphite, as well as vitreous silica. To this end, least-squares fits of broken power-law densities are performed to heat capacity data covering several logarithmic decades in temperature, the high- and low-temperature regimes and especially the intermediate temperature range where the Debye theory is of limited accuracy. The analytic fits of the heat capacities are then temperature integrated to obtain the entropy and caloric EoS, i.e. the internal energy. Multiply broken power laws are also employed to model the isothermal EoSs of metals (Al, Cu, Mo, Ta, Au, W, Pt) at ambient temperature, over a pressure range up to several hundred GPa. In the case of copper, the empirical pressure range is extended into the TPa interval with data points from DFT calculations. For each metal, the parameters defining the isothermal EoS (i.e. the density–pressure relation) are inferred by nonlinear regression. The analytic pressure dependence of the compression modulus of each metal is obtained as well, over the full data range.

Keywords

Multi-parameter equation of state (EoS) Caloric EoS of carbon allotropes Specific heat of vitreous silica Thermal EoS and compression modulus of metals High-pressure regime Multiply broken power laws 

1 Introduction

The aim of this paper is to develop analytic equations of state (EoSs) for solids which can reproduce empirical data sets covering several orders in temperature and pressure, including the extended crossovers between the asymptotic low and high pressure and temperature regimes. The proposed EoSs are multiply broken power laws, which do not involve truncated series expansions in density, pressure or temperature (frequently used in empirical EoSs, cf. e.g. the reviews [, , , , ]) and are, therefore, equally suitable for the mentioned asymptotic regions.

At first, we study caloric EoSs, i.e. the temperature dependence of the internal energy, obtained by integration of the isochoric heat capacity. We work out three specific examples, obtaining closed analytic expressions for the heat capacities of diamond, graphite and vitreous silica by least-squares regression. The isochoric heat capacities are structured as multiply broken power laws [, , ],
CV(T)=b0Tβ0k=1n(1+(T/bk)βk/|ηk|)ηk
(1)
with positive amplitudes b0 and bk, k=1,,n, and bk<<bk+1. The exponents βk, k=1,,n are positive, β0 is real, and the exponents ηk can be positive or negative. CV(T) is analytic on the positive real axis and consists of n+1 approximate power-law segments, Tβ0, Tβ0+β1sign(η1),,Tβ0+k=1nβksign(ηk) in the intervals T<<b1, b1<<T<<b2,,bn<<T, respectively. The amplitudes bk define the break points between the power-law segments and the exponents ηk determine the extent of the transitional regions. Power laws in log–log plots appear as approximately straight segments, and the exponents ηk determine the extent of the transitional regions between the power-law segments.

The isochoric heat capacities of diamond, graphite and vitreous SiO2, discussed in Sect. 2, are special cases of the broken power-law density (1). In the case of diamond, CV(T) interpolates between the constant Dulong–Petit high-temperature limit and the Debye T3 low-temperature slope. In the intermediate temperature range, the broken power law (1) is sufficiently adaptable to model deviations from the Debye theory such as the boson peaks of glasses. In the case of graphite, CV(T) interpolates between the linear low-temperature slope of the degenerate electron gas and the classical Dulong–Petit regime, and in the case of the SiO2 glass, the linear low-temperature slope is replaced by a power law with non-integer index close to one, generated by a fermionic two-level system. In the latter two examples, a phononic cubic temperature slope does not emerge in the empirical data sets, as the low-temperature regime is dominated by Fermi systems.

In recent years, new phenomenological EoSs have been proposed to model density–pressure data sets obtained from Hugoniot shock compression of, for instance, alkali metals [, ], alkaline earths [], aluminum [, , ], iron [], copper [], tin [] and tungsten [], to mention but a few. In the second part of this paper, multiply broken power laws are employed as isothermal EoSs of metals, with emphasis on the high-pressure (GPa and TPa) regime. In this case, the pressure dependence of the mass density ρ has the analytic shape
ρ(P)=ρ0k=1n(1+P/bk)ηk
(2)
with positive amplitudes ρ0, bk, bk<<bk+1, and real exponents ηk, k=1,,n. These parameters are temperature dependent, but will be treated as constants in the examples studied here, at ambient temperature of 300 K. Density (2) consists of n+1 power-law segments, 1, Pη1,,Pk=1nηk, in the intervals P<<b1, b1<<P<<b2,,bn<<P. In contrast to the broken power law (1), we have put β0=0 and βk=|ηk| in (2), so that ρ(P) is analytic at P=0, which is essential to model the compression modulus in the low-pressure range consistent with ultrasonic measurements. When discussing the compression modulus in Sect. 3, we will also need the logarithmic derivative of density (2), ρ(P)/ρ(P)=k=1nηk/(P+bk), to show how the low-pressure limit of EoS (2) is related to the Murnaghan EoS [, , , , , ].

In Sect. 3, the EoS (2) will be put to test by performing least-squares fits to high-pressure data sets of Al, Cu, Mo, Ta, Au, W, and Pt, which cover an extended pressure range, from ambient (zero) pressure to several hundred GPa [, , ]. In the case of copper, the available experimental pressure range (up to 450 GPa []) will be extended with data sets obtained from DFT calculations []. The least-squares fit of the EoS of copper then covers pressures reaching 60 TPa. In Sect. 4, we present our conclusions.

2 Heat capacity, caloric EoS, and entropy of diamond, graphite and vitreous silica

In this section, the modeling of empirical heat capacity data by multiply broken power-law densities is discussed. Two carbon allotropes, diamond and graphite, and a glass, v - SiO2, are studied as specific examples. Explicit formulas for the molar isochoric heat capacities are obtained by nonlinear least-squares regression, cf. Figs. 1, 2 and 3. Comparisons with the Debye theory are depicted in Fig. 4. The temperature variation of the internal energy and entropy variables obtained from the regressed heat capacities is shown in Fig. 5. Alternative attempts to find caloric EoSs for diamond and graphite are discussed in Refs. [, , , ] and references therein.
Fig. 1

Isochoric heat capacity of diamond, cf. Sect. 2.1. Data points from Ref. [] (circles), Ref. [] (squares) and Ref. [] (diamonds). The χ2 fit (solid red curve) is performed with CV(T) in (3), the fitting parameters are recorded in Table 1. For comparison, the black dashed curve is the Debye approximation (4), with constant Debye temperature of θdiamond=2186 K. The classical 3R Dulong–Petit limit is indicated by the black dotted line. The green dotted straight line depicts the tangent cTκ at the inflection point (T=95.53K, CV=0.2085J/(mol K)), with slope κ=3.547 and amplitude c=1.972×108J/(mol K1+κ)

Fig. 2

Isochoric heat capacity of graphite, cf. Section 2.2. Data points from Ref. [] (circles, Madagascar natural graphite), Ref. [] (squares, Canadian natural graphite), Ref. [] (rectangles, Acheson graphite), and Ref. [] (diamonds, Acheson graphite). The experimental isobaric CP data points have been converted into isochoric CV points, cf. (6). The χ2 fit (red solid curve) is performed with the analytic broken power law CV(T) in (7), the fitting parameters are listed in Table 1. The dotted blue asymptote CVb0T is the low-temperature limit of the heat capacity of the electron plasma. The CV(T) curve has an inflection point at T=3.146K, CV=7.170×104J/(molK). The dotted green line is the tangent cTκ at the inflection point, with amplitude c=3.702×105J/(molK1+κ) and slope κ=2.586, which is the maximum slope attained. See also Fig. 4 for the Debye approximation

Fig. 3

Isochoric heat capacity of v - SiO2, cf. Section 2.3. Data points from Ref. [] (rectangles), Ref. [] (circles), and Ref. [] (squares). The least-squares fit (red solid curve) is performed with the broken power law CV(T) in (8), the fitting parameters are recorded in Table 1. The classical 9R limit is indicated by the black dotted line. The dotted blue low-temperature asymptote CVb0T1.22 depicts the heat capacity of the two-level Fermi system discussed in Sect. 2.3, which dominates the phononic heat capacity at low temperature. The tangent cTκ at the inflection point (T=5.240K, CV=2.480×102J/(mol K)) has slope κ=3.770 and amplitude c=4.815×105J/(molK1+κ)

Fig. 4

Comparison of the molar isochoric heat capacities CV(T) of diamond, graphite and vitreous silica. The blue, red and black solid curves show the broken power laws CV(T) in (3), (7) and (8), respectively, with fitting parameters in Table 1. (The fits are depicted in Figs. 1, 2 and 3). The dashed curves are the Debye heat capacities, cf. (4). The Debye temperature of diamond is θdiamond=2186K (cD=b0, cf. (4) and Table 1), inferred from the low-temperature limit CVb0T3 of the broken power law (3). The Debye temperatures θgraphite=438.7K and θv - SiO2=323.4K have been chosen so that the Debye heat capacity (4) intersects the fitted CV(T) curves at their inflection point, since the empirical heat capacities of graphite and v - SiO2 do not exhibit a T3 slope in any temperature range

Fig. 5

Caloric EoS U(T)=0TCVdT and molar entropy S(T)=0T(CV/T)dT of diamond, graphite and vitreous silica, cf. (5). The caloric EoSs (thermal component of the internal energy) are depicted as solid curves, the entropies as dashed ones. At high temperature, U(T)T and the entropy diverges logarithmically. The isochoric heat capacities in the integrands are defined in (3), (7) and (8), with fitting parameters in Table 1. The low-temperature slopes read U(T)T1+β0 and S(T)Tβ0, with exponent β0 in Table 1

2.1 Diamond

We perform a χ2 fit to the available data sets [, , ] of the diamond heat capacity, depicted in the double-logarithmic plot in Fig. 1, by employing a broken power law of type (1) as isochoric heat capacity,
CV(T)=b0T3(1+(T/b1)β1/η1)η11(1+(T/b2)β2/η2)η2
(3)
with amplitudes b1<<b2. The exponents βi, ηi, i=1,2 are positive, and β2=3+β1, so that the classical Dulong–Petit limit CV(T)3R is recovered, with gas constant R=8.314 J/(K mol). This limit also requires amplitudes in (3) related by b0=3Rb1β1/b2β2. The low-temperature limit is CV(T0)b0T3; the units used are CV[J/(K mol)], b0[J/(K4 mol)], and bi[K].
Broken power laws composed of multiple factors (1+(T/bi)βi/|ηi|)ηi are quite efficient for data sets stretching over several decades in temperature, as demonstrated in the subsequent examples. In (3), we have three successive power laws, T3, T3+β1, T3+β1β2, in the intervals T<<b1, b1<<T<<b2 and b2<<T, respectively, which appear as approximately straight segments in log–log plots, and the exponents η1, η2 determine the transitional regions around the break points b1 and b2. The parameters b1, b2, η1, η2 and β1 obtained from the least-squares fit are recorded in Table 1. In contrast to the Debye heat capacity, cf. (4), the heat capacity of diamond exhibits an inflection point in the crossover region between the low- and high-temperature regimes, see Fig. 1; the tangent of CV at the inflection point is shown as green dotted line depicting the power law T3.547.
Table 1

Fitting parameters of the molar isochoric heat capacity CV(T) of diamond, graphite and vitreous silica, see Figs. 1, 2 and 3

 

Diamond

Graphite

v - SiO2

b0

1.8605×107

1.4843×105

1.0618×104

b1[K]

67.435

0.60277

2.6677

b2[K]

282.02

40.466

10.585

b3[K]

562.35

247.30

β0

3

1

1.22

β1

1.2496

1.6796

4.3172

β2

β0+β1

1.3235

4.0656

β3

β0+β1β2

β0+β1β2

η1

0.30536

0.69130

2.7558

η2

2.1816

1.1347

1.7243

η3

0.56727

0.93528

χ2

0.144

0.0539

0.0635

dof

117–5

114–8

78–8

SE

0.070

0.070

0.431

1R2

2.41×104

5.55×105

5.16×104

The listed parameters (amplitudes bi, exponents βi, ηi) define the multiply broken power laws (3) (for diamond), (7) (graphite) and (8) (vitreous SiO2) representing the empirical heat capacities. Some of these parameters are interrelated, cf. Sect. 2. b0 is in units of J/(K1+β0mol). Also recorded are the minimum of the least-squares functional χ2=i=1N(CV(Ti)CVi)2/CVi2 and the degrees of freedom (dof: number N of data points (Ti,CVi) minus number of independent fitting parameters). The standard error of the fits, SE=(i=1N(CV(Ti)CVi)2/N)1/2, and the coefficient of determination, R2=1i=1N(CV(Ti)CVi)2/(Nσ2), with sample variance σ2=i=1N(CViC¯V)2/N and mean C¯V=i=1NCVi/N, are listed as well

In Figs. 1 and 4, we have also indicated the Debye approximation,
CD(T)=9na/mR[4D(θ/T)θ/Teθ/T1],D(x):=1x30xy3dyey1,θ=(125π4na/mRcD)1/3.
(4)

The asymptotic limits of the Debye function are D(x>>1)π4/(15x3) and D(x<<1)1/3, so that CD(T0)cDT3 and CD(T)3na/mR, where na/m denotes the number of atoms per molecule. The units are cD[J/(K4 mol)] and CD[J/(K mol)] as above. The amplitude cD is taken from the least-squares fit of CV(T) in (3), cD=b0, cf. Table 1, to recover the cubic low-temperature slope. Accordingly, the Debye temperature (4) of diamond is θ=2186 K. The low-temperature amplitude cD is the only adjustable parameter of the Debye heat capacity, so that it is not surprising that the Debye approximation becomes inaccurate in the crossover region.

The temperature dependence of the caloric EoS (molar internal energy with zero-point energy subtracted) and molar entropy of diamond,
U(T)[J/ mol]=0TCVdT,S(T)[J/(K mol)]=0TCVTdT
(5)
is shown in Fig. 5, calculated by substituting CV(T) in (3) with fitting parameters recorded in Table 1.

2.2 Graphite

The heat capacity data of graphite tabulated in the experimental papers [, , , ] refer to the isobaric heat capacity CP. The conversion of isobaric (at ambient pressure) to isochoric heat capacities CV is done with the approximate formula CVCP/(1+0.526Tα(T)), where 0.526 is the dimensionless Grüneisen constant of graphite [] and α the thermal expansion coefficient perpendicular to the basal plane, cf. Refs. [, , ],
α(0T80)=5.35×109T23.755×1011T3,α(80T273)=2.435×107T7.69×1010T2+8.875×1013T3,α(273T1100)=2.722×105+3.05×109(T273),α(1100T3000)=2.975×105+9.604×109(T1100).
(6)

The units are α[1/K] and T[K]. The expansion α|| in the basal plane is negligible compared with α. In the case of diamond, cf. Sect. 2.1, the conversion to isochoric heat capacities has already been done in the experimental papers. In the case of vitreous silica, cf. Sect. 2.3, CVCP in the temperature range of the available data points.

The heat capacity of graphite has an electronic and a phonon component, cf. Fig. 2; at low temperature, the linear electronic heat capacity overpowers the phonon component. For the least-squares fit depicted in Fig. 2, we use a broken power law similarly structured as in (3):
CV(T)=b0T(1+(T/b1)β1/η1)η1×1(1+(T/b2)β2/η2)η21(1+(T/b3)β3/η3)η3,
(7)
where the factors are ordered by increasing magnitude of the amplitudes, b1<<b2<<b3, and the exponents βi, ηi, i=1,2,3, are positive. We put β3=1+β1β2 so that CV(T)3R, which also requires amplitudes related by b0[J/(K2 mol)]=3Rb1β1/(b2β2b3β3). The fitting parameters are bi, ηi, i=1,2,3, and β1, β2, cf. Table 1. The tangent at the inflection point of CV(T)[J/(K mol)] is depicted as dotted green line T2.586 in Fig. 2, and the electronic low-temperature asymptote CV(T)b0T is also shown in this figure.

There is no indication of a T3 slope anywhere to be seen in the data set in Fig. 2. Therefore, we choose the amplitude cD defining the Debye temperature in a way that the low-temperature T3 slope of the Debye curve CD(T) [stated in (4)] cuts through the inflection point of the empirical heat capacity CV(T), see Fig. 4. This gives a Debye temperature of θ=438.7 K [with cD=2.303×105J/(K4mol) in (4)]. A different choice of θ would just shift the T3 slope parallel to the depicted slope. It is evident from Fig. 4 that the standard Debye approximation (4) cannot give a reasonable fit to the heat capacity of graphite, irrespective of the choice of θ, except at very high temperature; see also Ref. [] and references therein for modifications of the Debye theory regarding graphite. The internal energy and entropy functions of graphite are shown in Fig. 5, obtained by integrating the empirical CV(T) in (7) (with fitting parameters in Table 1) according to Eq. (5).

2.3 Vitreous SiO2

For the heat capacity of vitreous silica [, , , , ], we use a broken power law similar to that of graphite:
CV(T)=b0Tβ0(1+(T/b1)β1/η1)η1×1(1+(T/b2)β2/η2)η21(1+(T/b3)β3/η3)η3,
(8)
where the positive amplitudes bi[K] are ordered by increasing magnitude, b1<<b2<<b3. The exponents βi and ηi, i=1,2,3, are positive, and we put β3=β0+β1β2 so that CV(T)9R, which also requires b0[J/(K1+β0 mol)]=9Rb1β1/(b2β2b3β3). The data points in Fig. 3 refer to the total heat capacity of the phonons and the fermionic two-level system which dominates the phonon heat capacity of the glass at low temperature [, ]. The low-temperature heat capacity of the two-level system is slightly different from linear, with power-law exponent of β0=1.22 for v - SiO2 [, ]. In the least-squares fit depicted in Fig. 3, we take this exponent β0 as input parameter in (8); the low-temperature limit of (8) is CV[J/(K mol)]b0Tβ0. The fitting parameters are bi, ηi, i=1,2,3, and β1, β2, cf. Table 1. The tangent of CV at the inflection point is shown as dotted green line T3.770 in Fig. 3.

The Debye approximation CD(T) of the v - SiO2 heat capacity is depicted in Fig. 4, cf. (4). As in the case of graphite, there is no T3 slope visible in the measured heat capacity. The Debye temperature θ=323.4 K [cD=1.724×104J/(K4mol) in (4)] is chosen so that CD(T) intersects the empirical heat capacity CV(T) [in (8)] at the inflection point. For comparison, the heat capacities CV(T) of diamond and graphite, cf. (3), (7) and Table 1, are also indicated in Fig. 4. The molar internal energy and entropy of v - SiO2 are depicted in Fig. 5, calculated via (5) and (8).

To quantify the two-level system defining the heat capacity at low temperature [, ], we use a Fermi distribution with zero chemical potential and a power-law mode density. The spectral density and the internal energy then read
dρ(E)=a0Eβ01dEeE/T+1,
(9)
U(T)=0Edρ(E)=a0T1+β0(12β0)Γ(1+β0)ζ(1+β0)
(10)
with positive exponent β0 and amplitude a0 to be determined from heat capacity measurements. Γ(x) and ζ(x) denote the gamma function and Riemann zeta function, cf. e.g. Ref. [], and we have put =kB=1. The heat capacity is CV=U(T)=(1+β0)U/T. By comparing with the low-temperature limit CVb0Tβ0 of the empirical heat capacity (8), we can specify the exponent β0=1.22 and the amplitude in (9),
a0=b0(12β0)Γ(2+β0)ζ(1+β0)
(11)
with b0 in Table 1, so that a0=5.089×105J/(K2.22 mol). The partition function is related to the internal energy by
logZ=a00log(1+eE/T)Eβ01dE=1β0UT,
(12)
where we used integration by parts, and the entropy reads S=logZ+U/T=CV/β0.
The spectral density dρ(E) in (9) can be written in the equivalent quasi-particle momentum representation
dρ^(p)=4πs(2π)3p2dpeE(p)/T+1,U=0E(p)dρ^(p),
(13)
where s=2 is the spin degeneracy and
E(p)=c0p3/β0,c0:=(4πs(2π)3β03a0)1/β0
(14)
is the power-law dispersion relation. Density (13) can be derived by box quantization; the dispersion relation (14) is to be regarded as the leading order of an ascending power series, and the thermodynamic variables derived from (9) or (13) are asymptotic low-temperature limits.

In Sects. 2.12.3, we have studied heat capacities and caloric EoSs obtained by fitting broken power laws (1) to empirical data. In the next section, we will use broken power-law densities to model isothermal EoSs of solids at high pressure, as indicated in (2).

3 Isothermal EoS of metals at high pressure

We start with the Murnaghan EoS P=(K0/K0)((ρ/ρ0)K01), cf. e.g. Refs. [, , ], where K0 denotes the bulk modulus K(P) at zero pressure and K0 its pressure derivative at P=0 (practically ambient pressure). ρ(P) denotes the mass density and ρ0 the mass density at zero pressure. The temperature dependence of ρ(P), K(P) and of the constants K0, K0, ρ0 will not be explicitly indicated; the data sets studied here refer to a constant ambient temperature of 300K. Inverting the above EoS, we find ρ(P)/ρ0=(1+PK0/K0)1/K0 and the compressibility κT:=ρ(P)/ρ(P)=1/(K0+K0P), which gives a linear pressure dependence of the compression modulus K(P)=1/κT=K0+K0P. Accordingly, (ρ(P)/ρ(P))|P=0=K0=K(P)|P=0 and (ρ(P)/ρ(P))|P=0=K0=K(P)|P=0. This linear relation and the Murnaghan EoS are usually applicable up to pressures of a few GPa, cf. e.g. Ref. [].

To obtain density–pressure relations extending into the high-pressure range, we write the broken power-law density (2) as
ρ(P)ρ0=(1+K^0K^0P)1/K^0k=2n(1+P/bk)ηk,
(15)
where we have put b1=K^0/K^0 and η1=1/K^0. The first factor in (15) is modeled after the inverted Murnaghan EoS. The amplitudes in (15) are ordered according to bk<<bk+1, see after (2). For pressures up to several hundred GPa (achievable in current shock compression experiments), two factors [n=2 in (15)] suffice to obtain an accurate density–pressure relation. In this case, the EoS (15) is composed of three successive power laws, 1, P1/K0^, P1/K0^+η2, in the intervals P<<K^0/K^0, K^0/K^0<<P<<b2 and b2<<P, respectively.
The compression modulus derived from EoS (15) reads
K(P)=ρ(P)ρ(P)=K^0+K^0P1+Δ(P),Δ(P):=(K^0+K^0P)k=2nηkbk11+P/bk,
(16)
where we made use of the logarithmic derivative of ρ(P) stated after (2). K(P) admits a Taylor expansion K(P)=K0+K0P+O(P2) with coefficients
K0=K^01+K^0A,K0=K^0+K^02B(1+K^0A)2,A:=k=2nηkbk,B:=k=2nηkbk2.
(17)
Accordingly, the parameters K^0 and K^0 defining the first factor of EoS (15) are related to the bulk modulus at zero pressure, K0=K(P)|P=0, and to its derivative K0=K(P)|P=0 by
K^0=K01K0A,K0^=K0K02B(1K0A)2,
(18)
which is the inversion of (17). We substitute these relations for K^0 and K^0 in EoS (15), so that the first factor of EoS (15) depends on the parameters K0, K0 and bk, ηk, k=2,,n. Evidently, if |K0A|<<1 and |K02B/K0|<<1, then K^0K0 and K^0K0. The bulk modulus K0 at zero pressure and its derivative K0 are taken as measured input in EoS (15), inferred from acoustic low-pressure experiments. The amplitudes and exponents bk, ηk, k=2,,n in EoS (15) are to be determined by least-squares regression. If ultrasonic measurements of K0 are not available, we can take K0 as additional fit parameter, and the same holds for K0. As mentioned, the EoS (15) with two factors suffices for pressures up to several hundred GPa, so that only two fit parameters b2, η2 are needed for data sets presently obtainable by shock compression.
We test EoS (15) with pressure isotherms of Al (Fig. 6), Cu (Fig. 7), Mo (Fig. 8), Ta (Fig. 9), Au (Fig. 10), W (Fig. 11) and Pt (Fig. 12), all at ambient temperature of 300 K. The least-squares fits (red solid curves) are based on EoS (15) (with n=2 and relations (18) substituted) and data sets from Refs. [, , ]. The fit parameters b2, η2 and the input parameters ρ0 and K0, K0 (the latter two obtained from ultrasonic measurements [, , , , , , , , , , , ]) as well as the goodness-of-fit parameters (χ2/dof, standard error, determination coefficient) are recorded in Table 2. In the case of Mo and Pt, K0 is treated as a third fit parameter, for lack of ultrasonic estimates. In Fig. 13, the pressure range of copper (by shockless compression up to 450 GPa [], cf. Figure 7) has been extended to 60TPa using data points from DFT calculations [], in which case a third factor can be specified in EoS (15) (n=3), depending on two additional fit parameters b3, η3 recorded in the last column of Table 2.
Fig. 6

Pressure isotherm at 300 K and compression modulus of aluminum. Data points up to 200 GPa (by Hugoniot shock compression) from Ref. []. The χ2 fit (solid red curve) is performed with the isothermal EoS ρ(P) in (15) (n=2), the fitting parameters b2, η2 are recorded in Table 2. The solid blue curve depicts the compression modulus K(P) calculated from the fitted EoS, cf. (16). ρ0 and K0 denote mass density and compression modulus at zero pressure, cf. Table 2. The dashed green lines are asymptotes to ρ(P)/ρ0 and K(P)/K0. The dotted black curves depict the Murnaghan approximations of the EoS and compression modulus, cf. after (18), calculated with K0 and its derivative K0 obtained from ultrasonic measurements, cf. Table 2

Fig. 7

Pressure isotherm and compression modulus of copper. Data points up to 450 GPa (via shockless compression) from Ref. []. The caption to Fig. 6 applies. The χ2 fit (solid red curve) is performed with EoS ρ(P) in (15), the fitting parameters are listed in Table 2. The solid blue curve shows the compression modulus K(P), cf. (16). The dashed green lines are asymptotes. The dotted black curves depict the Murnaghan approximations, cf. after (18). See also Fig. 13 for the extension of the EoS into the TPa range

Fig. 8

Pressure isotherm and compression modulus of molybdenum. Data points up to 1 TPa (by shock compression) from Ref. []. The caption of Fig. 6 applies. The χ2 fit (solid red curve) is performed with EoS ρ(P) in (15) and fitting parameters in Table 2. The solid blue curve shows the compression modulus K(P), cf. (16). The dashed green lines are asymptotes and the dotted black curves depict the Murnaghan approximations

Fig. 9

Pressure isotherm and compression modulus of tantalum. Data points up to 300 GPa by shock compression []. The χ2 fit (solid red curve) is performed with EoS ρ(P) in (15) and fitting parameters in Table 2. The compression modulus K(P), cf. (16), is depicted as blue solid curve. The dashed green lines are the asymptotes of ρ(P)/ρ0 and K(P)/K0. The dotted black curves depict the Murnaghan EoS and the linear compression modulus derived from it, cf. after (18)

Fig. 10

Pressure isotherm at 300 K and compression modulus of gold. Data points up to 500 GPa by shock compression []. The χ2 fit (solid red curve) is performed with EoS ρ(P) in (15), the fitting parameters are recorded in Table 2. The solid blue curve shows the compression modulus K(P), cf. (16). The dashed green lines are asymptotes and the dotted black curves depict the Murnaghan approximations

Fig. 11

Pressure isotherm at 300 K and compression modulus of tungsten. Data points up to 300 GPa by shock compression []. The χ2 fit (solid red curve) is performed with EoS ρ(P) in (15) and fitting parameters in Table 2. The solid blue curve is the compression modulus K(P), cf. (16). The dotted black curves depict the Murnaghan EoS and the linear approximation of the compression modulus, cf. after (18). The dashed green lines are asymptotes

Fig. 12

Pressure isotherm and compression modulus of platinum. Data points up to 660 GPa by shock compression []. The χ2 fit (solid red curve) is performed with EoS ρ(P) in (15), the fitting parameters are recorded in Table 2. The solid blue curve shows the compression modulus K(P), cf. (16). The dashed green lines are asymptotes and the dotted black curves depict the Murnaghan approximations, cf. after (18)

Table 2

Fitting parameters of the pressure isotherms of Al, Cu, Mo, Ta, Au, W and Pt, at ambient temperature of 300 K. The isothermal EoS used for the fits is defined in (15)

 

Al

Cu

Mo

Ta

Au

W

Pt

Cu @ TPa

ρ0[g/cm3]

2.707

8.939

10.22

16.67

19.24

19.25

21.41

8.939

K0[GPa]

73

133.5

264.87

194

166.7

296

280.03

133.5

K0

4.42

5.36

3.7499

3.83

6.23

4.3

5.0886

5.36

b2[GPa]

78.084

120.03

612.12

90.405

114.00

531.46

169.13

113.31

η2

0.13699

0.14094

0.14521

0.28648

0.17773

0.25268

0.10226

0.13916

b3[GPa]

6507.1

η3

0.15077

K^0[GPa]

83.723

158.32

282.63

503.58

225.24

344.48

337.11

160.28

K0^

5.6564

7.2929

4.2386

16.918

10.680

5.7177

6.9681

7.4471

χ2

6.06×105

2.53×105

1.68×105

1.02×104

7.75×105

1.27×105

5.00×107

5.40×104

dof

82

82

84

80

81

75

78

112

SE

1.04×103

6.37×104

6.88×104

1.34×103

1.06×103

4.34×104

1.12×104

6.57×103

1R2

2.26×105

8.56×106

6.23×106

5.22×105

2.76×105

1.20×105

4.21×107

3.57×105

The mass density ρ0, cf. Ref. [], and the bulk modulus K0 at zero pressure and its pressure derivative K0 inferred from ultrasonic measurements [, , , , , , , , , , , ] are taken as input parameters. In the case of Mo and Pt, K0 is treated as fitting parameter, for lack of acoustic measurements. Otherwise, there are only two fitting parameters in EoS (15) (with n=2), the amplitude b2 and exponent η2 defining the second factor of the EoS. The pressure isotherms are depicted in Figs. 6, 7, 8, 9, 10, 11 and 12, covering pressures up to a few hundred GPa (subject to availability of data points). In the last column, we have indicated the parameters of the EoS of copper extended to pressures up to 60 TPa with high-pressure data points from DFT calculations [], see Fig. 13. In this case, a third factor in EoS (15) can be specified (n=3), depending on two additional fitting parameters b3 and η3. Also listed are the constants K^0 and K0^ defining the first factor of the EoS (15), which are calculated from the input and fitting parameters according to (17) and (18). The minimum of the least-squares functional χ2, the degrees of freedom (dof), the standard error SE and determination coefficient R2 (see the caption to Table 1) of the least-squares fits in Figs. 6, 7, 8, 9, 10, 11, 12 and 13 are recorded as well

Fig. 13

Pressure isotherm at 300 K and compression modulus of copper up to 60 TPa. Data points up to 450 GPa (circles) obtained by shockless compression [] and up to 60 TPa (squares) from DFT calculations []. The χ2 fit (solid red curve) is performed with the isothermal EoS ρ(P) in (15) (with n=3), the fitting parameters are listed in Table 2. The solid blue curve shows the compression modulus K(P), cf. (16). The dotted black curves depict the Murnaghan EoS and the linear compression modulus derived from it, cf. after (18). The dashed green straight lines indicate the asymptotes of the pressure isotherm and compression modulus

In Figs. 6, 7, 8, 9, 10, 11, 12 and 13, we have also depicted the pressure dependence of the compression modulus K(P) (solid blue curves) defined in (16), using input and fitting parameters of the regressed EoS (15) listed in Table 2. In these figures, we also compare the EoS (15) with the Murnaghan EoS ρM(P)/ρM0=(1+(K0/K0)P)1/K0 outlined at the beginning of this section [we write here ρM(P) and ρM0 for density and density at zero pressure to distinguish this EoS from the general EoS in (15)]. The compression modulus K(P) in (16) is also compared with the linear relation KM(P)=K0+K0P obtained from the Murnaghan EoS. (The linearity of KM(P) is somewhat hidden in the log–log representation of the figures.) Actually, this linear relation, experimentally verified up to pressures of a few GPa (but usually invalid above 10 GPa, see Figs. 6, 7, 8, 9, 10, 11 and 12) is the starting point when deriving the Murnaghan EoS, by substituting KM(P)=ρM(P)/ρM(P) and integrating.

The compression modulus K(P) in (16) coincides with the Murnaghan approximation KM(P) in linear order, cf. (17). The EoS (15) is analytic at P=0 and can be expanded in an ascending series,
ρ(P)ρ0=1+1K0P+1K02K02P2+
(19)
with K0 and K0 in (17), by making use of the zero pressure identities (ρ(P)/ρ(P))|P=0=K0 and (ρ(P)/ρ(P))|P=0=K0. The Murnaghan EoS admits the same second-order expansion. As is evident from Figs. 6, 7, 8, 9, 10, 11 and 12, a linear compression modulus is quite accurate up to about 5 GPa, and the Murnaghan approximation of EoS (15) remains valid up to about 50 GPa.
In the opposite high-pressure regime, the leading order of EoS (15) is a power law,
ρ(P)aPα,α:=1K0^+k=2nηk,a:=ρ0(K0^K^0)1/K0^k=2nbkηk,
(20)
and it is convenient to write Δ(P) in (16) as
Δ(P)=K0^(1+K^0K0^P)k=2nηk1+bk/P,
(21)
which converges to a constant at high pressure, Δ(P)=K0^k=2nηk+O(1/P). The corresponding asymptotic limits of the compression modulus (16) and its derivative are K(P)=KP+O(1) and K(P)=K+O(1/P2), where K=K(P)|P=1/α with α(K0^,ηk)=1/K0^+k=2nηk as defined in (20).

The EoS ρ(P)P3/5 of a non-relativistic degenerate electron gas in the Thomas–Fermi free-electron approximation gives K=5/3 [, ], leading to the condition α(K0^,ηk)=3/5 to be satisfied by the exponents K0^ and ηk in (15) and (20). Application of this relation to the EoS of copper depicted in Fig. 13 (which is accurate up to 60 TPa and based on EoS (15) with n=3 and parameters in Table 2) suggests that an additional factor (1+P/b4)η4 with η40.176 will be necessary in EoS (15) (n=4) to extend the density–pressure curve beyond 60 TPa. (In the case of an ultra-relativistic degenerate electron plasma, K=5/3 is replaced by K=4/3, so that α=3/4.) Phenomenological thermodynamic arguments were used in Refs. [, ] to suggest the inequality K>5/3 instead of K=5/3. In contrast to the positivity of the heat capacities and compressibilities, this is not a necessary equilibrium condition but presumably more realistic for planetary cores than the Thomas–Fermi limit [, ]. The inequality K>5/3 weakens the above condition to α(K0^,ηk)<3/5 and gives the constraint η4<0.176 on the exponent of the fourth factor in the ultra-high pressure EoS of copper applicable beyond 60 TPa.

4 Conclusion

The examples discussed in Sects. 2 and 3 demonstrate the efficiency of multiply broken power laws in modeling empirical equations of state of solids. The heat capacities CV(T) and mass densities ρ(P) defined in Sect. 1 are analytic functions composed of power-law segments joint by smooth analytic transitions; they do not involve series expansions, being assembled as products of power-law factors (1+(x/bk)βk/|ηk|)ηk, k=1,,n, cf. (1) and (2), where x stands for the temperature or pressure variable. Broken power laws are particularly suitable to model data sets where pressure or temperature varies over several orders of magnitude, interpolating between different asymptotic regimes. The condition bk<<bk+1 on the amplitudes defining the power-law factors allows us to systematically assemble caloric and isothermal EoSs over an ever increasing temperature or pressure range; since bk<<bk+1, the factor with amplitude bk+1 does not significantly affect the EoS in the range xbk.

In Sect. 2, we discussed three examples of caloric EoSs (of two carbon allotropes and vitreous SiO2); the corresponding isochoric heat capacities exhibit very different low-temperature power-law scaling and also deviate noticeably from the Debye theory in the intermediate temperature range. The log–log plots in Figs. 1, 2 and 3 depict least-squares fits of the heat capacities [modeled as broken power laws, cf. (3), (7) and (8)] to the respective isochoric data sets of diamond, graphite and v - SiO2. For these materials, heat capacity measurements (including the conversion from isobaric to isochoric heat capacities by way of Grüneisen parameter and thermal expansion coefficient) are available over an extended temperature range covering the low- and high-temperature regimes. As these examples demonstrate, broken power laws are sufficiently adaptable to accurately reproduce the heat capacities over the full empirical temperature range, including features such as the boson peak of the glass in Fig. 4 emerging at around 10 K or the excess heat capacity (as compared to the Debye theory) of diamond peaking at 200 K, cf. Figs. 1 and 4. The analytic heat capacities obtained from the least-squares fits can be temperature integrated to obtain the caloric EoS and entropy variable, see Fig. 5.

In Sect. 3, we discussed isothermal EoSs of specific metals, capable of reproducing high-pressure data sets. The examples studied cover a wide range of mass densities (at ambient pressure), from Al to Pt, cf. Table 2. In contrast to the multiply broken power laws modeling the heat capacities in Sect. 2, which are non-analytic at T=0, we used broken power laws analytic at zero pressure, cf. (2). The EoS can then be made to converge to the Murnaghan EoS in the low-pressure regime, where the compression modulus is known to vary linearly with pressure. The least-squares fits of the isothermal EoS (15) to high-pressure data sets of Al, Cu, Mo, Ta, Au, W and Pt are depicted in Figs. 6, 7, 8, 9, 10, 11 and 12. In all cases, the fits are uniformly accurate over the full empirical pressure range, from ambient pressure to several hundred GPa. In Fig. 13, the empirical EoS of Cu is extended into the TPa regime, using data points from DFT calculations for the least-squares regression. In Sect. 3, we also explained the implementation of the ultra-high pressure Thomas–Fermi limit into empirical isothermal EoSs defined by multiply broken power laws.

Notes

References

  1. 1.
    W.B. Holzapfel, High Press. Res. 16, 81 (1998)ADSCrossRefGoogle Scholar
  2. 2.
    W.B. Holzapfel, Z. Kristallogr. 216, 473 (2001)Google Scholar
  3. 3.
    J.S. Tse, W.B. Holzapfel, J. Appl. Phys. 104, 043525 (2008)ADSCrossRefGoogle Scholar
  4. 4.
    J. Hama, K. Suito, J. Phys. Condens. Matter 8, 67 (1996)ADSCrossRefGoogle Scholar
  5. 5.
    F.D. Stacey, Rep. Prog. Phys. 68, 341 (2005)ADSCrossRefGoogle Scholar
  6. 6.
  7. 7.
    R. Tomaschitz, Physica A 483, 438 (2017)ADSMathSciNetCrossRefGoogle Scholar
  8. 8.
    R. Tomaschitz, Fluid Phase Equilib. 496, 80 (2019)CrossRefGoogle Scholar
  9. 9.
    K.V. Khishchenko, J. Phys: Conf. Ser. 946, 012082 (2018)Google Scholar
  10. 10.
    K.V. Khishchenko, J. Phys. Conf. Ser. 1147, 012001 (2019)CrossRefGoogle Scholar
  11. 11.
    K.V. Khishchenko, Tech. Phys. Lett. 30, 829 (2004)ADSCrossRefGoogle Scholar
  12. 12.
    D.V. Minakov, P.R. Levashov, K.V. Khishchenko, AIP Conf. Proc. 1426, 836 (2012)ADSCrossRefGoogle Scholar
  13. 13.
    D.V. Minakov, P.R. Levashov, K.V. Khishchenko, V.E. Fortov, J. Appl. Phys. 115, 223512 (2014)ADSCrossRefGoogle Scholar
  14. 14.
    M.A. Kadatskiy, K.V. Khishchenko, J. Phys: Conf. Ser. 653, 012079 (2015)Google Scholar
  15. 15.
    M.A. Kadatskiy, K.V. Khishchenko, J. Phys. Conf. Ser. 774, 012005 (2016)CrossRefGoogle Scholar
  16. 16.
    M.A. Kadatskiy, K.V. Khishchenko, Phys. Plasmas 25, 112701 (2018)ADSCrossRefGoogle Scholar
  17. 17.
    K.V. Khishchenko, J. Phys. Conf. Ser. 121, 022025 (2008)CrossRefGoogle Scholar
  18. 18.
    K.V. Khishchenko, J. Phys. Conf. Ser. 653, 012081 (2015)CrossRefGoogle Scholar
  19. 19.
    J.R. Macdonald, Rev. Mod. Phys. 38, 669 (1966)ADSCrossRefGoogle Scholar
  20. 20.
    B.G. Yalcin, Appl. Phys. A 122, 456 (2016)ADSCrossRefGoogle Scholar
  21. 21.
    S. Khatta, S.K. Tripathi, S. Prakash, Appl. Phys. A 123, 582 (2017)ADSCrossRefGoogle Scholar
  22. 22.
    M. Kaddes, K. Omri, N. Kouaydi, M. Zemzemi, Appl. Phys. A 124, 518 (2018)ADSCrossRefGoogle Scholar
  23. 23.
    W. Ouerghui, M.S. Alkhalifah, Appl. Phys. A 125, 374 (2019)ADSCrossRefGoogle Scholar
  24. 24.
    A. Laroussi, M. Berber, B. Doumi, A. Mokaddem, H. Abid, A. Boudali, H. Bahloul, H. Moujri, Appl. Phys. A 125, 676 (2019)ADSCrossRefGoogle Scholar
  25. 25.
    A.D. Chijioke, W.J. Nellis, I.F. Silvera, J. Appl. Phys. 98, 073526 (2005)ADSCrossRefGoogle Scholar
  26. 26.
    R.G. Kraus, J.-P. Davis, C.T. Seagle, D.E. Fratanduono, D.C. Swift, J.L. Brown, J.H. Eggert, Phys. Rev. B 93, 134105 (2016)ADSCrossRefGoogle Scholar
  27. 27.
    Y. Wang, R. Ahuja, B. Johansson, J. Appl. Phys. 92, 6616 (2002)ADSCrossRefGoogle Scholar
  28. 28.
    C.W. Greeff, J.C. Boettger, M.J. Graf, J.D. Johnson, J. Phys. Chem. Solids 67, 2033 (2006)ADSCrossRefGoogle Scholar
  29. 29.
    L.E. Fried, W.M. Howard, Phys. Rev. B 61, 8734 (2000)ADSCrossRefGoogle Scholar
  30. 30.
    K.V. Khishchenko, V.E. Fortov, I.V. Lomonosov, M.N. Pavlovskii, G.V. Simakov, M.V. Zhernokletov, AIP Conf. Proc. 620, 759 (2002)ADSCrossRefGoogle Scholar
  31. 31.
    K.V. Khishchenko, V.E. Fortov, I.V. Lomonosov, Int. J. Thermophys. 26, 479 (2005)ADSCrossRefGoogle Scholar
  32. 32.
    S.Sh. Rekhviashvili, Kh.L. Kunizhev, High Temp. 55, 312 (2017)CrossRefGoogle Scholar
  33. 33.
    J.E. Desnoyers, J.A. Morrison, Philos. Mag. 3, 42 (1958)ADSCrossRefGoogle Scholar
  34. 34.
    W. DeSorbo, J. Chem. Phys. 21, 876 (1953)ADSCrossRefGoogle Scholar
  35. 35.
    A.C. Victor, J. Chem. Phys. 36, 1903 (1962)ADSCrossRefGoogle Scholar
  36. 36.
    B.J.C. van der Hoeven, P.H. Keesom, Phys. Rev. 130, 1318 (1963)ADSCrossRefGoogle Scholar
  37. 37.
    W. DeSorbo, G.E. Nichols, J. Phys. Chem. Solids 6, 352 (1958)ADSCrossRefGoogle Scholar
  38. 38.
    W. DeSorbo, W.W. Tyler, J. Chem. Phys. 21, 1660 (1953)ADSCrossRefGoogle Scholar
  39. 39.
    M.W. Chase, NIST-JANAF Thermochemical Tables, 4th ed. (AIP, Woodbury, 1998), https://janaf.nist.gov
  40. 40.
    A.T.D. Butland, R.J. Maddison, J. Nucl. Mater. 49, 45 (1973)ADSCrossRefGoogle Scholar
  41. 41.
    T. Nihira, T. Iwata, Phys. Rev. B 68, 134305 (2003)ADSCrossRefGoogle Scholar
  42. 42.
    V.N. Senchenko, R.S. Belikov, J. Phys: Conf. Ser. 891, 012338 (2017)Google Scholar
  43. 43.
    J.C. Lasjaunias, A. Ravex, M. Vandorpe, S. Hunklinger, Solid State Commun. 17, 1045 (1975)ADSCrossRefGoogle Scholar
  44. 44.
    R.O. Pohl, in: Amorphous Solids, W.A. Phillips, ed. (Springer, Berlin, 1981)Google Scholar
  45. 45.
    R.B. Stephens, Phys. Rev. B 8, 2896 (1973)ADSCrossRefGoogle Scholar
  46. 46.
    P. Flubacher, A.J. Leadbetter, J.A. Morrison, B.P. Stoicheff, J. Phys. Chem. Solids 12, 53 (1959)ADSCrossRefGoogle Scholar
  47. 47.
    R.C. Lord, J.C. Morrow, J. Chem. Phys. 26, 230 (1957)ADSCrossRefGoogle Scholar
  48. 48.
    P.W. Anderson, B.I. Halperin, C.M. Varma, Philos. Mag. 25, 1 (1972)ADSCrossRefGoogle Scholar
  49. 49.
    W.A. Phillips, Rep. Prog. Phys. 50, 1657 (1987)ADSCrossRefGoogle Scholar
  50. 50.
    I.S. Gradshteyn, I.M. Ryzhik, Table of Integrals, Series, and Products, 8th edn. (Academic Press, Waltham, 2015)zbMATHGoogle Scholar
  51. 51.
    W.B. Holzapfel, Rep. Prog. Phys. 59, 29 (1996)ADSCrossRefGoogle Scholar
  52. 52.
    W.B. Holzapfel, High Press. Res. 22, 209 (2002)ADSCrossRefGoogle Scholar
  53. 53.
    G.M. Amulele, M.H. Manghnani, S. Marriappan, X. Hong, F. Li, X. Qin, H.P. Liermann, J. Appl. Phys. 103, 113522 (2008)ADSCrossRefGoogle Scholar
  54. 54.
    A. Dewaele, P. Loubeyre, M. Mezouar, Phys. Rev. B 70, 094112 (2004)ADSCrossRefGoogle Scholar
  55. 55.
    W.B. Holzapfel, High Press. Res. 30, 372 (2010)ADSCrossRefGoogle Scholar
  56. 56.
    K. Katahara, M. Manghnani, E. Fisher, J. Appl. Phys. 47, 434 (1976)ADSCrossRefGoogle Scholar
  57. 57.
    K.W. Katahara, M.H. Manghnani, E.S. Fisher, J. Phys. F: Met. Phys. 9, 773 (1979)ADSCrossRefGoogle Scholar
  58. 58.
    P. van’t-Klooster, N.J. Trappeniers, S.N. Biswas, Physica B + C 97, 65 (1979)Google Scholar
  59. 59.
    S.N. Biswas, P. van’t-Klooster, N.J. Trappeniers, Physica B + C 103, 235 (1981)Google Scholar
  60. 60.
    J.L. Tallon, A. Wolfenden, J. Phys. Chem. Solids 40, 831 (1979)ADSCrossRefGoogle Scholar
  61. 61.
    D. Steinberg, J. Phys. Chem. Solids 43, 1173 (1982)ADSCrossRefGoogle Scholar
  62. 62.
    W. Holzapfel, M. Hartwig, W. Sievers, J. Phys. Chem. Ref. Data 30, 515 (2001)ADSCrossRefGoogle Scholar
  63. 63.
    K. Syassen, W.B. Holzapfel, J. Appl. Phys. 49, 4427 (1978)ADSCrossRefGoogle Scholar
  64. 64.
    K. Takemura, A. Dewaele, Phys. Rev. B 78, 104119 (2008)ADSCrossRefGoogle Scholar
  65. 65.
    W.B. Holzapfel, M.F. Nicol, High Press. Res. 27, 377 (2007)ADSCrossRefGoogle Scholar
  66. 66.
    E.E. Salpeter, Astrophys. J. 134, 669 (1961)ADSMathSciNetCrossRefGoogle Scholar
  67. 67.
    F.D. Stacey, Geophys. J. Int. 143, 621 (2000)ADSCrossRefGoogle Scholar
  68. 68.
    F.D. Stacey, P.M. Davis, Phys. Earth Planet. Inter. 142, 137 (2004)ADSCrossRefGoogle Scholar
  69. 69.
    F.D. Stacey, J.H. Hodgkinson, Phys. Earth Planet. Inter. 286, 42 (2019)ADSCrossRefGoogle Scholar

Copyright information

© Springer-Verlag GmbH Germany, part of Springer Nature 2020

Personalised recommendations