Characterizing Atomic Interactions in Interstitial Non-Stoichiometric Compounds by Statistical Thermodynamics: Engineering Usage of Estimated Values of Statistical Thermodynamic Parameters

Statistical thermodynamics allows us to estimate atomistic interactions in interstitial non-stoichiometric compounds MX _x through analysis of experimentally determined pressure-temperature-composition ( PTC) relationships for MX _x being in equilibrium with X ₂ in gaseous state (X=H,N,P or S) or for non-stoichiometric carbide MCx being in equilibrium with excess C. In case of analysis for MC _x, chemical activity a(C) of C in place of partial pressure p(X ₂ ) of X ₂ gas must be known. On statistical modelling of crystal lattice structure for MX _x, an a priori assumption of constant nearest-neighbour X-X interaction energy E(X-X ) within a homogeneity composition range at arbitrary temperature T was accepted to determine number θ of available interstitial sites for occupation by X atoms per M atom. Values of interaction parame-ters estimated as such appear rational and realistic noting consistency of the values for M’s in the same group in the Periodic Table of the Elements and compatibility with enthalpy values evaluated by conventional thermodynamic approach. Engineering insights gained for MX _x through analysis of atomistic interaction parameter values evaluated by the statistical thermodynamics are reviewed comprehensively in this paper. M might be substitutional alloy A _1-y B _y composed of constituents, A and B, or MZ _z containing another interstitial constituent Z besides X. Insights acquired from this line of statistical thermodynamic analysis appear to be of pragmatic use for advanced alloy design as shall be demonstrated hereafter.

• Statistical Thermodynamics
• Non-Stoichiometry
• Interstitial Compound
• Hydride
• Nitride
• Carbide
• Phosphide
• Sulfide

1. Introduction

Statistical thermodynamic analysis procedures were comprehensively summarized by Fowler and Guggenheim in a classical monograph published in 1949 [1] . Statistical thermodynamics is considered as a bridge connecting between invisible atomistic scale microscopic world and experimentally observable macroscopic state for interstitial non-stoichiometric compound MX_x possessing composition being in equilibrium with X₂ gas at partial pressure at temperature T. By statistical thermodynamic analysis of equilibrium pressure-temperature-composition (PTC) relationships for MX_x, nearest-neigh- bour atomic interaction energy between i and j atoms and atomic partition function of constituent i in MX_x might be calculated.

Statistical thermodynamic parameters evaluated for extensive range of interstitial non-stoichiometric compounds including hydride, carbide, nitride, phosphide and sulfide were compiled in a monograph published by the author [2] that included calculation results reported by 2012 [3] - [46] . All these analyses [2] - [48] were made accepting an a priori assumption of constant interaction energy between nearest-neighbour interstitial atoms X within a homogeneity composition range of MX_x lattice at arbitrary T. Parameter values estimated for M’s in the same group in the Periodic Table of the Elements for given X were comparable to each other. This evidence appeared to support validity of the a priori assumption of the constant within a homogeneity composition range of MX_x at any T although there is no rigorous first-principle-based justification for this a priori assumption. Further, statistical thermodynamic parameter values for and evaluated as such yielded enthalpy values comparable to those determined by the conventional thermodynamics for Cr₂N [3] as well as for several hydrides [6] [18] . Hence, the atomic interaction parameter values evaluated as such by statistical thermodynamics must be considered realistic as well as rational.

Besides analysis for pure M, analysis was made also for substitutional alloy with consisting of two alloying constituents, A and B [8] [9] [11] [12] [16] [17] [18] [19] [24] [29] [33] [35] [36] [37] [38] [40] [42] [44] [46] [47] as well as for ternary alloy MZ_zX_x containing another interstitial constituent Z besides X in which affinity of Z to M was stronger than that of X to M [13] [31] [32] [34] .

In the early stage of this line of work to characterize nature of atomistic interaction in interstitial non-stoichiometric compound MX_x [2] - [47] , attention was not paid explicitly on engineering significance of the parameter values evaluated by the statistical thermodynamic analysis. However, after the analysis was made to evaluate interaction parameters for H absorption behaviours for Va-group metal-based alloy membranes [47] , it occurred to the author that it might be of pragmatic convenience if the correlation was established between the estimated values of the interaction parameters by statistical thermodynamic analysis and the reported H permeation performance for the Va-group metal-based alloy membrane materials. This led the author to summarize somewhat speculative paper [48] soon after [47] . The background idea for this attempt of correlating the statistical thermodynamic parameter values evaluated for Va-group metal-based alloy membrane to the H permeation performance of the alloy membrane was to screen promising ones from candidate Va-group metal-based alloys so that the number of H permeation experiments could be minimized. H permeation experiment is time-consuming and the results are dependent on setting of on the inlet side and that on the outlet side.

This special issue of Journal of Modern Physics bears title “Engineering Thermal Physics” with “statistical thermodynamics” being included as one of the possible fields of concern. Thus, the author decided to summarize this manuscript to review comprehensively the engineering significances of the interaction parameters estimated by statistical thermodynamics reported in the published works during the last four decades [2] - [48] .

As the main purpose of this manuscript is to demonstrate potential usefulness of evaluated atomic interaction parameters for MX_x by statistical thermodynamics for advanced alloy design, PTC data sources used in the analyses are not cited as the References. Statistical thermodynamic analysis procedures for interstitial non-stoichiometric compound MX_x shall be reviewed in the next Chapter although they might be referred to elsewhere [2] [3] [6] [44] [47] [48] as the statistical thermodynamic analysis procedure, unlike mathematically well-defined conventional thermodynamic analysis procedure, is not yet widely accepted as a standard analysis tool among materials researchers.

Among literatures cited in References section of this paper, [22] [23] [25] and [28] were works in which results of statistical thermodynamic analysis were made use of for interpretation of the discussed matters rather than works of statistical thermodynamic analysis itself and [41] was a preparative work to convert the equilibrium data format reported for Fe-Cr-P system by the original authors of the experimental work to a format adequate for straightforward statistical thermodynamic analysis that was published eventually as [42] .

2. Statistical Thermodynamic Analysis Procedure

2.1. Fundamental Equations

Generalized fundamental formulae proposed for this line of analysis of interstitial non-stoichiometric condensed phase MX_x are as follows.

Symbols used in the above formulae are classified as follows:

R: universal gas constant (=8.31451 J・mol⁻¹・K⁻¹),

h: Planck constant (=6.6260755 × 10⁻³⁴ J・s),

k: Boltzmann constant (=1.380658 × 10⁻²³ J・K⁻¹),

m_X: mass of X atom,

ρ: nuclear spin weight,

: characteristic temperature for rotation of X₂,

: characteristic temperature for vibration of X₂,

: electronic state of normal state of X₂ molecule,

: dissociation energy of X₂ molecule per mole,

β: factor determined from crystal structure consideration,

θ₀: geometrically available number of interstitial site per M in MX_x,

: statistical weight of tightly bound electrons around X in MX_x,

ν: vibrational frequency of X atom in MX_x lattice,

: distribution function,

: equilibrium pressure of ideal gas X₂,

T: absolute temperature (K),

x: composition (atom ratio) in MX_x,

n_X: number of X atoms in MX_x,

n_M: number of M atoms in MX_x,

Q: degree of stabilisation of X atom in MX_x lattice with reference to isolated X and M atoms in vacuum,

: interaction energy between i and j atoms in MX_x lattice,

: lattice energy,

: partition function of X atom in MX_x,

: partition function of M atom in MX_x,

K & g: parameters determined by Equations (1) & (2), from the experimental PTC data for an assigned value of θ,

θ: number of the interstitial sites per M atom available for occupation by X atoms in MX_x,

Z: extent of blocking of interstitial sites by X in; that is, when one interstitial site in MX_x is occupied by an X atom, neighbouring interstitial sites are blocked from occupation by other X atoms.

For example, in case that X atoms in MX_x occupy octahedral interstitial sites (O-sites) expression for Q in close packed lattices like fcc (face centred cubic) and hcp (hexagonal close packed) is simply,

but that for bcc (body centred cubic) lattice is expressed as

taking into account second nearest neighbour interactions, and

, besides nearest neighbour interaction due to openness of the atom packing in the bcc crystal lattice [2] [8] [18] .

On the other hand, geometrical factor β to in Equation (1) might be non-integral number. For example, β is 4/3 if X atoms are distributed over O-sites in bcc lattice [2] [8] [18] .

Value of θ to fulfill the a priori assumption of constant within a homogeneity range of MX_x at arbitrary T is usually close to the solubility limit of X in the MX_x. For example, in the statistical thermodynamic analysis of hypo-stoichiometric Cr₂N phase, θ was chosen to be 0.50 to fulfill the condition of constant over the homogeneity composition range of Cr₂N [3] . When θ was chosen to be 1 (=θ₀ for O-site occupation of N in the hcp lattice), varied with x showing trend of increasing positive (repulsive)

with increasing x. If such variation of takes place in MX_x, it is more natural to accept phase change to occur rather than to hold the same crystal lattice structure [2] .

2.2. Analysis Procedure

At the onset of the analysis, isothermal A vs. x plots must be prepared from available isothermal PC relationship at arbitrary T using Equation (1) by varying θ. As understood from Equation (1), slope of isothermal A vs. x plot would become proportional to. To fulfill the a priori assumption of constant within homogeneity composition range of MX_x at arbitrary T, θ yielding linear A vs. x relationship over entire homogeneity composition range of MX_x must be chosen for the subsequent calculations.

Then, from the intercept g(T) calculated using Equation (1), K(T) vs. T relationship must be drawn using Equation (2). Term Q on the right hand side in Equation (2) refers to extent of stabilization of atom X in the MX_x lattice due to formation of bonds in the MX_x lattice while the coefficient

to T refers to electronic contribution to entropy term in thermodynamic sense. In fact, partition function of X atom in the MX_x lattice is a T-dependent function as represented by Equation (4) but, as the T range of statistical thermodynamic analysis for MX_x is typically no wider than 500 K, it has been a common practice to approximate as a T-independent constant term [2] - [48] .

For convenience of the readers, flow chart of the calculation procedure is presented below as Figure 1.

As represented by Equation (5), term refers to the net extent of stabilization of X atom in the MX_x lattice, , taking into account the contribution of the interaction besides Q which represents contribution of the interaction alone where refers to lattice energy of compound MX_x calculated taking into account all nearest neighbour pairwise atomic interactions for all combinations of i and j.

For pragmatic convenience of calculating K(T) using Equation (2),

values for X = H and N are presented in tabulated form in [2] and [37] at 100 K interval from 0 K up to 3000 K so that

value at arbitrary T is calculated readily by interpolation although values of and were taken from JANAF Thermochemical Tables [49] or NIST-JANAF Thermochemical Tables [50] .

3. Some Insights Drawn from Statistical Thermodynamic Analysis Results for Interstitial Non-Stoichiometric Compounds

3.1. Stability of X in FeX x Lattice

As might be understood from expressions for fundamental equations reviewed in 2.1., reference state of energy in the statistical thermodynamic analysis is each constituent atom in infinite separation in vacuum whereas the reference state of constituent in conventional thermodynamic analysis is the pure substance in standard state. That is, by conventional thermodynamic analysis, enthalpy of formation of MX_x from M and X₂ represents the difference in energy between the reaction product MX_x and the reactants, M and, rather than evaluated by the statistical thermodynamic analysis. This makes straightforward comparison of extent of stabilization of different X atoms in a

Figure 1

Flow chart of the statistical thermodynamic analysis procedure accepting a priori assumption of constant within homogeneity composition range of MX x at arbitrary temperature T

given M lattice difficult through conventional thermodynamic analysis. In contrast, statistical thermodynamic analysis results allow us to compare straightforwardly the relative stability of different X’s in a given M as seen in Table 1 for M = Fe and X = H, C, N, P and S [20] .

The more stable the X in Fe lattice the more negative would become in FeX_x lattice. That is, according to Table 1, the stability of X in Fe lattice would decrease in the order of

implying that C is the most stable and H is the least stable in Fe lattice.

Further, it is notice in Table 1 that, for given X, stability in Fe lattice would vary depending on the lattice structure of Fe

implying that the most stable state of C in Fe is realized in molten state, that of N in γ phase and that of H in α phase.

In Table 1, θ value of some MX_x is not specified uniquely. This is due to inherent difficulty of determining exactly the value of θ for statistical thermodynamic

Table 1

Estimated values of Q in miscellaneous FeX x (reproduced from Table 1 in [ 20 ] )

Compound	Range of T	θ	Qb
	[K]		[kJ・mol−1]
α-FeHx (bcc)	<1175	>0.01	−171
γ-FeHx (fcc)	1185 - 1590	(0.50)a	−138
δ-FeHx (bcc)	1665 - 1715	(0.50)a	−100
α-FeCx (bcc)	<1000	>0.10	−648
α-FeCx (bcc)	1025 - 1150	>0.10	−613
γ-FeCx (fcc)	1175 - 1575	0.20	−679
FeCx (molten)	1550 - 1775	1.00	−699
α-FeNx (bcc)	<1115	>0.05	−420
γ-FeNx (fcc)	1250 - 1625	(0.50)a	−455
δ-FeNx (bcc)	1675 - 1715	(0.50)a	−352
FeNx (molten)	1850 - 2000	>0.10	−427
FePx (molten)	1475 - 1775	0.50	−347
FeSx (molten)	1775 - 1875	1.00	−307

a. Value of θ used for convenience on calculating Q value for the very dilute interstitial solution. b. Q corresponds to partial molar enthalpy of solution h(X) of X into Fe. Some h(X) values reported by McLellan and co-workers (da Silva, J. R. G and McLellan, R. B. (1976) The Solubility of Hydrogen in Super-pure-ron Single Crystals. J. Less Coomon Met., 50, 1 - 5.; McLellan, R. B. and Farraro, R. J. Thermodynamics of the Iron-Nitrogen System. (1980) Acta. Metall., 28, 417-422.) were in good accord with the corresponding values of Q. h(H)^α = −177 kJ・mol⁻¹: Q(H)^α = −171 kJ・mol⁻¹, h(C)^α = −603 kJ・mol⁻¹: Q(C)^α(T > T_C) = −613 kJ・mol⁻¹, Q(C)^α(T < T_C) = −648 kJ・mol⁻¹, h(C)^γ = −650 kJ・mol⁻¹: Q(C)^γ = −699 kJ・mol⁻¹, h(N)^α = −424 kJ・mol⁻¹: Q(N)^α = −420 kJ・mol⁻¹, h(N)^γ = −460 kJ・mol⁻¹: Q(N)^γ = −455 kJ・mol⁻¹, where T_C refers to Curie temperature 1043 K for Fe.

analysis in very dilute interstitial solution under certain circumstances as discussed in some detail in [15] .

First cases of statistical thermodynamic analysis for very dilute interstitial solutions was made in [11] in which a priori condition of constant was set to fulfill the condition

noting the reality that, in the very dilute interstitial compound, there must be no neighbouring interstitial atom around any interstitial atom.

However, when solutions of H, C and N in α-Fe was investigated in terms of statistical thermodynamics, unambiguous specification of θ to fulfill condition (12) was difficult but, instead, when θ value was taken to be greater than certain threshold value, estimated value of Q converged to a constant level whereas, in the range of θ smaller than the threshold level, estimated value of Q showed steady variation with varying θ (cf. Figure 2 in [15] ). On account of this situation, unique specification of θ was given up for some very dilute interstitial compounds and, as a compromising solution, θ value which must have been greater than the threshold level was used for the analysis because, by so doing, realistic value for Q was evaluated as discussed in [15] although value of the product Zf_X varied as a function of θ in the range of θ where Q value became constant with θ.

3.2. Atom Clustering in Fe 1−y M y X x around X Atom

During the course of statistical thermodynamic analysis of PTC relationships reported for N solution in molten Fe_1−yM_y in which affinity of M to N is stronger than that of Fe to N, it was concluded that certain types of atom clustering might develop around interstitial N atom [19] [24] [26] . This aspect shall be reviewed in the following.

As always in this line of statistical thermodynamic analysis, θ parameter values on analysis of molten Fe_1−yCr_yN_x for varying y were determined accepting an a priori assumption of constant over homogeneity composition of Fe_1−yCryNx as reproduced in Figure 2 and, by the statistical thermodynamic

Figure 2

Relationship between θ and y in molten Fe 1−y Cr y N x to fulfill the a priori condition of constant over homogeneity composition range at arbitrary T (reproduced from Figure 3 .57 in [ 2 ] or Figure 4 in [ 24 ] )

analysis done with the θ values determined as such, values of R ln Zf_N(Fe_1−yCr_yN_x) (a) and Q(Fe_1−yCr_yN_x) (b) were obtained as a function of y as reproduced in Figure 3. In spite of somewhat peculiar variation pattern of θ with y (Figure 2), variation patterns of Q and R ln Zf_N with respect to y looked quite “regular” (Figure 3). In this analysis, molten Fe_1−yCr_yN_x at temperatures close to liquidus temperature above Fe_1−yCr_yN_x solid phase possessing fcc structure was assumed to hold fcc structure. In the range of low y not exceeding 0.2, θ varied following

For this range of θ (<0.2), the interpretation was quite simple. That is, N atom in an O site was assumed to become surrounded by one Cr atom and 5 Fe atoms (1 Cr/5 Fe cluster or Cr-N dipole) as depicted in Figure 4(a). Q values determined

Figure 3

Estimated values of R ln Zf N [J・K −1 ・mol −1 ] (a) and Q [kJ・mol −1 ] (b) for molten Fe 1−y Cr y N x plotted as a function of y. In Figure 2 (b), positions of values of Q estimated from proportional sum of = −72 [kJ・mol −1 ] and = −93 [kJ・mol −1 ] at various satom ratios of Cr to Fe are given by horizontal dotted line (reproduced from Figure 3 .58 in [ 2 ] or Figure 5 in [ 24 ] )

Figure 4

Possible atom clusters formed in fcc Fe 1−y Cr y N x lattice in which affinity of M to N is stronger than that of Fe to N. (a) 1 M/5 Fe cluster (composed of one M atom and five Fe atoms around N); θ = y, (b) 2 M/4 Fe cluster; θ = y/2 and (c) 4 M/2 Fe cluster, θ = y/4 (reproduced from Figure 3 .59 in [ 2 ] or Figure 3 in [ 26 ] )

in the range of y smaller than 0.20 was consant with y being represented approxi- mately by

where refers to interaction energy (≈−93 [kJ・mol⁻¹]) in molten CrN_x and N-Fe interaction (≈−72 [kJ・mol⁻¹]) in molten FeN_x [2] [24] .

On the other hand, it was felt difficult to appreciate rationally the variation pattern of θ with y in the range of y higher than 0.4 at first glance. However, as seen in Figure 3, Q values determined in the range of 0.4 ≤ y < 1 was consant with y being represented approximately by

implying formation of 4 Cr/2 Fe cluster as depicted in Figure 4(c).

Detected deviation of θ vs. y relationship from the one represented by

in Figure 2 was interpreted to be the consequence of Guinier-Preston zone type planar extensiton of 4 Cr/2 Fe clusters as detected in Figure 4(c).

To explain why θ vs. y relationship in range of y between 0.4 and 0.9 in Figure 2 deviated from the relationsip defined by Equation (16), model Guinier-Preston zone type planar extensions of 4 M/2 Fe clusters for a fixed numnber 12 of M atoms leading to different values of θ are depicted in Figure 5. As seen in Figure 5(b) and Figure 5(c), increased degree of planar extensiton would yield higher value of θ than the one anticipated from Equation (16) defined for the isolated 4 M/2 Fe clusters depcited in Figure 5(a).

It is intriguing to note that no evidence of existence of 2 M/4 Fe cluster as depicted in Figure 4(b) was detected for A_1−yB_yX_x type interstitial non-stopichio- metric compounds analyzed so far.

3.3. Design Guideline for H Permeable Alloy Membrane

Yukawa and collaborators at Nagoya University [51] [52] [53] experimentally

Figure 5

Some possible ways of planar extention of the 4 M/2 Fe cluster depicted in Figure 3 (c) over the (002) plnae of fcc lattice leading to different values of θ with a fixed number of 12 M atoms. (a) isolated clusters, θ = y/4, (b) planar extensiton leading to θ = (5/12)y and (c) planar extenstion leading to θ = (6/12)y = y/2 (reproduced from Figure 3 .60 in [ 2 ] or Figure 4 in [ 26 ] )

investigated H permeation behaviors as well as H absorption behaviors for Va-group metal-based alloy membranes. The author [44] [47] analyzed the reported PCT relationships by Yukawa and collaborators [49] [50] [51] and obtained values for parameters, Q and R ln Zf_H, as summarized in Table 2.

According to Yukawa and co-workers, Va-group metal-based alloys identified as favuorable H permeation membrane includes V_0.95Fe_0.05 [49] , Nb_0.95Ru_0.05 and Nb_0.95W_0.05 [50] as well as Ta_0.95W_0.05 [51] . Looking at values of θ and Q for these A_1−yM_y type alloys containing Va-group metal (represented by A) in Table 2, it is noticed that θ was smaller and Q was more negative in this group of alloys than those in pure Va-group metal A except Ta_0.95W_0.05. Thus, it was proposed [48] to use the simultaneous fulfillment of conditions

for screening of H permeation alloy membrane from among the candidate alloys

Table 2

Available statistical thermodynamic interaction parameter for bcc A 1−y M y H x that showed suppressed H solubility compared to that in bcc AH x where A refers to Va-group metals (V, Nb or Ta) (reproduced from Table 1 in [ 48 ] )

bcc A1−yMyHx	θ	Qa	R ln ZfH
		[kJ・mol−1]	[J・K−1・mol−1]
VHx	0.55	−223.6	64.7
V0.96Cr0.04Hx	0.525	−220.0	26.9
V0.916Cr0.084Hx	0.475	−207.2	54.5
V0.949Mo0.051Hx	0.525	−207.3	37.5
V0.95Fe0.05Hx	0.45	−229.4	23.7
V0.948Co0.052Hx	0.45	−230.1	21.5
NbHx	0.75	−229.5	61.7
Nb0.95Ru0.05Hx	0.55	−221.8	41.2
Nb0.95W0.05Hx	0.725	−243.1	14.1
Nb0.90Mo010Hx	0.45	−225.5	65.4
Nb0.80Mo0.20Hx	0.30	−228.2	61.3
Nb0.70Mo0.30Hx	0.20	−220.8	67.7
Nb0.95Al0.05Hx	0.60	−225.8	36.9
Nb0.95Cu0.05Hx	0.60	−223.5	41.2
Nb0.95Sn0.05Hx	0.60	−231.8	30.6
Nb0.95Ni0.05Hx	0.60	−219.2	45.0
Nb0.95Pd0.05Hx	0.60	−231.8	26.1
Nb0.90Pd0.10Hx	0.45	−213.9	45.5
TaHx	0.55	−229.4	62.4
Ta0.95W0.05Hx	0.55	−228.6	32.1

a. Q values of θ for A_1−yM_yH_x that were evaluated to be more negative than that for AH_x are displayed with bold letter.

based on Va-group metal.

On H permeation process, H₂ gas pressure p(H₂)ⁱⁿ on the inlet side of the membrane is set higher than p(H₂)^out on the outlet side. On the inlet side of the membrane, adsorbed H₂ gas over the membrane surface must be subjected to dissociation into adsorbed monatomic H atoms before being absorbed into A_1−yM_y alloy lattice

Then, by concentration gradient along the membrane thickness, absorbed H in the A_1−yM_y lattice is subjected to diffusion towards the outlet side of the membrane. On the reaction (20) to proceed at the inlet side of the membrane, condition (18) is certainly favourable to suck faster the H atoms into the A_1−yM_x lattice from the inlet side surface.

Then, on release of the transported H atoms through the outlet side surface of the A_1−yM_y membrane, successive inverse reactions, (19) and (20) in this order, must proceed to recombine the absorbed monatomic H atoms in the A_1−yM_yX_x alloy lattice to be released in form of diatomic H₂ gas molecules. For this process of H₂ release to take place faster on the outlet side of the membrane surface, condition (17) is considered to be of convenience.

As such, simultaneous fulfillment of conditions, (17) and (18), was appreciated as rational for the alloy design guideline for Va-group metal-based H permeation membrane although this criterion did not seem to apply to Ta_0.95W_0.05 alloy.

Among Va-group metal-based alloys listed in Table 2, V_0.948Co_0.052, Nb_0.95Sn_0.05 and Nb_0.95Pd_0.05 fulfill the conditions, (17) and (18), simultaneously although the H permeation performance of these alloys remains unknown.

3.4. Constant-a(C) Curves in γ-FeC x Phase

On account of pragmatic industrial importance of steel materials, intensive efforts have been invested on characterizing basic phase relationship for Fe-C binary system in equilibrium state. Taking advantage of abundance of equilibrium data for binary Fe-C system with high qualitative precision, statistical thermodynamic analysis for Fe-C system [20] was done choosing experimental data reported by Ban-ya et al. [54] in which chemical activity a(C) of C in equilibrium with γ-FeC_x was varied widely through control of p(CO)/p(CO₂) ratio instead of using C in solid state.

In common experimental equilibrium study of metal carbide, excess graphite (reference state of C) is arranged to co-exist in the synthesized carbide MC_x. Under such condition, a(C) is fixed to be 1 and, as such, influence of a(C) on x in MC_x cannot be evaluated.

From the statistical thermodynamic analysis, values of θ and Q listed for γ-FeC_x in Table 1 were calculated and constant-a(C) curves as reproduced in Figure 6 were drawn [20] . This presentation of Figure 6 might be of no practical industrial importance but must be of fundamental significance towards profound

Figure 6

Binary Fe-C equilibrium phase diagram compiled by Hansen and Anderko <7> with the estimated constant-a(C) curves and some available experimental results <4>, <5>, <8>, <9> (reproduced from Figure 1 in [ 20 ] ). <4> Ban-ya, S, Elliott, J. F. and Chipman, J. (1969) Activity of Carbon in Fe-C Alloys at 1150˚C. Trans. Metall. Soc. AIME, 245, 1199 - 1206; <5> Ban-ya, S., Elliott, J. F. and Chipman, J. (1970) Thermodynamics of Austenitic Fe-C Alloys, Metall. Trans., 1, 1313 - 1320; <7> Hansen, M. and Anderko, K. (1958) Constitution of Binary Alloys, 2nd Ed., McGraw-Hill, New York, Tronto and London; <8> Chipman, J. (1970) Thermodynamics of Liquid Fe-C Solutions, Metall. Trans., 1, 2163 - 2168; <9> Chipman, J. (1972) Thermodynamics and Phase Diagram of the Fe-C System. Metall. Trans., 3, 55-64

understanding for inherent nature of interstitial non-stoichiometric compounds like γ-FeC_x.

4. Conclusions

A few example cases of estimating properties of interstitial non-stoichiometric compounds with potential industrial applications on the basis of atomic interaction parameters evaluated by statistical thermodynamic analysis were demonstrated in this review article. Looking at the variation pattern of θ parameter value referring to number of available interstitial sites per metal atom M (M might be pure M, A_1−yB_y type substitutional alloy or AZ_z type compound containing another interstitial constituent Z besides interstitial constituent X) with respect to change of y or z, significant insight in atom clustering tendency in the condensed phase might be gained. There are several other materials properties predictable by referring to statistical thermodynamic analysis results including interstitial site occupation information for intermetallic alloys. Interested readers are advised to refer to original papers by the author [8] [12] [18] to look into further details.

The reviewed standardized statistical thermodynamic analysis procedure accepting an a priori assumption of constant in MX_x within homogeneity composition range at arbitrary T was proved applicable to interstitial compound holding metallic characteristics but this analysis procedure is not applicable to non-stoichiometric compounds with ionic bonding characteristics like non-stoichiometric oxide.

Compared with standardized conventional thermodynamic analysis procedure to determine enthalpy, entropy and a few types of free energies through well-established mathematical procedure, statistical thermodynamic analysis is quite tedious demanding reliable PCT data set at least at three different T levels over certain range of p(X₂) and additional necessity for composing realistic statistical model. This is certainly a drawback of statistical thermodynamic analysis compared with conventional thermodynamics but this feature of statistical thermodynamic approach might be considered as a merit in some sense as the evaluated interaction parameters possess unambiguous physical significance provided that the statistical model used for the analysis is a valid one.

Acknowledgements

The author would like to thank sincerely Prof. Dr. Masahiro KATSURA who introduced the statistical thermodynamic analysis procedure to the author during the years of apprenticeship at Department of Nuclear Engineering, Faculty of Engineering, Osaka University in 1970s through reading together the classical text book on statistical thermodynamics authored by Fowler and Guggenheim.

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4. Shohoji, N. (1983) Comments on “Hysteresis in Metal Hydrides”. Journal of the Less Common Metals, 90, L5-L6. https://doi.org/10.1016/0022-5088(83)90129-7

5. Shohoji, N. (1983) On the Construction of a Statistical Model for Primary Solid Solutions of Hydrogen in the Group Va Transition Metals (Vanadium, Niobium and Tantalum). Journal of the Less Common Metals, 90, L27-L29. https://doi.org/10.1016/0022-5088(83)90082-6

6. Shohoji, N. (1983) Statistical Thermodynamic Approach to Some Hyperstoichiometric Dihydrides of Lanthanides (La, Ce, Pr, Nd, Sm) and Actinides (Np, Pu, Am). Physica Status Solidi (B), 118, 811-822. https://doi.org/10.1002/pssb.2221180238

7. Shohoji, N. (1983) Statistical Thermodynamics of Hydrogen Solution in Some Lanthanides. Physica Status Solidi (B), 119, K87-K90. https://doi.org/10.1002/pssb.2221190169

8. Shohoji, N. (1984) Statistical Thermodynamics of Metal-Hydrogen Systems. Journal of the Less Common Metals, 102, 53-65. https://doi.org/10.1016/0022-5088(84)90388-6

9. Shohoji, N. (1985) Statistical Model for the Hydrogen Solution in bcc Nb_1-yM_yAlloys (M = Al, Cu, Sn, Ni, Pd). Materials Letters, 3, 206-208. https://doi.org/10.1016/0167-577X(85)90056-4

10. Shohoji, N. (1985) Statistical Thermodynamics of Carbon Solutions in Metals. Materials Chemistry and Physics, 13, 567-575. https://doi.org/10.1016/0254-0584(85)90006-9

11. Shohoji N. ,et al. (1985)Statistical Thermodynamics of the Very Dilute Interstitial Solid Solutions Zeitschrift fur Metallkunde 76, 192-197.

12. Shohoji, N. (1985) The Application of Statistical Thermodynamics to Interstitial Solid Solutions. Journal of the Less Common Metals, 114, 249-256. https://doi.org/10.1016/0022-5088(85)90443-6

13. Shohoji, N. (1985) Statistical Thermodynamic Study of the Ternary Compounds ThXyHx (X = C, N; y < 1, x < 2). Journal of Nuclear Materials, 127, 88-96. https://doi.org/10.1016/0022-3115(85)90064-9

14. Shohoji, N. (1986) Interaction between Hydrogen Atoms in Metals. Journal of Materials Science Letters, 5, 522-524. https://doi.org/10.1007/BF01728678

15. Shohoji, N. (1986) Comparative Study of Solubilities of Hydrogen, Nitrogen and Carbon in Iron. Journal of Materials Science, 21, 2147-2152. https://doi.org/10.1007/BF00547962

16. Shohoji N. ,et al. (1986)Statistical Thermodynamic Analysis of Phosphorus Solubility in Molten Iron Transactions of the Iron and Steel Institute of Japan 26, 194-197.

17. Shohoji, N. (1986) Statistical Thermodynamics of Sulphur Solution in Molten Iron. Transactions of the Iron and Steel Institute of Japan, 26, 547-550. https://doi.org/10.2355/isijinternational1966.26.547

18. Shohoji, N. (1986) Statistical Thermodynamic Aspects of Hydrogen in Metals. Surface and Coatings Technology, 28, 365-382. https://doi.org/10.1016/0257-8972(86)90093-9

19. Shohoji, N. (1987) Statistical Model for Nitrogen Solution in Molten Iron and Molten Iron Alloys. Materials Science and Technology, 3, 43-48. https://doi.org/10.1179/mst.1987.3.1.43

20. Shohoji, N. (1987) Carbon Solubilities in Iron at Elevated Temperatures Analysed by Statistical Thermodynamics. Materials Science and Technology, 3, 404-410. https://doi.org/10.1179/mst.1987.3.6.404

21. Shohoji, N. and Marcelo, T. (1987) Tetragonality in Crystal Lattice of Zirconium Dihydride. Journal of Materials Science Letters, 6, 1251-1253. https://doi.org/10.1007/BF01794578

22. Shohoji, N. and Marcelo, T. (1987) Ordering of Carbon Atoms in Titanium Monocarbide. Materials Chemistry and Physics, 16, 475-488. https://doi.org/10.1016/0254-0584(87)90068-X

23. Shohoji, N. (1987) Estimation of Carbon-Metal Interaction in the Carbides of d-Transition Metals. Materials Chemistry and Physics, 17, 391-398. https://doi.org/10.1016/0254-0584(87)90089-7

24. Shohoji, N. (1988) Statistical Model for Molten Fe_1-yCr_yN_x (0.4 &le; y &le; 0.9). Materials Science and Technology, 4, 867-870. https://doi.org/10.1179/026708388790221160

25. Shohoji, N. and Botas, J. (1988) Glass-forming Ability of Multicomponent Alloys Viewed from a Statistical Thermodynamic Standpoint. Journal of Materials Science Letters, 7, 903-905. https://doi.org/10.1007/BF00720724

26. Shohoji, N. (1989) Clustering of Atoms in Molten Fe_1-yTi_yN_x. Materials Chemistry and Physics, 24, 163-174. https://doi.org/10.1016/0254-0584(89)90055-2

27. Shohoji, N. (1990) Stability of Interstitial Elements in Metal Lattice Evaluated by Statistical Thermodynamics. ISIJ International, 30, 472-474. https://doi.org/10.2355/isijinternational.30.472

28. Shohoji, N. and Katsura, M. (1990) Statistical Thermodynamic Appreciation of Decomposition of Metal Nitrides at Elevated Temperatures. Journal of Nuclear Materials, 170, 109-112. https://doi.org/10.1016/0022-3115(90)90333-I

29. Shohoji, N. (1991) Nitrogen Solution in Molten Fe_1-yM_y (M = Al, Mn) Analysed Using Statistical Thermodynamics. Materials Science and Technology, 7, 213-217. https://doi.org/10.1179/mst.1991.7.3.213

30. Monteiro Dias, M.C. and Shohoji, N. (1992) Stability of Hydrogen and Nitrogen in VIa-Group Metals (Cr, Mo, W) and Iron-Group Metals (Fe, Co, Ni) Evaluated by Statistical Thermodynamics. Journal of Materials Science, 27, 5154-5158. https://doi.org/10.1007/BF02403809

31. Shohoji, N. (1992) Statistical Model for Nitrogen Solution in Molten Iron Containing Another Interstitial Constituent (Carbon or Silicon). Materials Chemistry and Physics, 32, 153-159. https://doi.org/10.1016/0254-0584(92)90271-9

32. Monteiro Dias, M.C. and Shohoji, N. (1995) Atomic Configuration in Hexagonal-Close-Packed TiCzHx Phase Estimated by Statistical Thermodynamics. Materials Chemistry and Physics, 39, 193-199. https://doi.org/10.1016/0254-0584(94)01429-K

33. Shohoji, N. (1996) Statistical Thermodynamic Approach to Carbon Solubility in Face Centred Cubic Fe_1-yNi_y Alloy Lattice. Materials Science and Technology, 12, 373-377. https://doi.org/10.1179/026708396790165867

34. Monteiro Dias, M.C. and Shohoji, N. (1997) A Theory of Suppressed Nitrogen Solubility in Fe-Z-N Ternary Alloy Systems in the Relatively High Range of Concentrations of Z (Z = Si or C). Materials Chemistry and Physics, 50, 275-279. https://doi.org/10.1016/S0254-0584(97)01944-5

35. Shohoji, N. (1997) Carbon Solubility in Face Centred Cubic Co_1-yNi_y Alloy Lattice Analysed by Statistical Thermodynamics. Materials Chemistry and Physics, 51, 265-268. https://doi.org/10.1016/S0254-0584(97)80316-1

36. Shohoji N. ,et al. (2001)Atomic Clustering in Non-Stoichiometric Interstitial Alloy Systems Evaluated by Statistical Thermodynamics—Example Cases of Analysis of Short-Range Ordering for Molten Fe_1-yM_yN_x (M = Cr, Ti, V, Mn, Al) Advances in Materials Engineering Technology 1, 41-48.

37. Shohoji, N. (2001) Statistical Thermodynamics as a Tool for Evaluating Atom Clustering around Interstitial Atom. Materials Transactions, 42, 2225-2231. https://doi.org/10.2320/matertrans.42.2225

38. Shohoji, N. and Monteiro Dias, M.C. (2003) Statistical Thermodynamic Approach to Austenitic Fe_1-yNb_yN_xSystem. Materials Science and Technology, 19, 429-434. https://doi.org/10.1179/026708303225009319

39. Shohoji, N. (2003) Interaction Energy Parameters in Hypo-Stoichiometric Mono-Carbides, TiC_x and NbC_x, Evaluated by Statistical Thermodynamics. Materials Science and Technology, 19, 1469-1472. https://doi.org/10.1179/026708303225006033

40. Shohoji, N. (2004) M-C Dipole Formation in fcc (Face Centred Cubic) Fe_1-yM_yC_xSolid Solution (M = Ti, Nb). Materials Science and Technology, 20, 301-306. https://doi.org/10.1179/026708304225012297

41. Shohoji, N. and Monteiro Dias, M.C. (2005) Empirical Expression of Phosphorous Solubility in Molten Fe_1-yCr_y Expressed as Functions of Temperature and Phosphorous Activity. ISIJ International, 45, 1226-1231. https://doi.org/10.2355/isijinternational.45.1226

42. Shohoji, N. and Figueiredo Marques, S. (2008) Statistical Thermodynamic Approach to Molten Fe-Cr-P. International Journal of Materials Research, 99, 245-250.

43. Shohoji, N. (2010) Hydrogen Absorption in Epitaxial bcc V (001) Thin Films Analysed by Statistical Thermodynamics. Thin Solid Films, 518, 7167-7173. https://doi.org/10.1016/j.tsf.2010.06.052

44. Shohoji N. ,et al. (2012)Suppressed Hydrogen Solubility in Body Centred Cubic Va-Group Metal (Nb and Ta) by Alloying with W or Ru Analysed on the Basis of Statistical Thermodynamics International Journal of Materials Engineering and Technology 7, 33-54.

45. Shohoji, N. (2012) Statistical Thermodynamic Analysis for Hydrogen Absorption Behaviour in a Four Monolayers (4 ML) Thick bcc Vanadium (110) Superlattice being in Contact with Molybdenum Layer. Materials Transactions, 53, 1273-1277. https://doi.org/10.2320/matertrans.M2012071

46. Shohoji, N. (2012) Statistical Thermodynamic Analysis for Isothermal Hydrogenation Performances of Mg_2-yPr_yNi₄ Intermetallics (y = 0.6, 0.8, 1.0). International Journal of Materials and Chemistry, 2, 90-100. https://doi.org/10.5923/j.ijmc.20120203.02

47. Shohoji, N. (2016) Suppressed Hydrogen (H) Solubility in Body Centered Cubic Vanadium (V) by Alloying with Molybdenum (Mo), Chromium (Cr) or Cobalt (Co) Appreciated in Terms of Statistical Thermodynamics. Materials Transactions, 57, 321-328. https://doi.org/10.2320/matertrans.M2015415

48. Shohoji, N. (2016) Proposing Design Guideline for Hydrogen Permeation Membrane Alloy Based on Va-Group Metals (V, Nb and Ta) Taking into Account Atomic Interaction Energy Parameter Evaluated by Statistical Thermodynamics. International Journal of Materials Engineering and Technology, 15, 75-92. https://doi.org/10.17654/MT015010075

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51. Yukawa, H., Nambu, T., Matsumoto, Y., Watanabe, N., Zhang, G.X. and Morinaga, M. (2008) Alloy Design of Nb-Based Hydrogen Permeable Membrane with Strong Resistance to Hydrogen Embrittlement. Materials Transactions, 49, 2202-2207. https://doi.org/10.2320/matertrans.MA200805

52. Yukawa, H., Nambu, T. and Matsumoto, Y. (2011) Ta-W Alloy for Hydrogen Permeable Membranes. Materials Transactions, 52, 610-613. https://doi.org/10.2320/matertrans.MA201007

53. Suzuki, A., Yukawa, H., Ijiri, S., Nambu, T., Matsumoto, Y. and Murata, Y. (2015) Alloying Effects of Hydrogen Solubility and Hydrogen Permeability for V-Based Alloy Membranes. Materials Transactions, 56, 1688-1692. https://doi.org/10.2320/matertrans.MAW201511

54. Ban-Ya, S., Elliott, J.F. and Chipman, J. (1969) Activity of Carbon in Fe-C Alloys at 1150 &deg;C. Transactions of the Metallurgical Society of AIME, 245, 1199-1206.