Author(s)

Nobumitsu Shohoji

LEN-Laboratório de Energia, LNEG-Laboratório Nacional de Energia e Geologia, Lisboa, Portugal.

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 X₂ 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(X₂) of X₂ 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-yB_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

Shohoji, N. (2017) Characterizing Atomic Interactions in Interstitial Non-Stoichiometric Compounds by Statistical Thermodynamics: Engineering Usage of Estimated Values of Statistical Thermodynamic Parameters. Journal of Modern Physics, 8, 365-381. doi: 10.4236/jmp.2017.83025.