Chemical thermodynamics simulations based

For experimental studies, a chemical thermodynamic modelling approach could theoretically reduce unnecessary experimental effort and hence the overall cost of a research project. Once experiments are underway, the computer simulation should also offer valuable assistance in the interpretation of results. Modelling techniques with particular reference to radionuclide speciation have been discussed by Cross and Day (1986) who pointed out that models are only as good as the thermodynamic data upon which they are based. For example, formation constants (a prerequisite for chemical modelling) are invariably generated in idealised laboratory conditions and their use seldom reflects the natural environment... 

The difficulties of experimentally determining the speciation of actinides present at very low concentrations in natural waters have encouraged the use of computer simulations, based on thermodynamic data, as a means of predicting their speciation and hence their environmental behaviour. The use of modelling techniques to describe the speciation, sorption, solubility and kinetics of inorganic systems in aqueous media has been reviewed in the papers given at an international conference in 1978. Both chemical equilibrium models, exemplified by computer programs such as MINEQL and SOLMNQ, and dynamic reaction path models, exemplified by EQ6, have been developed. Application of the equilibrium models to radioactive waste disposal... 

Moreover, most processes in the chemical industry are governed by nanoscale phenomena. In many cases the nanoscale structure plays an important role, e.g., the local concentrations and not the overall concentrations govern reactions at active sites of catalysts. Phenomenological thermodynamics provides no route to obtain insight in these nanoscale structures and processes, whereas molecular simulations based on forces fields do. The key is to carry them out with models that are suitably developed and reasonably represent the compounds. 

The general formalism for thermodynamic simulation methods follows from early work by Zwanzig [33], and provides a tool for the computation of thermodynamic properties, AA, AE and AS, as well as barriers for chemical processes occurring on long timescales [34]. These methods take on several guises in present implementations. The two approaches which we will describe are termed thermodynamic cycle perturbation theory (TP) [35] and thermodynamic integration (TI) [36]. Both of the methods are based on the definition of a hybrid Hamiltonian which represents some mixture of the initial state (1) and final state (2) of the system [37]. If /.represents the coordinate describing the pathway used to interconvert the two systems, then the hybrid Hamiltonian may be defined by [35, 37]. 

For the equihbrium properties and for the kinetics under quasi-equilibrium conditions for the adsorbate, the transfer matrix technique is a convenient and accurate method to obtain not only the chemical potentials, as a function of coverage and temperature, but all other thermodynamic information, e.g., multiparticle correlators. We emphasize the economy of the computational effort required for the application of the technique. In particular, because it is based on an analytic method it does not suffer from the limitations of time and accuracy inherent in statistical methods such as Monte Carlo simulations. The task of variation of Hamiltonian parameters in the process of fitting a set of experimental data (thermodynamic and... 

The most important aspect of the simulation is that the thermodynamic data of the chemicals be modeled correctly. It is necessary to decide what equation of state to use for the vapor phase (ideal gas, Redlich-Kwong-Soave, Peng-Robinson, etc.) and what model to use for liquid activity coefficients [ideal solutions, solubility parameters, Wilson equation, nonrandom two liquid (NRTL), UNIFAC, etc.]. See Sec. 4, Thermodynamics. It is necessary to consider mixtures of chemicals, and the interaction parameters must be predictable. The best case is to determine them from data, and the next-best case is to use correlations based on the molecular weight, structure, and normal boiling point. To validate the model, the computer results of vapor-liquid equilibria could be checked against experimental data to ensure their validity before the data are used in more complicated computer calculations. 

A second obvious line of research for the future must be that related to the development and improvement of computer-based simulation of long-term environmental behaviour of radionuclides. Most currently available models are still comparatively simple compared with the physical, chemical and biological complexity of environments they purport to represent but, as noted in Section 13.5, our ability to construct ever more complex conceptual models for predicting the future behaviour of radionuclides is improving. However, the more complex the model, the more demands it places on the basic thermodynamic data and knowledge of likely speciation. The challenge for the future will therefore be to produce high-quality data for model construction and to devise realistic ways to validate those models once produced. 

All of the above Europan simulations were done at 1.01 bar (1 atm) total pressure. A 100-km ice-covered ocean on Europa would have a pressure >1200 bars at the base of the ocean. What effect would such a high pressure have on chemical equilibria and the thermodynamic properties of such a Europan ocean How might pressure affect the likely composition of seafloor sedimentary deposits, the chemistry of possible hydrothermal brines,... 

The past three decades have witnessed the development of three broad techniques—molecular dynamics (MD), Monte Carlo (MC), and cellular automata simulations—that approach the study of molecular systems by simulating submicroscopic chemical events at this intermediate level. All three methods focus attention on a modest number of molecules and portray chemical phenomena as being dependent on dynamic, and interactive events (a portrayal consistent with our scientific intuition and a characteristic not intrinsic to either thermodynamics or the traditional deterministic approach based on differential equations). These techniques lend themselves to a visual portrayal of the evolution of the configurations of the systems under study. Because each approach has its own particular advantages and shortcomings, one must take into consideration the pros and cons of each, especially in light of the nature of the problem to be solved. 

Table 8.1 describes the steps of the methodology in more detail. The procedure starts with the Problem definition production rate, chemistry, product specifications, safety, health and environmental constraints, physical properties, available technologies. Then, a first evaluation of feasibility is performed by an equilibrium design. This is based on a thermodynamic analysis that includes simultaneous chemical and physical equilibrium (CPE). The investigation can be done directly by computer simulation, or in a more systematic way by building a residue curve map (RCM), as explained in the Appendix A. This step will identify additional thermodynamic experiments necessary to consolidate the design decisions, mainly phase-equilibrium measurements. Limitations set by chemical equilibrium or by thermodynamic boundaries should be analyzed here. 

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