Kenneth Kroenlein

ThermoData Engine (TDE): software implementation of the dynamic data evaluation concept. 3. Binary mixtures.

ThermoData Engine (TDE) is the first full-scale software implementation of the dynamic data evaluation concept, as reported in this journal. The present paper describes the first application of this concept to the evaluation of thermophysical properties for ternary chemical systems. The method involves construction of Redlich-Kister type equations for individual properties (excess volume, thermal conductivity, viscosity, surface tension, and excess enthalpy) and activity coefficient models for phase equilibrium properties (vapor-liquid and liquid-liquid equilibrium). Constructed ternary models are based on those for the three pure component and three binary subsystems evaluated on demand through the TDE software algorithms. All models are described in detail, and extensions to the class structure of the program are provided. Reliable evaluation of properties for the binary subsystems is essential for successful property evaluations for ternary systems, and algorithms are described to aid appropriate parameter selection and fitting for the implemented activity coefficient models (NRTL, Wilson, Van Laar, Redlich-Kister, and UNIQUAC). Two activity coefficient models based on group contributions (original UNIFAC and NIST-KT-UNIFAC) are also implemented. Novel features of the user interface are shown, and directions for future enhancements are outlined.

ThermoData Engine (TDE): Software Implementation of the Dynamic Data Evaluation Concept. 5. Experiment Planning and Product Design§

ThermoData Engine (TDE) is the first full-scale software implementation of the dynamic data evaluation concept, as reported recently in this journal. In the present paper, we describe development of an algorithmic approach to assist experiment planning through assessment of the existing body of knowledge, including availability of experimental thermophysical property data, variable ranges studied, associated uncertainties, state of prediction methods, and parameters for deployment of prediction methods and how these parameters can be obtained using targeted measurements, etc., and, indeed, how the intended measurement may address the underlying scientific or engineering problem under consideration. A second new feature described here is the application of the software capabilities for aid in the design of chemical products through identification of chemical systems possessing desired values of thermophysical properties within defined ranges of tolerance. The algorithms and their software implementation to achieve this are described. Finally, implementation of a new data validation and weighting system is described for vapor-liquid equilibrium (VLE) data, and directions for future enhancements are outlined.

ThermoData Engine (TDE): software implementation of the dynamic data evaluation concept. 8. Properties of material streams and solvent design.

ThermoData Engine (TDE) is the first full-scale software implementation of the dynamic data evaluation concept, as reported in this journal. The present paper describes the first application of this concept to the evaluation of thermophysical properties for material streams involving any number of chemical components with assessment of uncertainties. The method involves construction of Redlich-Kister type equations for individual properties (excess volume, thermal conductivity, viscosity, surface tension, and excess enthalpy) and activity-coefficient models for phase equilibrium properties (vapor-liquid equilibrium). Multicomponent models are based on those for the pure-components and all binary subsystems evaluated on demand through the TDE software algorithms. Models are described in detail, and extensions to the class structure of the program are provided. Novel program features, such as ready identification of key measurements for subsystems that can reduce the combined uncertainty for a particular stream property, are described. In addition, new product-design features are described for selection of solvents for optimized crystal dissolution, separation of binary crystal mixtures, and solute extraction from a single-component solvent. Planned future developments are summarized.

Uncertainty assessment of equations of state with application to an organic Rankine cycle

ABSTRACT Evaluations of equations of state (EoS) should include uncertainty. This study presents a generic method to analyse EoS from a detailed uncertainty analysis of the mathematical form and the data used to obtain EoS parameter values. The method is illustrated by comparison of Soave–Redlich–Kwong (SRK) cubic EoS with perturbed-chain statistical associating fluid theory (PC-SAFT) EoS for an organic Rankine cycle (ORC) for heat recovery to power from the exhaust gas of a marine diesel engine using cyclopentane as working fluid. Uncertainties of the EoS input parameters including their corresponding correlation structure, are quantified from experimental measurements using a bootstrap method. Variance-based sensitivity analysis is used to compare the uncertainties from the departure function and the ideal-gas contribution. A Monte Carlo procedure propagates fluid parameter input uncertainty onto the model outputs. Uncertainties in the departure function (SRK or PC-SAFT EoS) dominate the total uncertainties of the ORC model output. For this application and working fluid, SRK EoS has less predictive uncertainty in the process model output than does PC-SAFT EoS, though it cannot be determined if this is due to differences in the data for parameter estimation or in the mathematical form of the EoS or both.

Aqueous Ion Trapping and Transport in Graphene-Embedded 18-Crown-6 Ether Pores

Using extensive room-temperature molecular dynamics simulations, we investigate selective aqueous cation trapping and permeation in graphene-embedded 18-crown-6 ether pores. We show that in the presence of suspended water-immersed crown-porous graphene, K+ ions rapidly organize and trap stably within the pores, in contrast with Na+ ions. As a result, significant qualitative differences in permeation between ionic species arise. The trapped ion occupancy and permeation behaviors are shown to be highly voltage-tunable. Interestingly, we demonstrate the possibility of performing conceptually straightforward ion-based logical operations resulting from controllable membrane charging by the trapped ions. In addition, we show that ionic transistors based on crown-porous graphene are possible, suggesting utility in cascaded ion-based logic circuitry. Our results indicate that in addition to numerous possible applications of graphene-embedded crown ether nanopores, including deionization, ion sensing/sieving, and energy storage, simple ion-based logical elements may prove promising as building blocks for reliable nanofluidic computational devices.