Andrei F. Kazakov

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.

Fiber laser welding of dual-phase galvanized sheet steel (DP590): traditional analysis and new quality assessment techniques

Laser welding has many advantages over traditional joining methods, yet remains underutilized. NIST has undertaken an ambitious initiative to improve predictions of weldability, reliability, and performance of laser welds. This study investigates butt welding of galvanized and ungalvanized dual-phase automotive sheet steels (DP 590) using a 10 kW commercial fiber laser system. Parameter development work, hardness profiles, microstructural characterization, and optical profilometry results are presented. Sound welding was accomplished in a laser power range of 2.0 kW to 4.5 kW and travel speed of 2000 mm/min to 5000 mm/min. Vickers hardness ranged from approximately 2 GPa to 4 GPa across the welds, with limited evidence of heat affected zone softening. Decreased hardness across the heat affected zone directly correlated to the appearance of ferrite. A technique was developed to non-destructively evaluate weld quality based on geometrical criteria. Weld face profilometry data were compared between light optical, metallographic sample, and frequency-modulated continuous-wave laser detection and ranging (FMCW LADAR) methods.

Efficient Estimation of Formation Enthalpies for Closed-Shell Organic Compounds with Local Coupled-Cluster Methods

Efficient estimation of the enthalpies of formation for closed-shell organic compounds via atom-equivalent-type computational schemes and with the use of different local coupled-cluster with single, double, and perturbative triple excitation (CCSD(T)) approximations was investigated. Detailed analysis of established sources of uncertainty, inclusive of contributions beyond frozen-core CCSD(T) and errors due to local CCSD(T) approximations and zero-point energy anharmonicity, suggests the lower limit of about 2 kJ·mol-1 for the expanded uncertainty of the proposed estimation framework. Among the tested computational schemes, the best-performing cases demonstrate expanded uncertainty of about 2.5 kJ·mol-1, based on the analysis against 44 critically evaluated experimental values. Computational efficiency, accuracy commensurable with that of a typical experiment, and absence of the need for auxiliary reactions and additional experimental data offer unprecedented advantages for practical use, such as prompt validation of existing measurements and estimation of missing values, as well as resolution of experimental conflicts. The utility of the proposed methodology was demonstrated using a representative sample of the most recent experimental measurements.