Measurement of Gibbs energies of formation of CoF2 and MnF2 using a new composite dispersed solid electrolyte

Gibbs energies of formation of CoF₂ and MnF₂ have been measured in the temperature range from 700 to 1100 K using Al₂O₃-dispersed CaF₂ solid electrolyte and Ni+NiF₂ as the reference electrode. The dispersed solid electrolyte has higher conductivity than pure CaF₂ thus permitting accurate measurements at lower temperatures. However, to prevent reaction between Al₂O₃ in the solid electrolyte and NiF₂ (or CoF₂) at the electrode, the dispersed solid electrolyte was coated with pure CaF₂, thus creating a composite structure. The free energies of formation of CoF₂ and MnF₂ are (± 1700) J mol⁻¹; {fx37-1} The third law analysis gives the enthalpy of formation of solid CoF₂ as ΔH° (298·15 K) = −672·69 (± 0·1) kJ mol⁻¹, which compares with a value of −671·5 (± 4) kJ mol⁻¹ given in Janaf tables. For solid MnF₂, ΔH°(298·15 K) = − 854·97 (± 0·13) kJ mol⁻¹, which is significantly different from a value of −803·3 kJ mol⁻¹ given in the compilation by Barinet al.     

Self-similarity in diffraction by a self-similar fractal screen

Using the Sierpinski gasket as an example, it has been shown here that the paraxial Fraunhoffer-zone diffracted field of a self-similar fractal screen also exhibits self-similarity. This also establishes that fractal structures can be used with great profit in problems involving array syntheses. Recently, it has been shown that the Sierpinski gasket is itself a member of a much wider class of gaskets, and the potential for the use of fractal structures in electromagnetic (EM) problems may be vast indeed.     

An Investigation into Glucose as a Potential Precursor of N-Nitrosothiazolidine in Bacon

The possible involvement of glucose in the formation of N-nitrosothiazolidine (NTHZ) in bacon was investigated by pumping pork bellies with brines containing added glucose (2 and 4%). Raw bacon samples processed with glucose had significantly lower levels of N-nitrosothiazolidine-4-carboxylic acid than the smoked control bacons. When the bacon samples with glucose were fried for 6 and 12 min, no NTHZ was detected in the fried products. N-Nitrosopyrrolidine (NPYR) levels in these samples were much lower than those in the fried control samples. Results of this study demonstrate that the contribution of glucose to NTHZ formation in bacon is minimal relative to that of formaldehyde in the wood smoke.     

Partitioning for pseudo-exhaustive testing is NP-complete

In the letter, two schemes of circuit partitioning for pseudo-exhaustive testing are described. The complexities of both are proved to be NP-complete.     

The low process yield of some PNP power transistors

A study is presented of the symptoms of the devices in a slice of PNP power transistors with a poor yield. The failure modes over the slice are analysed. In specific areas the electrical characteristics and optical appearance of the devices were studied and failure statistics are presented. The low yield is ascribed to cracks in the phosphosilicate glass used for the base diffusion. The effect of these cracks is just visible in the optical and scanning electron microscope.     

Convergence of genetic algorithms

The mean convergence of various versions of a genetic algorithm are considered. A number of convergence statements are formulated and relevant estimates are obtained. A hypothesis concerning the form of these estimates under variation of the structure of a genetic algorithm is put forward. Roman Riviyanovich Sharapov. Born 1981. Graduated from the Faculty of Mechanics and Mathematics, Ural State University, in 2003. Presently, a postgraduate at the Department of Mathematical Economics at the same university. Scientific interests: genetic algorithms, neural networks, and financial mathematics. Aleksandr Vyacheslavovich Lapshin. Born 1980. Graduated from the Faculty of Mechanics and Mathematics, Ural State University, in 2003. Presently, a postgraduate at the Department of Mathematical Economics at the same university. Scientific interests: financial mathematics, genetic algorithms, and neural networks.