Relation between integral and partial properties of ternary solutions along different composition trajectories

The relations between partial and integral properties of ternary solutions along composition trajectories suggested by Kohler, Colinet and Jacob, and along an arbitrary path are derived. The chemical potentials of the components are related to the slope of integral free energy by expressions involving the binary compositions generated by the intersections of the composition trajectory with the sides of the ternary triangle. Only along the Kohler composition trajectory it is possible to derive the integral free energy from the variation of the chemical potential of a single component with composition or vice versa. Along all other paths the differential of the integral free energy is related to two chemical potentials. The Gibbs-Duhem integration proposed by Darken for the ternary system uses the Kohler isogram. The relative merits of different limits for integration are discussed.

Thermodynamic modeling to analyse composition of carbonaceous coatings of MnO and other oxides of manganese grown by MOCVD

Equilibrium thermodynamic analysis has been applied to the low-pressure MOCVD process using manganese acetylacetonate as the precursor. ``CVD phase stability diagrams'' have been constructed separately for the processes carried out in argon and oxygen ambient, depicting the compositions of the resulting films as functions of CVD parameters. For the process conduced in argon ambient, the analysis predicts the simultaneous deposition of MnO and elemental carbon in 1: 3 molar proportion, over a range of temperatures. The analysis predicts also that, if CVD is carried out in oxygen ambient, even a very low flow of oxygen leads to the complete absence of carbon in the film deposited oxygen, with greater oxygen flow resulting in the simultaneous deposition of two different manganese oxides under certain conditions. The results of thermodynamic modeling have been verified quantitatively for low-pressure CVD conducted in argon ambient. Indeed, the large excess of carbon in the deposit is found to constitute a MnO/C nanocomposite, the associated cauliflower-like morphology making it a promising candidate for electrode material in supercapacitors. CVD carried out in oxygen flow, under specific conditions, leads to the deposition of more than one manganese oxide, as expected from thermodynamic analysis ( and forming an oxide-oxide nanocomposite). These results together demonstrate that thermodynamic analysis of the MOCVD process can be employed to synthesize thin films in a predictive manner, thus avoiding the inefficient trial-and-error method usually associated with MOCVD process development. The prospect of developing thin films of novel compositions and characteristics in a predictive manner, through the appropriate choice of CVD precursors and process conditions, emerges from the present work.

Automatic decomposition of unstructured meshes employing genetic algorithms for parallel FEM computations

Parallel execution of computational mechanics codes requires efficient mesh-partitioning techniques. These mesh-partitioning techniques divide the mesh into specified number of submeshes of approximately the same size and at the same time, minimise the interface nodes of the submeshes. This paper describes a new mesh partitioning technique, employing Genetic Algorithms. The proposed algorithm operates on the deduced graph (dual or nodal graph) of the given finite element mesh rather than directly on the mesh itself. The algorithm works by first constructing a coarse graph approximation using an automatic graph coarsening method. The coarse graph is partitioned and the results are interpolated onto the original graph to initialise an optimisation of the graph partition problem. In practice, hierarchy of (usually more than two) graphs are used to obtain the final graph partition. The proposed partitioning algorithm is applied to graphs derived from unstructured finite element meshes describing practical engineering problems and also several example graphs related to finite element meshes given in the literature. The test results indicate that the proposed GA based graph partitioning algorithm generates high quality partitions and are superior to spectral and multilevel graph partitioning algorithms.

Identification of delamination in composite beams using spectral estimation and a genetic algorithm

An efficient strategy for identification of delamination in composite beams and connected structures is presented. A spectral finite-element model consisting of a damaged spectral element is used for model-based prediction of the damaged structural response in the frequency domain. A genetic algorithm (GA) specially tailored for damage identification is derived and is integrated with finite-element code for automation. For best application of the GA, sensitivities of various objective functions with respect to delamination parameters are studied and important conclusions are presented. Model-based simulations of increasing complexity illustrate some of the attractive features of the strategy in terms of accuracy as well as computational cost. This shows the possibility of using such strategies for the development of smart structural health monitoring softwares and systems.

Machine-tool selection and operation allocation in FMS: solving a fuzzy goal-programming model using a genetic algorithm

The decision-making process for machine-tool selection and operation allocation in a flexible manufacturing system (FMS) usually involves multiple conflicting objectives. Thus, a fuzzy goal-programming model can be effectively applied to this decision problem. The paper addresses application of a fuzzy goal-programming concept to model the problem of machine-tool selection and operation allocation with explicit considerations given to objectives of minimizing the total cost of machining operation, material handling and set-up. The constraints pertaining to the capacity of machines, tool magazine and tool life are included in the model. A genetic algorithm (GA)-based approach is adopted to optimize this fuzzy goal-programming model. An illustrative example is provided and some results of computational experiments are reported.

Assessment of genetic diversity and identification of core collection in sandalwood germplasm using RAPDS

Sandalwood is an economically important aromatic tree belonging to the family Santalaceae. The trees are used mainly for their fragrant heartwood and oil that have immense potential for foreign exchange. Very little information is available on the genetic diversity in this species. Hence studies were initiated and genetic diversity estimated using RAPD markers in 51 genotypes of Santalum album procured from different geographcial regions of India and three exotic lines of S. spicatum from Australia. Eleven selected Operon primers (10mer) generated a total of 156 consistent and unambiguous amplification products ranging from 200bp to 4kb. Rare and genotype specific bands were identified which could be effectively used to distinguish the genotypes. Genetic relationships within the genotypes were evaluated by generating a dissimilarity matrix based on Ward's method (Squared Euclidean distance). The phenetic dendrogram and the Principal Component Analysis generated, separated the 51 Indian genotypes from the three Australian lines. The cluster analysis indicated that sandalwood germplasm within India constitutes a broad genetic base with values of genetic dissimilarity ranging from 15 to 91 %. A core collection of 21 selected individuals revealed the same diversity of the entire population. The results show that RAPD analysis is an efficient marker technology for estimating genetic diversity and relatedness, thereby enabling the formulation of appropriate strategies for conservation, germplasm management, and selection of diverse parents for sandalwood improvement programmes.

278. Studies on ass's milk: Composition

The total solids of samples of ass's milk ranged from 7·80 to 9·10, the solids-not-fat from 7·14 to 8·50, and the fat from 0·54 to 0·71%. The nitrogen distribution in ass's milk is: casein 39·5, albumin 35·0, globulin 2·7 and non-protein nitrogen 22·8% of the total nitrogen. Ass's milk contains: casein 0·70, albumin 0·62 and globulin 0·07%. The total protein content is 1·39%. Ass's milk is therefore characterized by a low casein, a low globulin and a high albumin content. The non-protein nitrogen consists of amino nitrogen 8·1, urea nitrogen 24·3 and uric acid 0·7 mg./100 ml. of milk. The urea content is twice that present in cow's milk. The mean chloride and lactose contents of the milk samples are 0·037 and 6·1% respectively. The average calcium and phosphorus content of ass's milk are 0·081 and 0·059% respectively. Half the calcium is ionic, and half is in colloidal form. The phosphorus distribution is: total acid soluble 84·0, acid soluble organic 38·5, easily hydrolysable ester 27·4, inorganic 46·0, and colloidal inorganic 23·0 % of the total phosphorus. The ratio of CaO: P2O5 is 1:1. 46 % of the total phosphorus is in ester form; this is high when compared with only 12 % in cow's milk; most of the phosphoric ester forms soluble barium salts, which is a distinguishing feature of ass's milk. The total sulphur content is 15·8 mg./100 ml. The fat has a penetrating odour and is coloured orange-yellow. It has an iodine value of about 86, which is much higher than that for human milk fat. The Reichert (9·5) and Kirschner values (5·7) are low. In general, the composition of ass's milk resembles that of human rather than of cow's milk.