Textural evolution in electrodeposits under the influence of adsorbed foreign species: Part I Textural evolution in iron electrodeposits affected by hydrogen co-deposition

Textural evolution in electrodeposits is strongly affected by foreign species in the electrolyte and also by the co-deposition of hydrogen. The effects of foreign species on textural development in electrodeposits were studied by employing a Monte Carlo model. This model is based on physical principles and incorporates parameters which are used to control electrodeposition processes. An attempt was made in the simulation to reflect the basic process of the deposit growth, and to identify the factors responsible for the texture formation and its variation with the deposition condition. It is assumed that the texture of the deposit results from the minimization of the free energy of the system. Based on this assumption, it was demonstrated that the surface-energy anisotropy played an important role in the formation of fibre texture. In particular, the model can be used to simulate textural evolution under the influence of adsorbed foreign species, because the surface-energy anisotropy is modified by the adsorbed foreign species. Part I of the paper presents results of our studies on iron electrodeposition with the emphasis on the effect of hydrogen adsorption on iron deposit texture. Relevant experimental results have also been presented to corroborate the simulation study. Part II of the paper presents simulation studies of textural evolution in copper deposits under the influence of adsorbed potassium and chloride ions. This revised version was published online in November 2006 with corrections to the Cover Date.     

A Markovian Extension of Valiant′s Learning Model

An "Occam algorithm" learning model maintains a tentative hypothesis consistent with past observations and, when a new observation is inconsistent with the current hypothesis, updates to the next-simplest hypothesis consistent with all observations. In previous work, observations were assumed to be stochastically independent. This paper initiates study of such models under weaker Markovian assumptions on the observations, In the special case where the sequence of hypotheses satisfies a monotonicity condition, it is shown that the number of mistakes in classifying the first t observations is O(√t log 1/π_i), where π_i is the stationary probability of the initial state, i, of the Markov chain.     

Modeling of current-voltage characteristics for strained andlattice matched HEMT's on InP substrate using a variational chargecontrol model

A model for the calculation of the current-voltage characteristics of strained In_0.52Al_0.48As/In_xGa_1-xAs on InP substrate High Electron Mobility Transistors (HEMT's), based on a variational charge control model, is presented. A polynomial fit of the two-dimensional electron gas (2DEG) density is used for the calculation of the current-voltage characteristics. The effect of strain is introduced into the 2DEG density versus gate voltage relation. Very good agreement between the calculated and measured I-V characteristics was obtained. In addition, our results show that, for an indium mole fraction of the In_xGa_1-xAs channel in the range 0.53-0.60, increasing the indium mole fraction lowers the threshold voltage and hence increases the drain current at the same gate bias     

Investigation of iron borate on the submillimeter waves

Antiferromagnetic resonance (AFMR) in iron borate at the frequency of 300 GHz at the room temperature in weak (down to 0.1T) external magnetic fieldH has been studied. The loss in AFMR line increased or decreased depending on the direction and magnitude ofH. Such properties ofFeBO ₃ monocrystals allows to design undirectional and modulation devices.     

Toward successful compliance with JCAHO standard NC.1

Recommendations resulting from a JCAHO survey can be a true blessing as they force nursing departments to assess critically their professional practice and documentation systems. Systematic preparation, begun at least two years prior to the survey, includes Nursing Administration, a Nursing Documentation Task Force and all staff nurses. Educational consultants assigned to each unit bring nurses up-to-date on nursing process and nursing diagnosis. Mock surveys and cross-training in chart review prepare staff nurses for confident participation in the accreditation process.