Lithium ion clusters Li
+ with n ranging up to 19 have been observed from liquid lithium ion sources by using a magnetic mass analyzer. The ion intensity as a function of cluster size showed local maxima at n=7, 9, 13, and 19. Only n=9 and 19 can be explained by the electronic shell model, which successfully predicts magic numbers of other alkali metal (Na, K) clusters. On the other hand, the geometrical atom packing model explains the observed magic numbers except for n=9.
The contribution of substituent groups to the extractability of phenols and benzoic acids was examined by using a substituent constant, n, derived from the distribution coefficients of nonionic substances. This constant is defined as nx=log KD(x)-log KD(H), where KD(x) is the distribution coefficient of a derivative and log KD(H) is that of the parent compound. The substituent constants of the groups at the ortho-position of phenol were found to vary with a variation of the extraction solvent, possibly due to competition between the hydration and solvation of an organic solvent. From the KD values of the phenols and benzoic acids determined between chloroform and water, the substituent constants of halogeno, cyano, trifluoromethyl and nitro groups were calculated. In phenols, the m values of the ortho-substituting group (ic°) were greater than those of the mew-and para-substituting group, irm and np, respectively, whereas in benzoic acids i° are smaller than xm and np. Such results can be explained by a masking effect and the overlapping effect: the masking effect increases the n° values, whereas the overlapping effect decreases the n° values. A method for predicting the total n values of di-and tri-substituted phenols and benzoic acids is proposed.
Our thermodynamic approach to the study and design of robust optimal control processes in nonlinear (in general global unstable) dynamic systems used soft computing based on genetic algorithms with a fitness function as minimum entropy production. Control objects were nonlinear dynamic systems involving essentially nonlinear stochastic differential equations. An algorithm was developed for calculating entropy production rate in control object motion and in control systems. Part 1 discusses relation of the Lyapunov function (measure of stability) and the entropy production rate (physical measure of controllability). This relation was used to describe the following qualitative properties and important relations: dynamic stability motion (Lyapunov function), Lyapunov exponent and Kolmogorov-Sinai entropy, physical entropy production rates, and symmetries group representation in essentially nonlinear systems as coupled oscillator models. Results of computer simulation are presented for entropy-like dynamic behavior for typical benchmarks of dynamic systems such as Van der Pol, Duffing, and Holmes-Rand, and coupled oscillators. Parts 2 and 3 discuss the application of this approach to simulation of dynamic entropy-like behavior and optimal benchmark control as a 2-link manipulator in a robot for service use and nonlinear systems under stochastic excitation.
In this paper, an L-band transmitter and receiver MMIC, which is known as a core chip for phased array communication and radar applications is presented. The MMIC is fabricated in 0.18 μm SiGe-BiCMOS process, comprises an RX amplifier, a 5-bit active phase shifter, SPDT switches, and a TX amplifier. The RX amplifier realized low noise and high linearity with dual bias-feed techniques. The measurement results show, in receive mode, a gain of 25.5 dB, a noise figure of 1.9 dB, and an input P1dB of -16 dBm in L-band. The MMIC is capable of providing 32 phase states from 0° to 360°, with an RMS phase error of lower than 2.3° and an RMS gain error of lower than 0.5dB. In transmit mode, the gain of 32 dB, and the saturated output power of 15 dBm are achieved.
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