Synthesis Cost Functions

The synthesis tool performs optimization by minimizing cost functions - one for design rule costs and the other for optimization costs. These cost values are usually displayed during optimization. The optimization cost function consists of four parts in the following order of importance  

Min delay cost is second in priority after max delay in cost calculation. The min delay cost calculation is independent of path groups. It is the sum of all the worst min.delay violators. The min delay violation is calculated as the difference between the expected delay and the actual delay. A violation occurs when the expected delay is greater than 

Max power cost is only in the case of ECL technology. It is simply the difference between the current power and the max power specified. A violation implies that the former exceeds the later. Synopsys introduced DesignPower, a power estimation capability for CMOS technology and is due to introduce a power optimzation tool in the future. The discussion of these is beyond the scope of this book. 

Max Area cost has the least priority in cost calculation. By default, the tool does not optimize for area once the timing constraints are met. In other words, if explicit area constraints are specified, DC performs area optimization. Since synthesis results are dependent to a large extent on a number of factors such as constraints, libraries and coding styles, optimization of a design is an iterative process. 

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The objective function used in the zero effluent synthesis formulation is the minimisation of cost. The cost function is defined in constraint (8.62). The cost in... 

Unlike polybenzimidazole-based thermo-oxidatively stable supports, polyimides can be prepared under relatively mild conditions from starting materials of only low or modest cost [7,8], Polyimide particulates were prepared in a bead form without functional [9,10], We now report the synthesis of functional polyimide beads and their use as epoxidation catalyst supports. The presence of the functional group in the polyimides allows further chemical exploitation, particularly as a catalyst support capable of operating under rather severe oxidative conditions. 

One of the primary factors slowing the growth of functional polymers has been the relative complexity and cost of their preparation. The synthesis of functional polymers is often made difficult because of chemical or phase incompatibilities or antagonisms. This chapter surveys the general methods for functional polj er syntheses. It reviews the scope and limtations of functionalization by direct polymerization (e.g. anionic, cationic, free radical and organometallic methods), as weU as post-polymerization bulk and surface modification of preformed backbones. 

Diaz, F. C., Alba, J. L., and Banga, E. R. A neural network approach for the design of the target cost function in unit-selection speech synthesis. n Proceedings of Eurospeech 2005 (2005). 

Hirschfeld, D. Comparing static and dynamic features for segmental cost function calculation in concatenative speech synthesis. In Proceedings of the International Conference on Spoken Language Processing 2000 (2000). 

M Lee, D. P. L., and Olive, J. P. A text-to-speech platform for variable length optimal unit searching using perceptual cost functions. In Proceedings of the Fourth ISCA Workshop on Speech Synthesis (2001). 

Hyunchul Shin and Nam S. Woo, A Cost Function Based Optimization Technique for Scheduling in Data Path Synthesis , Proc. ofICCD 89, pages 424-427, October 1989. 

In the current manufacturing process, only -15% of the total labor cost derives from synthesis, since the majority of work is associated with HPLC purification, postpurification processing, multiple in-process quality control analyses, final product analyses, and comprehensive documentation, as needed in the context of current Good Manufacturing Practices (GMP). Further scale-up of solid-phase synthesis could reduce synthesis labor to only -5% of the total synthesis cost, which would therefore be almost entirely a function of the raw materials consumed, i.e., 200/g of a hypothetical purified 21 mer. 

Combinatorial. Combinatorial methods express the synthesis problem as a traditional optimization problem which can only be solved using powerful techniques that have been known for some time. These may use total network cost direcdy as an objective function but do not exploit the special characteristics of heat-exchange networks in obtaining a solution. Much of the early work in heat-exchange network synthesis was based on exhaustive search or combinatorial development of networks. This work has not proven useful because for only a typical ten-process-stream example problem the alternative sets of feasible matches are cal.55 x 10 without stream spHtting. 

Historically, the discovery of one effective herbicide has led quickly to the preparation and screening of a family of imitative chemicals (3). Herbicide developers have traditionally used combinations of experience, art-based approaches, and intuitive appHcations of classical stmcture—activity relationships to imitate, increase, or make more selective the activity of the parent compound. This trial-and-error process depends on the costs and availabiUties of appropriate starting materials, ease of synthesis of usually inactive intermediates, and alterations of parent compound chemical properties by stepwise addition of substituents that have been effective in the development of other pesticides, eg, halogens or substituted amino groups. The reason a particular imitative compound works is seldom understood, and other pesticidal appHcations are not readily predictable. Novices in this traditional, quite random, process requite several years of training and experience in order to function productively. 

Because of the high functional values that polyimides can provide, a small-scale custom synthesis by users or toU producers is often economically viable despite high cost, especially for aerospace and microelectronic appHcations. For the majority of iudustrial appHcations, the yellow color generally associated with polyimides is quite acceptable. However, transparency or low absorbance is an essential requirement iu some appHcations such as multilayer thermal iusulation blankets for satellites and protective coatings for solar cells and other space components (93). For iutedayer dielectric appHcations iu semiconductor devices, polyimides having low and controlled thermal expansion coefficients are required to match those of substrate materials such as metals, ceramics, and semiconductors usediu those devices (94). 

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