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Computer-Aided Experiments

1 Computer-Aided Experiments Computers have become common tools for the analysis of NMR data as Fourier transform spectrometers have replaced CW instruments. These computers perform the basic processing of data, including digital filtering, Fourier transformation, and phase correction. [Pg.487]

Time domain filtering is based upon a simple mathematical manipulation. FID are multiplied by the term C,  [Pg.487]

Frequency domain filtering is carried out by using the polynomial filters where each point x, is replaced by x  [Pg.488]

The term a (n = —N. iV) is a series of coefficients defining the filter. The most common of these filters is the moving-average filter defined by [Pg.488]

Linear prediction is a method to directly obtain the resonance frequencies and relaxation rates from time domain signals, which are a superposition of exponents, by solving the characteristic polynomials. Phases and intensities are calculated interactively using a least-squares procedure. The correlation spectroscopy of a two-dimensional NMR spectrometer employs several specific programs such as RELAY and TOCSY. The recognition of response peaks, the isolations of signals from noise and artifacts, and the spectral position (e.g., chemical shift) are all carried out by computers. [Pg.488]


J. Finkle, Computer Aided Experiments Interfacing to Minicomputers, John Wiley and Sons, New York, 1975. [Pg.448]

P. G. Khalatur and Yu. G. Papulov, "Computer-Aided Experiment in the Conformational Analysis of Polymers, Kalinin. Gos. Univ., Kalinin, USSR, 1982. [Pg.281]

It has been a long way from the early pulse radiolysis experiments where pictures were taken from the oscilloscope screen, via the first application of a computer to record experimental curves, to today s computer-aided kinetic experiments. Such a computer-aided experiment should feature easy performance, precision in calculating data, and, most importantly, should eliminate human error. However, a certain standard in data acquisition hardware is also required, such as depicted in Fig. 5 for the simultaneous recording of two channels. The hardware for processing the electrical signals is the same for both channels allowing various detectors, such as photomultipliers, semiconductor photodiodes, or circuits for detecting conductometric... [Pg.110]

In running the experiment, averaging data in order to improve signal-to-noise ratio is one of the most important features of computer-aided experiments. During the last few years several results have only become possible by extensive signal averaging. One has to keep in mind that most pulse radiolysis experiments utilize concentrations of a few micromol and that absorptivity is already very low, so low that it extends beyond the limits of commercially available steady-state photospectrometer. In some cases quite a few of averages need to be performed because noise reduction is proportional to the square root of the number of experiments. [Pg.112]

The particular advantages of CGMDE found in computer aided experiments important for a process monitoring system are ... [Pg.154]

Kennard R W and L A Stone 1969. Computer Aided Design of Experiments. Technometrics 11 137 148. [Pg.739]

Both the need to reduce experimental costs and increasing reHabiHty of mathematical modeling have led to growing acceptance of computer-aided process analysis and simulation, although modeling should not be considered a substitute for either practical experience or reHable experimental data. [Pg.139]

Computer-aided flow-simulation programs are also available for dies. All the programs can successfully predict a certain amount of shrinkage under specific conditions that can be applied to experience. The actual shrinkage is finally determined after molding or extruding the products. When not in spec process control changes can meet the requirements unless some drastic error had been included in the analysis. [Pg.443]

In order for us to effectively develop and use these new tools, we must make the transition from an empirical, retrospective use of modeling to a planned design approach. The question to be addressed should not be Why didn t this experiment work Rather, we need a prospective outlook Can this work These new theoretical tools should be bringing new information to the chemist to be used in conjunction with experimental data already available. The success of computer aided design of chemicals will arrive when a chemist can sit at the terminal as the first step in the development process. [Pg.38]

This problem was first approached in the work of Denisov [59] dealing with the autoxidation of hydrocarbon in the presence of an inhibitor, which was able to break chains in reactions with peroxyl radicals, while the radicals produced failed to contribute to chain propagation (see Chapter 5). The kinetics of inhibitor consumption and hydroperoxide accumulation were elucidated by a computer-aided numerical solution of a set of differential equations. In full agreement with the experiment, the induction period increased with the efficiency of the inhibitor characterized by the ratio of rate constants [59], An initiated inhibited reaction (vi = vi0 = const.) transforms into the autoinitiated chain reaction (vi = vio + k3[ROOH] > vi0) if the following condition is satisfied. [Pg.500]

Kennard, R. W., Stone, L. A. Technometrics 11, 1969, 137-148. Computer-aided design of experiments. [Pg.206]

A series of computer aids for the control of polymer processing will be discussed, emphasizing the practical aspects of choosing the proper tool for the application. Where possible, examples of production, or at least developmental experience, will be included. Because there are a variety of processes used in polymer processing, the advantages and disadvantages of each method will be discussed in the context of the types of processes. [Pg.442]

Evensen, E., Joseph-McCarthy, D., Weiss, G. A., Schreiber, S. L., Karplus, M. (2007) Ligand design by a combinatorial approach based on modeling and experiment application to HLA-DR4. J Comput Aided Mol Des 21, 395—418. [Pg.251]

The use of computed spectra to bolster structural assignments has seen heavy use in matrix isolation experiments. This is a slightly atypical example, insofar as the species involved actually require some careful attention to non-dynamical correlation, but represents an excellent example of how theory can aid experiment in the identification of short-lived reactive species. [Pg.351]


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