Errors chemical

Romagnoli, J.A. and G. Stephanopoulos, Rectification of Process Measurement Data in the Presence of Gross Errors, Chemical Engineeiing Science, 36(11), 1981, 1849-186.3. 

For single rings (i.e. mononuclear systems) up to ten atoms in size, there is no question but that Hantzsch-Widman names are overwhelmingly the most widely used, and specialists can be presumed to recognize them readily. However, when one of the trivial names of Table 1 can be used, it prevails almost exclusively. Thiophene will be immediately understood by specialists and most nonspecialists, whereas thiole will distract the reader s attention from the chemistry while he considers the writer s intention is the Hantzsch-Widman system indeed being used, or is it a typographical error Chemical Abstracts also uses these trivial names in its indexes. 

D. K. Lorenzo, A Manager s Guide to Reducing Human Errors, Chemical Manfacturers Association, Washington, D.C., 1990, p. 18. 

Geyer, T. A., Bellamy, L. J., Astley, J. A., Hurst, N. W. (1990). Prevent Pipe Failures Due to Human Errors. Chemical Engineering Progress, November. 

In a gavage study where rats were administered 570, 1,140, or 4,000 mg/kg/day -hexanc for 90-120 days, 3 rats died due to gavage error (chemical pneumonitis immediately following dosing), but no other deaths were reported (Krasavage et al. 1980). 

Phase errors Chemical shifts also evolve during the application of a gradient pulse due to the static Bq field. Therefore, gradient pulses are generally applied within a spin-echo to refocus this evolution and thus remove phase errors when phase-sensitive displays are required. 

Mayer, I., Surjan, P. R. (1992). Monomer geometry relaxation and the basis set superposition error. Chemical Physics Letters, 191, 497-499. 

This method applies only to liquids whose constituents have reduced temperatures less than 1. The average error is about 10% the most important differences are observed in mixtures of components belonging to different chemical families. 

For precise measurements, diere is a slight correction for the effect of the slightly different pressure on the chemical potentials of the solid or of the components of the solution. More important, corrections must be made for the non-ideality of the pure gas and of the gaseous mixture. With these corrections, equation (A2.1.60) can be verified within experimental error. 

A completely difierent approach to scattering involves writing down an expression that can be used to obtain S directly from the wavefunction, and which is stationary with respect to small errors in die waveftmction. In this case one can obtain the scattering matrix element by variational theory. A recent review of this topic has been given by Miller [32]. There are many different expressions that give S as a ftmctional of the wavefunction and, therefore, there are many different variational theories. This section describes the Kohn variational theory, which has proven particularly useftil in many applications in chemical reaction dynamics. To keep the derivation as simple as possible, we restrict our consideration to potentials of die type plotted in figure A3.11.1(c) where the waveftmcfton vanishes in the limit of v -oo, and where the Smatrix is a scalar property so we can drop the matrix notation. 

Also, the result of any diffraction-based trial-and-error fitting is not necessarily unique it is always possible that there exists another untried structure that would give a better fit to experiment. Hence, a multi-teclmique approach that provides independent clues to the structure is very fniithil and common in surface science such clues include chemical composition, vibrational analysis and position restrictions implied by other structural methods. This can greatly restrict the number of trial structures which must be investigated. 

An observation of the results of cross-validation revealed that all but one of the compounds in the dataset had been modeled pretty well. The last (31st) compound behaved weirdly. When we looked at its chemical structure, we saw that it was the only compound in the dataset which contained a fluorine atom. What would happen if we removed the compound from the dataset The quahty ofleaming became essentially improved. It is sufficient to say that the cross-vahdation coefficient in-CTeased from 0.82 to 0.92, while the error decreased from 0.65 to 0.44. Another learning method, the Kohonen s Self-Organizing Map, also failed to classify this 31st compound correctly. Hence, we had to conclude that the compound containing a fluorine atom was an obvious outlier of the dataset. 

After selection of descriptors/NN training, the best networks were applied to the prediction of 259 chemical shifts from 31 molecules (prediction set), which were not used for training. The mean absolute error obtained for the whole prediction set was 0.25 ppm, and for 90% of the cases the mean absolute error was 0.19 ppm. Some stereochemical effects could be correctly predicted. In terms of speed, the neural network method is very fast - the whole process to predict the NMR shifts of 30 protons in a molecule with 56 atoms, starting from an MDL Molfile, took less than 2 s on a common workstation. 

Deserno M and C Holm 1998b. How to Mesh Up Ewald Sums. II. An Accurate Error Estimate for the Particle-Particle-Particle-Mesh Algorithm. Journal of Chemical Physics 109 7694-7701. 

This discussion may well leave one wondering what role reality plays in computation chemistry. Only some things are known exactly. For example, the quantum mechanical description of the hydrogen atom matches the observed spectrum as accurately as any experiment ever done. If an approximation is used, one must ask how accurate an answer should be. Computations of the energetics of molecules and reactions often attempt to attain what is called chemical accuracy, meaning an error of less than about 1 kcal/mol. This is suf-hcient to describe van der Waals interactions, the weakest interaction considered to affect most chemistry. Most chemists have no use for answers more accurate than this. 

The system of atomic units was developed to simplify mathematical equations by setting many fundamental constants equal to 1. This is a means for theorists to save on pencil lead and thus possible errors. It also reduces the amount of computer time necessary to perform chemical computations, which can be considerable. The third advantage is that any changes in the measured values of physical constants do not affect the theoretical results. Some theorists work entirely in atomic units, but many researchers convert the theoretical results into more familiar unit systems. Table 2.1 gives some conversion factors for atomic units. 

It is important to verify that the simulation describes the chemical system correctly. Any given property of the system should show a normal (Gaussian) distribution around the average value. If a normal distribution is not obtained, then a systematic error in the calculation is indicated. Comparing computed values to the experimental results will indicate the reasonableness of the force field, number of solvent molecules, and other aspects of the model system. 

As shown in Figure 4.12c, the limit of identification is selected such that there is an equal probability of type 1 and type 2 errors. The American Chemical Society s Committee on Environmental Analytical Chemistry recommends the limit of quantitation, (Sa)loq> which is defined as ... 

Accuracy When spectral and chemical interferences are minimized, accuracies of 0.5-5% are routinely possible. With nonlinear calibration curves, higher accuracy is obtained by using a pair of standards whose absorbances closely bracket the sample s absorbance and assuming that the change in absorbance is linear over the limited concentration range. Determinate errors for electrothermal atomization are frequently greater than that obtained with flame atomization due to more serious matrix interferences. 

When possible, quantitative analyses are best conducted using external standards. Emission intensity, however, is affected significantly by many parameters, including the temperature of the excitation source and the efficiency of atomization. An increase in temperature of 10 K, for example, results in a 4% change in the fraction of Na atoms present in the 3p excited state. The method of internal standards can be used when variations in source parameters are difficult to control. In this case an internal standard is selected that has an emission line close to that of the analyte to compensate for changes in the temperature of the excitation source. In addition, the internal standard should be subject to the same chemical interferences to compensate for changes in atomization efficiency. To accurately compensate for these errors, the analyte and internal standard emission lines must be monitored simultaneously. The method of standard additions also can be used. 

Despite the variety of methods that had been developed, by 1960 kinetic methods were no longer in common use. The principal limitation to a broader acceptance of chemical kinetic methods was their greater susceptibility to errors from uncontrolled or poorly controlled variables, such as temperature and pH, and the presence of interferents that activate or inhibit catalytic reactions. Many of these limitations, however, were overcome during the 1960s, 1970s, and 1980s with the development of improved instrumentation and data analysis methods compensating for these errors. ... 

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