The Quaternary System Acetic Acid–Chloroform–Acetone–Water at 25°C.

Brancker, A. V.; Hunter, T. G.; Nash, A. W.

doi:10.1021/j150402a001

Cited by 26 publications

(8 citation statements)

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“…This method was used (Brancker et al, 1941) to predict equilibrium data for the system acetic acid-acetone-chloroform-water, and the results were in excellent agreement with the experimental values reported earlier by Brancker et al (1940). However, the method has apparently been verified for only two other Type I quaternary systems.…”

Section: Literature Citedsupporting

confidence: 75%

Prediction of Quaternary Liquid Equilibria

Conti¹,

Riebling²

1967

Ind. Eng. Chem. Fund.

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Section: Literature Citedsupporting

confidence: 75%

Prediction of Quaternary Liquid Equilibria

Conti¹,

Riebling²

1967

Ind. Eng. Chem. Fund.

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“…It is now well established that phase equilibrium data for three-component and single solvent-oil systems can be used to forecast solvent extraction results. Since it has been shown here and in a previous publication (1) that phase equilibrium data for four-component and double solvent-oil systems can be readily handled, the forecasting of extraction results for such cases may be placed on an equally sound basis.…”

Section: Chloro-aceticmentioning

confidence: 89%

Mixed Solvent Extraction

Brancker¹,

Hunter²,

Nash³

1941

Ind. Eng. Chem.

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General information of the conditions under which 18-8 stainless steels corrode aids in establishing conditions to minimize failure in this and similar steels. Detailed study was made of the effect of temperature, concentration, and pH of aerated sodium chloride solutions, noting the nature of corrosion and corrosion rate for 24-hour periods. Corrosion of 18-8 increases sharply with temperature, going through a maximum at approximately 90°C. for 4 and 10 per cent sodium chloride and above 90°C. for 1 per cent solution. Corrosion is by pitting. At the boiling point corrosion decreases to nearly zero in 24-hour tests owing to lack of dissolved oxygen.Increased salt concentration at 90°C. increases corrosion of 18-8 from zero in distilled water to a maximum at 4 per cent sodium chloride. Identical tests with mild steel show significant corrosion in distilled water and maximum corrosion in 2 per cent sodium chloride. At higher concentrations corrosion is less, dropping off more rapidly for mild steel. In 25 per cent solution the corrosion rates of 18-8 by pitting and mild steel by uniform solution approach each other. At 90°C. in 4 per cent sodium chloride the logarithm of corrosion weight loss is a linear function of pH in the range pH 12 to 8. Corrosion falls off rapidly below pH 5, goes through a minimum at 2.9 to 4.5, and increases sharply at 2.9. Pitting is observed above pH 2.8, and uniform solution accompanied by hydrogen evolution occurs in more acid solutions. The number of pits per square decimeter follow the minimum and Vol. 33, No. 7 maximum of corrosion plotted with pH. Maximum pit penetration occurs at pH 6 to 7.The effects of pH in the alkaline region are explained on the basis of increasing effective cathode areas surrounding the pits with decrease in pH. The corrosion minimum is accounted for by partial breakdown of passivity. The sharp upturn of corrosion at pH 2.9 is due to corrosion by hydrogen evolution.The results indicate that at 90°C. corrosion of 18-8 in aerated sodium chloride solutions is less if the solutions are made acid to pH 3 or 4. Least corrosion occurs in the alkaline region of pH 12.

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“…This is a very well-known system, with several equilibrium data sets available in the literature. The experimental data used in this example are from Bancroft and Hubard, Brancker and Hunter, Reinders and De Minjer, and Ruiz and Prats, all of them also reported by Sørensen and Artl . Figure shows the experimental tie lines of these four data sets.…”

Section: Thermodynamic Applicationsmentioning

confidence: 99%

Effect of Systematic and Random Errors in Thermodynamic Models on Chemical Process Design and Simulation: A Monte Carlo Approach

Vásquez

Whiting

1999

Ind. Eng. Chem. Res.

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A Monte Carlo method is presented to separate and study the effects of systematic and random errors present in thermodynamic data on chemical process design and simulation. From analysis of thermodynamic data found in the literature, there is clear evidence of the presence of systematic errors, in particular, for liquid−liquid equilibria data. For systematic errors, the data are perturbed systematically with a rectangular probability distribution, and to analyze random errors, the perturbation is carried out randomly with normal probability distributions. Thermodynamic parameters are obtained from appropriate regression methods and used to simulate a given unit operation and to obtain cumulative frequency distributions, providing a quantitative risk assessment and a better understanding of the role of uncertainty in process design and simulation. The results show that the proposed method can clearly distinguish when one type of error is more significant. Potential applications are safety factors, process modeling, and experimental design.

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The Quaternary System Acetic Acid–Chloroform–Acetone–Water at 25°C.

Cited by 26 publications

References 1 publication

Prediction of Quaternary Liquid Equilibria

Prediction of Quaternary Liquid Equilibria

Mixed Solvent Extraction

Effect of Systematic and Random Errors in Thermodynamic Models on Chemical Process Design and Simulation: A Monte Carlo Approach

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