Pretreatment stage is usually a requirement for any adsorption based air separation process. Carbon dioxide and water vapor present in the atmosphere act as contaminants, deactivating adsorbents, particularly zeolites used in oxygen pressure swing adsorption processes. Such systems usually present one or more prelayers to ensure full removal of these two contaminants, protecting the oxygen/nitrogen selective layer. In the present study, two 13X-type zeolites-one activated alumina and one highly pure silica-are compared in terms of capacity for water vapor and carbon dioxide removal from air. Water and carbon dioxide adsorb irreversibly on these adsorbents up to a certain extension and then effective adsorption isotherms and breakthroughs curves were obtained. The effective properties were attained after three cycles under close to vacuum pressure swing adsorption conditions. A combination of two layers for the precolumns is suggested: the first, composed by either silica or alumina to remove most of the water without significant loss of cyclic adsorption capacity, and a second, composed by zeolite, to reduce the amount of water and carbon dioxide down to parts per million (ppm) levels. These should prevent contamination and consequent loss of efficiency in the nitrogen/oxygen selective layer.

Commercial adsorbents do not exhibit argon/oxygen equilibrium selectivity above 1. However, in the past decade, Air Products and Chemicals developed an argon/oxygen selective silver-based zeolite, AgLiLSX. In this contribution, the authors studied and characterized the AgLiLSX adsorbent to provide fundamental data to evaluate its potential for high-purity oxygen production in a single-stage PSA unit. Oxygen, nitrogen, and argon adsorption isotherms and breakthroughs curves were obtained, and moderate equilibrium selectivity (αN2/O2 = 4.98 and αAr/O2 = 1.14 at 1 bar and 25 °C), high working capacity (0.45 mol·kg–1 for nitrogen, between 1.4 and 0.2 bar at 25 °C), and superior performance were observed. The authors concluded that this adsorbent can allow the production of a 95+% oxygen stream in a single-stage PSA operation.

Amino resins are produced by two main processes: the strong acid process and the alkaline-acid process. Both use formaldehyde and a base (e.g. sodium hydroxide) in their formulation. In this work, Forward Interval Partial Least Squares methodology was applied to create prediction models for the determination of the concentration of formaldehyde and residual methanol (that is present in the formaldehyde solution) used in the production of amino resins. Near infrared (NIR) spectra were acquired at two different temperatures: 18 and 35°C. A Partial Least Squares calibration models were established with the measured values from reference methods: namely, sodium sulfite (formaldehyde) and gas chromatography (methanol). The performances of the best models were compared using the root mean square error of cross validation (RMSECV) and coefficient of determination for prediction (r2). The best results obtained a r2 above 0.994. The RMSECV values obtained were 0.063% (m/m) and 0.031% (m/m) for the formaldehyde and methanol concentration, respectively. External validation was performed using different formaldehyde solution samples. The NIR methodology presented in this work proved to be effective and enables a significant time reduction, when compared to the reference methods, in the measurement of formaldehyde and methanol concentrations.

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