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Adsorption of Reactive Black 5 and Congo Red from aqueous solution by coffee waste modified with polyethylenimine was investigated. The removal percentages of both dyes increased with amount of polyethyleneimine in the modified adsorbent. Characterization revealed that polyethyleneimine modification improved the adsorbent surface chemistry, while slight improvement of adsorbent textural properties was also observed. The adsorbent’s excellent performance was demonstrated by high removal percentages towards the anionic dyes in most experimental runs. The modelling result showed that anionic dyes adsorption occurred via monolayer adsorption, and chemisorption was the rate-controlling step. The adsorbent possesses higher maximum adsorption capacity towards Reactive Black 5 (77.52 mg/g) than Congo Red (34.36 mg/g), due to the higher number of functional groups in Reactive Black 5 that interact with the adsorbent. This study reveals the potential of adsorbent derived from coffee waste in textile wastewater treatment. Furthermore, surface chemistry modification is proven as an effective strategy to enhance the performance of biowaste-derived adsorbents.

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Flash point has safety implications and is therefore used to ascertain associated explosion hazards and fire of a flammable solution. Technological advances in the synthesis of new blends and chemical waste handlers have created a high demand for the flash point database and the flash point estimation methods of flammable liquid mixtures have become important. The present study reviewed the estimation model of the flammable liquid mixture flash point. These models are based on the following parameters: (1) either a normal boiling point or a composition range, (2) molecular structure (molecular descriptors), and (3) vapor pressure. Models based on boiling points or the composition ranges are empirically obtained using a mathematical regression method or an artificial neural network (ANN) approach. The quantitative structure–property relationship (QSPR) method is used to analyze the relationship between the flash point and the molecular structures that exist in a flammable mixture. Vapor-pressure-based models, which were formulated using Le Chatelier’s rule are more reliable, compared to other prediction models. However, the prediction efficiencies of these vapor-pressure-based models for nonideal mixtures are strongly depend on the accuracy of the activity coefficient models used. Several activity coefficient models are discussed at the end of this paper. In summation, there is no universal flash point prediction model for all flammable mixtures.

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