Modeling, analysis and multi-objective optimization of an industrial batch process for the production of tributyl citrate

Water-Doped Brønsted Acidic Protic Ionic Liquids for Enhanced Tributyl Citrate Synthesis in a Two-Phase Esterification System

Tributyl citrate (TBC) plays a crucial role as a plasticizer, enhancing the flexibility of polymers such as polyvinyl chloride. Its biodegradability and non-toxic nature contribute to eco-friendly appeal, making it a preferred additive in diverse industries, including food packaging, medical devices, toys, and consumer goods. Herein, a method for the synthesis of TBC using inexpensive Brønsted acidic protic ionic liquids (ILs) in a two-phase reaction system is presented. The esterification process is carried out with high yield (>99 %), selectivity (up to 98 %) and short reaction time of 2 h. The catalyst in the form of IL shows excellent performance and stability, desirable for industrial applications.

Probabilistic Bayesian Deep Learning Approach for Online Forecasting of Fed-Batch Fermentation

The microbial fermentation process often involves various biological metabolic reactions and chemical processes. The mixed bacterial culture process of 2-keto-l-gulonic acid has strong nonlinear and time-varying characteristics. In this study, a probabilistic Bayesian deep learning approach is proposed to obtain a highly accurate and robust prediction of product formation. The Bayesian optimized deep neural network (BODNN) is utilized as basic model for prediction, the structural parameters of which are optimized. Then, the training datasets are classified into different categories according to the prior evaluation of prediction error. The final forecasting is a weighted combination of BODNN models based on the Bayesian hybrid method. The weights can be interpreted as Bayesian posterior probabilities and are computed recursively. The validation of 95 industrial batches is carried out, and the average root mean square errors are 1.51 and 2.01% for 4 and 8 h ahead prediction, respectively. The results illustrate that the proposed approach can capture the dynamics of fermentation batches and is suitable for online process monitoring.

Aconitic Acid Recovery from Renewable Feedstock and Review of Chemical and Biological Applications

Aconitic acid (propene-1,2,3-tricarboxylic acid) is the most prevalent 6-carbon organic acid that accumulates in sugarcane and sweet sorghum. As a top value-added chemical, aconitic acid may function as a chemical precursor or intermediate for high-value downstream industrial and biological applications. These downstream applications include use as a bio-based plasticizer, cross-linker, and the formation of valuable and multi-functional polyesters that have also been used in tissue engineering. Aconitic acid also plays various biological roles within cells as an intermediate in the tricarboxylic acid cycle and in conferring unique survival advantages to some plants as an antifeedant, antifungal, and means of storing fixed pools of carbon. Aconitic acid has also been reported as a fermentation inhibitor, anti-inflammatory, and a potential nematicide. Since aconitic acid can be sustainably sourced from renewable, inexpensive sources such as sugarcane, molasses, and sweet sorghum syrup, there is enormous potential to provide multiple streams of additional income to the sugar industry through downstream industrial and biological applications that we discuss in this review.

Applications of Multi-Objective Optimization to Industrial Processes: A Literature Review

Industrial processes provide several of the products and services required for society. However, each industry faces different challenges from different perspectives, all of which must be reconciled to obtain profitable, productive, controllable, safe and sustainable processes. In this context, multi-objective optimization has become a powerful tool to aid the decision-making mechanism in the synthesis, design, operation and control of such processes. The solution to the mathematical models provides the necessary tools to asses the system performance in terms of different metrics and evaluate the trade-offs between the objectives in conflict. The number of applications of multi- objective optimization in industrial processes is ample and each application has its own challenges. In the present literature review, a broad panorama of the applications in multi-objective optimization is presented, including future perspectives and open questions that still need to be addressed.

A survey on fractionation: the optimal control of distilling in batch and semibatch configurations

Since the middle of the last century, discussion about the operation of discontinuous fractionation to meet multifarious goals, such as product purity and recovery rate, by monitoring process variables including reflux or/and heat duty, is been on. The engineering practice showed intolerable events to occur; hereof the operation must be supervised, which makes it difficult to be in agreement with the batch distillation objectives. Hence, to uphold the effectuation of new operating policies into the industrial “know-how” techniques, different optimal control strategies can be conceived. The objective of this work is to offer a literature survey on the investigations of optimal control functioning for selected simple distillation column configurations employed in batch/semibatch distillation of homogeneous/reactive mixtures, as well as the approaches used in this regard. Available optimal control schemes have been reviewed in detail, emphasizing its major assets.