Empirical design of slot-die having shallow reservoir for thin-film printed electronics

Slot-die coating plays an important role in printed electronics, which are fabricated by stacking thin films and patterns. As electronic devices are being required to have higher performance, the importance of coating uniformity cannot be overestimated in the slot-die coating. The coating uniformity consists of two directions: nozzle direction, which is affected by the interior design of the head, and machine direction, which is majorly related to exterior operating conditions. In this research, the empirical design procedure of a slot-die head is proposed. The internal resistance values of the slot-die were calculated using the experimental parameter obtained through a coating experiment, and the acquired resistances were reflected in the modeling of the interior design of the slot-die head. The hanger type reservoir was adapted to minimize the consumption of ink. After fabricating the slot-die head, coating experiments were carried out using PEDOT:PSS ink. The resulting deviation of the coating thickness was within ±1.7%, thus proving that the proposed design predicted the uniformity of the actual thickness of the coating correctly. The significance of the slot-die design method presented in this paper is that it is based on the experimental equation that can be readily applied to the printed electronics industry.

Predictive and correlative techniques for the design, optimisation and manufacture of solid dosage forms

There is much interest in predicting the properties of pharmaceutical dosage forms from the properties of the raw materials they contain. Achieving this with reasonable accuracy would aid the faster development and manufacture of dosage forms. A variety of approaches to prediction or correlation of properties are reviewed. These approaches have variable accuracy, with no single technique yet able to provide an accurate prediction of the overall properties of the dosage form. However, there have been some successes in predicting trends within a formulation series based on the physicochemical and mechanical properties of raw materials, predicting process scale-up through mechanical characterisation of materials and predicting product characteristics by process monitoring. Advances in information technology have increased predictive capability and accuracy by facilitating the analysis of complex multivariate data, mapping formulation characteristics and capturing past knowledge and experience.