Design and characterization of a flow reaction calorimeter based on FlowPlate® Lab and Peltier elements

Continuous manufacturing and development of flow processes depend significantly on an optimized and adapted determination of thermokinetic data of chemical reactions. Reaction calorimetry represents a prominent technique to quantify the heat release of exothermic reactions. This work presents a continuous flow calorimetric measurement system based on a commercially available hastelloy C-22 microreactor. A sensor array of Peltier elements is added to the existing microreactor setup to enable the additional functionality of flow calorimetry. The calorimeter and its additional equipment are connected to open-source soft- and hardware for data acquisition and processing as well as automated reaction screening. The reaction calorimeter can be operated in both isoperibolic and isothermal operation mode. The calorimeter's performance is investigated on the basis of model reactions, where good agreement with literature was obtained for determined reaction enthalpies

Concept for Predicting Vibrations in Machine Tools Using Machine Learning

Vibrations have a significant influence on quality and costs in metal cutting processes. Existing methods for predicting vibrations in machine tools enable an informed choice of process settings, however they rely on costly equipment and specialised staff. Therefore, this contribution proposes to reduce the modelling effort required by using machine learning based on data gathered during production. The approach relies on two sub-models, representing the machine structure and machining process respectively. A method is proposed for initialising and updating the models in production

The role of parental investments for cognitive and noncognitive skill formation : evidence for the first 11 years of life

This paper examines the impact of parental investments on the development of cognitive, mental and emotional skills during childhood using data from a longitudinal study, the Mannheim Study of Children at Risk, starting at birth. Our work offers three important innovations. First, we use reliable measures of the child’s cognitive, mental and emotional skills as well as accurate measures of parental investment. Second, we estimate latent factor models to account for unobserved characteristics of children. Third, we examine the skill development for girls and boys separately, as well as for children who were born with either organic or psychosocial risk. We find a decreasing impact of parental investments on cognitive and mental skills, while emotional skills seem to be unaffected by parental investment throughout childhood. Thus, initial inequality persists during childhood. Since families are the main sources of education during the first years of life, our results have important implications for the quality of the parent-child relationship