Posterpresentatie gegeven tijdens bezoek SBE (Samenwerkende Bedrijven Eemsdelta) aan de Hanzehogeschool
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Dit document bevat in grote lijnen de opzet van ZAP. Binnen Zernike Advanced Processing (ZAP) wordt de mogelijkheid gecreëerd voor het uitvoeren van opschalingsexperimenten op het gebied van bioprocestechnologie en groene chemie.
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Social media firestorms pose a significant challenge for firms in the digital age. Tackling firestorms is difficult because the judgments and responses from social media users are influenced by not only the nature of the transgressions but also by the reactions and opinions of other social media users. Drawing on the heuristic-systematic information processing model, we propose a research model to explain the effects of social impact (the heuristic mode) and argument quality and moral intensity (the systematic mode) on perceptions of firm wrongness (the judgment outcome) as well as the effects of perceptions of firm wrongness on vindictive complaining and patronage reduction. We adopted a mixed methods approach in our investigation, including a survey, an experiment, and a focus group study. Our findings show that the heuristic and systematic modes of information processing exert both direct and interaction effects on individuals’ judgment. Specifically, the heuristic mode of information processing dominates overall and also biases the systematic mode. Our study advances the literature by offering an alternative explanation for the emergence of social media firestorms and identifying a novel context in which the heuristic mode dominates in dual information processing. It also sheds light on the formulation of response strategies to mitigate the adverse impacts resulting from social media firestorms. We conclude our paper with limitations and future research directions.
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Currently, many novel innovative materials and manufacturing methods are developed in order to help businesses for improving their performance, developing new products, and also implement more sustainability into their current processes. For this purpose, additive manufacturing (AM) technology has been very successful in the fabrication of complex shape products, that cannot be manufactured by conventional approaches, and also using novel high-performance materials with more sustainable aspects. The application of bioplastics and biopolymers is growing fast in the 3D printing industry. Since they are good alternatives to petrochemical products that have negative impacts on environments, therefore, many research studies have been exploring and developing new biopolymers and 3D printing techniques for the fabrication of fully biobased products. In particular, 3D printing of smart biopolymers has attracted much attention due to the specific functionalities of the fabricated products. They have a unique ability to recover their original shape from a significant plastic deformation when a particular stimulus, like temperature, is applied. Therefore, the application of smart biopolymers in the 3D printing process gives an additional dimension (time) to this technology, called four-dimensional (4D) printing, and it highlights the promise for further development of 4D printing in the design and fabrication of smart structures and products. This performance in combination with specific complex designs, such as sandwich structures, allows the production of for example impact-resistant, stress-absorber panels, lightweight products for sporting goods, automotive, or many other applications. In this study, an experimental approach will be applied to fabricate a suitable biopolymer with a shape memory behavior and also investigate the impact of design and operational parameters on the functionality of 4D printed sandwich structures, especially, stress absorption rate and shape recovery behavior.
By transitioning from a fossil-based economy to a circular and bio-based economy, the industry has an opportunity to reduce its overall CO2 emission. Necessary conditions for effective and significant reductions of CO2-emissions are that effective processing routes are developed that make the available carbon in the renewable sources accessible at an acceptable price and in process chains that produce valuable products that may replace fossil based products. To match the growing industrial carbon demand with sufficient carbon sources, all available circular, and renewable feedstock sources must be considered. A major challenge for greening chemistry is to find suitable sustainable carbon that is not fossil (petroleum, natural gas, coal), but also does not compete with the food or feed demand. Therefore, in this proposal, we omit the use of first generation substrates such as sugary crops (sugar beets), or starch-containing biomasses (maize, cereals).
Electrohydrodynamic Atomization (EHDA), also known as Electrospray (ES), is a technology which uses strong electric fields to manipulate liquid atomization. Among many other areas, electrospray is currently used as an important tool for biomedical applications (droplet encapsulation), water technology (thermal desalination and metal recovery) and material sciences (nanofibers and nano spheres fabrication, metal recovery, selective membranes and batteries). A complete review about the particularities of this technology and its applications was recently published in a special edition of the Journal of Aerosol Sciences [1]. Even though EHDA is already applied in many different industrial processes, there are not many controlling tools commercially available which can be used to remotely operate the system as well as identify some spray characteristics, e.g. droplet size, operational mode, droplet production ratio. The AECTion project proposes the development of an innovative controlling system based on the electrospray current, signal processing & control and artificial intelligence to build a non-visual tool to control and characterize EHDA processes.
