This is an open access article under the terms of the Creative Commons Attribution License, which permits use, distribution and reproduction in any medium, provided the original work is properly cited. Dedicated to Prof. Dr.-Ing. Matthias Kraume on the occasion of his 65th birthday Oxygen supply in aerobic bioprocesses is of crucial importance. For this reason, this paper presents the oxygen demand of different cells and summarizes experimental and numerical possibilities for the determination of oxygen transfer in bioreactors. The focus lies on the volumetric oxygen mass transfer coefficient (k L a) calculation using computational fluid dynamics and state-of-the-art models for surface-aerated and forced-aerated bioreactors. In addition, experimental methods for the determination of the k L a value and the gas bubble size distribution are presented.

Optimal oxygen supply is vitally important for the cultivation of aerobically growing cells, as it has a direct influence on cell growth and product formation. A process engineering parameter directly related to oxygen supply is the volumetric oxygen mass transfer coefficient kLa. It is the influences on kLa and computing time of different interfacial force and population balance models in stirred bioreactors that have been evaluated in this study. For this investigation, the OpenFOAM 7 open-source toolbox was utilized. Firstly, the Euler–Euler model with a constant bubble diameter was applied to a 2L scale bioreactor to statistically examine the influence of different interfacial models on the kLa value. It was shown that the kL model and the constant bubble diameter have the greatest influence on the calculated kLa value. To eliminate the problem of a constant bubble diameter and to take effects such as bubble breakup and coalescence into account, the Euler–Euler model was coupled with population balance models (PBM). For this purpose, four coalescence and five bubble breakup models were examined. Ultimately, it was established that, for all of the models tested, coupling computational fluid dynamics (CFD) with PBM resulted in better agreement with the experimental data than using the Euler–Euler model. However, it should be noted that the higher accuracy of the PBM coupled models requires twice the computation time.

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Energy and carbon management systems (ECMS) are a class of green information systems that has the potential to increase environmental sustainability in organizations and across supply chains. Employing a design science research approach, we define the scope of ECMS in the supply chain context, identify requirements, design an expository instantiation, and develop an information systems design theory, including key constructs and design principles. We instantiate this theory in four supply chain contexts to validate and revise the proposed design in two rounds. We identify six system components data collection, energy monitoring, supply chain coordination, ECMS workflow engine, reporting, and carbon footprint estimator that integrate and coordinate four types of information flows (transactional, contextual, energy, and product environmental), and formulate design principles. Our evaluation indicates that the ECMS design theory, if instantiated, supports energy and carbon measurement and environmentally aware decision-making and practice in supply chains. We also highlight how considering energy information flows in combination with material features that afford environmentally aware decision-making and practice are key to qualifying information systems as green.

Optimizing bioprocesses requires an in-depth understanding, from a bioengineering perspective, of the cultivation systems used. A bioengineering characterization is typically performed via experimental or numerical methods, which are particularly well-established for stirred bioreactors. For unstirred, non-rigid systems such as wave-mixed bioreactors, numerical methods prove to be problematic, as often only simplified geometries and motions can be assumed. In this work, a general approach for the numerical characterization of non-stirred cultivation systems is demonstrated using the CELL-tainer bioreactor with two degree of freedom motion as an example. In a first step, the motion is recorded via motion capturing, and a 3D model of the culture bag geometry is generated via 3D-scanning. Subsequently, the bioreactor is characterized with respect to mixing time, and oxygen transfer rate, as well as specific power input and temporal Kolmogorov length scale distribution. The results demonstrate that the CELL-tainer with two degrees of freedom outperforms classic wave-mixed bioreactors in terms of oxygen transport. In addition, it was shown that in the cell culture version of the CELL-tainer, the critical Kolmogorov length is not surpassed in any simulation.