Different operational modes, various scales and complex phenomena make the design of a chemical process a challenging task. Besides conducting basic lab experiments and deriving fundamental kinetic and thermodynamic models, a crucial task within the entire process design is the synthesis of an optimal reactornetwork constituting the core of a chemical process. However, instead of directly up-scaling the process to large devices, it is wise to investigate process characteristics on miniplant-scale. For an existing miniplant for the hydroformylation of 1-dodecene using a rhodium catalyst and a thermomorphic solvent system for catalyst recovery, two optimized reactor designs are derived. Suitable reactor-networks were synthesized by applying the Flux Profile Analysis approach introduced in Kaiser et al. (2017). The combination of a first reactor with dynamic/distributed control options and a subsequent backmixed CSTR arose to be the most promising configurations. The technical design under miniplant conditions were carried out for two possible realizations of this network, namely (i) a continuous flow reactor and (ii) a periodically operated semibatch reactor, both followed by the existing CSTR which was originally operated in the miniplant. An optimization of the two optimal reactor configurations within an overall process including a Page 1 of 53 ACS Paragon Plus Environment Industrial & Engineering Chemistry Research liquid-liquid phase separation for catalyst recovery and a distillation column for separating the solvents and reactant evinced a selectivity w.r.t. the linear aldehyde around 94 % and a conversion around 98 %. This is a large improvement of the process performance of 24 % linear aldehyde selectivity and 40 % conversion when using the existing CSTR.

BackgroundThe green microalga Dunaliella salina accumulates a high proportion of β-carotene during abiotic stress conditions. To better understand the intracellular flux distribution leading to carotenoid accumulation, this work aimed at reconstructing a carbon core metabolic network for D. salina CCAP 19/18 based on the recently published nuclear genome and its validation with experimental observations and literature data.ResultsThe reconstruction resulted in a network model with 221 reactions and 212 metabolites within three compartments: cytosol, chloroplast and mitochondrion. The network was implemented in the MATLAB toolbox CellNetAnalyzer and checked for feasibility. Furthermore, a flux balance analysis was carried out for different light and nutrient uptake rates. The comparison of the experimental knowledge with the model prediction revealed that the results of the stoichiometric network analysis are plausible and in good agreement with the observed behavior. Accordingly, our model provides an excellent tool for investigating the carbon core metabolism of D. salina.ConclusionsThe reconstructed metabolic network of D. salina presented in this work is able to predict the biological behavior under light and nutrient stress and will lead to an improved process understanding for the optimized production of high-value products in microalgae.

Motivation: Distinguishing direct from indirect influences is a central issue in reverse engineering of biological networks because it facilitates detection and removal of false positive edges. Transitive reduction is one approach for eliminating edges reflecting indirect effects but its use in reconstructing cyclic interaction graphs with true redundant structures is problematic.Results: We present TRANSWESD, an elaborated variant of TRANSitive reduction for WEighted Signed Digraphs that overcomes conceptual problems of existing versions. Major changes and improvements concern: (i) new statistical approaches for generating high-quality perturbation graphs from systematic perturbation experiments; (ii) the use of edge weights (association strengths) for recognizing true redundant structures; (iii) causal interpretation of cycles; (iv) relaxed definition of transitive reduction; and (v) approximation algorithms for large networks. Using standardized benchmark tests, we demonstrate that our method outperforms existing variants of transitive reduction and is, despite its conceptual simplicity, highly competitive with other reverse engineering methods.Contact: klamt@mpi-magdeburg.mpg.deSupplementary information: Supplementary data are available at Bioinformatics online.

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Within the framework of elementary process functions (Freund and Sundmacher (2008)) an approach is developed to derive reactor-network candidates from the solution of a dynamic optimization of a batch process scheme by analyzing its optimal mass and energy control fluxes. Thereby, any characteristics of the reaction progress can be identified, e.g. benefits from mixing, back-mixing, recycling, heating, cooling, etc.The approach is used to (i) determine the attainable region for the modified, isothermal van-de-Vusse reaction, which matches literature results; and (ii) synthesize reactor-network candidates for the standard, non-isothermal van-de-Vusse reaction, which gives new insights compared to previous results from literature using superstructure optimization approaches. The results indicate how this approach can be used to determine the attainable region of a process and to rationally select candidates for detailed reactor design with, e.g. superstructure optimization. It further closes the gap between dynamic batch optimization and continuous reactor-network synthesis.