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The doping of SiO2 and Fe2O3 into hydrochars that were produced by the hydrothermal carbonization of cellulose was studied with respect to its impact on the resulting surface characteristics and sorption behavior of CO2, CH4, and O2. During pyrolysis, the structural order of the Fe-doped char changed, as the fraction of highly ordered domains increased, which was not observed for the undoped and Si-doped chars. The Si doping had no apparent influence on the oxidation temperature of the hydrochar in contrast to the Fe-doped char where the oxidation temperature was reduced because of the catalytic effect of Fe. Both dopants reduced the micro-, meso- and macroporous surface areas of the chars, although the Fe-doped chars had larger meso- and macroporosity than the Si-doped char. However, the increased degree in the structural order of the carbon matrix of the Fe-doped char reduced its microporosity relative to the Si-doped char. The adsorption of CO2 and CH4 on the chars at temperatures between 273.15 and 423.15 K and at pressures up to 115 kPa was slightly inhibited by the Si doping but strongly suppressed by the Fe doping. For O2, however, the Si doping promoted the observed adsorption capacity, while Fe doping also showed an inhibiting effect.

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The applied pyrolysis temperature was found to strongly affect composition, structure, and oxidation behavior of pure and iron oxide nanoparticle (NP)-loaded carbon materials originating from hydrothermal carbonization (HTC) of cellulose. A strong loss of functional groups during pyrolysis at temperatures beyond 300 °C of the HTC-derived hydrochars was observed, resulting in an increase of the carbon content up to 95 wt% for the carbon materials pyrolyzed at 800 °C and an increase of the specific surface area with a maximum of 520 m2 g-1 at a pyrolysis temperature of 600 °C. Devolatilization mainly took place in the range from 300 to 500 °C, releasing light pyrolysis gases such as CO, CO2, H2O and larger oxygen-containing molecules up to C11. The presence of iron oxide NPs lowered the specific surface areas by about 200 m2 g-1 and resulted in the formation of mesopores. For the iron oxide-containing composites pyrolyzed up to 500 °C, the oxidation temperature was decreased by about 100 °C, indicating tight contact between the iron oxide NPs and the carbon matrix. For higher pyrolysis temperatures, this catalytic effect of iron oxide on carbon oxidation vanished due to carbothermal reduction to iron and iron carbide, which, however, catalyzed the graphitization of the carbon matrix. Thus, the well-controlled two-step synthesis based on a biomass-derived precursor yielded stably embedded iron NPs in a corrosion-resistant graphitic carbon matrix.

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BACKGROUND: During the last decades, we face an increasing interest in superior plants to supply growing demands for human and animal nutrition and for the developing bio-based economy. Presently, our limited understanding of their metabolism and its regulation hampers the targeted development of desired plant phenotypes. In this regard, systems biology, in particular the integration of metabolic and regulatory networks, is promising to broaden our knowledge and to further explore the biotechnological potential of plants. RESULTS: The thale cress Arabidopsis thaliana provides an ideal model to understand plant primary metabolism. To obtain insight into its functional properties, we constructed a large-scale metabolic network of the leaf of A. thaliana. It represented 511 reactions with spatial separation into compartments. Systematic analysis of this network, utilizing elementary flux modes, investigates metabolic capabilities of the plant and predicts relevant properties on the systems level: optimum pathway use for maximum growth and flux re-arrangement in response to environmental perturbation. Our computational model indicates that the A. thaliana leaf operates near its theoretical optimum flux state in the light, however, only in a narrow range of photon usage. The simulations further demonstrate that the natural day-night shift requires substantial re-arrangement of pathway flux between compartments: 89 reactions, involving redox and energy metabolism, substantially change the extent of flux, whereas 19 reactions even invert flux direction. The optimum set of anabolic pathways differs between day and night and is partly shifted between compartments. The integration with experimental transcriptome data pinpoints selected transcriptional changes that mediate the diurnal adaptation of the plant and superimpose the flux response. CONCLUSIONS: The successful application of predictive modelling in Arabidopsis thaliana can bring systems-biological interpretation of plant systems forward. Using the gained knowledge, metabolic engineering strategies to engage plants as biotechnological factories can be developed.

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In recent years the number of sequenced and annotated plant genomes has increased significantly, and novel approaches are required to retrieve valuable information from these data sets. The field of systems biology has accelerated the simulation and prediction of phenotypes derived from specific genotypic modifications under defined growth conditions. The biochemical potential of a cell from a specific plant tissue (e.g., seed endosperm) can be derived from its genome in the form of a mathematical model by the method of metabolic network reconstruction. This model can be further analyzed by studying its network properties, analyzing feasible pathway routes through the network, or simulating possible flux distributions of the network . Here, we describe two approaches for identification of all feasible routes through the network (elementary mode analysis) and for simulation of flux distribution in the network based on plant physiological uptake and excretion rates (flux balance analysis).

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Organisms try to maintain homeostasis by balanced uptake of nutrients from their environment. From an atomic perspective this means that, for example, carbon:nitrogen:sulfur ratios are kept within given limits. Upon limitation of, for example, sulfur, its acquisition is triggered. For yeast it was shown that transporters and enzymes involved in sulfur uptake are encoded as paralogous genes that express different isoforms. Sulfur deprivation leads to up-regulation of isoforms that are poor in sulfur-containing amino acids, that is, methinone and cysteine. Accordingly, sulfur-rich isoforms are down-regulated. We developed a web-based software, doped Nutrilyzer, that extracts paralogous protein coding sequences from an annotated genome sequence and evaluates their atomic composition. When fed with gene-expression data for nutrient limited and normal conditions, Nutrilyzer provides a list of genes that are significantly differently expressed and simultaneously contain significantly different amounts of the limited nutrient in their atomic composition. Its intended use is in the field of ecological stoichiometry. Nutrilyzer is available at http://nutrilyzer.hs-mittweida.de. Here we describe the work flow and results with an example from a whole-genome Arabidopsis thaliana gene-expression analysis upon oxygen deprivation. 43 paralogs distributed over 37 homology clusters were found to be significantly differently expressed while containing significantly different amounts of oxygen.

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