Reversible solid oxide cells can provide efficient and cost-effective scheme for electrical-energy storage applications. However, this technology faces many challenges from material development to system-level operational parameters , which should be tackle for practical purposes. Accordingly, this study focuses on developing novel robust artificial intelligence-based blackbox models to optimize operational variables of the system. A genetic-programming algorithm is used for Pareto modeling of reversible solid oxide cells in a multi-objective fashion based on experimental input-output data. The robustness of the obtained optimal model evaluated using Monte Carlo simulations technique. An optimization study adopted to optimize the operating parameters, such as temperature and fuel composition using a differential evolution algorithm. The objective functions that have been considered for Pareto multi-objective modeling process are training error and model complexity. In addition, the discrepancy between maximum and minimum output voltage in the whole operation of the system is chosen as the optimization process objective function. The robustness of the optimal trade-off model is shown in terms of statistical indices for varied uncertainty levels from 1 to 10%. The optimized operational condition based on the suggested model reveals optimal intermediate temperature of 762 °C and fuel mixture of about 29% H 2 , 25% H 2 O, and 14% CO.
We investigated the use of bacterial cells isolated from paddy crab for the extraction of oil from Jatropha seed kernels in aqueous media while simultaneously preserving the protein structures of this protein-rich endosperm. A bacterial strain—which was marked as MB4 and identified by means of 16S rDNA sequencing and physiological characterization as either Bacillus pumilus or Bacillus altitudinis—enhanced the extraction yield of Jatropha oil. The incubation of an MB4 starter culture with preheated kernel slurry in aqueous media with the initial pH of 5.5 at 37 °C for 6 h liberated 73% w/w of the Jatropha oil. Since MB4 produces xylanases, it is suggested that strain MB4 facilitates oil liberation via degradation of hemicelluloses which form the oil-containing cell wall structure of the kernel. After MB4 assisted oil extraction, SDS-PAGE analysis showed that the majority of Jatropha proteins were preserved in the solid phase of the extraction residues. The advantages offered by this process are: protein in the residue can be further processed for other applications, no purified enzyme preparation is needed, and the resulting oil can be used for biodiesel production.
scite is a Brooklyn-based organization that helps researchers better discover and understand research articles through Smart Citations–citations that display the context of the citation and describe whether the article provides supporting or contrasting evidence. scite is used by students and researchers from around the world and is funded in part by the National Science Foundation and the National Institute on Drug Abuse of the National Institutes of Health.