Solar Thermochemical Conversion of Carbon Dioxide into Fuel via MnFe2O4 based Two-Step Redox Cycle

Thermodynamic efficiency analysis of [[EQUATION]] based CO 2 splitting (CDS) cycle is reported. HSC Chemistry software is used for performing the calculations allied with the model developed. By maintaining the reduction nonstoichiometry equal to 0.1, variations in the thermal energy required to drive the cycle ( [[EQUATION]] ) and solar-to-fuel energy conversion efficiency ( [[EQUATION]] ) as a function of the ratio of the molar flow rate of inert sweep gas ( [[EQUATION]] ) to the molar flow rate [[EQUATION]] ( [[EQUATION]] ), i.e., [[EQUATION]] , reduction temperature ( [[EQUATION]] ), and gas-to-gas heat recovery effectiveness ( [[EQUATION]] ) are studied. The rise in [[EQUATION]] is responsible for the decrease in [[EQUATION]] . At [[EQUATION]] = 0.7, [[EQUATION]] increases from 176.0 kW to 271.7 kW when [[EQUATION]] escalates from 10 to 100. Conversely, [[EQUATION]] reduces from 14.9% to 9.9% due to the similar increment in [[EQUATION]] . The difference between [[EQUATION]] at [[EQUATION]] = 10 and 100 decreases from 363.3 kW to 19.2 kW as [[EQUATION]] rises from 0.0 to 0.9. As [[EQUATION]] and subsequently [[EQUATION]] reduces as a function of [[EQUATION]] , [[EQUATION]] increases noticeably. At [[EQUATION]] equal to 0.9 and [[EQUATION]] equal to 10 as well as 20, the maximum [[EQUATION]] equal to 17.5% is realized.

Development and Experimental Validation of a Predictive Threshold Cycle Equation for Quantification of Virulence and Marker Genes by High-Throughput Nanoliter-Volume PCR on the OpenArray Platform

ABSTRACT Development of quantitative PCR (QPCR) assays typically requires extensive screening within and across a given species to ensure specific detection and lucid identification among various pathogenic and nonpathogenic strains and to generate standard curves. To minimize screening requirements, multiple virulence and marker genes (VMGs) were targeted simultaneously to enhance reliability, and a predictive threshold cycle (CT ) equation was developed to calculate the number of starting copies based on an experimental CT . The empirical equation was developed with Sybr green detection in nanoliter-volume QPCR chambers (OpenArray) and tested with 220 previously unvalidated primer pairs targeting 200 VMGs from 30 pathogens. A high correlation (R 2 = 0.816) was observed between the predicted and experimental CT s based on the organism's genome size, guanine and cytosine (GC) content, amplicon length, and stability of the primer's 3′ end. The performance of the predictive CT equation was tested using 36 validation samples consisting of pathogenic organisms spiked into genomic DNA extracted from three environmental waters. In addition, the primer success rate was dependent on the GC content of the target organisms and primer sequences. Targeting multiple assays per organism and using the predictive CT equation are expected to reduce the extent of the validation necessary when developing QPCR arrays for a large number of pathogens or other targets.