Standardized procedures important for improving single-component ceramic fuel cell technology

Standardized procedures important for improving single-component ceramic fuel cell technolog

Low carbon fuel production from combined solid oxide CO2 co-electrolysis and Fischer-Tropsch synthesis system: A modelling study

© 2019 The Authors CH4-assisted solid oxide electrolyzer cells (SOECs) can co-electrolyze H2O and CO2 effectively for simultaneous energy storage and CO2 utilization. Compared with conventional SOECs, CH4-assisted SOECs consume less electricity because CH4 in the anode provides part of the energy for electrolysis. As syngas (CO and H2 mixture) is generated from the co-electrolysis process, it is necessary to study its utilization through the subsequent processes, such as Fischer-Tropsch (F-T) synthesis to produce more value-added products. An F-T reactor can convert syngas into hydrocarbons, and thus it is very suitable for the utilization of syngas. In this paper, the combined CH4-assisted SOEC and F-T synthesis system is numerically studied. Validated 2D models for CH4-assisted SOEC and F-T processes are adopted for parametric studies. It is found that the cathode inlet H2O/CO2 ratio in the SOEC significantly affects the production components through the F-T process. Other operating parameters such as the operating temperature and applied voltage of the SOEC are found to greatly affect the productions of the system. This model is important for understanding and design optimization of the combined fuel-assisted SOEC and F-T synthesis system to achieve economical hydrocarbon generation

Facile Synthesis of Nitrogen and Sulfur Codoped Carbon from Ionic Liquid as Metal-Free Catalyst for Oxygen Reduction Reaction

Developing metal-free catalysts for oxygen reduction reaction (ORR) is a great challenge in the development of fuel cells. Nitrogen and sulfur codoped carbon with remarkably high nitrogen content up to 13.00 at % was successfully fabricated by pyrolysis of homogeneous mixture of exfoliated graphitic flakes and ionic liquid 1-butyl-3-methylimidazolium bis­(trifluoromethanesulfonyl)­imide ([Bimi]­[Tf₂N]). The exfoliated graphite flakes served as a structure-directing substance as well as additional carbon source in the fabrication. It was demonstrated that the use of graphite flakes increased the nitrogen doping level, optimized the composition of active nitrogen configurations, and enlarged the specific surface area of the catalysts. Electrochemical characterizations revealed that the N and S codoped carbon fabricated by this method exhibited superior catalytic activities toward ORR under both acidic and alkaline conditions. Particularly in alkaline solution, the current catalyst compared favorably to the conventional 20 wt % Pt/C catalyst via four-electron transfer pathway with better ORR selectivity. The excellent catalytic activity was mainly ascribed to high nitrogen doping content, appropriate constitution of active nitrogen configurations, large specific surface area, and synergistic effect of N and S codoping

BaCo_0.7Fe_0.22Y_0.08O_3−δ as an Active Oxygen Reduction Electrocatalyst for Low-Temperature Solid Oxide Fuel Cells below 600 °C

Solid oxide fuel cells (SOFCs) offer great promise as sustainable energy conversion devices due to their high chemical-to-electrical conversion efficiency, flexible fuel sources, and low pollutions. In recent years, much effort has been devoted to developing intermediate temperature SOFCs. Central to the devices is the availability of a highly effective electrocatalyst for oxygen reduction reaction with reduced temperature operation, especially below 600 °C. Here we present a novel B-site Y-doped perovskite-type oxide BaCo_0.7Fe_0.22Y_0.08O_3−δ (BCFY) with extremely low polarization resistances (e.g., 0.10 Ω cm² at 550 °C), which is ascribed to high cubic symmetry structure and fast oxygen kinetics. The superior electrocatalytic activity and stability enable BCFY to be a promising cathode candidate toward the application of reduced temperature SOFCs

Enabling thermal-neutral electrolysis for CO₂-to-fuel conversions with a hybrid deep learning strategy

High-temperature co-electrolysis of CO2/H2O through the solid oxide electrolysis cells (SOECs) is a promising method to generate renewable fuels and chemical feedstocks. Applying this technology in flexible scenario, especially when combined with variable renewable powers, requires an efficient optimisation strategy to ensure its safety and cost-effective in the long-term operation. To this purpose, we present a hybrid simulation method for the accurate and fast optimisation of the co-electrolysis process in the SOECs. This method builds multi-physics models based on experimental data and extends the database to develop the deep neural network and genetic algorithm. In the case study, thermal-neutral condition (TNC) is set as the optimisation target in various operating conditions, where the SOEC generates no waste heat and needs no auxiliary heating equipment. Small peak-temperature-gradient (PTG) inside the SOEC is found at the TNC, which is vital to prevent thermal failure in the operation. For the cell operating with 1023 K and 1123 K of inlet gas temperatures, the smallest PTGs reach 0.09 and 0.31 K mm−1 at 1.13 and 1.19 V, respectively. Finally, a 4-D map is presented to show the interactions among the applied voltage, required power density, inlet gas composition, and temperature under the TNC. The proposed method can be flexibly modified based on different optimisation targets for various applications in the energy sector

Data_Sheet_2_Spatiotemporal assembly and functional composition of planktonic microeukaryotic communities along productivity gradients in a subtropical lake.docx

Microeukaryotes play crucial roles in the microbial loop of freshwater ecosystems, functioning both as primary producers and bacterivorous consumers. However, understanding the assembly of microeukaryotic communities and their functional composition in freshwater lake ecosystems across diverse environmental gradients remains limited. Here, we utilized amplicon sequencing of 18S rRNA gene and multivariate statistical analyses to examine the spatiotemporal and biogeographical patterns of microeukaryotes in water columns (at depths of 0.5, 5, and 10 m) within a subtropical lake in eastern China, covering a 40 km distance during spring and autumn of 2022. Our results revealed that complex and diverse microeukaryotic communities were dominated by Chlorophyta (mainly Chlorophyceae), Fungi, Alveolata, Stramenopiles, and Cryptophyta lineages. Species richness was higher in autumn than in spring, forming significant hump-shaped relationships with chlorophyll a concentration (Chl-a, an indicator of phytoplankton biomass). Microeukaryotic communities exhibited significant seasonality and distance-decay patterns. By contrast, the effect of vertical depth was negligible. Stochastic processes mainly influenced the assembly of microeukaryotic communities, explaining 63, 67, and 55% of community variation for spring, autumn, and both seasons combined, respectively. Trait-based functional analysis revealed the prevalence of heterotrophic and phototrophic microeukaryotic plankton with a trade-off along N:P ratio, Chl-a, and dissolved oxygen (DO) gradients. Similarly, the mixotrophic proportions were significantly and positively correlated with Chl-a and DO concentrations. Overall, our findings may provide useful insights into the assembly patterns of microeukaryotes in lake ecosystem and how their functions respond to environmental changes.</p

Data_Sheet_1_Spatiotemporal assembly and functional composition of planktonic microeukaryotic communities along productivity gradients in a subtropical lake.xlsx

Microeukaryotes play crucial roles in the microbial loop of freshwater ecosystems, functioning both as primary producers and bacterivorous consumers. However, understanding the assembly of microeukaryotic communities and their functional composition in freshwater lake ecosystems across diverse environmental gradients remains limited. Here, we utilized amplicon sequencing of 18S rRNA gene and multivariate statistical analyses to examine the spatiotemporal and biogeographical patterns of microeukaryotes in water columns (at depths of 0.5, 5, and 10 m) within a subtropical lake in eastern China, covering a 40 km distance during spring and autumn of 2022. Our results revealed that complex and diverse microeukaryotic communities were dominated by Chlorophyta (mainly Chlorophyceae), Fungi, Alveolata, Stramenopiles, and Cryptophyta lineages. Species richness was higher in autumn than in spring, forming significant hump-shaped relationships with chlorophyll a concentration (Chl-a, an indicator of phytoplankton biomass). Microeukaryotic communities exhibited significant seasonality and distance-decay patterns. By contrast, the effect of vertical depth was negligible. Stochastic processes mainly influenced the assembly of microeukaryotic communities, explaining 63, 67, and 55% of community variation for spring, autumn, and both seasons combined, respectively. Trait-based functional analysis revealed the prevalence of heterotrophic and phototrophic microeukaryotic plankton with a trade-off along N:P ratio, Chl-a, and dissolved oxygen (DO) gradients. Similarly, the mixotrophic proportions were significantly and positively correlated with Chl-a and DO concentrations. Overall, our findings may provide useful insights into the assembly patterns of microeukaryotes in lake ecosystem and how their functions respond to environmental changes.</p

Condition-dependent transcriptional profiles of <i>S</i>. <i>fredii</i> CCBAU45436 and CCBAU25509 under free-living and symbiotic conditions.

<p>(<b>A-D</b>) Clustering analyses of Log₂-transformed RPKM values for genes within different hierarchical core/accessory subsets (I-IV) using the average linkage method based on Euclidean distance. CCBAU45436 and CCBAU25509 are represented by white and grey boxes respectively. S, stationary phase; M, mid-log phase; W/C, microsymbionts in nodules of <i>G</i>. <i>soja</i> W05 or <i>G</i>. <i>max</i> C08. Bootstrap values above 70% are indicated. (<b>E</b>) Gene expression level within different hierarchical core/accessory subsets under test conditions, dots and error bars refer to the means and standard errors of Log₂-transformed RPKM values. (<b>F</b>) Gene expression plasticity within different hierarchical core/accessory subsets under test conditions, dots and error bars refer to the means and standard errors of variances of Log₂-transformed RPKM values. Multi-copy genes were not included in these analyses.</p

Connectivity analyses of gene co-expression networks in the multipartite genome of <i>S</i>. <i>fredii</i> CCBAU25509.

<p><b>(A)</b> Gene connectivity degrees of the <i>Sinorhizobium</i> pangenome subsets for each replicon. Error bars represent standard error of mean. <b>(B)</b> Within- and between-replicon gene connectivity. The total number of gene connectivity identified for each replicon is shown in brackets. The relative abundances of within- and between-replicon gene connectivity are indicated by different sections of the perimeter colored according to the connected replicons (orange, the gene connectivity to the chromosome cSF25509; blue, the chromid pSF25509b; light green, the symbiosis plasmid pSF25509a). Between-replicon gene connectivity is depicted in grey. The within- and between-replicon connective patterns of CCBAU45436 (see <b><a href="http://www.plosgenetics.org/article/info:doi/10.1371/journal.pgen.1007428#pgen.1007428.s012" target="_blank">S4 Fig</a></b>) are similar to those of CCBAU25509 shown here. Multi-copy genes except one out of two <i>nifHDK</i> copies were not included in these analyses.</p

Biased distributions of core and accessory genes regarding replicons.

<p><b>(A)</b> A schematic diagram illustrating the hierarchical division of core/accessory subsets for the genomes of <i>S</i>. <i>fredii</i> CCBAU45436 and CCBAU25509. Subset I, genus core genes present in all strains; subset II, genes present in all <i>S</i>. <i>fredii</i> strains excluding subset I; subset III, genes shared by CCBUA45436 and CCBAU25509 but not present in all <i>S</i>. <i>fredii</i> strains, i.e. excluding subsets I and II; subset IV, the remaining accessory genes in either CCBAU45436 or CCBAU25509. The actual total gene numbers of each subset within the genome of CCBAU45436 (left) and CCBAU25509 (right) are shown in frames. The slight differences between two strains in the numbers of core genes in subsets I-III are due to the counting of multi-copy genes belonging to the same homologous gene cluster, which can include one or more genes in each strain. <b>(B)</b> Percentage values are the ratios of genes included in hierarchical core/accessory subsets (shades of colors from deep to light: I, II, III, IV), harbored by each replicon within the genome of CCBAU45436 or CCBAU25509. The actual total gene numbers of each replicon are shown in parentheses. Pearson's chi-square test of independence indicates the distribution of different core/accessory subsets on replicons is not random (CCBAU45436, X-squared = 1455.3, df = 12, <i>P</i> < 2.2E-16; CCBAU25509, X-squared = 1010.4, df = 6, <i>P</i> < 2.2E-16).</p