Using potassium catalytic gasification to improve the performance of solid oxide direct carbon fuel cells: Experimental characterization and elementary reaction modeling

The performance of a solid oxide electrolyte direct carbon fuel cell (SO-DCFC) is limited by the slow carbon gasification kinetics at the typical operating temperatures of cell: 650–850 °C. To overcome such limitation, potassium salt is used as a catalyst to speed up the dry carbon gasification reactions, increasing the power density by five-fold at 700–850 °C. The cell performance is shown to be sensitive to the bed temperature, emphasizing the role of gasification rates and that of CO production. Given the finite bed size, the cell performance is time-dependent as the amount of CO available changes. A reduced elementary reaction mechanism for potassium-catalyzed carbon gasification was proposed using kinetic data obtained from the experimental measurements. A comprehensive model including the catalytic gasification reactions and CO electrochemistry is used to examine the impact of the catalytic carbon gasification process on the device performance. The power density is maximum around 50% of the OCV, where carbon utilization is also near maximum. Results show that bed height and porosity impact the power density; a thicker bed maintains the power almost constant for longer times while lower porosity delivers higher power density in the early stages.National Natural Science Foundation (China) (20776078)National Natural Science Foundation (China) (51106085)Low Carbon Energy University Alliance (LCEUA) (Seed Funding

Nutrient limitation of woody debris decomposition in a tropical forest:contrasting effects of N and P addition

1.Tropical forests represent a major terrestrial store of carbon (C), a large proportion of which is contained in the soil and decaying organic matter. Woody debris plays a key role in forest C dynamics because it contains a sizeable proportion of total forest C. Understanding the factors controlling the decomposition of organic matter in general, and woody debris in particular, is hence critical to assessing changes in tropical C storage. 2.We conducted a factorial fertilization experiment in a tropical forest in South China to investigate the influence of nitrogen (N) and phosphorus (P) availability onwoody debris decomposition using branch segments (5-cm diameter) of four species (Acacia auriculaeformis, Aphanamixis polystachya, Schefflera octophylla, Carallia brachiata) in plots fertilized with +N, +P, or +NP, and controls. 3.Fertilization with +P and +NP increased decomposition rates by 5-53% and the magnitude was species-specific. Contrary to expectations, we observed no negative effect of +N addition on decay rates or mass loss of woody debris in any of the four study species. Decomposition rates of woody debris were higher in species with lower C:P ratios regardless of treatment. 4.We observed significant accumulation of P in the woody debris of all species in plots fertilized with +P and +NP during the early stages of decomposition. N-release from woody debris of Acacia (N-fixing) was greater in the +P plots towards the end of the study, whereas fertilization with +N had no impact on the patterns of nutrient release during decomposition. 5.Synthesis: Our results indicate that decomposition of woody debris is primarily constrained by P availability in this tropical forest. However, contrary to expectations, +N addition did not exacerbate P-limitation. It is conceivable that decay rates of woody debris in tropical forests can be predicted by C:P or lignin:P ratios but additional work with more tree species is needed to determine whether the patterns we observed are more generally applicable

Multi-Modality Multi-Scale Cardiovascular Disease Subtypes Classification Using Raman Image and Medical History

Raman spectroscopy (RS) has been widely used for disease diagnosis, e.g., cardiovascular disease (CVD), owing to its efficiency and component-specific testing capabilities. A series of popular deep learning methods have recently been introduced to learn nuance features from RS for binary classifications and achieved outstanding performance than conventional machine learning methods. However, these existing deep learning methods still confront some challenges in classifying subtypes of CVD. For example, the nuance between subtypes is quite hard to capture and represent by intelligent models due to the chillingly similar shape of RS sequences. Moreover, medical history information is an essential resource for distinguishing subtypes, but they are underutilized. In light of this, we propose a multi-modality multi-scale model called M3S, which is a novel deep learning method with two core modules to address these issues. First, we convert RS data to various resolution images by the Gramian angular field (GAF) to enlarge nuance, and a two-branch structure is leveraged to get embeddings for distinction in the multi-scale feature extraction module. Second, a probability matrix and a weight matrix are used to enhance the classification capacity by combining the RS and medical history data in the multi-modality data fusion module. We perform extensive evaluations of M3S and found its outstanding performance on our in-house dataset, with accuracy, precision, recall, specificity, and F1 score of 0.9330, 0.9379, 0.9291, 0.9752, and 0.9334, respectively. These results demonstrate that the M3S has high performance and robustness compared with popular methods in diagnosing CVD subtypes

Experimental characterization and elementary reaction modeling of solid oxide electrolyte direct carbon fuel cell

A detailed mechanistic model for solid oxide electrolyte direct carbon fuel cell (SO-DCFC) is developed while considering the thermo-chemical and electrochemical elementary reactions in both the carbon bed and the SOFC, as well as the meso-scale transport processes within the carbon bed and the SOFC electrode porous structures. The model is validated using data from a fixed bed carbon gasification experiment and the SO-DCFC performance testing experiments carried out using different carrier gases and at various temperatures. The analyzes of the experimental and modeling results indicate the strong influence of the carrier gas on the cell performance. The coupling between carbon gasification and electrochemical oxidation on the SO-DCFC performance that results in an unusual transition zone in the cell polarization curve was predicted by the model, and analyzed in detail at the elementary reaction level. We conclude that the carbon bed physical properties such as the bed height, char conversion ratio and fuel utilization, as well as the temperature significantly limit the performance of the SO-DCFC.National Natural Science Foundation (China) (20776078)National Natural Science Foundation (China) (51106085)Low Carbon Energy University Alliance (LCEUA) (Seed Funding

A novel anti-virulence gene revealed by proteomic analysis in Shigella flexneri 2a

<p>Abstract</p> <p>Background</p> <p><it>Shigella flexneri </it>is a gram-negative, facultative pathogen that causes the majority of communicable bacterial dysenteries in developing countries. The virulence factors of <it>S. flexneri </it>have been shown to be produced at 37 degrees C but not at 30 degrees C. To discover potential, novel virulence-related proteins of <it>S. flexneri</it>, we performed differential in-gel electrophoresis (DIGE) analysis to measure changes in the expression profile that are induced by a temperature increase.</p> <p>Results</p> <p>The ArgT protein was dramatically down-regulated at 37 degrees C. In contrast, the ArgT from the non-pathogenic <it>E. coli </it>did not show this differential expression as in <it>S. flexneri</it>, which suggested that <it>argT </it>might be a potential anti-virulence gene. Competitive invasion assays in HeLa cells and in BALB/c mice with <it>argT </it>mutants were performed, and the results indicated that the over-expression of ArgT_Y225Dwould attenuate the virulence of <it>S. flexneri</it>. A comparative proteomic analysis was subsequently performed to investigate the effects of ArgT in <it>S. flexneri </it>at the molecular level. We show that HtrA is differentially expressed among different derivative strains.</p> <p>Conclusion</p> <p>Gene <it>argT </it>is a novel anti-virulence gene that may interfere with the virulence of <it>S. flexneri </it>via the transport of specific amino acids or by affecting the expression of the virulence factor, HtrA.</p

Room-temperature continuous-wave topological Dirac-vortex microcavity lasers on silicon

Robust laser sources are a fundamental building block for contemporary information technologies. Originating from condensed-matter physics, the concept of topology has recently entered the realm of optics, offering fundamentally new design principles for lasers with enhanced robustness. In analogy to the well-known Majorana fermions in topological superconductors, Dirac-vortex states have recently been investigated in passive photonic systems and are now considered as a promising candidate for robust lasers. Here, we experimentally realize the topological Dirac-vortex microcavity lasers in InAs/InGaAs quantum-dot materials monolithically grown on a silicon substrate. We observe room-temperature continuous-wave linearly polarized vertical laser emission at a telecom wavelength. We confirm that the wavelength of the Dirac-vortex laser is topologically robust against variations in the cavity size, and its free spectral range defies the universal inverse scaling law with the cavity size. These lasers will play an important role in CMOS-compatible photonic and optoelectronic systems on a chip

Room-temperature continuous-wave Dirac-vortex topological lasers on silicon

Robust laser sources are a fundamental building block for contemporary information technologies. Originating from condensed-matter physics, the concept of topology has recently entered the realm of optics, offering fundamentally new design principles for lasers with enhanced robustness. In analogy to the well-known Majorana fermions in topological superconductors, Dirac-vortex states have recently been investigated in passive photonic systems and are now considered as a promising candidate for single-mode large-area lasers. Here, we experimentally realize the first Dirac-vortex topological lasers in InAs/InGaAs quantum-dot materials monolithically grown on a silicon substrate. We observe room-temperature continuous-wave single-mode linearly polarized vertical laser emission at a telecom wavelength. Most importantly, we confirm that the wavelength of the Dirac-vortex laser is topologically robust against variations in the cavity size, and its free spectral range defies the universal inverse scaling law with the cavity size. These lasers will play an important role in CMOS-compatible photonic and optoelectronic systems on a chip

Comparative genomic analysis of esophageal squamous cell carcinoma among different geographic regions

IntroductionEsophageal squamous cell carcinoma (ESCC) shows remarkable variation in incidence, survival, and risk factors. Although the genomic characteristics of ESCC have been extensively characterized, the genomic differences between different geographic regions remain unclear.MethodsIn this study, we sequenced 111 patients with ESCC from northern (NC) and southern (SC) China, combined their data with those of 1081 cases from previous reports, and performed a comparative analysis among different regions. In total, 644 ESCC cases were collected from six geographic regions (NC, SC, Xinjiang, China [XJC], Japan [JP], Vietnam [VN], and Europe &amp; America [EA]) as the discovery cohort. Validation cohort 1 included 437 patients with ESCC from the NC region. Validation cohort 2 included 54 and 57 patients from the NC and SC regions, respectively.ResultsPatients with ESCC in different regions had different genomic characteristics, including DNA signatures, tumor mutation burdens, significantly mutated genes (SMGs), altered signaling pathways, and genes associated with clinical features. Based on both the DNA mutation signature and the mutation profile of the most common genes, the NC and SC groups were clustered close together, followed by the JP, XJC, EA, and VN groups. Compared to patients with ESCC from SC, SMGs, including KMT2D, FAT1, and NOTCH1 were more frequently identified in patients with ESCC from NC. Furthermore, some genes (TDG and DNAH8) correlated with overall survival in completely opposite ways in patients with ESCC from different geographical regions.ConclusionsOur study provides insights into genomic differences in ESCC among different regions. These differences may be related to differences in environmental carcinogens, incidence, and survival