Electrochemical Capture of CO\u3csub\u3e2\u3c/sub\u3e from Natural Gas using a High-Temperature Ceramic-Carbonate Membrane

This study reports the first investigation of using a ceramic-carbonate dual-phase membrane to electrochemically separate CO2 from a simulated natural gas. The CO2 permeation flux density was systematically studied as a function of temperature, CO2 partial pressure and time. As expected, the flux density was observed to increase with temperature and CO2 partial pressure. Long-term stability test showed that flux density experienced an initial performance-improving “break-in” period followed by a slow decay. Post-test microstructural analysis suggested that a gradual loss of carbonate during the test could be the cause of the flux-time behavior observed

High Performance Low Temperature Solid Oxide Fuel Cells with Novel Electrode Architecture

In this study, we have fabricated high performance low temperature solid oxide fuel cells (LT-SOFCs) with both acicular anodes and cathodes with thin Gd-doped ceria (GDC) electrolyte film. The acicular Ni-Gd0.1Ce0.9O2−δ (Ni-GDC) anode was prepared using freeze drying tape casting, while the hierarchically porous cathode with nano-size Sm0.5Sr0.5CoO3 (SSC) particles covering an acicular GDC skeleton was prepared by a combination of freeze drying tape casting and self-rising approaches. The acicular electrodes with 5–200 μm pores/channels enhance mass transport, while SSC particles of about 50 nm in the cathode promote electrochemical reactions. Cells which have this novel electrode architecture show a significantly high power output of 1.44 W cm−2 and an extremely low cell polarization resistance of 0.0379 Ω cm2 at 600 °C

Ni-Doped Sr\u3csub\u3e2\u3c/sub\u3eFe\u3csub\u3e1.5\u3c/sub\u3eMo\u3csub\u3e0.5\u3c/sub\u3eO\u3csub\u3e6-δ\u3c/sub\u3e as Anode Materials for Solid Oxide Fuel Cells

10% Ni-doped Sr2Fe1.5Mo0.5O6-δ with A-site deficiency is prepared to induce in situ precipitation of B-site metals under anode conditions in solid oxide fuel cells. XRD, SEM and TEM results show that a significant amount of nano-sized Ni-Fe alloy metal phase has precipitated out from Sr1.9Fe1.4Ni0.1Mo0.5O6-δ upon reduction at 800◦C in H2. The conductivity of the reduced composite reaches 29 S cm−1 at 800◦C in H2. Furthermore, fuel cell performance of the composite anode Sr1.9Fe1.4Ni0.1Mo0.5O6-δ-SDC is investigated using H2 as fuel and ambient air as oxidant with La0.8Sr0.2Ga0.87Mg0.13O3 electrolyte and La0.6Sr0.4Co0.2Fe0.8O3 cathode. The cell peak power density reaches 968 mW cm−2 at 800◦C and the voltage is relatively stable under a constant current load of 0.54 A cm−2. After 5 redox cycles of the anode at 800◦C, the fuel cell performance doesn’t suffer any degradation, indicating good redox stability of Sr1.9Fe1.4Ni0.1Mo0.5O6-δ. Peak power density of 227 mW cm−2 was also obtained when propane is used as fuel. These results indicate that a self-generated metal-ceramic composite can been successfully derived from Sr2Fe1.5Mo0.5O6-δ by compositional modifications and Sr1.9Fe1.4Ni0.1Mo0.5O6-δ is a very promising solid oxide fuel cell anode material with enhanced catalytic activity and inherited good redox stability from the parent ceramic material

Stabilizing Electrochemical Carbon Capture Membrane with Al\u3csub\u3e2\u3c/sub\u3eO\u3csub\u3e3\u3c/sub\u3e Thin-Film Overcoating Synthesized by Chemical Vapor Deposition

Development of high-efficiency and cost-effective carbon capture technology is a central element of our effort to battle the global warming and climate change. Here we report that the unique high-flux and high-selectivity of electrochemical silver-carbonate dual-phase membranes can be retained for an extended period of operation by overcoating the surfaces of porous silver matrix with a uniform layer of Al2O3 thin-film derived from chemical vapor deposition

La\u3csub\u3e0.7\u3c/sub\u3eSr\u3csub\u3e0.3\u3c/sub\u3eFe\u3csub\u3e0.7\u3c/sub\u3eGa\u3csub\u3e0.3\u3c/sub\u3eO\u3csub\u3e3-δ\u3c/sub\u3e as Electrode Material for a Symmetrical Solid Oxide Fuel Cell

In this research, La0.7Sr0.3Fe0.7Ga0.3O3−δ (LSFG) perovskite oxide was successfully prepared using a microwave-assisted combustion method, and employed as both anode and cathode in symmetrical solid oxide fuel cells. A maximum power density of 489 mW cm−2 was achieved at 800 °C with wet H2 as the fuel and ambient air as the oxidant in a single cell with the configuration LSFG|La0.8Sr0.2Ga0.83Mg0.17O3−δ|LSFG. Furthermore, the cells demonstrated good stability in H2 and acceptable sulfur tolerance

Robust Representation Learning for Unified Online Top-K Recommendation

In large-scale industrial e-commerce, the efficiency of an online recommendation system is crucial in delivering highly relevant item/content advertising that caters to diverse business scenarios. However, most existing studies focus solely on item advertising, neglecting the significance of content advertising. This oversight results in inconsistencies within the multi-entity structure and unfair retrieval. Furthermore, the challenge of retrieving top-k advertisements from multi-entity advertisements across different domains adds to the complexity. Recent research proves that user-entity behaviors within different domains exhibit characteristics of differentiation and homogeneity. Therefore, the multi-domain matching models typically rely on the hybrid-experts framework with domain-invariant and domain-specific representations. Unfortunately, most approaches primarily focus on optimizing the combination mode of different experts, failing to address the inherent difficulty in optimizing the expert modules themselves. The existence of redundant information across different domains introduces interference and competition among experts, while the distinct learning objectives of each domain lead to varying optimization challenges among experts. To tackle these issues, we propose robust representation learning for the unified online top-k recommendation. Our approach constructs unified modeling in entity space to ensure data fairness. The robust representation learning employs domain adversarial learning and multi-view wasserstein distribution learning to learn robust representations. Moreover, the proposed method balances conflicting objectives through the homoscedastic uncertainty weights and orthogonality constraints. Various experiments validate the effectiveness and rationality of our proposed method, which has been successfully deployed online to serve real business scenarios.Comment: 14 pages, 6 figures, submitted to ICD

PCDHGB7 hypermethylation-based Cervical cancer Methylation (CerMe) detection for the triage of high-risk human papillomavirus-positive women:a prospective cohort study

BackgroundImplementation of high-risk human papillomavirus (hrHPV) screening has greatly reduced the incidence and mortality of cervical cancer. However, a triage strategy that is effective, noninvasive, and independent from the subjective interpretation of pathologists is urgently required to decrease unnecessary colposcopy referrals in hrHPV-positive women.MethodsA total of 3251 hrHPV-positive women aged 30–82 years (median = 41 years) from International Peace Maternity and Child Health Hospital were included in the training set (n = 2116) and the validation set (n = 1135) to establish Cervical cancer Methylation (CerMe) detection. The performance of CerMe as a triage for hrHPV-positive women was evaluated.ResultsCerMe detection efficiently distinguished cervical intraepithelial neoplasia grade 2 or worse (CIN2 +) from cervical intraepithelial neoplasia grade 1 or normal (CIN1 −) women with excellent sensitivity of 82.4% (95% CI = 72.6 ~ 89.8%) and specificity of 91.1% (95% CI = 89.2 ~ 92.7%). Importantly, CerMe showed improved specificity (92.1% vs. 74.9%) in other 12 hrHPV type-positive women as well as superior sensitivity (80.8% vs. 61.5%) and specificity (88.9% vs. 75.3%) in HPV16/18 type-positive women compared with cytology testing. CerMe performed well in the triage of hrHPV-positive women with ASC-US (sensitivity = 74.4%, specificity = 87.5%) or LSIL cytology (sensitivity = 84.4%, specificity = 83.9%).ConclusionsPCDHGB7 hypermethylation-based CerMe detection can be used as a triage strategy for hrHPV-positive women to reduce unnecessary over-referrals.Trial registrationChiCTR2100048972. Registered on 19 July 2021.<br/