Coulombic Efficiency for Practical Zinc Metal Batteries: Critical Analysis and Perspectives

Climate change and energy depletion are common worries of this century. During the global clean energy transition, aqueous zinc metal batteries (AZMBs) are expected to meet societal needs due to their large-scale energy storage capability with earth-abundant, non-flammable, and economical chemistries. However, the poor reversibility of Zn poses a severe challenge to AZMB implementation. Coulombic efficiency (CE) is a quantitative index of electrode reversibility in rechargeable batteries but is not well understood in AZMBs. Thus, in this work, the state-of-art CE to present the status quo of AZMB development is summarized. A fictional 120 Wh kg-1 AZMB pouch cell is also proposed and evaluated revealing the improvement room and technical goal of AZMB chemistry. Despite some shared mechanisms between AZMBs and lithium metal batteries, misconceptions prevalent in AZMBs are clarified. Essentially, AZMB has its own niche in the market with unique merits and demerits. By incorporating academic and industrial insights, the development pathways of AZMB are suggested. This work comprehensively explores recent advancements in the Coulombic efficiency of aqueous zinc ion batteries, illuminating overlooked test details. Setting a target of 99.9% efficiency, the researchers propose a hypothetical 120 Wh kg-1 MnO2/Zn pouch cell and delineate a three-stage plan to enhance energy density in future developments. Additionally, this work provides valuable insights for improving Coulombic efficiency and refining battery testing methodologies.imag

The conformation change of Bcl-2 is involved in arsenic trioxide-induced apoptosis and inhibition of proliferation in SGC7901 human gastric cancer cells

<p>Abstract</p> <p>Background</p> <p>Arsenic trioxide has been established as a first-line agent for treating acute promyelocytic leukemia. Experimental data suggest that arsenic trioxide also can have a potential use as chemotherapeutic agent for other malignancies. The precise mechanisms of action of arsenic trioxide have though not been elucidated. As the role of Bcl-2 in arsenic trioxide-mediated cell apoptosis and conformation change of Bcl-2 in response to arsenic trioxide treatment has not been studied. The aim of the present study was to determine whether conformation change of Bcl-2 is involved in the action of arsenic trioxide.</p> <p>Methods</p> <p>Human gastric cancer SGC7901 cells were exposed to different concentrations of arsenic trioxide. Proliferation was measured by using the Kit-8 cell counting assay. Analysis of nuclear morphology was observed by DAPI staining. The apoptosis rates of cells treated with arsenic trioxide were analyzed by flow cytometry using Annexin V-FITC staining. The conformation change of Bcl-2 and Bax activation were detected by immunostaining and Western blot analysis. Total expression of Bcl-2 and Bax were examined by Western blot analysis.</p> <p>Results</p> <p>Arsenic trioxide inhibited the growth of human gastric cancer SGC7901 cells and induced apoptosis. There were two Bcl-2 phenotypes coexisting in SGC7901 cells and the Bcl-2 cytoprotective phenotype could change into a cytodestructive phenotype following conformational change of Bcl-2, triggered by arsenic trioxide exposure. Bax activation might also be involved in arsenic trioxide-induced Bcl-2 conformational change. Arsenic trioxide did not change levels of total Bcl-2 expression, but up-regulated total Bax expression for the treatment time ranging from 3 to 24 hours.</p> <p>Conclusion</p> <p>Arsenic trioxide induces apoptosis through induction of Bcl-2 conformational change, Bax activation and up-regulation of total Bax expression rather than affecting total Bcl-2 expression in human gastric cancer SGC7901 cells. The conformational change of Bcl-2 may be a novel described mechanism of arsenic trioxide-induced apoptosis in cancer cells.</p

Termini restraining of small membrane proteins enables structure determination at near-atomic resolution

Small membrane proteins are difficult targets for structural characterization. Here, we stabilize their folding by restraining their amino and carboxyl termini with associable protein entities, exemplified by the two halves of a superfolder GFP. The termini-restrained proteins are functional and show improved stability during overexpression and purification. The reassembled GFP provides a versatile scaffold for membrane protein crystallization, enables diffraction to atomic resolution, and facilitates crystal identification, phase determination, and density modification. This strategy gives rise to 14 new structures of five vertebrate proteins from distinct functional families, bringing a substantial expansion to the structural database of small membrane proteins. Moreover, a high-resolution structure of bacterial DsbB reveals that this thiol oxidoreductase is activated through a catalytic triad, similar to cysteine proteases. Overall, termini restraining proves exceptionally effective for stabilization and structure determination of small membrane proteins

ERTNet: an interpretable transformer-based framework for EEG emotion recognition

BackgroundEmotion recognition using EEG signals enables clinicians to assess patients’ emotional states with precision and immediacy. However, the complexity of EEG signal data poses challenges for traditional recognition methods. Deep learning techniques effectively capture the nuanced emotional cues within these signals by leveraging extensive data. Nonetheless, most deep learning techniques lack interpretability while maintaining accuracy.MethodsWe developed an interpretable end-to-end EEG emotion recognition framework rooted in the hybrid CNN and transformer architecture. Specifically, temporal convolution isolates salient information from EEG signals while filtering out potential high-frequency noise. Spatial convolution discerns the topological connections between channels. Subsequently, the transformer module processes the feature maps to integrate high-level spatiotemporal features, enabling the identification of the prevailing emotional state.ResultsExperiments’ results demonstrated that our model excels in diverse emotion classification, achieving an accuracy of 74.23% ± 2.59% on the dimensional model (DEAP) and 67.17% ± 1.70% on the discrete model (SEED-V). These results surpass the performances of both CNN and LSTM-based counterparts. Through interpretive analysis, we ascertained that the beta and gamma bands in the EEG signals exert the most significant impact on emotion recognition performance. Notably, our model can independently tailor a Gaussian-like convolution kernel, effectively filtering high-frequency noise from the input EEG data.DiscussionGiven its robust performance and interpretative capabilities, our proposed framework is a promising tool for EEG-driven emotion brain-computer interface

Low-Temperature, Highly Selective, Gas-Phase Oxidation of Benzyl Alcohol over Mesoporous K-Cu-TiO2 with Stable Copper(I) Oxidation State

通讯作者地址: Fan, J (通讯作者), Zhejiang Univ, Dept Chem, Key Lab Appl Chem Zhejiang Prov, Hangzhou 310027, Zhejiang Peoples R China 地址: 1. Zhejiang Univ, Dept Chem, Key Lab Appl Chem Zhejiang Prov, Hangzhou 310027, Zhejiang Peoples R China 2. Univ Calif Santa Barbara, Dept Chem & Biochem, Santa Barbara, CA 93106 USA 电子邮件地址: [email protected], [email protected] newly developed mesoporous mixed metal oxide (K-Cu-TiO2) catalyst is capable of highly selective, gas-phase benzyl alcoholbenzaldehyde transformation at excellent yields (>99%) under surprisingly low temperatures (203 degrees C, bp of benzyl alcohol). The tow-temperature reaction conditions and integration of K and Cu(I) components into the TiO2 matrix are of vital importance for the stabilization of an active Cu(I) oxidation state and resultant stable, excellent catalytic performance.National Science Foundations of China 20873122 J0830413 National Science Foundation DMR 02-3372

On Wireless Ad Hoc Networks with Directional Antennas: Efficient Collision and Deafness Avoidance Mechanisms

Wireless ad hoc networks allow anywhere, anytime network connectivity with complete lack of central control, ownership, and regulatory influence. Medium access control (MAC) in such networks poses extremely timely as well as important research and development challenges. Utilizing directional antennas in wireless ad hoc networks is anticipated to significantly improve the network performance due to the increased spatial reuse and the extended transmission range. Nevertheless, using directional antennas in wireless ad hoc networks introduces some serious challenges, the most critical of which are the deafness and hidden terminal problems. This paper thoroughly explores these problems, one of which is discovered and reported for the first time in this paper. This paper also proposes a new MAC scheme, namely, directional MAC with deafness avoidance and collision avoidance (DMAC-DACA), to address both problems. To study the performance of the proposed scheme, a complete directional communication extension to layers 1, 2, and 3 is incorporated in the ns2 simulator. The simulation results show that DMAC-DACA significantly enhances the performance and increases the network throughput. This paper also reveals that deafness has a greater impact on network performance than the hidden terminal problem

On Wireless Ad Hoc Networks with Directional Antennas: Efficient Collision and Deafness Avoidance Mechanisms

Abstract Wireless ad hoc networks allow anywhere, anytime network connectivity with complete lack of central control, ownership, and regulatory influence. Medium access control (MAC) in such networks poses extremely timely as well as important research and development challenges. Utilizing directional antennas in wireless ad hoc networks is anticipated to significantly improve the network performance due to the increased spatial reuse and the extended transmission range. Nevertheless, using directional antennas in wireless ad hoc networks introduces some serious challenges, the most critical of which are the deafness and hidden terminal problems. This paper thoroughly explores these problems, one of which is discovered and reported for the first time in this paper. This paper also proposes a new MAC scheme, namely, directional MAC with deafness avoidance and collision avoidance (DMAC-DACA), to address both problems. To study the performance of the proposed scheme, a complete directional communication extension to layers 1, 2, and 3 is incorporated in the ns2 simulator. The simulation results show that DMAC-DACA significantly enhances the performance and increases the network throughput. This paper also reveals that deafness has a greater impact on network performance than the hidden terminal problem.</p

Double-layer ramp-metering model for incident congestion on expressway

In order to ensure stable traffic capacity and avoid incident congestion, a double-layer ramp metering model is proposed in this paper, based on coordination control theory, to predict and control the traffic flow at each on-ramp, when there is incident congestion on the expressway. The function of the lower model is to recognize where the incident congestion exists, based on an adaptive neural network with inputs of traffic flow, velocity and density. The outputs of the lower model are the number of section where the congestion occurs, the number of ramp which should be controlled, and real-time traffic flow information. These outputs should be transmitted to the upper model. The function of the upper model is to design the ramp-metering strategy based on nonlinear theory. The outputs of the upper model are a ramp-metering rate and traffic-flow state after ramp controlling on the expressway. The results of the simulation show that the double-layer ramp metering model could shorten the delay by about 25%, and the variance of the model results is 0. 002, which could certify the control strategy is equitable