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Conversion-type electrode materials have gained massive research attention in sodium-ion batteries (SIBs), but their limited reversibility hampers practical use. Herein, we report a bifunctional nanoreactor to boost highly reversible sodium-ion storage, wherein a record-high reversible degree of 85.65% is achieved for MoS2 anodes. Composed of nitrogen-doped carbon-supported single atom Mn (NC-SAMn), this bifunctional nanoreactor concurrently confines active materials spatially and catalyzes reaction kinetics. In-situ/ex-situ characterizations including spectroscopy, microscopy, and electrochemistry, combined with theoretical simulations containing density functional theory and molecular dynamics, confirm that the NC-SAMn nanoreactors facilitate the electron/ion transfer, promote the distribution and interconnection of discharging products (Na2S/Mo), and reduce the Na2S decomposition barrier.As a result, the nanoreactor-promoted MoS2 anodes exhibit ultra-stable cycling with a capacity retention of 99.86% after 200 cycles in the full cell. This work demonstrates the superiority of bifunctional nanoreactors with two-dimensional confined and catalytic effects, providing a feasible approach to improve the reversibility for a wide range of conversion-type electrode materials, thereby enhancing the application potential for long-cycled SIBs.
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Micrometer-sized silicon monoxide (SiO) is regarded as a high-capacity anode material with great potential for lithium ion batteries (LIBs). However, the problems of low initial Coulombic efficiency (ICE), poor electrical conductivity, and large volume change of SiO inevitably impede further application. Herein, the vacuum thermal reduced SiOx with amorphous AlPO4 and carbon double-coating layers is used as the ideal anode material in LIBs. The vacuum thermal reduction at low temperature forms fine silicon grains in the internal particles and maintains the external integrity of SiOx particles, contributing to mitigation of the stress intensification and the subsequent design of multifunctional coating. Meanwhile, the innovative introduction of the multifunctional amorphous AlPO4 layer not only improves the ion/electron conduction properties to ensure the fast reversible reaction but also provides a robust protective layer with stable physicochemical characteristics and inhibits the volume expansion effect. The sample of SiOx anode shows an ICE up to 87.6% and a stable cycling of 200 cycles at 1 A g-1 with an initial specific capacity of 1775.8 mAh g-1. In addition, the assembled pouch battery of 1.8 Ah can also ensure a cycling life of over 150 cycles, demonstrating a promising prospect of this optimized micrometer-sized SiOx anode material for industrial applications.
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Constructing structure-function relationships is critical for the rational design and development of efficient catalysts for CO2 electroreduction reaction (CO2RR). In2O3 is well-known for its specific ability to produce formic acid. However, how the crystal phase and surface affect the CO2RR activity is still unclear, making it difficult to further improve the intrinsic activity and screen for the most active structure. In this work, cubic and hexagonal In2O3 with different stable surfaces ((111) and (110) for cubic, (120) and (104) for hexagonal) are investigated for CO2RR. Theoretical results demonstrate that the adsorption of reactants on cubic In2O3 is stronger than that on hexagonal In2O3, with the cubic (111) surface being the most active for CO2RR. In experiments, synthesized cubic In2O3 nanosheets with predominantly exposed (111) surfaces exhibited a high HCOO- Faradaic efficiency (87.5%) and HCOO- current density (-16.7 mA cm-2) at -0.9 V vs RHE. In addition, an aqueous Zn-CO2 battery based on a cubic In2O3 cathode was assembled. Our work correlates the phases and surfaces with the CO2RR activity, and provides a fundamental understanding of the structure-function relationship of In2O3, thereby contributing to further improvements in its CO2RR activity. Moreover, the results provide a principle for the directional preparation of materials with optimal phases and surfaces for efficient electrocatalysis.
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Background: The occurrence of pulmonary adenocarcinoma coexisting with atypical carcinoid tumors is a rare phenomenon. The presence of EML4-ALK fusion in an atypical carcinoid component of a histologically mixed tumor is even more uncommon. Due to their infrequency, the origin and pathogenesis of these mixed tumors remain largely unknown. The advances of therapy development in such patients are still limited and there is no standard treatment. We present a case of collision tumor in the lung consisting of atypical carcinoid and adenocarcinoma to better understand the clinical characteristics of this disease. Case Description: We report an extremely rare case of EML4-ALK rearrangement in a pulmonary atypical carcinoid tumor that coexisting with adenocarcinoma. A 58-year-old woman, who was asymptomatic, underwent pulmonary lobectomy due to the detection of a gradually enlarging solitary pulmonary nodule in the right upper lung. Histological examination of the resected tumor revealed the presence of both atypical carcinoid (approximately 80%) and adenocarcinoma (approximately 20%) components. Metastases by the carcinoid component were observed in mediastinal lymph nodes (station 2R and 4R) and in the primary tumor. Anaplastic lymphoma kinase (ALK) rearrangement was detected in both the primary and metastatic lesions of the carcinoid tumor. Four cycles of chemotherapy with etoposide and carboplatin were dispensed after surgery. Conclusions: This is the first reported case of coexisting pulmonary adenocarcinoma and atypical carcinoid tumor with an ALK fusion only detected in the carcinoid component. The presence of ALK rearrangement in pulmonary carcinoid tumor is very uncommon, and there is currently no standard treatment for advanced stages. Therefore, comprehensive molecular testing, including ALK rearrangement analysis, should be recommended for mixed tumors exhibiting features of atypical carcinoid. ALK inhibitors could represent a potential treatment strategy for selected patients.
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Micro-mirror optical fiber hydrogen sensors have the advantages of compact structure and fast demodulation speed. All-optical sensor networks consisting of micro-mirror optical fiber hydrogen sensors are essentially necessary across the hydrogen value chain. A bus chain topology structure hydrogen leakage detecting system based on micro-mirror sensors is proposed and experimentally demonstrated. A compensating optical path with constant power supply is introduced, and the power dissipation scheme is theoretically and experimentally proposed by designating the splitting ratios of the splitters array. By constructing such a network with twenty micro-mirror hydrogen sensors, the system has been experimentally verified with good repeatability and stability under different concentrations of hydrogen. By employing this bus chain topology strategy, a quasi-distributed optical fiber hydrogen leakage detection system with micro-mirror hydrogen sensors array is realized. It will provide a promising solution with high feasibility on multi-point leakage detecting in hydrogen infrastructures.
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A novel, to the best of our knowledge, and compact fiber-optic hydrogen sensor based on light intensity demodulation and controllable optical heating technology is proposed and experimentally investigated. This system employs three photodetectors for optic signal transformation. The first PD is used to receive a little fraction of the amplified spontaneous emission (ASE) for calibration, and the second PD is utilized to detect optic signal reflected by a single mode fiber deposited with WO3-Pd2Pt-Pt composite film. The last PD is utilized to receive the optical power reflected by the short fiber Bragg grating (SFBG) with a central wavelength located in a steep wavelength range (the intensity decreases approximately linearly with the increase of the wavelength) of the ASE light source. A 980â nm laser and proportion integration differentiation (PID) controller were employed to ensure the hydrogen sensitive film working at an operating temperature of 60°C. This sensing system can display a quick response time of 0.4â s toward 10,000â ppm hydrogen in air. In addition, the detection limit of 5â ppm in air can be achieved with this sensing system. The stability of this sensor can be greatly enhanced with a controllable optical heating system, which can greatly promote its potential application in various fields.
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Nickel-rich layered oxide LiNixCoyMnzO2 (NCM, x + y + z = 1) is the most promising cathode material for high-energy lithium-ion batteries. However, conventional synthesis methods are limited by the slow heating rate, sluggish reaction dynamics, high energy consumption, and long reaction time. To overcome these challenges, we first employed a high-temperature shock (HTS) strategy for fast synthesis of the NCM, and the approaching ultimate reaction rate of solid phase transition is deeply investigated for the first time. In the HTS process, ultrafast average reaction rate of phase transition from Ni0.6Co0.2Mn0.2(OH)2 to Li- containing oxides is 66.7 (% s-1), that is, taking only 1.5 s. An ultrahigh heating rate leads to fast reaction kinetics, which induces the rapid phase transition of NCM cathodes. The HTS-synthesized nickel-rich layered oxides perform good cycling performances (94% for NCM523, 94% for NCM622, and 80% for NCM811 after 200 cycles at 4.3 V). These findings might also assist to pave the way for preparing effectively Ni-rich layered oxides for lithium-ion batteries.
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The Fenton reaction, induced by the H2O2 formed during the oxygen reduction reaction (ORR) process leads to significant dissolution of Fe, resulting in unsatisfactory stability of the iron-nitrogen-doped carbon catalysts (Fe-NC). In this study, a strategy is proposed to improve the ORR catalytic activity while eliminating the effect of H2O2 by introducing CeO2 nanoparticles. Transmission electron microscopy and subsequent characterizations reveal that CeO2 nanoparticles are uniformly distributed on the carbon substrate, with atomically dispersed Fe single-atom catalysts (SACs) adjacent to them. CeO2@Fe-NC achieves a half-wave potential of 0.89 V and a limiting current density of 6.2 mA cm-2, which significantly outperforms Fe-NC and commercial Pt/C. CeO2@Fe-NC also shows a half-wave potential loss of only 1% after 10 000 CV cycles, which is better than that of Fe-NC (7%). Further, H2O2 elimination experiments show that the introduction of CeO2 significantly accelerate the decomposition of H2O2. In situ Raman spectroscopy results suggest that CeO2@Fe-NC significantly facilitates the formation of ORR intermediates compared with Fe-NC. The Zn-air batteries utilizing CeO2@Fe-NC cathodes exhibit satisfactory peak power density and open-circuit voltage. Furthermore, theoretical calculations show that the introduction of CeO2 enhances the ORR activity of Fe-NC SAC. This study provides insights for optimizing SAC-based electrocatalysts with high activity and stability.
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Despite widely used as a commercial cathode, the anisotropic 1D channel hopping of lithium ions along the [010] direction in LiFePO4 prevents its application in fast charging conditions. Herein, an ultrafast nonequilibrium high-temperature shock technology is employed to controllably introduce the Li-Fe antisite defects and tensile strain into the lattice of LiFePO4. This design makes the study of the effect of the strain field on the performance further extended from the theoretical calculation to the experimental perspective. The existence of Li-Fe antisite defects makes it feasible for Li+ to move from the 4a site of the edge-sharing octahedra across the ab plane to 4c site of corner-sharing octahedra, producing a new diffusion channel different from [010]. Meanwhile, the presence of a tensile strain field reduces the energy barrier of the new 2D diffusion path. In the combination of electrochemical experiments and first-principles calculations, the unique multiscale coupling structure of Li-Fe antisite defects and lattice strain promotes isotropic 2D interchannel Li+ hopping, leading to excellent fast charging performance and cycling stability (high-capacity retention of 84.4% after 2000 cycles at 10 C). The new mechanism of Li+ diffusion kinetics accelerated by multiscale coupling can guide the design of high-rate electrodes.
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This paper focuses on the preparation and evaluation of a novel humidity-control material, vermiculite/(sodium polyacrylate(AA)-acrylamide(AM)), using inverse suspension polymerization. Acrylic acid and acrylamide were introduced into the interlayer of modified vermiculite during the polymerization process, leading to the formation of a strong association with the modified vermiculite. The addition of vermiculite increased the specific surface area and pore volume of the composites. To investigate the moisture absorption and desorption properties of the composites, an orthogonal experiment and single-factor experiment were conducted to analyze the impacts of vermiculite content, neutralization degree, and the mass ratio of AA to AM. According to the control experiment, the addition of vermiculite was found to enhance the pore structure and surface morphology of the composite material, surpassing both vermiculite and PAA-AM copolymer in terms of humidity control capacity and rate. The optimal preparation conditions were identified as follows: vermiculite mass fraction of 4 wt%, a neutralization degree of 90%, and mAA:mAM = 4:1. The moisture absorption rate and moisture release rate of the composite material prepared under these conditions are 1.285 g/g and 1.172 g/g. The humidity control process of the composite material is governed by pseudo second-order kinetics, which encompasses the complete adsorption process. These results indicate that the vermiculite/PAA-AM composite humidity control material has excellent humidity control performance and is a simple and efficient humidity control method.
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Emerging high entropy compounds (HECs) have attracted huge attention in electrochemical energy-related applications. The features of ultrafine size and carbon incorporation show great potential to boost the ion-storage kinetics of HECs. However, they are rarely reported because high-temperature calcination tends to result in larger crystallites, phase separation, and carbon reduction. Herein, using the NaCl self-assembly template method, by introducing a high-pressure field in the calcination process, the atom diffusion and phase separation are inhibited for the general formation of HECs, and the HEC aggregation is inhibited for obtaining ultrafine size. The general preparation of ultrafine-sized (<10â nm) HECs (nitrides, oxides, sulfides, and phosphates) anchored on porous carbon composites is realized. They are demonstrated by combining advanced characterization technologies with theoretical computations. Ultrafine-sized high entropy sulfides-MnFeCoCuSnMo/porous carbon (HES-MnFeCoCuSnMo/PC) as representative anodes exhibit excellent sodium-ion storage kinetics and capacities (a high rating capacity of 278â mAh g-1 at 10â A g-1 for full cell and a high cycling capacity of 281â mAh g-1 at 20â A g-1 after 6000 cycles for half cell) due to the combining advantages of high entropy effect, ultrafine size, and PC incorporation. Our work provides a new opportunity for designing and fabricating ultrafine-sized HECs.
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Graph Transformers (GTs) have achieved impressive results on various graph-related tasks. However, the huge computational cost of GTs hinders their deployment and application, especially in resource-constrained environments. Therefore, in this paper, we explore the feasibility of sparsifying GTs, a significant yet under-explored topic. We first discuss the redundancy of GTs based on the characteristics of existing GT models, and then propose a comprehensive Graph Transformer SParsification (GTSP) framework that helps to reduce the computational complexity of GTs from four dimensions: the input graph data, attention heads, model layers, and model weights. Specifically, GTSP designs differentiable masks for each individual compressible component, enabling effective end-to-end pruning. We examine our GTSP through extensive experiments on prominent GTs, including GraphTrans, Graphormer, and GraphGPS. The experimental results demonstrate that GTSP effectively reduces computational costs, with only marginal decreases in accuracy or, in some instances, even improvements. For example, GTSP results in a 30% reduction in Floating Point Operations while contributing to a 1.8% increase in Area Under the Curve accuracy on the OGBG-HIV dataset. Furthermore, we provide several insights on the characteristics of attention heads and the behavior of attention mechanisms, all of which have immense potential to inspire future research endeavors in this domain. Our code is available at https://github.com/LiuChuang0059/GTSP.
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Alluaudite sodium iron sulfate (NFS) exhibits great potential for use in sodium-ion battery cathodes due to its elevated operating potential and abundant element reserves. However, conventional solid-state methods demonstrate a low heating/cooling rate and sluggish reaction kinetics, requiring a long thermal treatment to effectively fabricate NFS cathodes. Herein, we propose a thermal shock (TS) strategy to synthesize alluaudite sodium iron sulfate cathodes using either hydrous or anhydrous raw materials. The analysis of the phase formation process reveals that TS treatment can significantly facilitate the removal of crystal water and decomposition of the intermediate phase Na2Fe(SO4)2 in the hydrous precursor. In the case of the anhydrous precursor, the kinetics of the combination reaction between Na2SO4 and FeSO4 can be also accelerated by TS treatment. Consequently, pure NFS phase formation can be completed after a substantially shorter time of post-sintering, thereby saving significant time and energy. The TS-treated NFS cathode derived from hydrous precursor exhibits higher retention after 200 cycles at 1C and better rate capability than the counterpart prepared by conventional long-term tube furnace sintering, demonstrating the great potential of this novel strategy.
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As dynamic graphs have become indispensable in numerous fields due to their capacity to represent evolving relationships over time, there has been a concomitant increase in the development of Temporal Graph Neural Networks (TGNNs). When training TGNNs for dynamic graph link prediction, the commonly used negative sampling method often produces starkly contrasting samples, which can lead the model to overfit these pronounced differences and compromise its ability to generalize effectively to new data. To address this challenge, we introduce an innovative negative sampling approach named Enhanced Negative Sampling (ENS). This strategy takes into account two pervasive traits observed in dynamic graphs: (1) Historical dependence, indicating that nodes frequently reestablish connections they held in the past, and (2) Temporal proximity preference, which posits that nodes are more inclined to connect with those they have recently interacted with. Specifically, our technique employs a designed scheduling function to strategically control the progression of difficulty of the negative samples throughout the training. This ensures that the training progresses in a balanced manner, becoming incrementally challenging, and thereby enhancing TGNNs' proficiency in predicting links within dynamic graphs. In our empirical evaluation across multiple datasets, we discerned that our ENS, when integrated as a modular component, notably augments the performance of four SOTA baselines. Additionally, we further investigated the applicability of ENS in handling dynamic graphs of varied attributes. Our code is available at https://github.com/qqaazxddrr/ENS.
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Redes Neurales de la ComputaciónRESUMEN
Homeobox A1 (HOXA1) is a protein coding gene involved in regulating immunity signaling. This study aims to explore the function and mechanism of HOXA1 in asthma. An asthma mouse model was established via ovalbumin (OVA) induction. Airway hyperresponsiveness was evaluated by the value of pause enhancement (Penh). Inflammatory cells in bronchoalveolar lavage fluid (BALF) were detected by Trypan blue and Wright staining. The pathological morphology of lung tissues was assessed by H&E staining. The IgE and inflammatory biomarkers (IL-1ß, IL-6, IL-17, and TNF-α) in BALF and lung tissues were measured by ELISA. Western blot was performed to detect the expression of NF-κB pathway-related proteins. HOXA1 was down-regulated in OVA-induced asthmatic mice. Overexpression of HOXA1 decreased Penh and relieved pathological injury of lung tissues in OVA-induced mice. Overexpression of HOXA1 also reduced the numbers of total cells, leukocytes, eosinophils, neutrophils, macrophages, and lymphocytes, as well as the levels of IgE, IL-1ß, IL-6, IL-17, and TNF-α in BALF of OVA-induced mice. The inflammatory biomarkers were also decreased in lung tissues by HOXA1 overexpression. In addition, HOXA1 overexpression blocked the NF-κB signaling pathway in OVA-induced mice. Overexpression of HOXA1 relieved OVA-induced asthma in female mice, which is associated with the blocking of the NF-κB signaling pathway.
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Asma , FN-kappa B , Femenino , Humanos , Animales , Ratones , Ovalbúmina , Interleucina-17 , Genes Homeobox , Interleucina-6 , Factor de Necrosis Tumoral alfa , Transducción de Señal , Asma/inducido químicamente , Interleucina-1beta , Biomarcadores , Inmunoglobulina ERESUMEN
Increasing the charging cutoff voltage of LiCoO2 to 4.6 V is significant for enhancing battery density. However, the practical application of LiâLiCoO2 batteries with a 4.6 V cutoff voltage faces significant impediments due to the detrimental changes under high voltage. This study presents a novel bifunctional electrolyte additive, 2-(trifluoromethyl)benzamide (2-TFMBA), which is employed to establish a stable and dense cathode-electrolyte interface (CEI). Characterization results reveal that an optimized CEI is achieved through the synergistic effects of the amide groups and trifluoromethyl groups within 2-TFMBA. The resulting CEI not only enhances the structural stability of LiCoO2 but also serves as a high-speed lithium-ion conduction channel, which expedites the insertion and extraction of lithium ions. The LiâLiCoO2 batteries with 0.5 wt% 2-TFMBA achieves an 84.7% capacity retention rate after enduring 300 cycles at a current rate of 1 C, under a cut-off voltage of 4.6 V. This study provides valuable strategic insights into the stabilization of cathode materials in high-voltage batteries.
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Potassium-sulfur batteries attract tremendous attention as high-energy and low-cost energy storage system, but achieving high utilization and long-term cycling of sulfur remains challenging. Here we show a strategy of optimizing potassium polysulfides for building high-performance potassium-sulfur batteries. We design the composite of tungsten single atom and tungsten carbide possessing potassium polysulfide migration/conversion bi-functionality by theoretical screening. We create two ligand environments for tungsten in the metal-organic framework, which respectively transmute into tungsten single atom and tungsten carbide nanocrystals during pyrolysis. Tungsten carbide provide catalytic sites for potassium polysulfides conversion, while tungsten single atoms facilitate sulfides migration thereby significantly alleviating the insulating sulfides accumulation and the associated catalytic poisoning. Resultantly, highly efficient potassium-sulfur electrochemistry is achieved under high-rate and long-cycling conditions. The batteries deliver 89.8% sulfur utilization (1504 mAh g-1), superior rate capability (1059 mAh g-1 at 1675 mA g-1) and long lifespan of 200 cycles at 25 °C. These advances enlighten direction for future KSBs development.
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Aqueous Zn-based batteries have emerged as compelling candidates for grid-scale energy storage, owing to their intrinsic safety, remarkable theoretical energy density and cost-effectiveness. Nonetheless, the dendrite formation, side reactions, and corrosion on anode have overshadowed their practical applications. Herein, we present an in situ grown carbon network reinforcing Zn matrix anode prepared by powder metallurgy. This carbon network provides an uninterrupted internal electron transport pathway and optimize the surface electric field distribution, thereby enabling highly reversible Zn deposition. Consequently, symmetrical cells demonstrate impressive stability, running for over 880â h with a low voltage hysteresis (≈32â mV). Furthermore, this Zn matrix composite anode exhibits enhanced performance in both the aqueous Zn-ion and the Zn-air batteries. Notably, Zn//MnO2 cells display superior rate capabilities, while Zn-air batteries deliver high power density and impressive Zn utilization rate (84.9 %). This work provides a new idea of powder metallurgy method for modified Zn anodes, showcasing potential for large-scale production.
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In recent years, the utilization of wastewater recycling as an alternative water source has gained significant traction in addressing urban water shortages. Accurate prediction of wastewater quantity is paramount for effective urban river water resource management. There is an urgent need to develop advanced forecasting technologies to further enhance the accuracy and efficiency of water quantity predictions. Decomposition ensemble models have shown excellent predictive capabilities but are challenged by boundary effects when decomposing the original data sequence. To address this, a rolling forecast decomposition ensemble scheme was developed. It involves using a machine learning (ML) model for prediction and progressively integrating prediction outcomes into the original sequence using complementary ensemble empirical mode decomposition with adaptive noise (CEEMDAN). Long short-term memory (LSTM) is then applied for sub-signal prediction and ensemble. The ML-CEEMDAN-LSTM model was introduced for wastewater quantity prediction, compared with non-decomposed ML models, CEEMDAN-based LSTM models, and ML-CEEMDAN-based LSTM models. Three ML algorithms-linear regression (LR), gradient boosting regression (GBR), and LSTM-were examined, using real-time prediction data and historical monitoring data, with historical data selected using the decision tree method. The study used daily water volumes data from two reclaimed water plants, CH and WQ, in Beijing. The results indicate that (1) ML models varied in their selection of real-time factors, with LR performing best among ML models during testing; (2) the ML-CEEMDAN-LSTM model consistently outperformed ML models; (3) the ML-CEEMDAN-LSTM hybrid model performed better than the CEEMDAN-LSTM model across different seasons. This study offers a reliable and accurate approach for reclaimed water volumes forecasting, critical for effective water environment management.
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Ríos , Agua , Conservación de los Recursos Naturales , Aguas Residuales , Agua Dulce , PredicciónRESUMEN
High-entropy-alloy nanoparticles (HEA-NPs) show great potential as electrocatalysts for water splitting, fuel cells, CO2 conversion, etc. However, fine-tuning the surface, morphology, structure, and crystal phase of HEA remains a great challenge. Here, the high-temperature liquid shock (HTLS) technique is applied to produce HEA-NPs, e.g., PtCoNiRuIr HEA-NPs, with tunable elemental components, ultrafine particle size, controlled crystal phases, and lattice strains. HTLS directly applied Joule heating on the liquid mixture of metal precursors, capping agents, and reducing agents, which is feasible for controlling the morphology and structure such as the atomic arrangement of the resulting products, thereby facilitating the rationally designed nanocatalysts. Impressively, the as-obtained PtCoNiRuIr HEA-NPs delivered superior activity and long-term stability for the hydrogen evolution reaction (HER), with low overpotentials at 10 mA cm-2 and 1 A cm-2 of only 18 and 408 mV, respectively, and 10000 CV stable cycles in 0.5 M H2SO4. Furthermore, in the near future, by combining the HTLS method with artificial intelligence (AI) and theoretical calculations, it is promising to provide an advanced platform for the high-throughput synthesis of HEA nanocatalysts with optimized performance for various energy applications, which is of great significance for achieving a carbon-neutral society with an effective and environmentally friendly energy system.