What Is the Real Origin of Single-Walled Carbon Nanotubes for the Performance Enhancement of Si-Based Anodes?

A large amount of lithium-ion storage in Si-based anodes promises high energy density yet also results in large volume expansion, causing impaired cyclability and conductivity. Instead of restricting pulverization of Si-based particles, herein, we disclose that single-walled carbon nanotubes (SWNTs) can take advantage of volume expansion and induce interfacial reactions that stabilize the pulverized Si-based clusters in situ. Operando Raman spectroscopy and density functional theory calculations reveal that the volume expansion by the lithiation of Si-based particles generates ∼14% tensile strains in SWNTs, which, in turn, strengthens the chemical interaction between Li and C. This chemomechanical coupling effect facilitates the transformation of sp2-C at the defect of SWNTs to Li-C bonds with sp3 hybridization, which also initiates the formation of new Si-C chemical bonds at the interface. Along with this process, SWNTs can also induce in situ reconstruction of the 3D architecture of the anode, forming mechanically strengthened networks with high electrical and ionic conductivities. As such, with the addition of only 1 wt % of SWNTs, graphite/SiOx composite anodes can deliver practical performance well surpassing that of commercial graphite anodes. These findings enrich our understanding of strain-induced interfacial reactions, providing a general principle for mitigating the degradation of alloying or conversion-reaction-based electrodes.

Particle Swarm Optimization of Multilayer Multi-Sized Metamaterial Absorber for Long-Wave Infrared Polarimetric Imaging.

Infrared polarization imaging holds significant promise for enhancing target recognition in both civil and defense applications. The Division of Focal Plane (DoFP) scheme has emerged as a leading technology in the field of infrared polarization imaging due to its compact design and absence of moving parts. However, traditional DoFP solutions primarily rely on micro-polarizer arrays, necessitating precise alignment with the focal plane array and leading to challenges in alignment and the introduction of optical crosstalk. Recent research has sought to augment the performance of infrared detectors and enable polarization and spectral selection by integrating metamaterial absorbers with the pixels of the detector. Nevertheless, the results reported so far exhibit shortcomings, including low polarization absorption rates and inadequate polarization extinction ratios. Furthermore, there is a need for a comprehensive figure of merit to systematically assess the performance of polarization-selective thermal detectors. In this study, we employ the particle swarm optimization algorithm to present a multilayer, multi-sized metamaterial absorber capable of achieving a remarkable polarization-selective absorption rate of up to 87.2% across the 8-14 µm spectral range. Moreover, we attain a polarization extinction ratio of 38.51. To elucidate and predict the resonant wavelengths of the structure, we propose a modified equivalent circuit model. Our analysis employs optical impedance matching to unveil the underlying mechanisms responsible for the high absorption. We also introduce a comprehensive figure of merit to assess the efficacy of infrared polarization detection through the integration of metamaterials with microbolometers. Finally, drawing on the proposed figure of merit, we suggest future directions for improving integrated metamaterial absorber designs, with the potential to advance practical mid-infrared polarization imaging technologies.

The P2Y1 receptor in the colonic myenteric plexus of rats and its correlation with opioid-induced constipation.

This study was designed to explore the expression changes of P2Y1 receptors in the distal colonic myenteric layer of rats. An opioid induced constipation(OIC) rat model was generated by intraperitoneal (i.p) injection of loperamide. At 7 days post-treatment, the model rats were assessed by calculating the fecal water content and the gastrointestinal transit ratio. The immunofluorescence (IF)-based histochemical study was used to observe the distribution of P2Y1 receptors in the distal colonic myenteric plexus. Western blotting (WB) was performed to evaluate the expression changes of P2Y1 proteins in the myenteric layer, and the electrophysiological approaches were carried out to determine the regulatory roles of P2Y1 receptors on distal colonic motor function. IF showed that P2Y1 receptors are co-expressed MOR in the enteric nerve cells of the distal colonic myenteric plexus. Moreover, the WB revealed that the protein levels of P2Y1 were significantly decreased in the distal colonic myenteric layer of OIC rats. In vitro tension experiments exhibited that the P2Y1 receptor antagonist MRS2500 enhanced the spontaneous contraction amplitude, adding EM2 and ß-FNA did not have any effect on MRS2500. Therefore, P2Y1 receptor expression could be associated with the occurrence of OIC in this rat model and the regulation of colonic motility by MOR may be related to the release of purine neurotransmitters such as ATP in the colonic nervous system.

DGW1, encoding an hnRNP-like RNA binding protein, positively regulates grain size and weight by interacting with GW6 mRNA.

Grain size and weight determine rice yield. Although numerous genes and pathways involved in regulating grain size have been identified, our knowledge of post-transcriptional control of grain size remains elusive. In this study, we characterize a rice mutant, decreased grain width and weight 1 (dgw1), which produces small grains. We show that DGW1 encodes a member of the heterogeneous nuclear ribonucleoprotein (hnRNP) family protein and preferentially expresses in developing panicles, positively regulating grain size by promoting cell expansion in spikelet hulls. Overexpression of DGW1 increases grain weight and grain numbers, leading to a significant rise in rice grain yield. We further demonstrate that DGW1 functions in grain size regulation by directly binding to the mRNA of Grain Width 6 (GW6), a critical grain size regulator in rice. Overexpression of GW6 restored the grain size phenotype of DGW1-knockout plants. DGW1 interacts with two oligouridylate binding proteins (OsUBP1a and OsUBP1b), which also bind the GW6 mRNA. In addition, the second RRM domain of DGW1 is indispensable for its mediated protein-RNA and protein-protein interactions. In summary, our findings identify a new regulatory module of DGW1-GW6 that regulates rice grain size and weight, providing important insights into the function of hnRNP-like proteins in the regulation of grain size.

Lightweight semantic segmentation network with configurable context and small object attention.

The current semantic segmentation algorithms suffer from encoding feature distortion and small object feature loss. Context information exchange can effectively address the feature distortion problem, but it has the issue of fixed spatial range. Maintaining the input feature resolution can reduce the loss of small object information but would slow down the network's operation speed. To tackle these problems, we propose a lightweight semantic segmentation network with configurable context and small object attention (CCSONet). CCSONet includes a long-short distance configurable context feature enhancement module (LSCFEM) and a small object attention decoding module (SOADM). The LSCFEM differs from the regular context exchange module by configuring long and short-range relevant features for the current feature, providing a broader and more flexible spatial range. The SOADM enhances the features of small objects by establishing correlations among objects of the same category, avoiding the introduction of redundancy issues caused by high-resolution features. On the Cityscapes and Camvid datasets, our network achieves the accuracy of 76.9 mIoU and 73.1 mIoU, respectively, while maintaining speeds of 87 FPS and 138 FPS. It outperforms other lightweight semantic segmentation algorithms in terms of accuracy.

A fatty acid photodecarboxylase-mimicking photonanozyme with defect-induced enzymatic substrate-binding pockets.

Hydrocarbon synthesis hints at the significance of in-depth investigations and detailed explanations of mimicking fatty acid photodecarboxylase (FAP). Considering the importance of photodecarboxylases in hydrocarbon synthesis, we present the potential of defective semiconductor nanomaterials as a novel type of photonanozymes (PNZs) that mimic enzyme-like performance, serving as alternatives to FAP. Ferrum-doped titanium dioxide (Fe-TiO2) was synthesized to introduce appropriate amounts of surface defects including reduced Ti3+ sites and oxygen vacancies, which reduce the band gap of TiO2 and enhance the visible-light absorption, thereby facilitating efficient charge trapping. Notably, the surface defects of Fe-TiO2 PNZs singularly act as enzymatic substrate-binding pockets that enable efficient carboxylic acid adsorption during the dark process, conversely facilitating the formation of more defects and boosting the FAP-like activity for photocatalytic decarboxylation reactions. This work provides a creative strategy for designing substrate-dependent higher-concentration defects as enzyme-like binding sites on promising PNZs that mimic natural photoenzymes.

Computer Vision-Based Bridge Inspection and Monitoring: A Review.

Bridge inspection and monitoring are usually used to evaluate the status and integrity of bridge structures to ensure their safety and reliability. Computer vision (CV)-based methods have the advantages of being low cost, simple to operate, remote, and non-contact, and have been widely used in bridge inspection and monitoring in recent years. Therefore, this paper reviews three significant aspects of CV-based methods, including surface defect detection, vibration measurement, and vehicle parameter identification. Firstly, the general procedure for CV-based surface defect detection is introduced, and its application for the detection of cracks, concrete spalling, steel corrosion, and multi-defects is reviewed, followed by the robot platforms for surface defect detection. Secondly, the basic principle of CV-based vibration measurement is introduced, followed by the application of displacement measurement, modal identification, and damage identification. Finally, the CV-based vehicle parameter identification methods are introduced and their application for the identification of temporal and spatial parameters, weight parameters, and multi-parameters are summarized. This comprehensive literature review aims to provide guidance for selecting appropriate CV-based methods for bridge inspection and monitoring.

Silver Ion-Facilitated Singular Poulos-Kraut Mechanism of O-O Heterolysis to Enhance the Light Activation of H2O2 over Peroxidase-Mimicking Photonanozymes.

The Poulos-Kraut heterolytic O-O cleavage mechanism is essential for natural peroxidases to activate H2O2. Current existing peroxidase-mimicking nanozymes, including photonanozymes (PNZs), however, are generally believed to prefer the Fenton-type mechanism of O-O homolysis, which produces •OH radicals. Here, Ag+ ions are introduced into TiO2 PNZs to boost the hot hole-driven O-O heterolysis for the expedited H2O2 activation in the peroxidase-like photonanozymatic reaction while inhibiting the Fenton-type O-O homolysis. The Ag+-facilitated Poulos-Kraut heterolytic O-O cleavage mechanism for H2O2 activation is explicated in terms of the speedy capture and exhaustion of photogenerated electrons by Ag+ and the dissociation of the peroxo-oxygen bridge in Ti-O-OH promoted by accumulated hot holes. Moreover, the enhanced photonanozymatic activity of TiO2 PNZs enables the construction of a rapid colorimetric sensing platform for Ag+ determination. This work provides valuable insights into the mechanism of H2O2 activation and exemplifies a novel photoregulation strategy for controlling reaction pathways in nanozymes.

Interface engineering for high-performance, triple-halide perovskite-silicon tandem solar cells.

Improved stability and efficiency of two-terminal monolithic perovskite-silicon tandem solar cells will require reductions in recombination losses. By combining a triple-halide perovskite (1.68 electron volt bandgap) with a piperazinium iodide interfacial modification, we improved the band alignment, reduced nonradiative recombination losses, and enhanced charge extraction at the electron-selective contact. Solar cells showed open-circuit voltages of up to 1.28 volts in p-i-n single junctions and 2.00 volts in perovskite-silicon tandem solar cells. The tandem cells achieve certified power conversion efficiencies of up to 32.5%.

Managing Excess Lead Iodide with Functionalized Oxo-Graphene Nanosheets for Stable Perovskite Solar Cells.

Stability issues could prevent lead halide perovskite solar cells (PSCs) from commercialization despite it having a comparable power conversion efficiency (PCE) to silicon solar cells. Overcoming drawbacks affecting their long-term stability is gaining incremental importance. Excess lead iodide (PbI2 ) causes perovskite degradation, although it aids in crystal growth and defect passivation. Herein, we synthesized functionalized oxo-graphene nanosheets (Dec-oxoG NSs) to effectively manage the excess PbI2 . Dec-oxoG NSs provide anchoring sites to bind the excess PbI2 and passivate perovskite grain boundaries, thereby reducing charge recombination loss and significantly boosting the extraction of free electrons. The inclusion of Dec-oxoG NSs leads to a PCE of 23.7 % in inverted (p-i-n) PSCs. The devices retain 93.8 % of their initial efficiency after 1,000 hours of tracking at maximum power points under continuous one-sun illumination and exhibit high stability under thermal and ambient conditions.

Stabilization of Inorganic Perovskite Solar Cells with a 2D Dion-Jacobson Passivating Layer.

Inorganic metal halide perovskites such as CsPbI3 are promising for high-performance, reproducible, and robust solar cells. However, inorganic perovskites are sensitive to humidity, which causes the transformation from the black phase to the yellow δ, non-perovskite phase. Such phase instability has been a significant challenge to long-term operational stability. Here, a surface dimensionality reduction strategy is reported, using 2-(4-aminophenyl)ethylamine cation to construct a Dion-Jacobson 2D phase that covers the surface of the 3D inorganic perovskite structure. The Dion-Jacobson layer mainly grows at the grain boundaries of the perovskite, effectively passivating surface defects and providing favourable interfacial charge transfer. The resulting inorganic perovskite films exhibit excellent humidity resistance when submerged in an aqueous solution (isopropanol:water = 4:1 v/v) and exposed to a 50% humidity air atmosphere. The Dion-Jacobson 2D/3D inorganic perovskite solar cell (PSC) achieves a power conversion efficiency (PCE) of 19.5% with a Voc of 1.197 eV. It retains 83% of its initial PCE after 1260 h of maximum power point tracking under 1.2 sun illumination. The work demonstrates an effective way for stabilizing efficient inorganic perovskite solar cells.

Integrating reduced amino acid composition into PSSM for improving copper ion-binding protein prediction.

Copper ion-binding proteins play an essential role in metabolic processes and are critical factors in many diseases, such as breast cancer, lung cancer, and Menkes disease. Many algorithms have been developed for predicting metal ion classification and binding sites, but none have been applied to copper ion-binding proteins. In this study, we developed a copper ion-bound protein classifier, RPCIBP, which integrating the reduced amino acid composition into position-specific scoring matrix (PSSM). The reduced amino acid composition filters out a large number of useless evolutionary features, improving the operational efficiency and predictive ability of the model (feature dimension from 2900 to 200, ACC from 83 % to 85.1 %). Compared with the basic model using only three sequence feature extraction methods (ACC in training set between 73.8 %-86.2 %, ACC in test set between 69.3 %-87.5 %), the model integrating the evolutionary features of the reduced amino acid composition showed higher accuracy and robustness (ACC in training set between 83.1 %-90.8 %, ACC in test set between 79.1 %-91.9 %). Best copper ion-binding protein classifiers filtered by feature selection progress were deployed in a user-friendly web server (http://bioinfor.imu.edu.cn/RPCIBP). RPCIBP can accurately predict copper ion-binding proteins, which is convenient for further structural and functional studies, and conducive to mechanism exploration and target drug development.

The Metal-binding Protein Atlas (MbPA): An Integrated Database for Curating Metalloproteins in All Aspects.

Metal-binding proteins are essential for the vital activities and engage in their roles by acting in concert with metal cations. MbPA (The Metal-binding Protein Atlas) is the most comprehensive resource up to now dedicated to curating metal-binding proteins. Currently, it contains 106,373 entries and 440,187 sites related to 54 metals and 8169 species. Users can view all metal-binding proteins and species-specific proteins in MbPA. There are also metal-proteomics data that quantitatively describes protein expression in different tissues and organs. By analyzing the data of the amino acid residues at the metal-binding site, it is found that about 80% of the metal ions tend to bind to cysteine, aspartic acid, glutamic acid, and histidine. Moreover, we use Diversity Measure to confirm that the diversity of metal-binding is specific in different area of periodic table, and further elucidate the binding modes of 19 transition metals on 20 amino acids. In addition, MbPA also embraces 6855 potential pathogenic mutations related to metalloprotein. The resource is freely available at http://bioinfor.imu.edu.cn/mbpa.

A cost-effective machine learning-based method for preeclampsia risk assessment and driver genes discovery.

BACKGROUND: The placenta, as a unique exchange organ between mother and fetus, is essential for successful human pregnancy and fetal health. Preeclampsia (PE) caused by placental dysfunction contributes to both maternal and infant morbidity and mortality. Accurate identification of PE patients plays a vital role in the formulation of treatment plans. However, the traditional clinical methods of PE have a high misdiagnosis rate. RESULTS: Here, we first designed a computational biology method that used single-cell transcriptome (scRNA-seq) of healthy pregnancy (38 wk) and early-onset PE (28-32 wk) to identify pathological cell subpopulations and predict PE risk. Based on machine learning methods and feature selection techniques, we observed that the Tuning ReliefF (TURF) score hybrid with XGBoost (TURF_XGB) achieved optimal performance, with 92.61% accuracy and 92.46% recall for classifying nine cell subpopulations of healthy placentas. Biological landscapes of placenta heterogeneity could be mapped by the 110 marker genes screened by TURF_XGB, which revealed the superiority of the TURF feature mining. Moreover, we processed the PE dataset with LASSO to obtain 497 biomarkers. Integration analysis of the above two gene sets revealed that dendritic cells were closely associated with early-onset PE, and C1QB and C1QC might drive preeclampsia by mediating inflammation. In addition, an ensemble model-based risk stratification card was developed to classify preeclampsia patients, and its area under the receiver operating characteristic curve (AUC) could reach 0.99. For broader accessibility, we designed an accessible online web server ( http://bioinfor.imu.edu.cn/placenta ). CONCLUSION: Single-cell transcriptome-based preeclampsia risk assessment using an ensemble machine learning framework is a valuable asset for clinical decision-making. C1QB and C1QC may be involved in the development and progression of early-onset PE by affecting the complement and coagulation cascades pathway that mediate inflammation, which has important implications for better understanding the pathogenesis of PE.

SGCAST: symmetric graph convolutional auto-encoder for scalable and accurate study of spatial transcriptomics.

Recent advances in spatial transcriptomics (ST) have enabled comprehensive profiling of gene expression with spatial information in the context of the tissue microenvironment. However, with the improvements in the resolution and scale of ST data, deciphering spatial domains precisely while ensuring efficiency and scalability is still challenging. Here, we develop SGCAST, an efficient auto-encoder framework to identify spatial domains. SGCAST adopts a symmetric graph convolutional auto-encoder to learn aggregated latent embeddings via integrating the gene expression similarity and the proximity of the spatial spots. This framework in SGCAST enables a mini-batch training strategy, which makes SGCAST memory-efficient and scalable to high-resolution spatial transcriptomic data with a large number of spots. SGCAST improves the overall accuracy of spatial domain identification on benchmarking data. We also validated the performance of SGCAST on ST datasets at various scales across multiple platforms. Our study illustrates the superior capacity of SGCAST on analyzing spatial transcriptomic data.

Strain Relaxation on Perovskite Surface via Light-Enhanced Ionic Homogeneity.

The efficiency and stability of perovskite solar cells (PSCs) can be either deteriorated or enhanced by strain at interfaces, which is sensitive to various external conditions, particularly light illumination. Here we investigated the vertical strain distribution in perovskite films synthesized under light illumination with various wavelengths. The films were formed by reacting formamidinium iodide (FAI)/methylammonium chloride (MACl) vapor with vapor-deposited PbI2 (CsBr) films. Strain in the films was evaluated with incident-angle-dependent grazing-incidence wide-angle X-ray scattering, which showed out-of-plane compressive and in-plane tensile strains, particularly on the surface. Short-wavelength light relaxed the strain on the perovskite surface via promotion of ionic diffusion, including FA, MA, Cs, and I, to reach vertical ionic homogeneity. With the charge trap concentration being reduced, both the efficiency and stability were greatly improved. This finding provides deep insight into the effect of light on strain in PSCs.

Nano-optical designs for high-efficiency monolithic perovskite-silicon tandem solar cells.

Perovskite-silicon tandem solar cells offer the possibility of overcoming the power conversion efficiency limit of conventional silicon solar cells. Various textured tandem devices have been presented aiming at improved optical performance, but optimizing film growth on surface-textured wafers remains challenging. Here we present perovskite-silicon tandem solar cells with periodic nanotextures that offer various advantages without compromising the material quality of solution-processed perovskite layers. We show a reduction in reflection losses in comparison to planar tandems, with the new devices being less sensitive to deviations from optimum layer thicknesses. The nanotextures also enable a greatly increased fabrication yield from 50% to 95%. Moreover, the open-circuit voltage is improved by 15 mV due to the enhanced optoelectronic properties of the perovskite top cell. Our optically advanced rear reflector with a dielectric buffer layer results in reduced parasitic absorption at near-infrared wavelengths. As a result, we demonstrate a certified power conversion efficiency of 29.80%.

Resonance Suppression of Servo System Based on State Equalizer Method.

Aiming at the problem of mechanical resonance faced by the servo control system of the aero-optical stabilization platform, based on the proportional integral and disturbance observer combination (PI+DOB) control algorithm, a state equalizer speed closed loop is proposed. Compared with the traditional PI+DOB control algorithm, this new control structure can suppress the resonance peak and the anti-resonance peak at the same time. The experimental results show that compared with the PI+DOB control algorithm, after adding the state equalizer speed closed-loop to compensate for the model, the closed-loop bandwidth is increased by 42%. The anti-disturbance capability of the control system has been significantly improved, and it has good robustness under vibration conditions. To sum up, adding the state equalizer speed closed loop on the basis of PI+DOB has an obvious effect on the suppression of mechanical resonance and the performance improvement of the control system.

Agmatine mitigates palmitate (PA)-induced mitochondrial and metabolic dysfunction in microvascular endothelial cells.

Agmatine is an arginine metabolite that has neuroprotective capacity. Recently, it has been found to ameliorate atherosclerosis progression in rabbits. However, further molecular mechanisms of its anti-atherosclerotic properties remain unclear. High plasma levels of free fatty acids (FFAs) are an important risk factor for atherosclerosis due to their detrimental effects on vascular endothelial cells (ECs). Here, we used palmitate (PA), a kind of FFA, to induce endothelial dysfunction in human microvascular endothelial cells (HMECs) to determine the possible biological functions of agmatine. We found that PA caused ECs dysfunction in HMEC-1 cells, decreased cell viability, and elevated lactate dehydrogenase (LDH) release which could be reversed by agmatine treatment. Agmatine also improved the nitric oxide (NO) production and endothelial nitric oxide synthase (eNOS) activity in PA-induced HMEC-1 cells. The PA-caused mitochondrial dysfunction of HMEC-1 cells was diminished after agmatine treatment, as proven by the increased intracellular Adenosine Triphosphate (ATP) level, decreased mitochondrial reactive oxygen species (ROS) level, and increased mitochondrial oxygen consumption rate (OCR). Further, agmatine could alleviate PA-caused lipid accumulation with increased levels of Triglyceride (TG) and total cholesterol (TC) in HMEC-1 cells. Furthermore, Western blot analysis revealed that agmatine administration markedly decreased the expression levels of phosphorylated-AMP-activated protein kinase α (p-AMPKα), p-protein kinase B (p-AKT), and p-eNOS in PA-induced HMEC-1 cells. Inhibition of AMPK by compound C reversed the protective effects of agmatine on PA-induced HMEC-1 cells. Taken together, we hypothesize that agmatine mitigated PA-induced HMEC-1 cell dysfunction by alleviating mitochondrial and metabolic dysfunction via the AMPK/PI3K/Akt/eNOS signaling pathway.

Catalytic Regio- and Enantioselective Protonation for the Synthesis of Chiral Allenes: Synergistic Effect of the Counterion and Water.

A highly enantioselective tandem Pudovik addition/[1,2]-phospha-Brook rearrangement of α-alkynylketoamides with diarylphosphine oxides was achieved with a N,N'-dioxide/ScIII complex as the catalyst. This protocol features broad substrate scope, high regio- and enantioselectivity, and good functional-group compatibility, providing a straightforward route to various trisubstituted allenes with a diarylphosphinate functionality in good yields with high enantioselectivities (up to 97 % yield, 96 % ee). Control experiments and theoretical calculations revealed that a synergistic effect of the counterion and water was critical for the regio- and enantioselective protonation after [1,2]-phospha-Brook rearrangement. The synthetic utility of this methodology was demonstrated by the conversion of products into complex bridged polycyclic architectures through intramolecular dearomatizing arene/allene cycloaddition.