Blood cell counting based on U-Net++ and YOLOv5

Clinical information about a variety of disorders is available through blood cell counting, which is usually done by manual methods. However, manual methods are complex, time-consuming and susceptible to the subjective experience of inspectors. Although many efforts have been made to develop automated blood cell counting algorithms, the complexity of blood cell distribution and the highly overlapping nature of some red blood cells (RBCs) remain significant challenges that limit the improvement of analytical accuracy. Here, we proposed an end-to-end method for blood cell counting based on deep learning. Firstly, U-Net++ was used to segment the whole blood cell image into several regions of interest (ROI), and each ROI contains only one single cell or multiple overlapping cells. Subsequently, YOLOv5 was used to detect blood cells in each ROI. Specifically, we proposed several strategies, including fine classification of RBCs, adaptive adjustment for non-maximal suppression (NMS) threshold and blood cell morphology constraints to improve the accuracy of detection. Finally, the detection outcomes for each ROI were combined and superimposed. The results show that our method can effectively address the issue of high overlap and precisely segment and detect blood cells, with a 98.18% accuracy rate for blood cell counting.     

Himawari-8气溶胶变分同化对PM2.5污染模拟的改进

利用地球静止轨道卫星Himawari-8 气溶胶光学厚度 (AOD) 产品能够估算空间覆盖范围广、时间分辨率高的 近地表 PM2.5 浓度。基于三维变分同化系统将AOD估算得到的 PM2.5 资料同化进入WRF-Chem大气化学模式中, 通过 控制实验与同化实验的对比与分析, 探讨了AOD估算得到的PM2.5资料同化对 PM2.5 污染模拟的改进作用。实验结果 表明： (1) AOD估算得到的 PM2.5 资料同化能够改进 PM2.5 污染模拟效果;(2) PM2.5 污染模拟改进效果存在时空差异。 此外, 与其他研究中使用AOD观测算子直接同化AOD的方法相比, 该方法的操作更加简单。     

Nanocellulose-Carboxymethylcellulose Electrolyte for Stable,High-Rate Zinc-Ion Batteries

Aqueous Zn ion batteries (ZIBs) are one of the most promising battery chemistries for grid-scale renewable energy storage. However, their application is limited by issues such as Zn dendrite formation and undesirable side reactions that can occur in the presence of excess free water molecules and ions. In this study, a nanocellulose-carboxymethylcellulose (CMC) hydrogel electrolyte is demonstrated that features stable cycling performance and high Zn²⁺ conductivity (26 mS cm⁻¹), which is attributed to the material's strong mechanical strength (≈70 MPa) and water-bonding ability. With this electrolyte, the Zn-metal anode shows exceptional cycling stability at an ultra-high rate, with the ability to sustain a current density as high as 80 mA cm⁻² for more than 3500 cycles and a cumulative capacity of 17.6 Ah cm⁻² (40 mA cm⁻²). Additionally, side reactions, such as hydrogen evolution and surface passivation, are substantially reduced due to the strong water-bonding capacity of the CMC. Full Zn||MnO₂ batteries fabricated with this electrolyte demonstrate excellent high-rate performance and long-term cycling stability (>500 cycles at 8C). These results suggest the cellulose-CMC electrolyte as a promising low-cost, easy-to-fabricate, and sustainable aqueous-based electrolyte for ZIBs with excellent electrochemical performance that can help pave the way toward grid-scale energy storage for renewable energy sources.     

Sufficient Utilization of Mn2+/Mn3+/Mn4+ Redox in NASICON Phosphate Cathodes towards High-Energy Na-Ions Batteries

Na superionic conductor of Na₃MnTi(PO₄)₃ only containing high earth-abundance elements is regarded as one of the most promising cathodes for the applicable Na-ion batteries due to its desirable cycling stability and high safety. However, the voltage hysteresis caused by Mn²⁺ ions resided in Na⁺ vacancies has led to significant capacity loss associated with Mn reaction centers between 2.5–4.2 V. Herein, the sodium excess strategy based on charge compensation is applied to suppress the undesirable voltage hysteresis, thereby achieving sufficient utilization of the Mn²⁺/Mn³⁺ and Mn³⁺/Mn⁴⁺ redox couples. These findings indicate that the sodium excess Na_3.5MnTi_0.5Ti_0.5(PO₄)₃ cathode with Ti⁴⁺ reduction has a lowest Mn²⁺ occupation on the Na⁺ vacancies in its initial composition, which can improve the kinetics properties, finally contributing to a suppressed voltage hysteresis. Based on these findings, it is further applied the sodium excess route on a Mn-richer phosphate cathode, which enables the suppressed voltage hysteresis and more reversible capacity. Consequently, this developed Na_3.6Mn_1.15Ti_0.85(PO₄)₃ cathode achieved a high energy density over 380 Wh kg⁻¹ (based on active substance mass of cathode) in full-cell configurations, which is not only superior to most of the phosphate cathodes, but also delivers more application potential than the typical oxides cathodes for Na-ion batteries.     

Doped/Undoped A1-A2 Typed Copolymers as ETLs for Highly Efficient Organic Solar Cells

The electron transport layer (ETL) is a critical component in achieving high device performance and stability in organic solar cells. Conjugated polyelectrolytes (CPEs) have become an attractive alternative due to film-forming properties and ease of preparation. However, p-type CPEs generally exhibit poor charge mobility and conductivity, incorporation of electron-withdrawing units forming alternated D-A conjugated backbone can make up for these deficiencies. Herein, the ratio of electron withdrawing moieties are further increased and two poly(A1-alt-A2) typed PIIDNDI-Br and PDPPNDI-Br based on the combination of naphthalene diimide (NDI) with isoindigo (IID) or diketopyrrolopyrrole (DPP) via direct arylation polycondensation are synthesized. These CPEs possess excellent alcohol solubility, a suitable lowest unocuppied molecular orbital energy level, and work function tunability. Surprisingly, the incorporation of IID and DPP units generate distinct self-doping behaviors, which are confirmed by UV–vis absorption and ESR spectra. However, no matter doped or undoped, both CPEs present better charge-transporting properties and conductivity when utilized as ETLs. The PIIDNDI-Br and PDPPNDI-Br display good universal compatibility with the blend of PM6:Y6 and PM6:L8-BO, and PCEs of 18.32% and 18.36% are obtained, respectively, which also present excellent storage stability. In short, the combination of two different acceptors demonstrates an efficient strategy to design highly efficient ETLs for high performance photovoltaic devices.     

Mimosa-Inspired High-Sensitive and Multi-Responsive Starch Actuators

Artificial intelligent actuators are extensively explored for emerging applications such as soft robots, human-machine interfaces, and biomedical devices. However, intelligent actuating systems based on synthesized polymers suffer from challenges in renewability, sustainability, and safety, while natural polymer-based actuators show limited capabilities and performances due to the presence of abundant hydrogen-bond lockers. Here this study reports a new hydrogen bond-mediated strategy to develop mimosa-inspired starch actuators (SA). By harnessing the unique features of gelatinization and abundant hydrogen bonds, these SA enable high-sensitivity and multi-responsive actuation in various scenarios. The non-gelatinized SA can be irreversibly programmed into diverse shapes, such as artificial flowers, bowl shapes, and helix structures, using near-infrared light. Furthermore, the gelatinized SA exhibit reversibly multi-responsive actuation when exposed to low humidity (10.2%), low temperature (37 °C), or low-energy light (0.42 W cm⁻²). More importantly, the SA demonstrate robust applications in smart living, including artificial mimosa, intelligent lampshade, and morphing food. By overcoming the hydrogen-bond lockers inherent in natural polymers, SA open new avenues for next-generation recyclable materials and actuators, bringing them closer to practical applications.     

Functional 2D Phases in Mixed Dimensional Perovskite Photovoltaics

Organic-inorganic hybrid perovskite solar cells (PSCs) with unique properties exhibit their powerful competitiveness in the photovoltaic field over the past few years. However, the challenges of stability for perovskite devices limit the commercialization and further development. The 2D/3D hybrid structures combine the superior efficiency of bulk perovskites and the superior stability of layered perovskites and gradually get hotspots of the photovoltaic field. In addition, there remains a lack of comprehensive understanding and systematic summary of the function of 2D perovskite attributed to the complex nature of 2D/3D structures. Here, the latest progress of 2D/3D hybrid structures and focus on the functionality of 2D phases in mixed structures and the underlying mechanism from the perspective of their different distributions in the perovskite layer is summarized. Then, the insight and vital factors for overall improvements in the stability of 2D/3D structures are thoroughly discussed. Finally, it is expected that this review will contribute to the present challenges and future research prospects in the photovoltaic industry.     

Local Electronic Structure Modulation Enables Fast-Charging Capability for Li-Rich Mn-Based Oxides Cathodes With Reversible Anionic Redox Activity

Anionic and cationic redox chemistries boost ultrahigh specific capacities of Li-rich Mn-based oxides cathodes (LRMO). However, irreversible oxygen evolution and sluggish kinetics result in continuous capacity decay and poor rate performance, restricting the commercial fast-charging cathodes application for lithium ion batteries. Herein, the local electronic structure of LRMO is appropriately modulated to alleviate oxygen release, enhance anionic redox reversibility, and facilitate Li⁺ diffusion via facile surface defect engineering. Concretely, oxygen vacancies integrated on the surface of LRMO reduce the density of states of O 2p band and trigger much delocalized electrons to distribute around the transition metal, resulting in less oxygen release, enhancing reversible anionic redox and the MnO₆ octahedral distortion. Besides, partially reduced Mn and lattice vacancies synchronously stimulate the electrochemical activity and boost the electronic conductivity, Li⁺ diffusion rate, and fast charge transfer. Therefore, the modified LRMO exhibits enhanced cyclic stability and fast-charging capability: a high discharging capacity of 212.6 mAh·g⁻¹ with 86.98% capacity retention after 100 cycles at 1 C is obtained and to charge to its 80%, SOC is shortened to 9.4 min at 5 C charging rate. This work will draw attention to boosting the fast-charging capability of LRMO via the local electronic structure modulation.     

A Dilute Fluorinated Phosphate Electrolyte Enables 4.9 V-Class Potassium Ion Full Batteries

Potassium ion batteries using graphite anode and high-voltage cathodes are considered to be optimizing candidates for large-scale energy storage. However, the lack of suitable electrolytes significantly hinders the development of high-voltage potassium ion batteries. Herein, a dilute (0.8 m ) fluorinated phosphate electrolyte is proposed, which exhibits extraordinary compatibility with both graphite anode and high-voltage cathodes. The phosphate solvent, tris(2,2,2-trifluoroethyl) phosphate (TFP), has weak solvating ability, which not only allows the formation of robust anion-derived solid electrolyte interphase on graphite anode but also effectively suppresses the corrosion of Al current collector at high voltage. Meanwhile, the high oxidative stability of fluorinated TFP solvent enables stable ultrahigh-voltage (4.95 V) cycling of a potassium vanadium fluorophosphate (KVPO₄F) cathode. Using TFP-based electrolyte, the 4.9 V-class potassium ion full cell based on graphite anode and KVPO₄F cathode shows rather remarkable cycling performance with a high capacity retention of 87.2% after 200 cycles. This study provides a route to develop dilute electrolytes for high-voltage potassium ion batteries, by utilizing solvents with both weak solvating ability and high oxidative stability.     

基于多域特征融合的旋翼无人机分类识别

为提高雷达旋翼无人机的识别效果,本文提出一种基于多域特征融合的旋翼无人机分类方法。首先利用K波段连续波（Continuous Wave,CW）雷达观测多旋翼无人机,对采集到的雷达回波信号进行信号处理依次得到时频图、节奏速度图（Cadence?Velocity Diagram, CVD）和节奏频谱图（Cadence Frequency Spectrum,CFS）,然后将时频图和CVD图分别输入SqueezeNet网络,CFS数据输入一维卷积神经网络（1?D?CNN）提取回波信号在时频域、节奏速度域和节奏频率域的特征,最后将特征融合输入支持向量机（Support Vector Machine, SVM）进行分类。实测雷达数据处理的结果表明基于多域特征融合的旋翼无人机分类识别方法对三类旋翼无人机的分类准确率达到99.14%。