基于C-V2X的车路协同自动驾驶关键技术与应用

随着车联网技术的演进,自动驾驶在单车智能的基础上,又有了新的发展形态——车路协同自动驾驶。通过“人-车-路-云”深度融合形成的一体化复杂信息物理系统（cyber physical system,CPS）,可以与自动驾驶车辆实现协同感知、协同决策规划甚至协同控制,提升自动驾驶安全性,帮助克服各类复杂交通环境。首先介绍了车路协同的复杂信息物理系统的概念内涵和总体架构,并提出了车路协同自动驾驶的一系列典型应用场景、技术原理、C-V2X(cellular vehicle-to-everything)性能要求、车路协同系统功能与性能要求,可以为下一阶段智能网联汽车与智能交通的深度融合发展提供参考和解决思路。     

基于sMLD特征的远红外航空图像配准算法

航空场景下的远红外图像迫切需要准确、鲁棒、快速的特征描述与自动配准方法。由于已有的多重线型描述符MLD特征存在“特征孤岛”和“尺度变换受限”的问题,因此针对远红外航空图像的配准问题,文章提出了一种聚合特征点以及线型描述符分段统计的特征描述方式,即sMLD特征。结合sMLD特征相互连接构成网状拓扑结构的特性,还提出了一种由粗到细的分支加速匹配算法RF-BA。其中,RF-BA粗匹配充分利用拓扑图的结构,通过局部寻优算法提高匹配的效率。RF-BA精匹配利用最小外接凸四边形原则和GMS校验原则,提升配准精度。实验结果表明,与已有的几种代表性配准方法相比,所提方法在配准精度和时间开销方面均具有更好的性能。     

基于transformer自适应特征向量融合的图像分类

针对目前基于transformer的图像分类模型直接应用在小数据集上性能较差的问题,本文提出了transformer自适应特征向量融合网络,该网络在特征提取器中将不同阶段的特征进行融合,减少特征信息丢失的同时获得更多不同感受野下的信息,同时利用最大池化来去除特征中的冗余信息,从而使提取的特征更具有判别性。此外,为了充分利用图像的各级特征信息来进行分类预测,本文将网络各阶段产生的特征向量进行融合,使融合后的特征向量更具有表征能力,从而减少网络对大数据集的依赖,使网络在小数据集中也能获得很好的性能。实验表明,本文提出的 算法在数据集Mini-ImageNet-100、CIFAR-100和ImageNet-1k上的TOP-1准确率分别达到了74.22%、85.86%和81.4%。在没有增加计算量的情况下,在baseline上分别提高了6.0%、3.0%和0.1%,且参数量减少了18.3%。本文代码开源在“https://github.com/xhutongxue/afvf”。     

Solar-Driven Interfacial Evaporation Accelerated Electrocatalytic Water Splitting on 2D Perovskite Oxide/MXene Heterostructure

The rational design of economic and high-performance electrocatalytic water-splitting systems is of great significance for energy and environmental sustainability. Developing a sustainable energy conversion-assisted electrocatalytic process provides a promising novel approach to effectively boost its performance. Herein, a self-sustained water-splitting system originated from the heterostructure of perovskite oxide with 2D Ti₃C₂T_x MXene on Ni foam (La_1-xSr_xCoO₃/Ti₃C₂T_x MXene/Ni) that shows high activity for solar-powered water evaporation and simultaneous electrocatalytic water splitting is presented. The all-in-one interfacial electrocatalyst exhibits highly improved oxygen evolution reaction (OER) performance with a low overpotential of 279 mV at 10 mA cm⁻² and a small Tafel slope of 74.3 mV dec⁻¹, superior to previously reported perovskite oxide-based electrocatalysts. Density functional theory calculations reveal that the integration of La_0.9Sr_0.1CoO₃ with Ti₃C₂T_x MXene can lower the energy barrier for the electron transfer and decrease the OER overpotential, while COMSOL simulations unveil that interfacial solar evaporation could induce OH⁻ enrichment near the catalyst surfaces and enhance the convection flow above the catalysts to remove the generated gas, remarkably accelerating the kinetics of electrocatalytic water splitting.     

Activatable NIR-II Lanthanides-Polymetallic Oxomolybdate Hybrid Nanosensors for Monitoring Chemotherapy Induced Enteritis

Chemotherapy-induced enteritis is one of the side effects associated with cancer therapy, which significantly affects the treatment effect, but there is no effective clinical detection method that can early diagnose its occurrence and progression. Here, a series of second near-infrared window (NIR-II) hybrid nanosensors are designed that consisted of lanthanide nanoparticles and β-Mo2C-derived polymetallic oxomolybdate nanoclusters (Ln@POM). Based on the high sensitivity of POM to reactive oxygen species (ROS) closely related to chemotherapy-induced enteritis, the NIR-II luminescence intensity and lifetime of Ln@POM (Ln: Yb³⁺, Nd³⁺, Ho³⁺, Tm³⁺, Er³⁺) show excellent responsiveness to H₂O₂ and HClO with the detection limit down to 0.15 and 0.14 µm , respectively. Utilizing Nd@POM as a ROS-activated NIR-II nanosensor, the chemotherapeutic enteritis is successfully detected within 7 h after induction of chemotherapy drugs, which is significantly earlier than the gold standard method (immunohistochemistry, 24 h). These results demonstrate that the designed hybrid nanosensors are promising optical tools for the early diagnosis of ROS-related diseases.     

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.     

Self-Adhesive Polydimethylsiloxane Foam Materials Decorated with MXene/Cellulose Nanofiber Interconnected Network for Versatile Functionalities

Polydimethylsiloxanes (PDMS) foam as one of next-generation polymer foam materials shows poor surface adhesion and limited functionality, which greatly restricts its potential applications. Fabrication of advanced PDMS foam materials with multiple functionalities remains a critical challenge. In this study, unprecedented self-adhesive PDMS foam materials are reported with worm-like rough structure and reactive groups for fabricating multifunctional PDMS foam nanocomposites decorated with MXene/cellulose nanofiber (MXene/CNF) interconnected network by a facile silicone foaming and dip-coating strategy followed by silane surface modification. Interestingly, such self-adhesive PDMS foam produces strong interfacial adhesion with the hybrid MXene/CNF nano-coatings. Consequently, the optimized PDMS foam nanocomposites have excellent surface super-hydrophobicity (water contact angle of ≈159^o), tunable electrical conductivity (from 10⁻⁸ to 10 S m⁻¹), stable compressive cyclic reliability in both wide-temperature range (from −20 to 200 ^oC) and complex environments (acid, sodium, and alkali conditions), outstanding flame resistance (LOI value of >27% and low smoke production rate), good thermal insulating performance and reliable strain sensing in various stress modes and complex environmental conditions. It provides a new route for the rational design and development of advanced PDMS foam nanocomposites with versatile multifunctionalities for various promising applications such as intelligent healthcare monitoring and fire-safe thermal insulation.     

19.28% Efficiency and Stable Polymer Solar Cells Enabled by Introducing an NIR-Absorbing Guest Acceptor

Here, a near-infrared (NIR)-absorbing small-molecule acceptor (SMA) Y-SeNF with strong intermolecular interaction and crystallinity is developed by combining selenophene-fused core with naphthalene-containing end-group, and then as a custom-tailor guest acceptor is incorporated into the binary PM6:L8-BO host system. Y-SeNF shows a 65 nm red-shifted absorption compared to L8-BO. Thanks to the strong crystallinity and intermolecular interaction of Y-SeNF, the morphology of PM6:L8-BO:Y-SeNF can be precisely regulated by introducing Y-SeNF, achieving improved charge-transporting and suppressed non-radiative energy loss. Consequently, ternary polymer solar cells (PSCs) offer an impressive device efficiency of 19.28% with both high photovoltage (0.873 V) and photocurrent (27.88 mA cm⁻²), which is one of the highest efficiencies in reported single-junction PSCs. Notably, ternary PSC has excellent stability under maximum-power-point tracking for even over 200 h, which is better than its parental binary devices. The study provides a novel strategy to construct NIR-absorbing SMA for efficient and stable PSCs toward practical applications.     

Femtosecond Laser 4D Printing of Light-Driven Intelligent Micromachines

Intelligent micromachines that respond to external light stimuli have a broad range of potential applications, such as microbots, biomedicine, and adaptive optics. However, artificial light-driven intelligent micromachines with a low actuation threshold, rapid responsiveness, and designable and precise 3D transformation capability remain unachievable to date. Here, a single-material and one-step 4D printing strategy are proposed to enable the nanomanufacturing of agile and low-threshold light-driven 3D micromachines with programmable shape-morphing characteristics. The as-developed carbon nanotube-doped composite hydrogel simultaneously enhanced the light absorption, thermal conductivity, and mechanical modulus of the crosslinked network, thus significantly increasing the light sensitivity and response speed of micromachines. Moreover, the structural design and assembly of asymmetric microscale mechanical metamaterial unit cells enable the highly efficient additive nanomanufacturing of 3D shape-morphable micromachines with large dynamic modulation and spatiotemporal controllability. Using this strategy, the world's smallest artificial beating heart with programmable light-stimulus responsiveness for the cardiac cycle is successfully printed. This 4D printing method paves the way for the construction of multifunctional intelligent micromachines for bionics, drug delivery, integrated microsystems, and other fields.