Mitigating Surface Deficiencies of Perovskite Single Crystals Enables Efficient Solar Cells with Enhanced Moisture and Reverse-Bias Stability

Metal halide perovskite single crystals are promising for diverse optoelectronic applications due to their outstanding properties. In comparison to the bulk, the crystal surface suffers from high defect density and is moisture sensitive; however, surface modification strategies of perovskite single crystals are relatively deficient. Herein, solar cells based on methylammonium lead triiodide (MAPbI₃) thin single crystals are selected as a prototype to improve single-crystal perovskite devices by surface modification. The surface trap passivation and protection against moisture of MAPbI₃ thin single crystals are achieved by one bifunctional molecule 3-mercaptopropyl(dimethoxy)methylsilane (MDMS). The sulfur atom of MDMS can coordinate with bare Pb²⁺ of MAPbI₃ single crystals to reduce surface defect density and nonradiative recombination. As a result, the modified devices show a remarkable efficiency of 22.2%, which is the highest value for single-crystal MAPbI₃ solar cells. Moreover, MDMS modification mitigates surface ion migration, leading to enhanced reverse-bias stability. Finally, the cross-link of silane molecules forms a protective layer on the crystal surface, which results in enhanced moisture stability of both materials and devices. This work provides an effective way for surface modification of perovskite single crystals, which is important for improving the performance of single-crystal perovskite solar cells, photodetectors, X-ray detectors, etc.     

Simultaneous CO2 and H2O Activation via Integrated Cu Single Atom and N Vacancy Dual-Site for Enhanced CO Photo-Production

Photocatalytic conversion of CO₂ into fuels using pure water as the proton source is of immense potential in simultaneously addressing the climate-change crisis and realizing a carbon-neutral economy. Single-atom photocatalysts with tunable local atomic configurations and unique electronic properties have exhibited outstanding catalytic performance in the past decade. However, given their single-site features they are usually only amenable to activations involving single molecules. For CO₂ photoreduction entailing complex activation and dissociation process, designing multiple active sites on a photocatalyst for both CO₂ reduction and H₂O dissociation simultaneously is still a daunting challenge. Herein, it is precisely construct Cu single-atom centers and two-coordinated N vacancies as dual active sites on CN (Cu₁/N_2CV-CN). Experimental and theoretical results show that Cu single-atom centers promote CO₂ chemisorption and activation via accumulating photogenerated electrons, and the N_2CV sites enhance the dissociation of H₂O, thereby facilitating the conversion from COO* to COOH*. Benefiting from the dual-functional sites, the Cu₁/N_2CV-CN exhibits a high selectivity (98.50%) and decent CO production rate of 11.12 µmol g⁻¹ h⁻¹. An ingenious atomic-level design provides a platform for precisely integrating the modified catalyst with the deterministic identification of the electronic property during CO₂ photoreduction process.     

A Hybrid Strategy-Based Ultra-Narrow Stretchable Microelectrodes with Cell-Level Resolution

Stretchable ultra-narrow (e.g., 10 µm in width) microelectrodes are crucial for the electrophysiological monitoring of single cells providing the fundamental understanding to the working mechanism of neuro network or other electrically functional cells. Current fabrication strategies either focus on the preparation of normal stretchable electrodes with hundreds of micrometers or millimeters in width by using inorganic conductive materials or develop conductive organic polymer gel for ultra-narrow electrodes which suffer from low stretchability and instability for long-term implantation, therefore, it is still highly desirable to explore bio-interfacial ultra-narrow stretchable inorganic electrodes. Herein, a hybrid strategy is reported to prepare ultra-narrow multi-channel stretchable microelectrodes without using photolithography or laser-assisting etching. A 10 µm × 10 µm monitoring window is fabricated with enhanced interfacial impedance by the special rough surface. The stretchability achieves to 120% for this 10 µm-width stretchable electrode. Supported by these superior properties, it is demonstrated that the stretchable microelectrodes can detect electrophysiological signals of single cells in vitro and collect electrophysiological signals more precisely in vivo. The reported strategy will open up the accessible preparation of the fine-size stretchable microelectrode. It will significantly improve the resolution of monitoring and stimulation of inorganic stretchable electrodes.     

Functional Materials for Memristor-Based Reservoir Computing: Dynamics and Applications

The booming development of artificial intelligence (AI) requires faster physical processing units as well as more efficient algorithms. Recently, reservoir computing (RC) has emerged as an alternative brain-inspired framework for fast learning with low training cost, since only the weights associated with the output layers should be trained. Physical RC becomes one of the leading paradigms for computation using high-dimensional, nonlinear, dynamic substrates. Among them, memristor appears to be a simple, adaptable, and efficient framework for constructing physical RC since they exhibit nonlinear features and memory behavior, while memristor-implemented artificial neural networks display increasing popularity towards neuromorphic computing. In this review, the memristor-implemented RC systems from the following aspects: architectures, materials, and applications are summarized. It starts with an introduction to the RC structures that can be simulated with memristor blocks. Specific interest then focuses on the dynamic memory behaviors of memristors based on various material systems, optimizing the understanding of the relationship between the relaxation behaviors and materials, which provides guidance and references for building RC systems coped with on-demand application scenarios. Furthermore, recent advances in the application of memristor-based physical RC systems are surveyed. In the end, the further prospects of memristor-implemented RC system in a material view are envisaged.     

Direct Observation of Oxygen Ion Dynamics in a WO3-x based Second-Order Memristor with Dendritic Integration Functions

Direct observation of oxygen dynamics in an oxide-based second-order memristor can provide the valid evidence to clarify the memristive mechanism, however, which is still limited for now. In this study, the migration and diffusion of oxygen ions in the region of Pt/WO_3-x Schottky interface are observed in the WO_3-x second-order memristor by using the technique of in situ transmission electron microscopy (TEM) and the electron energy loss spectroscopy. Interestingly, the coexistence of memristive and memcapacitive switching can be implemented in this memristor. Combined with the analysis of depth-profile X-ray photoelectron spectroscopy (XPS), an interface-barrier-modulation second-order memristive model is proposed based on the above results. Notably, temporally correlative oxygen dynamics in the memristor offers the platform to integrate signals from multiple inputs, enabling the realization of the dendritic functions of synchronous and asynchronous integration for the application of logic operations with fault-tolerance capability and associative learning. These findings provide the experimental evidence to in-depth understanding of oxygen dynamics and switching mechanism in second-order memristor, which can support the optimization of memristive performance and the achievement of biorealistic synaptic functions.     

基于机器学习的超声造影分析综述

超声造影（Contrast-enhanced ultrasound, CEUS）通过外周静脉注入超声造影剂,显著增强来自肿瘤微血管的血流信号,便于临床医生以实时、动态的方式评估肿瘤血管生成、周边浸润等,广泛应用于多器官病变诊断、预后评估和治疗方案规划等方面。近年来,以深度学习为代表的机器学习方法快速发展,为动态超声造影智能分析带来新的机遇。深度学习方法很大程度上拓宽了超声造影临床应用范围,提高了其诊疗效能。但与常规超声影像类似,超声造影仍然存在斑点噪声、呼吸运动干扰和标准化程度低等问题,使得动态灌注时间、空间信息挖掘面临挑战。本文系统性回顾了近年来超声造影智能分析相关工作,涵盖良恶性鉴别、恶性分级、疗效预测和诊疗方案选择等方面应用,总结了当前影像组学及深度学习方法在超声造影分析领域的最新进展,并指出当前研究的局限性和未来发展方向。     

Extended state observer-based finite-region control for 2-D Markov jump systems

In this article, an extended state observer-based finite-region control scheme is presented for two-dimensional Markov jump systems with unknown mismatched disturbances. The mathematical model of the two-dimensional Markov jump systems is built on the well-known Roesser model. By establishing special recursive formulas and utilizing the 2-D Lyapunov function theory, sufficient conditions are obtained, which prove that the resultant system is finite-region bounded, if some linear matrix inequalities are achieved. Then, we provide an algorithm to solve the extended state observer-based controller gains. With the proposed control scheme, the external disturbances can be actively rejected from the system outputs. To conclude, a numerical example based on the Darboux equation is provided to demonstrate the validity and effectiveness of the devised control scheme.     

Regulation of Ionic Distribution and Desolvation Activation Energy Enabled by In Situ Zinc Phosphate Protective Layer toward Highly Reversible Zinc Metal Anodes

Despite the merits of high specific capacity, low cost, and high safety, the practical application of aqueous Zn metal batteries (AZMBs) is plagued by the dendritic growth and corrosion reaction of Zn metal anodes. To solve these issues, a Zn₃(PO₄)₂·4H₂O protective layer is in-situ constructed on Zn foil (Zn@ZnPO) by a simple hydrothermal method, avoiding the traditional slurry-casting process. The insulating and conformable ZnPO layer improves the wettability of Zn@ZnPO and aqueous electrolyte via decreasing the contact angle to 11.7^o. Compared with bare Zn, the Zn@ZnPO possesses a lower desolvation activation energy of 35.25 kJ mol^-1, indicating that the ZnPO fasters the desolvation of hydrated Zn²⁺ ions and thereby ameliorates their transport dynamics. Micro-morphology and structural characterization show that there are no dendrites forming on the post-cycling Zn@ZnPO anodes, and the interfacial ZnPO layer remains almost identical before and after cycles. It can be explained that the electrochemically stable ZnPO layer acts as an ionic modulator to enable the homogeneous distribution of Zn²⁺ ions, inhibiting the growth of Zn dendrites. Benefiting from these advantages, the Zn@ZnPO based symmetric and full cells deliver highly reversible Zn plating/stripping behavior and long cycling lifespans.     

一种用于心电信号采集的LCADC

设计了一种适用于心电信号处理的连续时间LCADC电路。电路去掉了传统电压模式的DAC模块,采用了N-bit电流舵DAC,解决了传统电压模式DAC存在的电容漏电问题。该电路包括一个电压至电流转换器、 7-bit电流舵DAC、电平交叉检测模块以及偏移标准补偿模块。 电路采用SMIC 0.18 μm CMOS工艺设计,电源电压为1 V。仿真结果表明,整体电路功耗为8.1 μW @500 Hz。通过MATLAB对数据进行处理,SNDR为53.8 dB @500 Hz,ENOB达到了8.64 bit,输入信号范围内SNDR范围为52.8~63.6 dB,电路功耗范围为7.3~8.5 μW。该电路适用于低频心电信号的采集。