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Two-dimensional organic-inorganic hybrid perovskite (2D-OIHP) heterostructures provide a versatile platform for crystal engineering because their composition, dimensionality, excitonic structure and interfacial energy alignment can be tuned at the molecular level. However, the same ionic softness that enables facile chemical transformation also leads to ion migration under thermal, electrical and optical stimuli. In 2D-OIHP heterostructures, ion migration is not only a degradation pathway; it determines whether a heterointerface remains sharp, becomes compositionally graded, evolves into a mixed-halide alloy, or forms a bias-programmed functional junction. This review summarizes recent progress in understanding ion migration in 2D-OIHP-based heterostructures, with emphasis on migration species, driving forces, pathways and interface evolution. We first classify representative fabrication strategies according to the initial interface profiles they generate. We then discuss thermally driven in-plane and out-of-plane halide migration, spacer-cation engineering for suppressing interdiffusion, and electric-field-induced directional migration in functional devices. Finally, we extract design rules and unresolved challenges for achieving stable, sharp or dynamically programmable perovskite heterostructures. The aim is to provide a mechanistic framework for using ion migration as both a stability criterion and a crystal-engineering tool in layered hybrid perovskites.

Flexible oxide electronics require dielectric layers that combine low-temperature processability, low leakage current, high capacitance density, and mechanical reliability. In this work, we prepared ZrAlOx-PVP hybrid dielectric films through a low-temperature self-combustion solution process at 180 °C and systematically investigated the effect of PVP doping (0–2 wt%). The results show that PVP promotes the formation of M-O-C related bonding environments, suggesting the construction of an organic–inorganic crosslinked structure. Moderate PVP incorporation effectively suppresses leakage pathways, whereas excessive PVP induces polymer aggregation and trap-assisted conduction. Among all samples, the film on flexible PI (polyimide) with a PVP doping concentration of 0.5 wt% exhibits the best overall performance, with a leakage current as low as 1.89 × 10−8 A/cm2 at 1 MV/cm, a dielectric constant of 8.88. After static bending at a radius of 20 mm, the film maintains stable dielectric behavior, indicating improved stress tolerance. Flexible IGZO TFT fabricated with the optimized dielectric shows a mobility of 11.84 cm2 V−1 s−1, a threshold voltage of 0.48 V, and a subthreshold swing of 0.24 V dec−1 before bending. This work demonstrates that moderate PVP crosslinking provides an effective balance between defect suppression and stress relaxation, offering a practical interface-engineering strategy for low-temperature flexible high-k dielectrics.

The responsive light intensity dynamic range (DR) of the human eye far exceeds that of existing visual systems, and the development of a biomimetic retinal detecting unit is currently an important challenge in the field of machine vision. Here, a two-terminal Au-contacted VO /WSe heterojunction photodetector with the same adaptive DR as retinal cells is developed. It is revealed that the VO /WSe heterojunction part-mimics the cone cell for strong light detection with photoresponsivity (R) of 320 mA W and the Au/WSe Schottky contact part-mimics the rod cell for weak light detection with an R of 217 A W and noise equivalent power (NEP) as low as 248.2 fW/√Hz. The dual-mode photodetector shows a fast response speed of less than 39.28 μs. Image fusion by the cone mode and rod mode shows enhanced recognition. These results demonstrate that contact engineering enables a photodetector with the functionality of both rod and cone cells, and the resulting visual imaging system can achieve performance comparable to that of the human eye in certain operating conditions.

In the quest for stable, lead-reduced perovskites, this study unravels the structural and electronic evolution of CsZnI3 across its α, β, and γ phases. DFT calculations spotlight the tetrahedral γ phase—with elongated Zn–I bonds (3.17 Å)—as the most stable, sidestepping the octahedral distortions of its metallic α and β counterparts. Pb2+ doping (>50%) drives a transformation to mixed octahedral–tetrahedral coordination, slashing the wide 3.15 eV bandgap to a solar-optimal 2.20 eV via lattice shrinkage. Above 50% doping, an optimum emerges—balancing structural integrity with efficient light absorption. These findings elevate Zn-doped or Zn-Pb-based compounds as promising and tunable perovskites for next-gen photovoltaics.

In-sensor computing is proposed to reduce energy expenditure and processing latency by unifying sensing and computation within the hardware layer, yet the application under extreme illuminating scenario remains constrained by simultaneously obtaining broadband responsivity, large linear dynamic range and fast response. Here, we report a fully vapor-deposited graded Pb-Sn alloyed perovskite heterojunction photodiode with improved crystal quality. It enables the detection of light from visible to infrared light with a 230 dB linear dynamic range and 33 ns response time. We also develop a wafer-scale imaging processor by integrating the photodiode to a reconfigurable array. With this approach, we demonstrate biomedical detection and spatiotemporal trajectory encoding. The in-sensor processor realizes low-power high-resolution visible to infrared wavelength edge detection, adaptive background suppression under dim light and noise-immune high-speed dynamic imaging. Our results extend the options for in-sensor computing hardware, and thus pave a way toward practical artificial intelligent machine vision. Zhan et al. report a fully vapor-deposited graded perovskite photodiode for visible-to-IR imaging with 230 dB linear dynamic range and 33 ns response time. Wafer-scale reconfigurable imaging processor is developed for edge detection, adaptive background suppression under dim light, and noise-immune high-speed dynamic imaging.

Background Influenza remains a significant public health concern globally. We assessed the impact of multifaceted health education on influenza vaccination rates and health literacy among primary school students in China. Methods This cluster randomized controlled trial enrolled fourth- and fifth-grade students from 20 primary schools in Dongguan, China. Schools were randomly allocated (1:1) by a computer program to either the intervention group, receiving multifaceted health education, or the control group, receiving standard health education. Data were collected at baseline and post-intervention. The primary outcome was influenza vaccination rate. Secondary outcomes included health literacy, influenza incidence, influenza-like illness incidence, and influenza vaccine protection rate. Both intention-to-treat (ITT) and per-protocol (PP) analyses were performed. Results A total of 3463 students (1544 [44.6%] females; mean [SD] age, 9.9 [0.7] years) were enrolled. The ITT analysis included 3463 participants (control group [ n  = 1811]; intervention group [ n  = 1652]) while the PP analysis included 3275 participants (control group [ n  = 1717]; intervention group [ n  = 1558]). The influenza vaccination rate was significantly higher in the intervention group than the control group (ITT: 173 [10.9%] vs 130 [7.4%], adjusted risk ratios 1.54 [95% CI, 1.23–1.93], P  < 0.001; PP: 165 [10.6%] vs 116 [6.8%], adjusted risk ratios 1.61 [95% CI, 1.27–2.03], P  < 0.001). The knowledge component of children’s health literacy scores significantly increased in the intervention group post-intervention (ITT: mean differences 0.12 [95% CI 0.04–0.20], P  < 0.01; PP: mean differences 0.12 [95% CI 0.04–0.21], P  < 0.01). No significant differences were observed for other secondary outcomes. Conclusions The multifaceted health education significantly enhanced influenza vaccination uptake in primary school students. However, the increase was modest, indicating that more effective school-based influenza prevention programs are urgently needed to improve vaccine uptake in children. Trial registration Registered at ClinicalTrials.gov on 09/08/2023 (registration number: NCT06048406).

Accurate non‐invasive monitoring of blood glucose (BG) is a challenging issue in the therapy of diabetes. Here near‐infrared (NIR) photoplethysmography (PPG) sensor based on a vapor‐deposited mixed tin‐lead hybrid perovskite photodetector is developed. The device shows a high detectivity of 5.32 × 1012 Jones and a large linear dynamic range (LDR) of 204 dB under NIR light, guaranteeing accurate extraction of eleven features from the PPG signal. By a combination of machine learning, accurate prediction of blood glucose level with mean absolute relative difference (MARD) as small as 2.48% is realized. The self‐powered PPG sensor also works for real‐time outdoor healthcare monitors using sunlight as a light source. The potential for early diabetes diagnoses by the perovskite PPG sensor is demonstrated. A mixed tin‐lead hybrid perovskite photodetector by vapor deposition method is presented, which shows high detectivity and LDR under the NIR region. The superior photoresponse stability guarantees the repeatable and accurate measurement of the PPG signal with blood glucose information and shows the potential of non‐invasive blood glucose detection in near‐infrared applications.

Memristive computing refers to the hardware implementation of artificial neural networks (ANNs) by employing memristive devices. It supports analog multiply‐and‐accumulation (MAC) operation in a compact and highly parallel manner, which can significantly enhance computing efficiency. However, applying memristive computing in advanced network structures, such as deep neural networks and multimodal networks, is inefficient because the partial analog computing requires frequently exchanging data between analog and digital domains. Here, a perovskite memristive computing unit with flexible reconfigurability and desired nonlinearity through fully vapor deposition is reported. It enables performing all the mathematical operations necessary for Transformer ANNs completely in the analog domain. A prototypical attention module is implemented by combining cells configured in different operators of dynamic MAC, activation, and softmax functions. By cascading the modules in a multi‐layer Transformer network, a neuromorphic engine is fabricated and tested RGB‐T tracking and visual question answering tasks, fully considering device non‐idealities. It is found that the network performance is close to that of operating on a graphics processing unit (GPU)‐accelerated workstation, but it consumes only 1.7% energy and increases power efficiency by 58 times. The results pave a new way toward efficient and accurate hardware memristive computing for advanced ANNs. This paper introduces a perovskite‐based memristive computing unit that performs all necessary operations for Transformer artificial neural networks entirely in the analog domain. The system achieves comparable performance to GPU‐based systems, but with only 1.7% of the energy consumption, boosting power efficiency by 58 times. This approach advances hardware implementation for efficient and accurate neural networks.

Two‐dimensional/three‐dimensional (2D/3D) halide perovskite heterojunctions are widely used to improve the efficiency and stability of perovskite solar cells. However, interfacial defects between the 2D and 3D perovskites and the poor coverage of the 2D capping layer still hinder long‐term stability and homogeneous charge extraction. Herein, a surface planarization strategy on 3D perovskite is developed that enables an epitaxial growth of uniform 2D/3D perovskite heterojunction via a vapor‐assisted process. The homogeneous charge extraction and suppression of interfacial nonradiative recombination is achieved by forming a uniform 2D/3D interface. As a result, a stabilized power output efficiency of 25.97% is achieved by using a 3D perovskite composition with a bandgap of 1.55 eV. To demonstrate the universality of the strategy applied for different perovskites, the champion device based on a 1.57 eV bandgap 3D perovskite results in an efficiency of 25.31% with a record fill factor of 87.6%. Additionally, perovskite solar modules achieve a designated area (24.04 cm2) certified efficiency of 20.75% with a high fill factor of 80.0%. Importantly, the encapsulated uniform 2D/3D modules retain 96.9% of the initial efficiency after 1246 h operational tracking under 65 °C (ISOS‐L‐3 protocol) and 91.1% after 862 h under the ISOS‐O‐1 protocol. By employing a surface planarization strategy, a uniform and dense p‐i‐n 2D/3D heterojunction is successfully developed. This approach has enabled planarized 2D/3D PSCs and modules to achieve remarkable efficiencies of 26.02% for a 0.1 cm2 area and 23.06% for a 22.8 cm2 area, primarily by suppressing interface nonradiative recombination. Additionally, these devices exhibit exceptional operational stability under accelerated testing protocols.

IntroductionInfluenza is a major public health threat, and vaccination is the most effective prevention method. However, vaccination coverage remains suboptimal. Low health literacy regarding influenza vaccination may contribute to vaccine hesitancy. This study aims to evaluate the effect of health education interventions on influenza vaccination rates and health literacy.Methods and analysisThis cluster randomised controlled trial will enrol 3036 students in grades 4–5 from 20 primary schools in Dongguan City, China. Schools will be randomised to an intervention group receiving influenza vaccination health education or a control group receiving routine health education. The primary outcome is the influenza vaccination rate. Secondary outcomes include health literacy levels, influenza diagnosis rate, influenza-like illness incidence and vaccine protection rate. Data will be collected through questionnaires, influenza surveillance and self-reports at baseline and study conclusion.Ethics and disseminationEthical approval has been sought from the Ethics Committee of the School of Public Health, Sun Yat-sen University. Findings from the study will be made accessible to both peer-reviewed journals and key stakeholders.Trial registration numberNCT06048406.