The intrinsic chiroptical properties of organic semiconductors provide a powerful platform for polarization-encoded optoelectronic signal processing. Here, we develop self-powered chiral organic photodiodes (COPs) based on chiral non-fullerene acceptors blended with achiral polymer donors, in which the circularly polarized light (CPL)-dependent responsivity provides the physical foundation for tunable convolutional weighting. Owing to their polarization-dependent photocurrent, mathematically formulated as the product of the CPL amplitude and a sine function of the retarder rotation angle, these COPs act as bias-free, dynamically reconfigurable convolutional filters capable of robust feature extraction under noisy optical propagation conditions. This materials-driven modulation mechanism enables effective contrast enhancement and noise suppression without external bias or additional circuit elements. When incorporated into an optical convolutional framework, CPL-responsive COPs improve the structural similarity index measure of extracted feature maps from 0.15 to 0.80 and increase handwritten-digit classification accuracy from 76% to 87% compared with natural-light-based counterparts. These results establish chiral organic photodiodes as a promising materials platform for low-power, noise-tolerant optical information processing.

Sodium-ion batteries (SIBs) represent a promising alternative to lithium-ion systems for energy storage, owing to sodium's natural abundance and low cost. However, their widespread adoption is hindered by issues with electrode–electrolyte interphases (EEIs). The larger ionic radius of Na⁺ creates original challenges of interfacial incompatibility during its insertion and extraction, posing critical issues for electrochemical performance in SIBs. Therefore, a systematic summary of recent research is necessary to illuminate the rational design strategies for stable EEIs. Here, the configuration characteristics of cathode materials for SIBs, accompanied by the associated issues, have been studied. The key factors that determine EEIs have been identified within a framework that reveals the specific mechanisms and outcomes between the crystal structure and surface chemistry of cathodes. Recent works on EEIs are classified and summarized into three categories: electrolyte engineering, auxiliary component engineering, and electrode engineering. Based on the critical assessment, several significant perspectives on future research directions and challenges are proposed. This review aims to offer valuable insights into developing better EEIs, acknowledging their pivotal role in practical SIBs cathode technology.

Highly responsive near-infrared (NIR) photodetectors (PDs) are increasingly required for advanced photoelectric systems. While silicon-based detectors benefit from mature fabrication and CMOS compatibility, their performance is limited by the intrinsic bandgap of 1.12 eV, which leads to weak responsivity in the NIR band. Herein, a high-responsivity silicon-based NIR PD is proposed by incorporating a heterostructure of black silicon (B-Si) and PtTe₂. The B-Si integrated in the photosensitive region of a Si p-i-n diode introduces sub-bandgap defect states, significantly enhancing NIR absorption. Further, the PtTe₂ film coated onto the B-Si surface induces energy band bending and enhances the interfacial electric field, which together promote the separation and collection of photogenerated carriers. Additionally, the PtTe₂ film forms a passivation layer on the B-Si surface, which repairs surface defects and suppresses carrier recombination, thereby reducing the dark current of the device. The PtTe₂/B-Si PD demonstrates remarkable NIR detection performance, achieving a responsivity of 0.64 A W^–1 at 1064 nm and showing a 146% improvement over conventional silicon photodiodes, while maintaining excellent detectivity (D*) of 3.54 × 10¹¹ Jones. This performance underscores the device's capability for weak-light detection and positions it as a viable candidate for CMOS-integrated NIR photonics.

Ultraviolet (UV) light-induced degradation at the buried interface poses a significant challenge to the long-term stability of perovskite solar cells (PSCs), resulting in substantial efficiency losses and hindering their commercialization. Here, we developed two simple deuterated self-assembled monolayers (SAMs), 2DPh-4PACz and 1DPh-4PACz. In particular, 2DPh-4PACz, featuring double deuterophenyl groups as π-conjugated extension units, demonstrates enhanced intrinsic UV stability, improved hole-extraction capability, and effective protection of the perovskite film against UV exposure, while simultaneously improving film quality. As a result, PSCs incorporating 2DPh-4PACz achieved a power conversion efficiency (PCE) of 26.34% (certified 25.9%) and retained 96.9% of their initial PCE after 240 h of continuous UV irradiation, representing the best UV light stability reported to date. Additionally, extensive UV-aging experiments were conducted comparing with Ph-4PACz, confirming deuteration of SAMs as an effective strategy to improve UV resistivity. Moreover, these devices maintained 92.8% of their initial PCE after over 900 h of thermal aging at 85°C, and 73% after more than 1380 h at 80% relative humidity (RH). This deuterophenyl groups design strategy with π-conjugated extension offers a promising molecular design route for next-generation SAMs in high-performance, durable PSCs.

Fast charging of lithium-ion batteries is critically constrained by the anode degradation processes—including Li plating, solid electrolyte interphase (SEI) formation, and stress accumulation—yet the impact of microstructural heterogeneity on these coupled degradation modes remains elusive. Here, we present a 3D digital twin framework to quantitatively reveal that phase-level heterogeneity is a decisive driver of reaction asymmetry, side-reaction imbalance, and stress localization. Using an experimentally informed electrode validated against measured charge profiles, we varied binder distribution, porosity, and electrode thickness to resolve their global and localized effects. Binder heterogeneity exerts only marginal impact on overall capacity in 50 μm electrodes; however, under steep gradients, its effect becomes markedly amplified—intensifying electrolyte concentration variations, disturbing Li-ion flux, promoting uneven Li plating and SEI formation, and inducing stress hotspots. Higher porosity moderates these imbalances by improving ionic transport. In contrast, mild gradients preserve more homogeneous reaction kinetics across the electrode depth. These effects become more pronounced in thicker electrodes (83 μm), where mild gradients clearly surpass the steep one. This work identifies microstructural heterogeneity as a predictive descriptor of anode degradation under fast charging, demonstrating that regulation of heterogeneity over averaged structural metrics mitigates Li plating, SEI growth, and stress localization effects.

The dazzling colors of butterfly wings and hummingbird feathers are not painted with pigments, but crafted by nature's invisible hand—nanoscale structures that sculpt light itself. This biological mastery of optics has ignited a revolution in photonics, where researchers are no longer just mimicking nature, but decoding its principles to create next-generation optical materials. We review this journey from biological blueprints to artificial metasurfaces, uncovering how natural designs for coloration, polarization control, and light confinement inspire advanced nanophotonic devices. These bio-inspired platforms transcend the limits of conventional optics, enabling breakthroughs in imaging beyond the diffraction limit, ultra-efficient radiative cooling, and novel polarization-based technologies. By bridging evolutionary wisdom with nanoscale engineering, this field charts a course toward sustainable, multifunctional optical systems for sensing, communication, and energy.

Neuromorphic vision systems (NVSs) that integrate perception and computing functions are important for edge intelligence. However, the existing implementations suffer from narrow spectral selectivity, the lack of wavelength-programmable functionality, and the architectural separation between perception and processing. Herein, inspired by the broad spectral perception of the American bullfrog's retina-pigment epithelium, we present a SnSe₂/organic semiconductor heterostructure photonic synaptic transistor. The photonic synaptic transistor exhibits wavelength-dependent duality, operating as a sensitive photodetector under ultraviolet (UV) illumination while exhibiting tunable synaptic plasticity under visible and near-infrared (NIR) illumination. The wavelength-dependent reconfigurability is enabled by engineered type-II band alignment, material absorption characteristics, and interfacial physical mechanisms. Furthermore, the device achieves a low energy consumption of 17 fJ per synaptic event at a low operating voltage of 0.001 V. By exploiting the wavelength-dependent synaptic characteristics of the device, reservoir computing (RC) is further employed to establish an integrated sensing-computing NVS. Attributed to the preprocessing capability of the device, the NVS achieves a facial recognition accuracy of ~92.7%, higher than that obtained without preprocessing. Eliminating external optical filtering and preprocessing circuits, this study demonstrates the potential of efficient wavelength-programmable neuromorphic vision for autonomous applications.