Zonglong Zhu

Herein, we study ferrocene derivates as interlayers in perovskite photodiodes. We achieved photovoltaics with 26.51% efficiency and photodetectors with a specific detectivity of 1.1 × 10 ¹³ Jones.

Molecular design of self‐assembled monolayers (SAMs) for perovskite photodetector (PD) applications has largely been inherited from photovoltaics, where molecules have been designed to maximize charge extraction rather than to minimize dark current density ( J _d ). Here, we move beyond conventional carbazole‐core SAMs and introduce ferrocene (Fc)‐based SAMs (Fc‐SAMs) as hole transport layers specifically designed for PD operation. These Fc‐SAMs enable a unique energy alignment strategy where the work function of ITO is modified to misalign with the valence band maximum of an adjacent metal halide perovskite. In doing so, interfacial band bending is reduced, suppressing thermally activated charge injection. Simultaneously, the Fc moiety passivates interfacial defects, lowering defect density two‐fold when compared to a benchmark SAM. These effects enable an ultralow J _d of 2.52 × 10 ⁻¹⁰ A cm ⁻² and a noise current of 3.80 × 10 ⁻¹⁵ A Hz ^−1/2 , which generates a state‐of‐the‐art specific detectivity ( D *) of 2.56 × 10 ¹³ Jones at 680 nm and −0.5 V. We also establish that Fc‐SAM performance is independent of alkyl chain length (0 ≤ n ≤ 6), contrasting established SAM design rules. Moreover, Fc‐SAM devices exhibit excellent operational stability, supporting LiFi communication rates exceeding 1 Mbps and highlighting their potential for commercial optoelectronic applications.

A coordination-reconfiguration strategy enables green-solvent air-processing of high-efficiency perovskite solar cells, achieving a PCE of 26.20%.

Nitrate pollutants in water systems pose significant health risks and contribute to eutrophication. The electrochemical nitrate reduction reactions (eNO ₃ RR) is a promising approach to address nitrate pollutants while generating wealth‐adding products. In this review, we explore the potential for applying eNO ₃ RRs to reduce nitrate levels in real wastewater. First, we identify the importance of reducing nitrate concentrations in water. Next, we discuss the advances of electrocatalysts for eNO ₃ RR based on the reaction mechanisms, highlighting the adoption of various catalytic systems in low‐concentration wastewaters, providing new insights for applying eNO ₃ RR in real pollutant systems. We also discuss the key challenges and technologies related to the development of scaling up eNO ₃ RR devices and ammonia collection materials. Finally, we outline future research perspectives essential for realizing sustainable, high‐performance, and cost‐effective electrochemical nitrate removal and the generation of wealth‐adding products. This review provides insights into catalyst design for nitrate reduction and strategies for converting nitrate pollutants to wealth‐adding products.

Fullerene-based electron transport layers (ETLs) used in inverted (p-i-n) perovskite solar cells face issues regarding cost, scalability, and instability, whereas highly stable inorganic oxides feature unfavorable energy alignment and enhance hysteresis, which reduce power conversion efficiency (PCE). We report a nonfullerene conjugated polymer, 2PB-T, that incorporates coplanar and electron-withdrawing perylene bisimide (PBI) units into its backbone. The PBI polymeric backbone and side-chain engineering address the instability of small-molecule ETLs by optimizing electron transport properties, film uniformity, and interfacial binding. Small-area devices achieved a champion PCE of 27.8%, with a certified maximum power point tracking (MPPT) efficiency of 27.3%. Perovskite modules with areas of 20.6 and 625 square centimeters reached PCEs of 24.4 and 22.5%, respectively. Small-area devices retained more than 98.6% of their initial PCE after 1752 hours of continuous MPPT at 85°C in air, and the 625-square-centimeter module maintained 96.9% of its initial PCE after 5900 hours of outdoor operation.

Next-generation optical wireless communication requires photodetectors that offer both high spectral selectivity and strong security against interception. However, conventional broadband devices remain vulnerable to spectral crosstalk and eavesdropping. Here we show a digitally encoded dual-narrowband organic photodetector that intrinsically integrates optical filtering with algorithm-assisted encryption to enable secure, high-fidelity optical wireless communication. Operating without an external power supply, the self-powered device employs a Fabry-Pérot cavity with a carefully designed organic spacer Liq to achieve selective detection at wavelengths of 485 nm and 910 nm, along with an ultrafast response time of 440 ns. By combining chaotic encryption with hardware-level wavelength selectivity, our hardware-software co-design system achieves an ultra-low bit-error rate of 9.17 × 10^-5 at 1.25 Mbps while demonstrating strong resilience to eavesdropping and external interference. Furthermore, precise cavity engineering allows the dual-narrowband response to be extended into the short-wave infrared region (>1230 nm), offering a scalable route toward multi-wavelength secure transmission, high-resolution spectroscopy, and intelligent photonic networks.

Formamidinium (FA)‐based perovskite absorbers possess near‐ideal bandgaps for high‐performance solar cell applications; however, controlling their crystallization kinetics remains a critical bottleneck toward unlocking their full potential. Conventionally, methylammonium chloride (MACl) is introduced as a volatile crystallization additive to promote desired α‐phase formation despite severe drawbacks, including rapid nucleation, residual impurities, and associated defects. Here we introduce a zwitterionic additive, 2‐chloro‐1‐(3‐sulfopropyl)pyridinium (Cl‐PPS), that controls perovskite crystallization through cooperative coordination and hydrogen‐bonding interactions within the perovskite precursor solution. Cl‐PPS induces a uniform colloidal network that enables controlled nucleation, promotes direct α‐phase transformation, and passivates bulk and interfacial defects. The resulting films exhibit enhanced crystallinity, preferential vertical orientation, and a homogeneous potential landscape. Consequently, devices incorporating Cl‐PPS achieve a power conversion efficiency of 26.61%. Furthermore, the encapsulated devices retain 97.1% of their initial efficiency after 1200 h of continuous MPPT operation at 65°C in air.

The commercialization of perovskite solar cells is bottlenecked by inefficient, trial-and-error approaches reliant on human expertise in both material discovery and device fabrication (1-3). Here, we introduce an autonomous closed-loop framework that integrates machine learning (ML)-driven material discovery with an automated manufacturing platform. The system employs active learning and quantum modeling to rapidly identify high-performance molecules, while the platform uses Bayesian optimization and symbolic regression in a feedback loop to continuously refine the fabrication process. This integrated approach enabled the discovery of a passivation molecule, 5-(aminomethyl)nicotinonitrile hydroiodide (5ANI), which yielded 0.05 cm² solar cells with a power conversion efficiency (PCE) of 27.22% (certified maximum power point tracking (MPPT) efficiency of 27.18%) and 21.4 cm² mini-modules with a PCE of 23.49%. Moreover, the devices exhibited long-term operational stability, retaining 98.7% of their initial efficiency after 1,200 hours of continuous operation under the ISOS-L-1I protocol. Crucially, the automated platform achieved an efficiency reproducibility nearly 5 times that of manual fabrication. This work establishes an automated closed-loop system that synergizes ML-powered discovery with the high-fidelity data from automated manufacturing, setting a benchmark for autonomous discovery and manufacturing in photovoltaics and materials.