SCIENCE CHINA Materials•2026•DOI: 10.1007/s40843-026-4210-6
Achieving low-energy-loss organic solar cells requires precise regulation of energetic disorder and intermolecular packing, which remains challenging at the molecular design level. Here, we report an aza-pyran-type molecular design strategy that integrates a sp3-hybridized nitrogen-centered core with a pyran structural motif to regulate aggregation behavior and energetic disorder in non-fullerene acceptors. Two representative acceptors, D10 and D11, are developed, both exhibiting broadened absorption and high open-circuit voltages, while D10 shows more balanced aggregation and improved long-range molecular ordering. When incorporated as guest acceptors into the PM6:L8-BO system, the optimized ternary device achieves a power conversion efficiency of 19.86% with a high VOC of 0.89 V. Detailed optoelectronic analyses reveal reduced non-radiative energy loss (ΔE3 ≈ 0.23 eV), enhanced electroluminescence quantum efficiency (~1.17 × 10-4), and lowered energetic disorder (EU = 25 meV) in the ternary blends. GIWAXS and charge-transport studies further demonstrate that the introduction of D10 promotes enlarged crystalline domains and more ordered π-π stacking, facilitating balanced carrier transport and suppressed recombination. This work establishes an effective molecular design paradigm that links aza-pyran molecular engineering with energy-loss management, providing new insights into the development of high-efficiency, low-energy-loss organic solar cells.
SCIENCE CHINA Materials•2026•DOI: 10.1007/s40843-026-4359-0
Organic solar cells (OSCs) require cathode interlayers (CILs) that combine high charge transport, defect passivation, and thickness insensitivity for scalable manufacturing. Here, we report the synthesis of a novel A-D-A-A'-type polymer, PDPP2F-NDI-N, via the green and efficient direct arylation polymerization (DArP) method. The multiple electron-deficient units in the backbone confer strong electron-withdrawing character, effective work function modulation, enhanced built-in potential, high crystallinity, and ordered molecular packing. PDPP2F-NDI-N exhibits a high electron mobility of 1.01 × 10⁻³ cm² V⁻¹ s⁻¹ and electrical conductivity of 3.13 × 10⁻³ S m⁻¹, facilitating efficient charge extraction and transport. Its interfacial modification capability suppresses interfacial defects and reduces non-radiative recombination losses. In ternary OSCs, PDPP2F-NDI-N achieves a high power conversion efficiency (PCE) of 20.44%, with outstanding thickness insensitivity retaining 92.8% of peak PCE at a 30 nm CIL thickness, and a T80 lifetime exceeding 1700 hours under photo-thermal aging. This work demonstrates that poly(A-D-A-alt-A') backbone design combined with DArP synthesis provides an effective strategy for developing high-performance, thickness-insensitive, and stable polymeric CILs, advancing efficient, stable, and scalable OSC applications.
SCIENCE CHINA Materials•2026•DOI: 10.1007/s40843-026-4394-x
Spiral graphene, characterized by Bernal-stacked layers and unique electronic properties, holds promise for advanced quantum and optoelectronic devices. However, its controlled synthesis remains challenging. Here, we report the self-assembly growth of single-crystal spiral graphene on a liquid heterogeneous substrate via chemical vapor deposition (CVD). A 50-μm-thick Cu foil was placed on a Ni support and heated to 1083 °C, the melting point of pure Cu, ensuring a fully molten Cu layer on solid Ni. Growth proceeded for 30 minutes under optimized conditions. The resulting spiral graphene exhibits a uniform Bernal stacking configuration, as confirmed by transmission electron microscopy and selected-area electron diffraction. Time-of-flight secondary ion mass spectrometry (ToF-SIMS) depth profiling and isotope-labeling experiments reveal that carbon incorporation occurs predominantly at the spiral step edges, following a self-assembly mechanism driven by the liquid substrate's dynamic surface. Control experiments on solid Cu-Ni alloys yield no spiral morphology, underscoring the critical role of the liquid phase. The liquid heterogeneous substrate facilitates rapid carbon diffusion and step-edge attachment, enabling the growth of high-quality single-crystal spirals with controlled layer number. This work provides a scalable route to synthesize spiral graphene with tailored stacking, advancing its application in twistronics and high-performance electronics.
Chinese Journal of Environmental Engineering•2026•DOI: 10.12030/j.cjee.202506020
The rotary kiln roasting of lepidolite for lithium extraction faces challenges of unstable lithium conversion rates and high energy consumption. To address this, a multi-objective optimization method coupling improved neural network simulation with a multi-objective genetic algorithm was proposed, targeting the synergistic optimization of lithium conversion rate (TRLi) and natural gas consumption intensity (EIng). Using long-term industrial time-series data of batching parameters and kiln operating variables, back-propagation (BP) neural network and its particle swarm optimization (PSO) improved variant were developed to model TRLi and EIng. The PSO-BP model demonstrated superior accuracy in capturing the complex nonlinear relationships, reducing mean absolute percentage errors (MAPE) to 0.278 and 0.284 for TRLi and EIng, respectively. Subsequently, the non-dominated sorting genetic algorithm II (NSGA-II) was employed to construct a multi-objective optimization model, yielding a Pareto-optimal set of process parameters that maximize TRLi and minimize EIng. The results revealed that under NSGA-II optimized conditions, TRLi could be stabilized between 82.45% and 87.96%, an average increase of 3.61 percentage points over baseline operations, while EIng could be reduced to 53.7 m3 per ton of clinker. For an annual processing capacity of 3.2×105 tons of lepidolite concentrate and sulfate mixture, this corresponds to an additional 127.1 tons of lithium metal recovery, a reduction of 1,964,912 m3 in natural gas consumption, and a decrease of 3,763.84 tons in CO2 emissions annually. This study provides theoretical and technical support for the green, high-quality, and low-carbon supply of critical raw materials for the lithium battery new energy industry.
Chinese Journal of Environmental Engineering•2026•DOI: 10.12030/j.cjee.202512072
Drainage pipeline defect detection predominantly relies on closed-circuit television (CCTV) inspection, which is labor-intensive, inefficient, and prone to missed detections. Although deep learning-based object detection has been applied, it suffers from low precision, recall, and speed in practical scenarios. This study proposes an engineering-oriented detection scheme achieving high recall and low miss rates. The annotation phase employs a cross-frame strategy combining manual labeling of first and last frames with interpolation and tracking-based refinement. Data preprocessing introduces perceptual hashing to identify similar images, enhancing training efficiency. For detection, a Faster R-CNN model is enhanced with Focal Loss to focus on hard examples, defect classification and grading, and a dynamic threshold strategy to improve recall. Validated on 5,068.72 m of real pipeline data, the method achieves a recall rate exceeding 98% across 16 defect categories, a miss rate of only 2% for grade 4 defects, and a 425% improvement in per-segment detection efficiency compared to manual screening. These results demonstrate the method's effectiveness in balancing recall, miss rate, and speed for engineering deployment.
SCIENCE CHINA Materials•2026•DOI: 10.1007/s40843-025-3786-8
Conventional cancer diagnostic techniques, such as tissue sampling and microscopy, are invasive and prone to misdiagnosis, driving the need for non-invasive, precise alternatives. Chiral biophotonics, exploiting circularly polarized light (CPL), offers unique polarization-selective interactions with biological tissues, enabling higher imaging contrast and molecular-level discrimination. However, current CPL detection technologies are passive and single-mode, lacking dynamic tunability and parallel processing capabilities. Meanwhile, AI-assisted diagnostics rely on separated sensing and computing units, suffering from poor integration and transmission inefficiency. Here, we report a near-infrared (NIR) chiral organic synaptic photodiode with electrically tunable dual-mode operation, enabling simultaneous CPL detection and neuromorphic processing. Under negative bias, the device operates as a highly sensitive CPL detector for chiroptical signal acquisition. Under positive bias, it exhibits history-dependent synaptic behavior with photocurrent dissymmetry factor (g_ph) dynamically tunable up to -0.06. By integrating this device into an optical convolutional neural network (OCNN), we achieved intelligent cancer detection with CPL-based imaging. Experimental results demonstrate that CPL detection accuracy reaches 83%, approaching the theoretical 87%, significantly outperforming natural light detection at 65%. The device enhances image contrast and feature extraction, laying a foundation for intelligent, adaptive diagnostic systems.
SCIENCE CHINA Materials•2026•DOI: 10.1007/s40843-025-3981-7
Solution-processable quasi-2D perovskites are promising laser gain media due to their high exciton binding energy and improved stability relative to 3D counterparts. However, conventional synthesis yields mixed n-value phases, introducing interfacial defects and energetic disorder that impede charge injection into desired emission centers. Here, we report the first demonstration of stimulated emission from a phase-pure quasi-2D perovskite (n=8) achieved via a solvent-sieving method for selective phase removal. This dynamic purification yields near-unity phase purity (99.85%) with no detectable low-n phases, as confirmed by X-ray diffraction and ultraviolet-visible spectroscopy. The phase-pure film exhibits a narrower and more intense (001) diffraction peak (FWHM 0.16 nm, intensity 16,129) compared to pristine films (FWHM 0.22 nm, intensity 3,304), indicating enhanced crystallinity and increased grain size. Time-resolved photoluminescence reveals a prolonged carrier lifetime of 6.98 ns, suggesting reduced trap density. Atomic force microscopy shows a nearly pinhole-free surface with root mean square roughness of 1.18 nm. Consequently, the amplified spontaneous emission threshold is reduced to 13.82 μJ cm−2, a 12.5% improvement over conventional mixed-phase films (15.8 μJ cm−2). This work provides an efficient route to pure-phase quasi-2D perovskites for low-threshold lasers.
SCIENCE CHINA Materials•2026•DOI: 10.1007/s40843-025-4034-3
The local concentration and configuration of active sites critically influence the selectivity of CO2 electroreduction, yet constructing well-defined structures to probe this relationship remains challenging. Here, we report a molten salt-assisted strategy to synthesize Ce-Ov-Cu cascade catalysts with tunable configurations and relative concentrations of Cu and Ce-Ov sites. Two distinct geometries were engineered: one with dense Cu sites surrounding Ce-Ov (Cu10CeOx) and another with isolated Cu centers encapsulated by Ce-Ov (CuCe10Ox). These configurations direct key intermediates (*CHO or *COH) toward either C-C coupling or deep hydrogenation, thereby switching product selectivity. CuCe10Ox achieves a CH4 Faradaic efficiency (FE) of 61.7% at -1.6 V vs. RHE, whereas Cu10CeOx favors C2 production with a maximum FE of 61.5% at -1.4 V vs. RHE. Mechanistic studies reveal that locally concentrated Cu sites exhibit strong *CO2 binding affinity, enhancing *CO surface coverage and facilitating *CO-*COH coupling. In contrast, Ce-Ov-rich regions with isolated copper centers supply abundant *H, promoting deep protonation of *CHO toward CH4. This work provides insights into catalyst design, demonstrating that manipulating structural chemistry can guide CO2RR toward targeted products.