SCIENCE CHINA Materials•2026•DOI: 10.1007/s40843-026-4245-4
The discrimination of volatile organic compounds (VOCs) at trace concentrations remains a critical challenge for environmental monitoring, industrial process control, and non-invasive disease diagnostics. Conventional electronic noses rely on sensor arrays comprising multiple chemically distinct receptors, which introduces fabrication complexity, calibration drift, and cross-sensitivity. Here, we demonstrate that a single-component Ti3C2Tx MXene (TM) sensor array, engineered through controlled surface chemistry and device architecture, generates independent and high-dimensional characteristics (IHC) sufficient for precise VOC pattern recognition. By exploiting the intrinsic heterogeneity of TM basal planes and edge sites, we achieve differential interaction motifs without expanding elemental composition. The array discriminates VOCs including acetone, ethanol, toluene, and hexane at concentrations down to 100 ppb with classification accuracy exceeding 95%. Principal component analysis reveals distinct clustering with cumulative variance of 92.3% captured by the first three principal components. The sensor exhibits a limit of detection of 50 ppb for acetone and response/recovery times of 12 s and 18 s, respectively. Long-term stability tests over 30 days show less than 5% signal degradation. This single-component strategy simplifies fabrication, reduces calibration overhead, and offers a scalable pathway for miniaturized, low-power VOC sensing platforms compatible with Internet of Things (IoT) deployment.
Environmental Chemistry•2026•DOI: 10.7524/j.issn.0254-6108.2026030202
High nitrogen (N) inputs, low N use efficiency, and substantial greenhouse gas emissions constrain sustainable double-cropping rice production in the middle and lower reaches of the Yangtze River. To evaluate whether humic acid urea (HAU) can reconcile yield stability with N reduction and carbon mitigation, a field experiment was conducted in a double-cropping rice system. Five treatments were established: conventional urea at the recommended N rate (U), HAU at the recommended N rate (HAU), conventional urea with a 20% reduction in N input (U-20), HAU with a 20% reduction in N input (HAU-20), and a no-N control (CK). Rice yield, N uptake and utilization, and the full life-cycle carbon footprint were quantified. Results showed that HAU significantly increased double-cropping rice yield by 6.46% (early rice) and 8.76% (late rice) compared to U (P < 0.05). HAU-20 maintained yield equivalent to U, while U-20 significantly reduced yield. HAU-20 significantly improved nitrogen fertilizer apparent utilization rate, agronomic efficiency, and partial factor productivity. Specifically, apparent utilization rate increased by 9.24 percentage points (early rice) and 7.80 percentage points (late rice); agronomic efficiency increased by 18.51% and 26.69%, and partial factor productivity by 22.79% and 25.58% for early and late rice, respectively (P < 0.05). Life-cycle carbon footprint was significantly reduced by 26.25% (early rice) and 40.38% (late rice) under HAU-20 compared to U, with per-unit product carbon footprint reduced by 0.22 t CO2-eq·t−1 and 0.86 t CO2-eq·t−1, respectively. The reduction was primarily attributed to decreased CH4 and N2O emissions: early rice CH4 and N2O cumulative emissions decreased by 28.92% and 44.34%, and late rice by 44.46% and 63.85% (P < 0.05). In conclusion, HAU with 20% N reduction sustains yield, enhances N use efficiency, and significantly lowers carbon footprint, offering a viable path for green and low-carbon double-cropping rice production.