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Abstract A method for the characterization of organic electrochemical transistors (OECTs) based on small signal analysis is presented that allows to determine the electronic mobility as a function of continuous gate potential using a standard two-channel AC potentiostat. Vector analysis in the frequency domain allows to exclude parasitic components in both ionic and electronic conduction regardless of film thickness, thus resulting in a standard deviation as low as 4%. Besides the electronic mobility, small signal analysis of OECTs also provides information about a wide range of other parameters including the conductance, transconductance, conductivity and volumetric capacitance through a single measurement. General applicability of small signal analysis is demonstrated by characterizing devices based on n-type, p-type, and ambipolar materials operating in accumulation or depletion modes. Accurate benchmarking of organic mixed ionic-electronic conductors through small signal analysis can be anticipated to guide both materials development and the design of bioelectronic devices.

Anthropogenic nitrogen (N) inputs can have detrimental environmental effects, necessitating a comprehensive understanding of the nitrogen budget (NB) and its spatial correlation with the water quality. This study, utilizing a 2016 dataset, scrutinized 850 subwatersheds with diverse land covers across the Republic of Korea (ROK). Employing Geographically Weighted Regression (GWR), it examined the spatial correlations between the NBs and the quality of the groundwater and river water at the watershed scale. Robust correlations (R2 = 0.87) were observed between the groundwater quality and NBs, surpassing those of the surface water (R2 = 0.48). Sensitivity analyses highlighted the importance of high-resolution spatial data in capturing nuances within complex land covers. The integration of such data led to increases in the spatial correlations between the groundwater and river water quality of approximately 0.6–0.9 and 0.3–0.5, respectively. Notably, when the agricultural land cover exceeded 10%, significant enhancements in the spatial correlations were observed, emphasizing the pivotal role of agriculture in nutrient and water quality. At a 10% cropland ratio, the spatial correlations between the watershed-scale NBs and river/groundwater quality increased by approximately 76% and 501%, respectively. This study provides novel insights into the spatial relationships among NBs, water quality, and land use, highlighting the significance of high-resolution data and the impact of agricultural practices on watershed management. These findings contribute valuable information for developing strategies to mitigate nitrogen pollution.