In the filed of connectomics, reconstructing an accurate and complete connectome requires considerable manpower, financial resources, and time. Efficient management of reconstruction projects to conserve resources and enable rapid reconstruction poses a significant challenge. This study views individual annotators as decision-making units from a microlevel perspective and uses data envelopment analysis to establish productivity and performance analysis model of annotators. By introducing advanced Artificial Intelligence (AI) algorithms to empower intelligent management of connectome reconstruction, we can mine users’ effective outputs in a more reliable and robust way. Edge computing performance is improved by embedding intelligent algorithms and data collection systems into user devices. Through the analysis of the inputs and outputs in the production activities of annotators, the effectiveness of the proposed model has been validated, which helps to understand and optimize user performance. The proposed method can be used for efficient management in connectome reconstruction to allocate resources equitably and optimize human resources within the company.

Carbon nanotube thin film transistors (CNT-TFTs) are a potential TFT technology for future high-performance macroelectronics. Practical application of CNT-TFTs requires the production of large-area, highly uniform, density-controllable, repeatable, and high-throughput CNT thin films. In this study, CNT films were fabricated on 4-inch Si wafers and 2.5^th generation (G2.5) backplane glasses (370 mm × 470 mm) by dip coating using a chloroform-dispersed high-purity semiconducting CNT solution. The CNT density was controlled by the solution concentration and coating times, but was almost independent of the substrate lifting speed (1–450 mm·min^-1), which enables high-throughput CNT thin film production. We developed an image processing software to efficiently characterize the density and uniformity of the large-area CNT films. Using the software, we confirmed that the CNT films are highly uniform with coefficients of variance (C_V) < 10% on 4-inch Si wafers and ~ 13.8% on G2.5 backplane glasses. High-performance CNT-TFTs with a mobility of 45–55 cm²·V^-1·s^-1 were obtained using the fabricated CNT films with a high-performance uniformity (C_V ≈ 11%–13%) on a 4-inch wafer. To our knowledge, this is the first fabrication and detailed characterization of such large-area, high-purity, semiconducting CNT films for TFT applications, which is a significant step toward manufacturing CNT-TFTs.