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Realizing efficient hydrogenation of N2 molecules in the electrocatalytic nitrogen reduction reaction (NRR) is crucial in achieving high activity at a low potential because it theoretically requires a higher equilibrium potential than other steps. Analogous to metal hydride complexes for N2 reduction, achieving this step by chemical hydrogenation can weaken the potential dependence of the initial hydrogenation process. However, this strategy is rarely reported in the electrocatalytic NRR, and the catalytic mechanism remains ambiguous and lacks experimental evidence. Here, we show a highly efficient electrocatalyst (ruthenium single atoms anchored on graphdiyne/graphene sandwich structures) with a hydrogen radical-transferring mechanism, in which graphdiyne (GDY) generates hydrogen radicals (H•), which can effectively activate N2 to generate NNH radicals (•NNH). A dual-active site is constructed to suppress competing hydrogen evolution, where hydrogen preferentially adsorbs on GDY and Ru single atoms serve as the adsorption site of •NNH to promote further hydrogenation of NH3 synthesis. As a result, high activity and selectivity are obtained simultaneously at -0.1 V versus a reversible hydrogen electrode. Our findings illustrate a novel hydrogen transfer mechanism that can greatly reduce the potential and maintain the high activity and selectivity in NRR and provide powerful guidelines for the design concept of electrocatalysts. Submitted/Accepted version This work was financially supported by the Ministry of Science and Technology of China (2018YFA0703502 and 2016YFA0200104), the National Natural Science Foundation of China (Grant Nos. 51720105003, 21790052, 52021006, 21974004, and T2188101), the Strategic Priority Research Program of CAS (XDB36030100), the Beijing National Laboratory for Molecular Sciences (BNLMS-CXTD-202001), the China Postdoctoral Science Foundation (Grant Nos. 8206300625 and 8206400103), and the Academic Research Fund Tier 1 (No. RG10/21).

Although large truck advanced safety technologies such as automatic emergency braking, lane departure warning, and video-based onboard monitoring are becoming more prevalent, adoption rates and use are lagging due to concerns about return on investment (ROI). To address this, researchers at the Virginia Tech Transportation Institute (VTTI) developed an Excel-based ROI calculator and accompanying user manual. This report describes an extension of that original project: a web-based version of that calculator available at https://www.vtti.vt.edu/roicalculator/. The report describes the rationale behind the calculator and an provides an overview of the resources available on the website.