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Atomistic Scale Modeling of Anode/Electrolyte Interfaces in Li-Ion Batteries

Atomistic Scale Modeling of Anode/Electrolyte Interfaces in Li-Ion Batteries
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South Korea , Kyongsang Bukto , Soult Ukpyolsi , Hyunguk Kwon , Jeonghyun Ko , Monte Carlo , Kyeounghak Kim , Yeongjun Yoon , University Of Notre Dame , Pennsylvania State University , Department Of Materials Science , Georgia Institute Of Technology , Battery Rd Center , A Software Package For Deep Potential Models , Energy Lett , University Of Seoul , Seoul National University , Energy Combust , Department Of Chemical Engineering , Hanyang University , Department Of Chemical Engineering At Hanyang University , University Of Pittsburgh , Generation Battery Center , Electrostatics In Neural Network Potentials , Energy Fuels , Energy Systems ,

"Regulating the Electronic Configuration of Supported Iron Nanoparticle" by Xiaowei Wang, Yanyan Zhao et al.

Electrocatalytic nitrogen reduction reaction (eNRR) is a sustainable alternative to the traditional Haber–Bosch process due to its eco-friendly nature and capability of utilizing renewable energy. However, its low Faradic efficiency (FE), caused by the excessive adsorption and reduction of protons, has been regarded as the main challenge, which leads to low ammonia yield as well. Herein, a carbon-supported iron electrocatalyst is reported, which is fabricated by low-temperature (300 °C) potassium vapor reduction of FeF3-intercalated graphite fluoride, for efficient electrochemical nitrogen reduction. The strategy enables the unique formation of exposed Fe nanoparticles uniformly anchored on graphene and in situ doped with fluorine heteroatoms. These specific features can alter the electronic configuration of the Fe nanoparticles, leading to strong surface polarization that boosts nitrogen absorption capability for eNRR, resulting in high FE (41.6%) and ammonia yield rate (53.3 μg h ....

Carbon Based Electrocatalyst , Electronic Configuration , Fluorine Functionalization , Ron Nanoparticle , Nitrogen Fixation ,