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Kim, Il‐Doo

Publications and source records attributed to Kim, Il‐Doo.

Molecular Fe-N 4 Moieties Coupled with Atomic Co-N 4 Sites Toward Improved Oxygen Reduction Performance

Research on high-efficiency and cost-efficient catalysts for oxygen reduction reaction (ORR) is still a vital but challenging issue for commercializing metal–air batteries. Herein, a single-molecule/atom hybrid catalyst is developed to boost the ORR, in which iron phthalocyanine molecules containing molecular Fe-N 4 moieties couple with atomic Co-N 4 sites on the surface of polyhedral carbon. Density functional theory calculations reveal that face-to-face laminated construction of Fe-N 4 and Co-N 4 in the hybrid catalyst can effectively modulate the electronic structure of active iron atoms and reduce the energy barrier of the rate-determining step for ORR. As a result, this hybrid catalyst demonstrates excellent ORR performance, featuring a half-wave potential of 0.904 V, a peak power density of 238.3 mW cm -2 for zinc–air battery, and outstanding electrocatalytic stability. Here, this work offers a distinctive and robust molecular/atomic engineering approach to creating efficient electrocatalysts, advancing the fields of metal–air batteries.

36 MATERIALS SCIENCE↗

Synergistic Integration of Chemo-Resistive and SERS Sensing for Label-Free Multiplex Gas Detection

Practical sensing applications such as real-time safety alerts and clinical diagnoses require sensor devices to differentiate between various target molecules with high sensitivity and selectivity, yet conventional devices such as oxide-based chemo-resistive sensors and metal-based surface-enhanced Raman spectroscopy (SERS) sensors usually do not satisfy such requirements. In this report a label-free, chemo-resistive/SERS multimodal sensor based on a systematically assembled 3D cross-point multifunctional nanoarchitecture (3D-CMA), which has unusually strong enhancements in both “chemo-resistive” and “SERS” sensing characteristics is introduced. 3D-CMA combines several sensing mechanisms and sensing elements via 3D integration of semiconducting SnO 2 nanowire frameworks and dual-functioning Au metallic nanoparticles. It is shown that the multimodal sensor can successfully estimate mixed-gas compositions selectively and quantitatively at the sub-100 ppm level, even for mixtures of gaseous aromatic compounds (nitrobenzene and toluene) with very similar molecular structures. This is enabled by combined chemo-resistive and SERS multimodal sensing providing complementary information.

36 MATERIALS SCIENCE↗