选择性
化学
吸附
化学物理
分子动力学
纳米技术
材料科学
生物芯片
分析物
电化学
异质结
催化作用
胺气处理
分子开关
分子
表面电荷
载流子
双功能
电荷密度
分子识别
动能
计算化学
化学种类
作者
Ravi Chand Singh,Wansik Oum,Yuxiang Shen,Ka Yoon Shin,Ryo Toyoshima,Ken Uchida,Sang Sub Kim,Hyoun Woo Kim
出处
期刊:ACS Sensors
[American Chemical Society]
日期:2026-09-26
卷期号:11 (10): 9588-9601
标识
DOI:10.1021/acssensors.6c03122
摘要
Controlling molecular selectivity in chemiresistive gas sensors remains a fundamental challenge, particularly for chemically analogous analytes that generate indistinguishable electronic responses. Here, we demonstrate that polymorph-engineered MoS2/SnO2 heterointerfaces establish a programmable molecular recognition platform for selective volatile amine detection. By tuning the 1T/2H phase distribution within MoS2/SnO2 nanorod heterostructures, distinct sensing pathways emerge for chemically similar molecules. Specifically, 1T-enriched heterostructures preferentially detect ammonia (NH3), whereas 2H-dominated architectures selectively respond to triethylamine (TEA). Neural Network Potential Molecular Dynamics (NNP-MD) simulations reveal that this selectivity originates from phase-dependent charge routing at the heterointerface, which governs the coupling between molecular rotational dynamics, surface reaction kinetics, and adsorption thermodynamics. Spectroscopic and gas-phase analyses indicate that 1T-rich interfaces promote kinetically driven catalytic activation of NH3, generating reactive intermediates that transiently oxidize Mo centers. In contrast, 2H-dominated interfaces favor thermodynamically stabilized dipole-mediated adsorption of TEA, producing a distinct electronic response with minimal surface oxidation. The optimized sensors achieve sub-parts-per-billion detection limits (0.5 ppb for NH3 and 0.6 ppb for TEA) and maintain stable operation under high humidity. Practical applicability is demonstrated through real-time monitoring of volatile amine emissions during pomfret fish spoilage under ambient storage. This work introduces a new paradigm in phase-engineered heterointerfaces as a generalizable materials-design strategy for programming intrinsic kinetic and thermodynamic selectivity for next-generation chemical sensors.
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