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Conformationally Adaptive SERS Receptors: Reconfiguring Binding Environments via Dynamic Gauche–Trans Transitions for Broad-Spectrum Ion Sensing
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DOI:10.1021/acsami.6c01066.png)
Abstract
En 中文
Chemical receptors capable of broadly differentiating small ions remain constrained by static binding architectures that limit adaptability across chemically diverse analytes. Here, we introduce sodium 3-mercaptoethanesulfonate (MES-Na) as a surface-bound, conformationally adaptive SERS receptor that exploits the coexistence of gauche and trans states as an intrinsic sensing dimension. Upon anchoring to a plasmonic silver surface, ion binding selectively redistributes the populations of coexisting conformations rather than inducing a single static complex. This conformation-dependent population modulation generates analyte-specific spectral responses governed by relative binding preferences instead of absolute interaction strength. Using this mechanism, we achieve accurate differentiation of 17 inorganic salts comprising cations spanning charges from +1 to +3 and both monatomic and polyatomic anions, with classification accuracies of 99.6% at micromolar concentrations, substantially outperforming a conformationally rigid control receptor. Beyond single-analyte identification, the bidirectional conformational response enables reliable individual and multiplex quantification of mixed ionic systems, with correlation coefficients exceeding 0.92. In addition, spectral augmentation based on experimentally resolved cation- and anion-specific responses enables accurate identification of previously unobserved cation–anion combinations. Collectively, this work establishes dynamic conformational redistribution as a general sensing principle in which population ratio modulation encodes rich interaction information that enables scalable, broad-range ion sensing.
Keywords:
Anions
Conformation
Ions
Receptors
Salts
surface-enhanced Raman scattering (SERS)
ion sensing
multiple conformation receptors
machine learning
density functional theory (DFT)
Journal
A
IF:
0
Papers:
65
Citations:
1
