journal article·2026-07-14Open access

Maximizing Nanoscale Disorder in Block Copolymers for Orientation‐Independent SERS Platform Toward Non‐Invasive Diagnostics

Jin Man Kim, Wonsik Kim, Wansun Kim, Yeon‐Hee Kim, Samjin Choi, Jang Hwan Kim, Hyeong Min Jin

Abstract

ABSTRACT The development of high‐performance optical molecular diagnostic platforms requires the precise engineering of light–matter interactions to ensure quantitative accuracy across diverse sensing environments. While high‐density nanogap architectures based on block copolymer‐derived lamellar patterns provide exceptional sensing performance, their inherent long‐range orientational order induces polarization‐dependent responses that compromise quantitative reliability. Here, we introduce controlled randomness into vertically aligned lamellae to induce optical isotropy while strictly preserving nanoscale periodicity. Inspired by natural ridge‐like architectures, grain‐size regulation generates stochastically oriented domains with short‐range orientational correlation. Engineering orientational disorder through grain‐size‐mediated diversity suppresses long‐range anisotropy while upholding the integrity of the periodic framework. Quantitative assessments of structural entropy and numerical simulations of localized hot‐spots provide in‐depth insights into the underlying mechanism. The resulting stochastic architectures exhibit SERS responses that are insensitive to polarization and incident direction while maintaining spatially uniform signal reproducibility. The statistically robust SERS platform enables high‐fidelity clinical diagnostics, demonstrated through the metabolic profiling of urine from pregnant women and AI‐driven predictive modeling, establishing a universal basis for quantitative molecular sensing.
Source: crossref · Quality: baseline

Research context

OpenAlex topics: Block Copolymer Self-Assembly · Gold and Silver Nanoparticles Synthesis and Applications · Advanced Polymer Synthesis and Characterization

SciVX discovery tags are terminology-based. OpenAlex topics are source-provided classifications.

Affiliations

Department of Organic Materials Engineering Chungnam National University Daejeon Republic of Korea

Department of Materials Science and Engineering Chungnam National University Daejeon Republic of Korea

Department of Energy Systems Research Ajou University Suwon Republic of Korea

Department of Biomedical Engineering College of Medicine, Kyung Hee University Seoul Republic of Korea

Department of Obstetrics and Gynecology College of Medicine The Catholic University of Korea Seoul Republic of Korea

Department of Materials Science and Engineering Ajou University Suwon Republic of Korea

Funding

Ministry of Education

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