# Morphology-adaptive Au-Ag nanowire elastronics for integrated FlexoSERS and bioelectrical sensing

## TL;DR

A flexible Au-Ag nanowire platform adapts to different shapes and enables both optical and electrical sensing for wearable health monitoring.

## Contribution

A morphology-adaptive Au-Ag nanowire platform that enables both FlexoSERS and bioelectrical sensing across diverse geometries.

## Key findings

- The nanowire arrays maintain stable SERS signals under 100% strain and after 2500 cycles.
- The platform enables accurate ECG-based sleep-wake classification using deep learning.
- The EMG signals captured include subtle motor activities like finger bending and typing.

## Abstract

We introduce a morphology-adaptive Au-Ag nanowire elastronic platform that conforms to diverse geometries while enabling multimodal optical-electrical sensing. Using a facile yet versatile template-guided growth strategy, vertically aligned Au-Ag nanowire arrays are directly fabricated on 1D nano/microneedles, 2D elastic films, and 3D porous architectures. On 2D substrates, the arrays act as FlexoSERS interfaces with high sensitivity, uniformity (RSD = 7.2%), and durability, maintaining stable SERS signals under 100% strain and after 2500 cycles. On 3D porous sponges, the NWs serve as dry bioelectrical electrodes, enabling stable electrocardiogram (ECG) and electromyogram (EMG) monitoring with long-term stability. Continuous ECG recording, combined with deep learning analysis, enables accurate classification between sleep and wake states. Meanwhile, the EMG signals capture subtle motor activities such as finger bending, typing, and clicking. By uniting strain-tolerant FlexoSERS with reliable bioelectrical sensing across 1D-3D substrates, this platform provides a robust material foundation and a scalable route toward next-generation wearable health monitors, intelligent sleep evaluation, and human-machine interfaces.

A vertically aligned Au-Ag nanowire array as a morphology-adaptive, dual-functional conformal sensing platform.