Graphene cellulose hybrids for biodegradable flexible sensing devices
Abstract
Paper-based sensors have emerged as a groundbreaking class of analytical devices, offering affordable, biodegradable, and flexible platforms for a broad range of applications, including environmental monitoring (e.g., heavy metals, PFAS, and microplastics detection), medical diagnostics (such as procalcitonin and glucose monitoring), food safety (like ammonia detection), and wearable electronics (for strain, pressure, and humidity sensing). This review looks at how using cellulosic-based materials with advanced nanomaterials-especially graphene and its variations-can improve the sensitivity, conductivity, and durability of sensors. The deploy of graphene-based electrodes, such as reduced graphene oxide (rGO), laser-induced graphene (LIG), and graphene-molybdenum disulphide (Gr/MoS2) composites, has developed devices with high responsiveness (up to 1.38 × 10-7 µA L-1 µg-1), low detection inhibits (as low as 1.36 pM), excellent mechanical flexibility, and strong thermal equilibrium (up to 700 °C). These developments highlight the immense potential of graphene-paper hybrid systems for constructing the next generation of environmentally friendly and multipurpose sensors that can tackle new worldwide issues in smart packaging, public health, the Internet of Things (IoT), and sustainable electronics.
Read the paper
Related studies
- Nano Biosensors: Properties, applications and electrochemical techniques
- Electrochemically Synthesized MIP Sensors: Applications in Healthcare Diagnostics
- Toward a Harmonization for Using in situ Nutrient Sensors in the Marine Environment
- Electrochemical determination of rutin by using NiFe2O4 nanoparticles-loaded reduced graphene oxide
- Application of Polyoxometalate-based composites for sensor systems: A review
- Sensitive Electrochemical and Thermal Detection of Human Noroviruses Using Molecularly Imprinted Polymer Nanoparticles Generated against a Viral Target
Go deeper in Evidence Hub
Evidence Hub adds a study data sheet (design, sample size, evidence level, key numbers), an AI summary and a chat grounded in the paper's text.