NERC-NSTC Dual-mode marine-Environment Examination of micro/nanoPlastics with integrated AI (DEEP-AI)

Our project, called DEEP-AI, aims to revolutionise how we detect tiny plastic particles in our oceans. Although large plastic waste is a visible problem, the real threat comes from micro and nanoscale plastics—tiny fragments that are hard to see, difficult to collect, and even harder to measure. These minute particles, often less than 1 micron in size, can travel across oceans, accumulate in marine life, and eventually enter the food chain, affecting both ecosystems and human health. Plastic pollution is a growing global challenge that demands smarter, faster solutions. Traditional methods for detecting microplastics are often slow, expensive, and require specialised lab equipment. DEEP-AI seeks to overcome these limitations by developing a cutting-edge sensor that combines two advanced detection techniques. The first, Localised Surface Plasmon Resonance (LSPR), and the second, Surface-Enhanced Raman Spectroscopy (SERS), work together to provide a sensitive and selective way to identify plastics at the nanoscale. Integrating these methods with artificial intelligence (AI) allows for real-time data analysis that can quickly pinpoint pollution hotspots and even predict future contamination patterns. The sensor system we are designing is portable, meaning it can be deployed on research vessels, coastal monitoring stations, or even autonomous underwater vehicles. This capability is especially important for addressing pollution in remote or rapidly changing marine environments. By drastically reducing the time between sample collection and analysis, our technology will enable faster, more informed decisions to protect marine life and public health. Our project is built on a strong international partnership that brings together top experts from both the UK and Taiwan. The UK team is responsible for sensor design, water sampling, and AI integration. Their expertise in materials science and environmental monitoring forms the backbone of the project. Meanwhile, our Taiwanese partners contribute specialised knowledge in advanced SERS sensing and sensor integration. Together, these teams combine complementary skills that are essential for developing a practical, field-ready solution. The project has two main objectives. First, we aim to foster knowledge exchange and build international capacity. This includes hosting online workshops, a mini-symposium in the UK, and reciprocal student and staff exchange programs. These activities will not only train the next generation of researchers but also ensure that our methods and findings are shared widely. Second, we plan to develop and validate the DEEP-AI sensor system through five work packages. These cover everything from sampling techniques and nanoparticle enrichment to sensor integration and AI-driven data analysis. Each stage is carefully designed to address the challenges of detecting minute plastic particles in a complex marine environment. The potential applications and benefits of DEEP-AI extend far beyond scientific research. By providing rapid, reliable data on plastic pollution, our project can help shape environmental policies, support sustainable practices, and protect the health of both marine ecosystems and human communities. Our innovative approach is timely, given the urgent global need to tackle plastic waste, and our international partnership ensures that the project benefits from diverse expertise and perspectives and it represents a transformative step forward in environmental monitoring. It harnesses state-of-the-art biosensor technology and AI to offer a real-time solution for detecting micro- and nanoplastics, promising significant benefits for marine conservation, policy-making, and public health.