Powered by OpenAIRE graph
Found an issue? Give us feedback


Nanoextraction, separation and detection of micropollutants in one single and simple step
Funder: European CommissionProject code: 862032 Call for proposal: ERC-2019-PoC
Funded under: H2020 | ERC | ERC-POC-LS Funder Contribution: 150,000 EUR
Open Access mandate
Research data: No

Sample preparation is considered to be the most difficult step in analytic workflow. Current methods for extraction and separation of minute substances in liquid samples are laborious, time-consuming, often involve large amounts of toxic organic solvents, and are often difficult to automatize, implying high costs of man-power. An innovative sample preparation technique which has the potential to overcome these shortcomings will be developed in this project. Based on the first promising results in the ERC-AdG project DDD, we propose a surface nanodroplet-based sensing approach for liquid-liquid extraction and online analysis of traces of analytes in aqueous solutions, including in biomedical, health, pharmaceutical and environmental contexts. The basis of our approach, referred to as nanoextraction, will be surface nanodroplets pre-formed on a substrate within a microflow channel. The principle of the nanoextraction is that the partition coefficient of the compound in the droplets is much higher than in the sample solution. The compound in the flow will thus be extracted to the nanodroplets that are immobilized on the channel walls. The concentration of the compound in the droplets will be quantified by surface-sensitive spectroscopic techniques. Our proposed approach can potentially achieve extraction-separation-detection of analytes at extremely low concentrations in one single and simple step. The ability to achieve extraction-separation- detection of micropollutants in one single step is creating new and unique market opportunities which we want to explore. First, the technology can improve the state-of-the-art solutions in current markets, because of the easy usage and the small scale, thus saving time and costs. Second, we foresee new markets for the method, due to the higher sensitivity and point-of-care character of the solution. Our final goal in this project is to create a solid and investor-ready business plan, supported by a prototype.

Data Management Plans
Powered by OpenAIRE graph
Found an issue? Give us feedback

Do the share buttons not appear? Please make sure, any blocking addon is disabled, and then reload the page.

All Research products
<script type="text/javascript">
document.write('<div id="oa_widget"></div>');
document.write('<script type="text/javascript" src="https://www.openaire.eu/index.php?option=com_openaire&view=widget&format=raw&projectId=corda__h2020::5c8c957812d675d3e828e2bfb9871b6f&type=result"></script>');
For further information contact us at helpdesk@openaire.eu

No option selected