{"id":82864,"date":"2025-12-15T15:31:14","date_gmt":"2025-12-15T14:31:14","guid":{"rendered":"https:\/\/www.kwrwater.nl\/actueel\/de-vingerafdruk-van-complexe-watermengsels-nemen\/"},"modified":"2025-12-17T16:23:23","modified_gmt":"2025-12-17T15:23:23","slug":"de-vingerafdruk-van-complexe-watermengsels-nemen","status":"publish","type":"post","link":"https:\/\/www.kwrwater.nl\/en\/actueel\/de-vingerafdruk-van-complexe-watermengsels-nemen\/","title":{"rendered":"Taking the \u2018fingerprint\u2019 of complex water mixtures"},"content":{"rendered":"
\n

Complex water mixtures such as wastewater are typically monitored with sensors that test individual parameters separately. But how convenient would it be if this could all happen simultaneously\u2014as if you were taking the “fingerprint” of the water? A recently completed TKI project has shown that Electrochemical Impedance Spectroscopy (EIS) is a promising sensing technology for this purpose. \u201cWe\u2019ve made great progress with inorganic contaminants,\u201d says Gijs Vermeij of Hypersoniq.<\/p>\n<\/div>\n

The water sector urgently needs reliable, real-time, and cost-effective detection of a wide range of substances at low concentrations, so that timely mitigation measures can be taken when necessary. In the TKI project Development of a Water Quality Sensor<\/a>, Electrochemical Impedance Spectroscopy (EIS) was investigated as a potential monitoring tool for saturated hydrocarbons and inorganic substances.<\/p>\n

New application<\/h2>\n

EIS technology itself is not new\u2014it is, for example, already used in studies to examine material degradation. However, its application as a monitoring tool for measuring certain types of pollution in wastewater is novel, explains Vermeij, Chief Technology Officer at Hypersoniq. \u201cOur startup is a spin-off from the Dutch sensor company TWTG, which was also a partner in the project. TWTG initiated this new direction for the EIS technology. When it became clear that the sensor still required significant research, KWR and TU Delft got involved. Hypersoniq was then established, and soon afterward this TKI project began. This allowed us to deepen the technical development of the sensor and explore its business case and potential industry applications.\u201d<\/p>\n

Heavy metals<\/h2>\n

The principle of EIS is based on measuring electrical resistance in water as an indicator of its composition. Vermeij explains: \u201cThe sensor has electrodes made of conductive material. By applying an electrical current through a water sample at various frequencies and measuring the resistance, we gain insights into the substances present. We\u2019ve successfully determined what properties the electrodes need to detect inorganic pollutants like heavy metals. Organic compounds, however, show little or no interaction with the electrode materials we\u2019ve tested so far. They don\u2019t show up in the signals. This means the electrode surfaces need further treatment to develop that selectivity. The technology isn\u2019t there yet.\u201d<\/p>\n

Machine learning<\/h2>\n

Before the EIS sensor can detect water contaminants, it must be trained using machine learning models. KWR researcher Patrick Bauerlein explains how: \u201cIt works similarly to how a computer is trained to recognize images of cats or dogs. Once trained with enough examples, the computer learns to recognize them independently. In our case, the computer was trained to interpret data from known water mixture samples. We had already gained experience with machine learning through microplastics monitoring. For heavy metals, we had to visualize the data a bit differently, but when the model finally works\u2014and the computer recognizes substances in the mixture on its own\u2014you just go: wow! That\u2019s when true monitoring becomes possible. We published an explanation of these machine learning models in the prestigious journal Nature Communications<\/a>, along with findings on how the electrodes function for water quality monitoring. A great result from the project.”<\/p>\n

Drinking water sector<\/h2>\n

Although the project focused primarily on wastewater quality measurements, the drinking water sector was also involved. \u201cAt KWR, we simulated a drinking water distribution system at laboratory scale,\u201d says Bauerlein. \u201cWe tested the EIS sensor in this setup for 24 hours and analyzed the data. While the processing takes some time and is not fully real-time, it\u2019s still much faster than collecting samples and sending them to a remote lab. The sensor\u2019s ability to detect heavy metals like arsenic could be of interest to drinking water companies with joint ventures in countries where this is a concern. That opens up international opportunities. KWR will present the EIS sensor findings at upcoming meetings of the Chemical Safety theme group within Waterwijs\u2014the collaborative research program of the drinking water companies<\/a>\u2014to gauge interest in this sensor technology.\u201d<\/p>\n

Unexpected turn<\/h2>\n

Beyond the advances in machine learning and monitoring of inorganic substances, the project took an unexpected turn for Hypersoniq, says Vermeij. \u201cThe core technology\u2014the sensor and measurement principle\u2014is not yet developed enough to bring what we\u2019ve learned into practice. One major drawback is that the electrodes quickly become contaminated when placed in real wastewater. Pollutants stick to them. We realized that solving this within our startup\u2019s financial timeframe wasn\u2019t feasible. However, since we had gained experience in data analysis and model development through the project, we saw an opportunity in using data from commercial sensors that clients were already collecting but not using optimally. We focused on turbidity sensors used in Dissolved Air Flotation\u2014commonly used in the food industry. In this process, tiny air bubbles attach to contaminants in water, causing them to float and be removed more easily. With the turbidity sensor data, we can develop models for clients to optimize chemical dosing, improve wastewater purification, reduce waste streams like sludge, and positively impact the environment. For one client, our models already cut chemical use by more than half. This marks the beginning of our commercial rollout.\u201d<\/p>\n

New focus<\/h2>\n

Essentially, Hypersoniq changed its business focus during the project. \u201cWe transitioned from a hardware startup to a software startup,\u201d says Vermeij. \u201cWe now collect, visualize, and analyze data from water treatment plants and develop models to optimize them. We remain very interested in the further development of EIS technology\u2014TU Delft is continuing that work. We\u2019re especially grateful to KWR for helping us launch our data science team. Without their support, this transition wouldn\u2019t have been possible. They also opened their network to us, which helped us gain insights into the world of sensors, regulation, and key industrial players. That\u2019s the strength of TKI\u2014you become part of an ecosystem that gives you access to people, resources, and knowledge you\u2019d never gather on your own.\u201d<\/p>\n

Project partners<\/h2>\n

The project ‘Development of a water quality sensor using Electrochemical Impedance Spectroscopy for measuring (micro)pollutants’ was carried out with the following partners: Hypersoniq, KWR, TWTG, Vopak Ventures, and with support from TU Delft.<\/p>\n","protected":false},"excerpt":{"rendered":"

Complex water mixtures such as wastewater are typically monitored with sensors that test individual parameters separately. But how convenient would it be if this could all happen simultaneously\u2014as if you were taking the “fingerprint” of the water? A…<\/p>\n","protected":false},"author":50,"featured_media":82789,"comment_status":"closed","ping_status":"closed","sticky":false,"template":"","format":"standard","meta":{"_acf_changed":false,"_relevanssi_hide_post":"","_relevanssi_hide_content":"","_relevanssi_pin_for_all":"","_relevanssi_pin_keywords":"","_relevanssi_unpin_keywords":"","_relevanssi_related_keywords":"","_relevanssi_related_include_ids":"","_relevanssi_related_exclude_ids":"","_relevanssi_related_no_append":"","_relevanssi_related_not_related":"","_relevanssi_related_posts":"","_relevanssi_noindex_reason":"","footnotes":""},"categories":[9],"tags":[1836],"class_list":["post-82864","post","type-post","status-publish","format-standard","has-post-thumbnail","hentry","category-news","tag-tki-watertechnologie-en","gtag-wastewater","gtag-tki-en"],"acf":[],"yoast_head":"\nTaking the \u2018fingerprint\u2019 of complex water mixtures - KWR<\/title>\n<meta name=\"robots\" content=\"index, follow, max-snippet:-1, max-image-preview:large, max-video-preview:-1\" \/>\n<link rel=\"canonical\" href=\"https:\/\/www.kwrwater.nl\/en\/actueel\/de-vingerafdruk-van-complexe-watermengsels-nemen\/\" \/>\n<meta property=\"og:locale\" content=\"en_US\" \/>\n<meta property=\"og:type\" content=\"article\" \/>\n<meta property=\"og:title\" content=\"Taking the \u2018fingerprint\u2019 of complex water mixtures - KWR\" \/>\n<meta property=\"og:description\" content=\"Complex water mixtures such as wastewater are typically monitored with sensors that test individual parameters separately. 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