Responsive Janus Droplets for Metal Ion Detection in Water Quality-Monitoring Platforms: Enhanced Specificity via Selective Ion Complexation

Abstract Water quality monitoring is essential across various industries, including environmental management, industrial processes, food safety, and agriculture. Among the many contaminants, heavy metal ions are particularly concerning due to their toxicity and persistence in water systems. Here, we present a liquid–liquid sensing platform for metal ion detection based on surfactant-stabilized biphasic oil-in-water emulsions. The detection mechanism relies on changes in surfactant behavior upon interaction with metal ions, including variations in critical micelle concentration (CMC), surface excess, and interfacial stabilization. The size and charge of metal ions significantly influence surfactant effectiveness, enabling both total ion content analysis and identification of specific aqueous signatures. To enhance specificity, we introduce selective ion complexation using chelating agents, such as EDTA, which reduces the impact of chelated ions on surfactant behavior and improves sensitivity toward unbound target ions. This approach also enables the indirect detection of chelating agents in water samples, including glyphosate, a widely used herbicide. Our findings expand the potential of Janus droplet-based sensing assays and support the development of modular, adaptive liquid-monitoring platforms for real-time water quality monitoring.

Authors

Institutions

Publication Details

Journal
ACS ES&T Water
Published
2026-10-27
DOI
https://doi.org/10.1021/acsestwater.6c00702
Primary Topic
Surfactants and Colloidal Systems
Type
article
Field-Weighted Citation Impact
0.00

Funders

Controls
|||
ALL TIME
JAN
FEB
MAR
APR
MAY
JUN
JUL
AUG
SEP
OCT
article

Responsive Janus Droplets for Metal Ion Detection in Water Quality-Monitoring Platforms: Enhanced Specificity via Selective Ion Complexation

Nenad Popov, Lukas Zeininger, Marko Pavlović, Karla Milčić et al.
2 links
ACS ES&T Water
Surfactants and Colloidal Systems
article

Responsive Janus Droplets for Metal Ion Detection in Water Quality-Monitoring Platforms: Enhanced Specificity via Selective Ion Complexation

Nenad Popov, Lukas Zeininger, Marko Pavlović, Karla Milčić, Heman Kumar Ramiya Ramesh Babu, Milan Vraneš, Lidija Petrović, Slavica Mitrović, Yuzi Hong, Teodora Despotovski Kiš, Jelena Bajac
article en

Abstract

Abstract Water quality monitoring is essential across various industries, including environmental management, industrial processes, food safety, and agriculture. Among the many contaminants, heavy metal ions are particularly concerning due to their toxicity and persistence in water systems. Here, we present a liquid–liquid sensing platform for metal ion detection based on surfactant-stabilized biphasic oil-in-water emulsions. The detection mechanism relies on changes in surfactant behavior upon interaction with metal ions, including variations in critical micelle concentration (CMC), surface excess, and interfacial stabilization. The size and charge of metal ions significantly influence surfactant effectiveness, enabling both total ion content analysis and identification of specific aqueous signatures. To enhance specificity, we introduce selective ion complexation using chelating agents, such as EDTA, which reduces the impact of chelated ions on surfactant behavior and improves sensitivity toward unbound target ions. This approach also enables the indirect detection of chelating agents in water samples, including glyphosate, a widely used herbicide. Our findings expand the potential of Janus droplet-based sensing assays and support the development of modular, adaptive liquid-monitoring platforms for real-time water quality monitoring.

ACS ES&T Water
Harvard University (US), The University of Melbourne (AU), University of Novi Sad (RS), University of Belgrade (RS), Max Planck Institute of Colloids and Interfaces (DE), Institute of General and Physical Chemistry (RS), Scientific Veterinary Institute "Novi Sad" (RS), BioSense Institute (RS), The Ohio State University (US)
Schweizerischer Nationalfonds zur Förderung der Wissenschaftlichen Forschung, Ministarstvo Prosvete, Nauke i Tehnološkog Razvoja, Horizon 2020 Framework Programme
Clean water and sanitation
Openalex Percentile: Top 26%
Surfactants and Colloidal Systems
AI Navigator

Ask Laika to Summarize, Analyze, and Connect papers live on the map.

Summarize Papers & Methodologies

Extract key findings, datasets, and comparative methods across publications.

Benchmark Rankings & Visual Analytics

Rank top research institutions, authors, funders, topics, and journals by Field-Weighted Citation Impact (FWCI) and paper volume with instant charts.

Connect Distant Disciplines

Bridge topological clusters on the map to find hidden collaborative intersections.

Laika access coming soon