# SENSORS FOR WATER CONTAMINANT DETECTION AND MONITORING

> **NIH NIH P42** · YALE UNIVERSITY · 2024 · $160,305

## Abstract

ABSTRACT 
Groundwater in Superfund sites is contaminated with a wide range of hazardous chemicals originating from 
anthropogenic and natural sources. Individuals exposed to these chemicals through contaminated drinking water 
can be subjected to adverse health effects. The YSRTP will focus on 1,4-dioxane (1,4-DX) and its co-occurring 
contaminants: trichloroethylene (TCE), 1,1,1-trichloroethane (TCA), and 1,1-dichloroethane (DCA). To protect 
drinking water supplies and human health, rapid approaches for the detection and monitoring of these 
contaminants are crucial. The overall goal of this project is to develop sensors for 1,4-DX and its co-contaminants 
with real-time monitoring via a wireless network. The project includes four specific aims: (1) developing and 
characterizing biosensors for 1,4-DX detection and quantification, (2) developing and characterizing chemical 
sensors for 1,4-DX co-occurring contaminants (TCE, TCA, and DCA), (3) 1,4-DX and co-contaminant detection 
via portable vacuum gas chromatography, and (4) demonstrating detection in a distributed wireless sensor 
network for contaminant monitoring. The main innovative aspects of the research include the following: (i) 
developing the first sensor for detecting low, health relevant concentrations of 1,4-DX, by employing an 
evolutionary selection process, an artificially antibody affinity maturation technique, and organometallic pre- 
binding molecules; (ii) developing a chemical sensor that exploits the unique solubility-based selectivity of lipid 
and block-copolymer bilayer vesicles for detecting TCE, DCA, and TCA as a proxy for 1,4-DX contamination; 
and (iii) demonstrating the use of 1,4-DX sensors and adapted portable vacuum gas chromatographers in a 
wireless sensor network (WSN) to enable responses to dynamic contamination and exposure events. The project 
is well integrated with the overall YSRTP. The real time data of contaminant concentrations provided by the WSN 
will be integrated Project 4 to improve remediation strategies and measure remediation effectiveness and help 
inform the biomedical projects (Projects 1,2) on exposures for communities in the vicinity of the Superfund sites, 
and inform the community—through the Community Engagement Core—on real-time concentrations of the 
target contaminants in drinking water sources. The project will also be engaged with the Data Management & 
Analysis Core (DMAC) to appropriately store and analyze all contaminant occurrence and concentration data 
pursuant to the above project interactions and for assistance in the WSN to meet the stated measurement goals.

## Key facts

- **NIH application ID:** 10868587
- **Project number:** 5P42ES033815-03
- **Recipient organization:** YALE UNIVERSITY
- **Principal Investigator:** Drew R Gentner
- **Activity code:** P42 (R01, R21, SBIR, etc.)
- **Funding institute:** NIH
- **Fiscal year:** 2024
- **Award amount:** $160,305
- **Award type:** 5
- **Project period:** 2022-09-07 → 2027-06-30

## Primary source

NIH RePORTER: https://reporter.nih.gov/project-details/10868587

## Citation

> US National Institutes of Health, RePORTER application 10868587, SENSORS FOR WATER CONTAMINANT DETECTION AND MONITORING (5P42ES033815-03). Retrieved via AI Analytics 2026-05-23 from https://api.ai-analytics.org/grant/nih/10868587. Licensed CC0.

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