Chowdhury, Ankita Dutta and Roy, Somenath (2026) Bridging Functional Material to Device Integration: Copper ferrite Nanocomposite based Point-of-Care Sensor for Selective Neurotransmitter Detection. In: International Conference on Functional Materials (ICFM 2026), 5-7 January 2026, IIT Kharagpur, West Bengal. (Submitted)

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Abstract

Emerging clinical interest in real time neurochemical profiling has intensified interests in smart, functional nanocomposites owing to their tuneable surface chemistry, catalytic activity and ability to distinguish between closely related neurotransmitters. In this scenario, copper ferrite (CuFe2O4), a transition metal oxide spinel, embedded on reduced graphene oxide (rGO) sheets is being deployed for selective and sensitive detection of dopamine, a major neurotransmitter whose imbalance is responsible for a plethora of diseased conditions like pheochromocytoma as well as psychiatric disorders. Though Cerebrospinal Fluid (CNS) is the traditional route of neurotransmitter collection, the painful approach of extraction, difficulty in sample storage and high turnaround time for receiving results from high end equipment like HPLC, LCMS has prompted researchers and clinicians to explore alternative strategies for sample collection and fabrication of point of care biosensor platform. Urinary neurotransmitters, being the viable, well established, painless route is being selected as the preferred sample choice owing to its non-invasive method of collection and higher stability as well as concentration than blood. Synthesized via one pot co precipitation route, the nanocomposite (CuFe2O4-rGO) is well characterized via sophisticated characterization techniques like XRD, TEM, SEM, XPS and Raman spectroscopy to shed light on its structure property relations as well as to gain clarity on its sensing behaviour. The nanocomposite modified electrode is deployed for electrochemical detection of dopamine for which the sensor exhibited well defined linearity in the range of 0.1-300 µM with 74 nM as the lower limit of detection (LoD). The functionalized screen-printed electrodes exhibited heightened sensitivity and specificity in simulated urine matrix and in presence of major interferents like uric acid and ascorbic acid. Extending the capability towards real-time, machine-assisted analyte identification, deep neural network (DNN) is employed to classify the electrochemical characteristics of dopamine in simulated urine. The model achieved an average classification accuracy of 97.8% and reliable concentration estimation, confirming selective recognition and quantification of the neurotransmitter within a complex biological matrix. Finally, as a step towards device integration, an IoT enabled smartphone interfaced handheld neurotransmitter device is being developed where quantitative analysis of dopamine is achieved by establishing an interface among the disposable sensing element, the electronic detector and the user’s smartphone, followed by dispensing a droplet of sample and launching an indigenous application software. The result, displayed on the user’s smartphone within a minute, can be shared with clinicians marking an advancement towards point of care device fabrication using functional materials for healthcare applications. Keywords: CuFe2O4-rGO, point-of-care, dopamine, biosensor

Item Type:	Conference or Workshop Item (Poster)
Uncontrolled Keywords:	CuFe2O4-rGO, point-of-care, dopamine, biosensor
Subjects:	Engineering Materials
Divisions:	Sensor and Actuator
Depositing User:	Ms Upasana Sahu
Date Deposited:	23 Sep 2026 09:05
Last Modified:	23 Sep 2026 09:05
URI:	https://cgcri.csircentral.net/id/eprint/5821

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