journal article·2023-06-27Open access

Supported Pt Nanoclusters on Single-Layer MoS2 for the Detection of Cortisol: From Atomistic Scale to Device Modeling

Gabriele Boschetto, Stefania Carapezzi, Aida Todri-Sanial

Abstract

The development of nonenzymatic sensors is a challenge which requires, on the one hand, careful design of the sensing materials with respect to the chosen analyte, and on the other hand, suitable device architectures. In this work, we propose single-layer molybdenum disulfide (MoS 2 ) decorated with subnanometer Pt clusters as the sensing platform for the detection of cortisol. The aim is to assess the suitability of such a sensing platform for the development of wearable and portable cortisol sensors. For this study, we performed multiscale computer simulations at the materials level up to device scale. First, ab initio simulations within the framework of density functional theory (DFT) allowed us to gain insights into the interaction, at the atomic level, between the analyte (cortisol) and the sensing platform (MoS 2 /Pt). Then, by carrying out technology computer-aided design (TCAD) simulations, we were able to consider a device architecture and investigate its performance as cortisol sensor. Following our multiscale simulation strategy, we were able to assess the proposed field-effect transistor (FET) sensor, whose channel is made of Pt-decorated MoS 2 . The sensing mechanism relies on the chemiresistive response of the device to the adsorption of cortisol on the channel, which leads to a sizable charge transfer from the analyte to the substrate and, consequently, to the measurable shift in the gate voltage threshold of the FET. Our findings suggest that both the choice of the sensing materials and the proposed FET architecture are suitable for detecting cortisol by non-enzymatic means. In the best case scenario, we predict theoretical gate voltage shifts between 76 and 780 mV with respect to the cluster concentration and between 27 and 780 mV when varying the cluster occupancy by cortisol. We may expect our results to provide the necessary basis to develop highly sensitive nonenzymatic cortisol sensors based on 2D materials decorated with Pt nanoclusters.
Source: openalex_inverted_index · Quality: baseline

Research context

OpenAlex topics: 2D Materials and Applications · Machine Learning in Materials Science · Advanced Thermoelectric Materials and Devices

SciVX discovery tags are terminology-based. OpenAlex topics are source-provided classifications.

Affiliations

Laboratory of Computer Science, Robotics, and Microelectronics, University of Montpellier, CNRS, 161 Rue Ada, 34095 Montpellier, France

Department of Electrical Engineering, Eindhoven University of Technology, Groene Loper 3, 5612 AE Eindhoven, Netherlands

Funding

Horizon 2020 Framework Programme

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