Transduction Cluster


Lead: Peter TÖRÖK

Professor, IDMxS Co-director
Nanyang Technological University

Converting spatially-arrayed biochemical recognition events into quantitative optical or electrical signals by integrating the detection platform with a physical transducer


To develop methods, strategies and devices that leverage principles developed by the Detection Cluster to turn chemical changes into detectable optical signals and, with contributions from the Analytics Cluster, to convert it into a digital signal.


The Cluster aims to develop optical readout devices, including their software and hardware environment, that can either autonomously or coupled to a mobile phone, provide low cost, low energy consumption, robust and on-site evaluation of labelled assays targeting the detection of analytes of interest.

One focus of the cluster will aim to develop readout devices based on classical refractive, single axis optics which will provide the first generation of readers both for laboratory and on-site use. We will also investigate the practicality of alternative readout devices primarily aiming at increasing the field of view (assay area) and/or simplifying the optical system. This work will heavily rely on input from computer science including computational optics and AI/machine learning and is the backbone of IDMxS’s assay evaluation.

The Transduction cluster will also investigate how label free detection can be made a practical reality. SERS provides a label free mechanism to identify analytes but technical challenges have to date prevented SERS to be applied at low cost, high throughput diagnostics. We will develop low cost nanostructured surfaces that will permit massively parallel interrogation of analytes of interest, whilst also developing novel imaging spectrometers. Finally, the cluster will research routes to monitor and detect conformal changes of individual protein molecules.

Principal Investigators

Matthew R. FOREMAN
Duane LOH
SUM Tze Chien

© 2022 - 2024 Institute for Digital Molecular Analytics and Science (IDMxS)