Goal

Inspired by the opportunities and challenges of measuring low-abundance, time-varying, and molecularly ill-defined chemical and biological targets in noisy and molecularly crowded physical environments, the Detection Cluster seeks to innovate suites of modular detection technologies that convert biomolecular recognition into physical read-outs ­– optical, electrochemical, and electronic – ready for integration with portable devices.

Strategies

To achieve our goal, we will innovate technologies that enable the detection of highly specific biomolecular interactions with extremely high (including single-molecule) sensitivity. Approaches include:

(1) Massively parallel measurements that allow for digital counting;

(2) Recognition (or binding)-induced signal enhancements and amplification through changes in material properties, such as by phase-separation, phase transition, aggregation, or hybridization chain reaction; and

(3) AI-guided analyses of microscopy images. We will also engineer approaches for multiplexed, error-tolerant, and label-free implementations of our detection strategies. The cluster will develop these approaches for detecting environmental pollutants, nucleic acids, proteins, lipids, and metabolites.

Principal Investigators