APPLICATIONS OF TECHNOLOGY:
• Point-of-care clinical diagnostics
• Remote sensing of hazardous materials
• Toxic gas leak detection
• Physical incorporation into cell phones or small devices for remote detection, e.g., drones
• High specificity in analyte identification
• Small in size for field portability
• Low power requirement and cost
Berkeley Lab researchers led by Hoi-Ying Holman have developed a new configuration for plasmonic optical spectroscopy and quantum dot spectroscopy. Known as plasmonic ultra-sensitive multiplex array (PUMA), the invention is an ultrasensitive and accurate sensing imager from VIS to IR for remote sensing of biological and chemical agents, detection of chemical/biological agents on surfaces, pollution monitoring, detection of plumes, and detection of targets and background.
PUMA is a chip-compatible plasmonic grating array platform integrated with a sensing backbone for portable hyperspectral sensing and imaging. Its low-loss plasmonic graded grating (PGG) components enable efficiently collection and concentration of light. These components are complemented with a sensing backbone, which has an individually addressable detection array that includes ultra-high spatial and spectral resolution sensors with charged-coupled devices (CCDs) or complementary metal-oxide semi-conductors (CMOS).
Additionally, PUMA possesses nano-surfaces for light-matter interaction, enabling up to sub-wavelength near- and far-field information with nanometer spatial precision, pico-molar concentration sensitivity, and single-molecule specificity. The technology reduces the spatial gap between the grading and the detector, ultimately yielding a more compact system.
Current instruments are generally bulky, consume substantial energy, and are prohibitively expensive for most applications. As an economically viable means of producing high-precision, compact sensors, PUMA’s ultrasensitive detection technology overcomes these limitations.
DEVELOPMENT STAGE: Proven principle
STATUS: Published U. S. Patent Application 16/152,204 (Publication No. 2019/0137540). Available for licensing or collaborative research.
REFERENCE NUMBER: 2017-054