SirenOpt is developing a real-time sensing and software platform to improve the manufacturing performance and yield of batteries, solar cells, and other renewable technologies. The sensor collects critical manufacturing data that is otherwise unobtainable, and the software uses the sensing data to quantify and mitigate manufacturing variability in real time.
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Jared O'Leary
Jared O'Leary is the co-founder and CEO of SirenOpt. O’Leary earned a Ph.D. in chemical engineering from UC Berkeley, where he investigated learning-based methods to characterize, model, and control advanced materials manufacturing processes. He co-founded SirenOpt to commercialize the technology he helped develop during his doctoral work. Previously, O’Leary worked as an engineer and team lead at Theranos and earned a B.S. with honors and distinction in chemical engineering at Stanford.
TECHNOLOGY
Critical Need
Advanced coatings, thin films, and micro- and nano-scale materials with unique functional properties enable many clean energy industries, such as lithium-based batteries, electronics, power generation, semiconductors, solar cells, and carbon conversion. Minimal-waste manufacturing of high-performance thin films will be vital for achieving society’s net-zero carbon emission goals. Because existing thin film sensors cannot operate within most sections of manufacturing lines, manufacturers often complete hundreds of processing steps before they can test their products, and often are only able to do so with destructive sample testing. Current thin-film manufacturing thus often yields many low-quality products, or off-spec products that must be discarded.
Technology Vision
SirenOpt is developing a real-time manufacturing intelligence platform to improve thin film manufacturing performance and yield. Its sensor, enabled by low-temperature plasmas and physics-informed machine learning, is compact, can be integrated into manufacturing lines, and can collect multiple thin film property measurements in parallel and in real-time. By measuring factors such as thickness, density, conductivity, chemical composition, and contamination, it collects critical manufacturing data that is otherwise unobtainable. SirenOpt’s optimization-based decision-making software then uses the sensing data to quantify and mitigate thin film manufacturing variability in real-time, and lays the groundwork for automatic real-time process control.
Potential for Impact
SirenOpt’s unique manufacturing intelligence platform enables more material-efficient, reliable, and higher-performance manufacturing of batteries, electronics, semiconductors, and other advanced products that are critical components of a sustainable economy. SirenOpt thus has the potential to substantially increase the adoption of these and future versions of such clean energy technologies, which will help society achieve net-zero carbon emissions on a global scale. Furthermore, by non-destructively accessing new nano-level understanding, SirenOpt can enable the design and manufacturing of electronic devices of the future, which have the potential to transform many other fields such as transportation and healthcare.