SBIR-STTR Award

An estimated 75% of litter along the shoreline globally is made of plastic. Plastic particles and debris find their way into oceans, rivers, lakes, sediment, and eventually into our bodies. Over 90% of the plastic contamination in the open ocean is attributed to microplastic particles (MP) - i.e. plastic objects with diameter <5mm. MP are even found in up to 94% of tap water in the United States. Due to their small size, it is especially difficult to accurately sample, quantify and characterize MP. Existing solutions to MP identification and characterization are mostly laboratory based and involve laborious, time-consuming processes, expensive equipment and expertise to operate.Lucendi proposes to develop a cost-effective, portable and automated platform for MP characterization, based on our lens-free computational microscopy technology coupled with machine learning and big data algorithms. The proposed effort will leverage Lucendi’s existing platform, which is built in a parallel effort, and will significantly redesign and develop a new platform for the purpose of high-throughput MP sampling, identification and characterization. Our platform will enable high-throughput monitoring (~100ml/hour, user adjustable), capable of identifying and characterizing MPs in a wider dynamic range (4µm – 1mm, can be adjusted), will be built as a portable and robust device aimed for in-field and in-lab applications alike and will be embedded with computational platform enabling it to operate autonomously for long-term unattended deployment scenarios. Furthermore, the proposed platform will be also integrated with a Machine Learning engine capable of automated MP identification and characterization.The proposed platform is envisioned to have wide applicability with primary modifications required in the types of objects it is trained to identify and characterize. Therefore, an initial beachhead market will be in general water monitoring and assessment (an estimated $4.6 billion market), with additional prospects for the platform to be easily extended into aquaculture ($242 billion market) and algae-based bioproducts research and cultivation ($5 billion market). Our initial market research and customer discovery process suggests that the initial users, i.e. first adopters, will likely be from the research and scientific community, with follow on models of the product designed and mass-produced for a wider groups of users.The proposed platform will significantly advance capabilities for cost-effective automated sampling,identification and characterization of MP in liquid samples and will provide opportunities to advance the state of the art and commercial opportunities across multiple applications and industries.

Annually over 8 million tons of plastic flows into the ocean causing an estimated $13 Billion damage to marine ecosystems. Microplastic particles (MP) are those with diameters <5mm and constitute the largest class of plastic pollution in the open ocean with recent estimates accounting for as much a s90% of all plastic litter. MP are even found in up to 94% of tap water in the United States. Due to their small size, it is especially difficult to accurately sample, quantify and characterize MP.Lucendi is developing Aqusens-MP -a cost-effective, portable and automated platform for MP identification and characterization. Our platform is based on lens-free computation microscopy with machine learning. It enables monitoring water samples with high-throughput (100ml-1L/hour), while maintaining a wide dynamic range of 4um - 1mm. In contrast, existing solutions to MP identification and characterization are mostly laboratory based and involve laborious, time-consuming processes, expensive equipment and expertise to operate.During Phase I we have tested an initial prototype and verified its capabilities to a) identify MP in flow and distinguish them from other microobjects, b) characterize identified MP by color, shape, size, morphology and phase properties. We have also demonstrated feasibility of our techniques to perform MP compostion estimation by applying phase metrics and lens-free polarization imaging via an additional mode we will be adding in Phase II. These results pave the way for productization and evaluation of Aqusens-MP in Phase II to validate its depolyment capabilities. We envision Aqusens-MP application as a cost-effective and high-throughput screening instrument that can be used to perform bulk MP measurement and statistics prior to othercharacterization methods.An initial focus for our technology will be in water quality sensor market (an estimated $5 billion market), with an early emphasis on MP and particulate monitoring at water treatment facilities (an estimated $660 million market in US and EU). Furthermore, secondary markets are currently explored for other versions of the platform, including aquaculture ($242 billion market) and algae-based bioproducts ($5 billion market). Our initial market research and customer discovery process suggests that the first adopters of our technology will likely be from the research and scientific community, with follow on models of the product designed and mass-produced for professional users.The proposed platform will also have far-reachning environmental benefits by enabling potable cost-effective analysis of water samples for MP, toxic algae and other microorganisms, as well as general particulates analysis.