Certainty in Microplastics Analysis

The average person consumes a credit card worth of plastic each week.

Tiny particles called microplastics are being discovered throughout all ecosystems of our planet. They accumulate in the environment and end up in food and drinking water.

Plastics impact human and ecosystem health.

Microplastics is a core issue of environmental concern.

Health regulators are creating policy frameworks for water treatment facilities, and large corporations need to test their products to ensure quality control and public safety standards are upheld.

Researchers and regulators need to identify the types of plastics that occur the most in our natural ecosystems.

How it works

Compound Connect improves lab result quality through machine learning.

Researchers who study microplastics can determine which plastics occur the most in our environments by their chemical signatures. Frequency and intensity of chemical signals can be visualized on a graph:

Compound Connect uses a “black box” machine learning artificial intelligence algorithm designed to recognize plastics and microplastics that have been altered by environmental weathering.

1. Input raman spectroscopy
(chemical signature) data

2. AI-trained model identifies
plastic polymers (chemical compounds)

3.  Polymer compounds and point-source data output in a standard format for
researchers and regulators


Product development and testing in collaboration with the University of Winnipeg

Business development assisted by the
North Forge Technology Accelerator

Research funding secured through the
Mitacs Accelerate Program

Use Compound Connect in your lab today.

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