001-40 WC 139 NOV-DEC24 PAPERTURN - Flipbook - Page 20
INNOVATION
of the system. “Our success in overcoming these challenges is
a testament to the brilliance and expertise of our team,” says
Ariya. “We worked tirelessly.”
The precision of the AI-assisted nano-DIHM system has
been verified using several other technologies. In an alarming real-world Canadian context, from test sites along Lake
Ontario and the St. Lawrence River, the team has found that 2
per cent of the water borne particles are nanoplastics, and 1 per
cent are microplastics.
How it works
Broadly, nano-DIHM directly obtains the interference patterns
of objects by recording the scattered light information originating from the objects. In more detail, water from the environment is drawn directly via a syringe pump and flow cell. The
DIHM system has a laser and camera. An interference pattern
(or hologram) is formed by the interaction between a reference
wave and the scattered light from the objects being analyzed.
The hologram is captured by a complementary metal-oxide
semiconductor-photosensitive matrix sensor. During automated reconstruction of each particle, the AI software scans a
number of the 1,000 reconstruction planes available for each
produced hologram, targeting particles below 1,000 micrometers. The system algorithms extract the particle morphological
characteristics and obtain 3D data from the recorded images.
This means that in addition to volume of micro/nanoplastics, AI-nano-DIHM provides physicochemical properties
of single particles or nano/microplastic clusters, including size,
shape, optical phase (a determination of where the electric field
of a particle sits within its oscillation cycle), perimeter, surface
area, roughness and edge gradient. “To our knowledge,” Ariya
says, “no one can provide all this different information for small
particles in real-time and in-situ.”
By combining these insights into 3D particle characteristics
with complementary modeling, these scientists have also successfully demonstrated that nano/microplastics have significantly-distinct 4-dimensional distribution patterns in water over time. This
makes AI-nano-DIHM, says Ariya, a “powerful tool” for not
only accurate nano/microplastic life-cycle analysis, but remediation of ‘hotspots’ (sites from which various pollutants are highly
concentrated and continuously being emitted).
“By using this technology, we will be able to perform sustainable recycling in a targeted manner, leading to better, faster and
more economical removal/recycling of these particles,” Ariya
explains. “If we could bring several smaller AI-nano-DIHM to a
site, we would get colossal amounts of information.”
Ariya notes that there are many excellent sites for testing the
amount of micro/nanoplastics present in the environment, including water treatment plants. While she acknowledges that cost
of the technology is a factor in achieving more widespread use of
20
WATER C AN ADA • NOV EMBER/ DECEMBER 2024
Other applications for AI-assisted nano-DIHM
In-situ and real-time nano/microplastic coatings and dynamics in water for
plastic lifecycle research Nano-DIHM data has provided evidence of distinct
coating patterns on nano/microplastic particles by oleic acid, magnetite
and phytoplankton, representing organic, inorganic and biological coatings
widely found in natural settings. This study also demonstrated that inorganic
ions in seawater and oleic acid organic coatings altered the sedimentation
velocity of studied plastics. In addition, while water dynamics was found to
be the driving force of plastic transport, the accumulation of plastics was
found to be selectively dependent on particle physicochemical properties
such as size and density.
Rapid detection of oil, heavy metals and biological spills in
aquatic systems
The fate of numerous human-made and natural particle contaminants in
diverse aquatic systems is largely unknown. However, nano-DIHM enables
automated 4D tracking of particles such as oil droplets in water and their
transformations in 3D space. This study also provided evidence that nanoDIHM can detect representative biological-viral material and mercurycontaining particles alongside other toxic heavy metals. Nano-DIHM can
also characterize the interactions of various particles in mixtures, as well as
particles with different coatings in a suspension.
Further understanding of dynamic airborne nano-sized particles such
as real-time 4D tracking of airborne virus-laden droplets and aerosols
AI-nano-DIHM addresses the need for real-time airborne virus tracking, for
which no method previously has existed.
AI-nano-DIHM at this time, miniaturization of the platform will
eventually make it very cost-competitive. “Indeed, our calculations
show that the cost can be a fraction of the leading technologies
while providing a much more accurate physicochemical process
while being in-situ and real-time, which no other technology can
do until now,” she says. “We will also work on other factors that
will make the small unit much more robust and accurate in different environmental conditions.”
Broad benefits
As if this new ability to help address environmental and human health issues caused by nano/microplastics weren’t exciting
enough, the technology is already being applied in other areas (see
sidebar).
Ariya reports “We have already demonstrated for a wide range
of particles in the top-tier international peer-reviewed journals,
and we will do so for many more applications.” The platform is
already being explored in DNA/RNA research, medical diagnostics and space sciences.
More ways to use the technology will continue to grow in the
future with further improvements, for example, in the area of
identifying in-depth particle surface characteristics. “With adequate
support,” says Ariya, “we can use this innovative technology for a
wide range of applications to serve our planet and humanity.”
WAT E R C A N A D A . N E T
