U of T ENGINEERING

U of T Engineering News

Researchers at U of T Engineering have observed that handwashing synthetic fabrics in water with higher total dissolved solids (TDS) leads to more microplastic fibres (MPF) being released, creating implications for billions of people without access to soft water or washing machines.

The study, described in a paper published in Scientific Reports, looked at polyester fabrics and how they fared when handwashed in various types of water.

Some fabrics were covered in a silicone-based coating meant to reduce the MPF release, but the researchers found that the efficacy of this coating varied under different conditions.

According to a report from the Changing Markets Foundation, synthetic fibres — such as polyester, nylon and acrylic, mainly used in fast fashion — account for about two-thirds (69%) of textile production and are projected to rise to nearly three-quarters (73%) by 2030.

When synthetic fabrics are laundered, the friction caused by the laundering process leads to MPFs being released into waterways.

A significant contributor to global plastic pollution, microplastics are difficult to fully remove from water. While the impacts to human health remain unclear, microplastics are a risk to marine life, as they can block digestive tracks and cause injury when swallowed.

Professor Kevin Golovin’s (MIE) DREAM lab had previously created a silicone-based coating to reduce friction in the laundering process and prevent the fibres from breaking off, but the coating was only tested with machine laundering fabrics.

When Amanuel Goliad (MSE 2T3, MASc student), lead researcher and author on the paper, started asking how the coating fared in hand-washed cycles, he realized there was a research gap and decided to address it.

Goliad, whose family is from Ethiopia, grew up knowing about handwashing and understanding how prevalent it is.

“Nearly two-thirds of the world does not have access to a washing machine,” says Goliad.

“Most people around the globe hand wash, yet nearly all the microfibre research focuses on machine laundering in high-resource settings.”

To conduct his study, Goliad adapted a bamboo washboard-based method from another research paper, noting that so little research is done on hand washing that it was difficult to even find a standardized method to pull from.

He then washed green and black polyester fabrics, both coated and uncoated, using deionized, tap and Lake Ontario water. After washing, he filtered the wash water to count and analyze the MPFs.

Under the microscope, Goliad found that not only were there significant amounts of MPFs being released but also that the coating didn’t always prevent as much MPF release as it had in previous research using washing machines.

When looking at the coated green polyester fabric, the coating reduced fibre shedding by about 92% in deionized water but only 37% in Lake Ontario water, illustrating how its efficacy declines as TDS increases.

“The biggest impact in the efficacy of the coating comes from the type of wash water,” says Golovin.

“Most people that hand wash clothing use whatever body of water is locally available; it could be a river, an ocean, a lake. There are more total dissolved solids within them, and that affects the release of these microfibres more than people realize.”

At the same time, most research is being conducted in labs using deionized water, which has a TDS of 0, meaning that studies don’t reflect the real washing conditions of much of the world.

“There are additional implications for communities that don’t have access to laundry machines,” says Golovin.

“They’re the ones being exposed to more microfibres, but the policies and standards don’t reflect this. A potential action item resulting from this research and hopefully follow-up research is that those communities might need better water filtration systems than what global policy is stipulating, because they’re exposed to more MPFs.”

Another surprising find in the study were the actual lengths of the fibres.

“Higher TDS levels resulted in shorter fibre lengths,” says Goliad.

“That’s important because shorter fibres are harder to filter out in filtration systems; they spread more quickly and they’re more easily ingested by aquatic life.”

Golovin says the discovery of shorter fibres also have implications for how they’re currently measured.

“We have a new hypothesis that the dissolved minerals in harder water may be breaking the fibres into smaller pieces,” says Golovin.

“This affects how we measure microfibre release. If they’re being chopped into smaller fragments, simply counting fibres does not give an accurate picture.”

Golovin is advocating for measuring the total mass of the fibres released over just the count. He also notes his lab is researching fabric coating that can better withstand being hand washed in water with higher TDS.

“I hope this work highlights the environmental impact of hand washing and the need for more inclusive research,” says Goliad.

An interdisciplinary case study from researchers at U of T Engineering and the Department of Geography & Planning demonstrates the challenges that can arise when governments adopt a ‘smart cities’ strategy — and points the way toward possible solutions. 

The study revolved around the city of Coimbatore in India’s Tamil Nadu state. Municipal water there is supplied via an intermittent system, which is turned on and off for each neighbourhood at various times throughout the week or month. 

“More than a billion people around the world get their water intermittently,” says Professor David Meyer (CivMin), who studies these types of systems, including how to effectively model them.  

“For many cities, upgrading to a 24/7 water supply is just not feasible. But one thing they can do as a stop-gap measure is to post the schedule online, so their users can at least plan around the times when they will receive water.” 

This was the case for Coimbatore: in line with the Smart Cities initiative launched by India’s national Ministry of Housing and Urban affairs, the city decided to post its water schedules online. 

“When they started posting the data online in April 2022, it gave us an opportunity to study the impact that open data and digital transparency can have on municipal services,” says Professor Nidhi Subramanyam from the Department of Geography & Planning, co-author along with Meyer of the new study, which is published in Environmental Research: Infrastructure and Sustainability. The research was funded by a Catalyst Grant from U of T’s Data Sciences Institute.

“As our study shows, it turned out to be a pretty laborious task, and it just couldn’t be sustained. They stopped posting after just a few months.” 

Meyer says one of the key challenges was the format in which the data was provided, as well as its sheer volume.  

“Each day, city staff would post a 50-page PDF document, a digitized version of the internal paper documents they used to determine the water schedule,” he says. 

“But as a user, you don’t care about most of that: you only want to know when your taps are going to be turned on. To find that, you have to scan through hundreds of rows of text, looking for your street name. And it might be in a different place each time — or it might not be there at all, which would mean that you’re not getting any water that day.” 

Meyer uses the analogy of a rainstorm in a desert to describe the switch. 

“Before this, there was no data at all, like a dry desert with no rain,” he says. 

“And then all of a sudden, you have a torrent of data, like a flood. But that doesn’t make things better; instead, it creates a whole new set of challenges.” 

In the paper, the team outlines simple changes that could have made the data much more useful. For example, posting the data in the form of a machine-readable spreadsheet instead of a PDF would have enabled third-party developers to create an app that automatically sends users a text message when their water is coming on. 

“Why didn’t they do that? To be empathetic to the city workers who we interviewed, a lot of it comes down to resources,” says Subramanyam. 

“The utility didn’t hire anyone to be in charge of the new system, or to think through the best way to do it. Instead, they just added it to the list of tasks that current workers had to do, without increasing their pay or providing incentives. So it’s no surprise that they did it in a way that would be easy, rather than useful.” 

“There’s also an element of ‘silent resistance.’ If you are asked to take on a new project that significantly adds to your workload, but you are not compensated for it, you have a good reason to want the project to fail. And in the end, that’s what happened here.” 

Meyer says that while implementation was not effective in this case, the strategies of digital transparency and open data still have the potential to improve how cities work. He hopes that the team’s work can point the way toward best practices that might enable these tools to better live up to their promise. 

“Right now, there’s no standard for how to do this effectively, so everyone is just kind of making it up as they go along,” he says. 

“What we’re hoping is that by highlighting what didn’t work in this case study, and by suggesting what might have worked better, we can set the stage for a more successful implementation. 

“If more places provide open data that is accurate, timely and accessible, it will do a lot to reduce the uncertainties and stress resulting from inadequate water supply.” 

A new open-access tool created by U of T Engineering researchers provides a systematic way to organize and synthesize knowledge about metal–organic frameworks (MOFs) — a class of materials with applications in drug delivery, catalysis, carbon capture and more. 

Metal–organic frameworks (MOFs) are an exceptionally versatile class of materials, distinguished by their ultra-high surface area and precisely tunable chemistry. Some MOFs have surface areas reaching up to 7,000 m²/g, meaning that a gram of this material contains enough internal surface area to cover a football field. 

This unique structure enables a wide range of promising applications. Some can be used as molecular sieves, separating carbon dioxide from other gases so it can be captured and sequestered. Others grab onto tiny molecules, enabling them to be detected at extremely low concentrations. Still others can help speed up industrially important reactions, or deliver drugs to certain areas of the body. 

The growing importance and transformative potential of MOFs in science and technology is underlined by the fact that they were the subject of the 2025 Nobel Prize in Chemistry. 

But with studies on MOFs accelerating across more than 25 application domains, keeping track of the field’s rapidly growing body of knowledge has proven increasingly challenging — not just for researchers, but also for the AI tools intended to support scientific discovery.

A team led by Professor Mohamad Moosavi in the Department of Chemical Engineering & Applied Chemistry, and the Vector Institute, has developed a new system to help address that challenge.

Their new tool is named Unifying Chemical Data for MOFs, abbreviated to MOF-ChemUnity. The work has been published in the Journal of the American Chemical Society, one of the most prestigious journals in chemistry; the study was selected for the cover of a recent issue.

“Scientific discovery begins with reading and synthesizing the literature, but this remains one of the most difficult steps to automate,” says Moosavi.   

“MOF-ChemUnity creates a unified foundation that both researchers and AI systems can build on.” 

A structured map of MOF knowledge 

The remarkable tunability of MOFs makes them suitable for a wide range of technologies, but the breadth and diversity of research across disciplines have made the field increasingly complex to navigate. 

MOF-ChemUnity addresses this challenge using a structured and scalable knowledge graph that systematically extracts and links information from MOF research papers, crystal structure repositories and computational materials databases. 

knowledge map of metal organic frameworks
The MOF-ChemUnity knowledge graph stores about 0.5 million data points and connections for over 15,000 metal-organic frameworks. The foreground shows examples of the types of information each material may be connected to, including associated properties, applications, synthesis procedures and more. (image by Thomas Pruyn)

At the core of the system is a multi-agent large language model (LLM) workflow designed to connect chemical names in the literature to the correct crystal structures. This enables synthesis procedures, material properties and potential applications to be represented in a consistent, machine-readable format. 

“A knowledge graph connects pieces of information like a web, linking things, like a MOF, its metal node, synthesis protocol, and adsorption property through their relationships — ‘made from’, ‘synthesized’,  ‘used for’,” says Moosavi. 

 “This lets AI not just store data but understand and reason about how materials, properties and applications are connected — exactly what MOF-ChemUnity enables.”  

Reducing AI hallucination through literature grounding 

The team demonstrated the system’s impact by integrating the knowledge graph with large language models to build a literature-informed AI assistant for MOFs. Unlike standard AI systems, which can produce plausible-sounding but incorrect statements, the literature-informed assistant draws on verified experimental and computational records. 

In blind evaluations performed by MOF experts from multiple institutions, the assistant’s responses were consistently rated as more accurate, interpretable and trustworthy than those produced by baseline LLMs such as GPT-4o. 

“This approach reduces hallucination, which is one of the major obstacles in applying large language models to scientific domains,” Moosavi says. 

“By grounding AI responses in curated and linked literature, we can support more reliable scientific reasoning.”

A foundation for future materials discovery 

The U of T team — Moosavi and his graduate students, Thomas Pruyn and Amro Aswad (both ChemE), who were key contributors to the work — have made the dataset and code openly available on GitHub, aiming to support continued progress in materials science and AI-driven research.

The main funder is the National Research Council of Canada’s Materials for Clean Fuels Challenge Program, and U of T’s Acceleration Consortium and Data Science Institute.  

Moosavi says the project lays groundwork for a broader shift in how scientific knowledge is organized and accessed. 

“This work will help break down silos in scientific research,” Moosavi says.  

“Human researchers are limited by the number of papers they can read, but MOF-ChemUnity takes a first step toward enabling AI systems that can process data across fields.  

“It establishes a new paradigm for literature-informed discovery, and we envision it as the beginning of generalized knowledge systems that can accelerate research across many fields.”

A reception held November 10 at U of T brought together more than 200 people from academia and industry, as well as partners from the Ontario government and First Nations, to explore how collaborations in battery innovation can bring about a cleaner and more prosperous future.

The event was jointly hosted by U of T’s Faculty of Arts & Science, the Department of Chemistry, the Faculty of Applied Science & Engineering and Asahi Kasei Corporation, a major producer of battery separators, critical components for lithium-ion batteries.

Attendees were treated to a lecture titled The Future Society Made Possible by Lithium-ion Batteries, given by Professor Akira Yoshino, one of three co-recipients of the 2019 Nobel Prize in Chemistry for the development of that technology. Yoshino is both a fellow of Asahi Kasei Corporation and a professor at Meijo University in Nagoya, Japan.

Since their invention in the mid-1980s, lithium-ion batteries have become ubiquitous, powering everything from mobile phones to electric vehicles to grid-scale energy storage facilities.

But as Yoshino explained, renewed innovation could enable this technology to serve even more roles in the future:

“In the coming years, I believe we’ll see meaningful progress in several key areas of battery technology – from advances in recycling that better support circularity, to next-generation materials that enhance battery performance across a broad range of applications,” said Yoshino.

“To accelerate these innovations, we must create resilient supply chains. That means responsibly developing new resources and fostering international cooperation. This includes minimizing uncertainty and attracting long-term investments in R&D and manufacturing capacity to support the clean energy transition.”

After the lecture, Yoshino met with U of T researchers working in areas relevant to battery technology. The attendees included experts in materials science, chemistry and power electronics, many of whom are members of world-leading U of T research hubs such as:

  • The Acceleration Consortium, which combines material science with the power of artificial intelligence, robotics, and advanced computing to rapidly design and test new materials and molecules.
  • The Lawson Climate Institute, which will galvanize and accelerate U of T’s capacity to advance the technologies, policies, and incentives needed to make the global transition to net zero.
  • The Centre for Quantum Information and Quantum Control, which promotes research collaborations in these rapidly evolving interdisciplinary fields.

The event also included tours of U of T facilities by representatives from Asahi Kasei Corporation and the Japanese ambassador to Canada. Asahi Kasei recently began work on a new manufacturing facility for battery separators in Port Colborne, Ont.

“We were pleased to team with the University of Toronto for this event and hope it sparks a long-term partnership that drives innovation, supports student and workforce development, and strengthens the battery supply chain, both in Ontario and North America,” said Samuel Mills, President of Asahi Kasei Battery Separator North America.

Dozens of U of T research groups are already pursuing research that builds on Yoshino’s work to advance energy storage solutions. Examples include the following:

“It was an honour to join the University of Toronto and Asahi Kasei for Dr. Akira Yoshino’s Distinguished Lecture,” said the Honourable Sam Oosterhoff, Ontario’s Associate Minister of Energy-Intensive Industries.

“Ontario’s universities offer world-class research, state-of-the-art facilities, and a highly skilled talent pool to help industry tackle real-world challenges. With its expertise in EVs, advanced batteries, and energy more broadly, the University of Toronto is uniquely positioned to support Ontario’s clean energy future — driving innovation, creating jobs, and strengthening our economy for decades to come.”

For Paige McFarlane (EngSci 2T5, BME PhD student) biomedical engineering was the perfect middle ground between two paths.  

“Where I come from, there’s this idea, you either go into medicine or you go into engineering,” she says. 

“I didn’t want to be a doctor or nurse, but I did want to work in health care, so this seemed like a good way to combine the two.” 

McFarlane, who grew up in Jamaica, came to U of T to pursue an undergrad in Engineering Science. She says her decision to pursue a PhD out of undergrad was in part motivated by receiving the Indigenous and Black Engineering and Technology (IBET) Momentum Fellowship.  

“At first I thought I’d do a master’s and then go for the PhD, but when I got the fellowship that would allow me to do my PhD directly, it was like a door opened and the idea really became possible,” she says. 

As a recipient of the 2025 fellowship, McFarlane will receive financial support, mentorship, training and networking opportunities throughout her PhD. The IBET PhD Project is intended to foster equitable and inclusive research environments to increase the presence of Indigenous and Black academics in STEM. 

She credits IBET with connecting her to two labs working on microfluidics, and is currently completing rotations in both.  

While she is still planning her PhD path, McFarlane is interested in microfluidics as they pertain to point of care. 

“Microfluidics studies how very small amounts of fluids, such as water or blood, flow through tiny channels,” she says.  

“I think of it like tiny plumbing. At the point of care, we’re talking about things like using microfluidics as a quick and easy tool for in-home testing, or diagnostic tests done in the doctor’s office. I think that’s where I’ll focus my research.”  

She is also keeping inclusivity in mind when thinking about her future research, noting the current lack of research around women’s health. 

“When you’re designing your own experiments, you can try and ensure an inclusive sample set for data collection,” she says.

“I’m hoping with my PhD to ensure that whatever research I do, it takes into account different biomarkers or variations that women have. The main thing I’m hoping is that my research ends up in the hands of those it’s intended to help, so that’s why I’m interested in the point-of-care diagnostics.” 

Outside of the lab, McFarlane is taking advantage of all that the IBET program has to offer. Over the summer, she attended a presentation by a previous fellowship recipient, where she got to see the reach of IBET’s community.  

“I’m excited for the mentorship that those who have gone before me can offer as well as the mentorship that I can hopefully give to those after me.” 

“I’m looking forward to IBET’s annual conference as it will be a nice first step and training ground into that kind of environment for presenting research work.” 

She is also partaking in mentorship opportunities by volunteering with U of T’s DISCOVERY program. McFarlane has previously assisted with the National Society of Black Engineers (NSBE) annual high school conference and spent two summers working for the Engineering Outreach Office in the Blueprint program. 

“That was probably my favourite program I’ve worked with because there were two students I mentored there who I saw on campus studying Engineering the following year,” she says. 

“It’s the best thing ever getting to mentor high school students and then seeing them pursue their dreams.” 

Funding from a Data Sciences Institute (DSI) Doctoral Student Fellowship will help power research into soft tactile-sensing robotic skin.

MIE PhD candidate Arman Arezoomand uses a biomimetic approach in his research, working with sensors that can detect the shape and texture of objects, just as human skin does. As the recipient of the new fellowship, Arezoomand will continue to develop and explore a new application of AI in tactile perception for robots.

“Receiving this fellowship allows me to address the current limitations in artificial tactile perception and develop prosthetic digits equipped with soft sensors that truly replicate the sensitivity of the human fingertip skin,” says Arezoomand.

Beyond prosthetics, the technology developed in Arezoomand’s project holds significant promise for embodied AI, where robots must interact intelligently with dynamic physical environments. In this field, the artificial skin could enable more sophisticated autonomous systems — such as humanoid robots that navigate cluttered spaces or perform intricate tasks like sorting fragile items — by providing real-time feedback on surface textures, pressures and slippage.

Future plans are to integrate the sensor into a prosthetic hand, restoring a sense of touch for upper-limb amputees. An embedded/edge AI within the prosthesis would process the sensor data in real-time, providing the user with tactile feedback.

“Our overarching objective is to develop a sensor that can make a real impact and improve the quality of life for partial hand amputees,” says Arezoomand.

“The goal of restoring tactile sensing in prosthetics has been a powerful motivation to develop a truly useful product to improve balance, motor control and gripping.”

Arezoomand is co-supervised by Professor Fae Azhari (MIE, CivMin) in the Decisionics Lab, and Professor Heather Baltzer, clinician investigator at the Krembil Research Institute, part of the University Health Network, director of the Hand Surgery group at Toronto Western Hospital, and professor at U of T’s Temerty Faculty of Medicine.

Arezoomand joined MIE after completing his Master of Science in Mechatronics Engineering at Sharif University of Technology in Tehran, Iran. He says he was drawn to U of T by its reputation as a hub for collaborative, multidisciplinary AI research — a perfect fit for his project.

“The complexity of the project allows us to break it down into smaller pieces for teams with different expertise, from mechanical engineering to medical science,” says Arezoomand.

“I am incredibly grateful to lead such a diverse and innovative effort in replicating the human sense of touch through artificial skin.”

The tactile sensing technology could also improve manufacturing and supply chains by creating more advanced automation systems that can perform delicate assembly tasks and take control of automated storage and retrieval systems in warehouses.

“Big tech companies have initiated research in this context, and they are competing, which shows the importance the tactile sensing challenges,” says Arezoomand.

“The scope and potential application of the research are so widespread, it’s fulfilling for myself and the team to work toward developing a sensor with substantial impact.”

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