The Microfluidic and Nanotechnology (MiNa) lab, headed by professor Mina Hoorfar, is one of only a few microfluidic research teams in Canada focused on conducting innovative research in the areas of flow in microstructures, integrating the fields of fluid mechanics, biochemistry, and fabrication of biosensors and gas sensors.
Our flagship microfluidic olfaction platform integrates a general-purpose sensing element (typically a metal oxide semiconductor (MOS)) into a microchannel to selectively identify target analytes based on their unique exposure-recovery response signal or "smell print". We often aim to improve the selectivity even further by coating the channel with a variety of specialized metals and polymers and by incorporating nanostructures into the channel design. The detector is paired with a machine-learning model trained for the classification and regression of any single analyte or mixtures of analytes. Our long-term objective is to enhance the selectivity and sensitivity of the microfluidic olfaction platform through the study of scientific and technical challenges and the implementation of different types of sensors, channel designs and data processing methods.
MOS sensors are one of the most popular gas sensors used in the market, hence, in addition to investigating and integrating microfluidic gas detection technologies, this active branch of our research is focused on material synthesis to both develop novel materials with high-performance, long-term stability, humidity resistance, and low power requirements, as well as to improve the importance of current/commercial MOS sensors.
Water contaminants pose a serious threat to public health, the environment, infrastructure, and the economy. Our goal is to develop efficient, low-cost, and user-friendly methods to detect contaminants using microfluidic and lab-on-chip approaches that are based on bio-affinity and electrochemical principles for accurate detection.
Our future goals are aimed at improving the long-term stability and operating requirements of sensors, so they can be integrated as low-cost personal health and safety monitoring solutions. Some of the research avenues we will be exploring are:
Contactless manipulation and separation of biological sample mixtures into distinct populations is a critical step in many bioanalytical and biomedical applications. Our aim is to design and optimize a label-free acoustofluidic method for the size-specific binning of exosomes, which are a group of lipid bilayer-enclosed biological nanoparticles with sizes ranging from 30 to 200 nm. Recently, our team has also developed a unique approach for design automation of acoustofluidic devices by integrating machine learning and multi-objective heuristic optimization approaches.
Our lab is developing microfluidic-assisted exosome capture and enrichment platforms based on the interactions of certain metal oxide nanomaterials with phosphate groups on the lipid bilayer of extracellular vesicles (such as exosomes) resulting in highly selective enrichment. We are also exploring machine-learning based methods to aid in material synthesis and performance.
Inflammation is the hallmark of any disease. Monitoring immune or inflammatory biomarkers using unobtrusive methods that require low sample and reagent volumes is paramount for clinical and diagnostic applications. Our research is focused on the development of bio-sensors for the detection of inflammatory biomarkers, such as cytokines, with high reliability and reproducibility.
Our future goals are aimed at developing innovative chips and wearables that can provide the end user with meaningful data on the presence and absence of a variety of biomarkers associated with disease for application in:
The aim of this research is to generate advanced encapsulation formulations for the oral delivery of small molecule drug compounds and bacteria for release in the gastrointestinal tract. We are investigating the use of enteric polymers for the controlled release of cargo into areas of ideal drug absorption and focused on the creation of formulations that maximize the bioavailability or bioactivity of the encapsulated material.
We are developing an electrochemical impedance measurement module that can analyze microcapsules in terms of their release time, quantity of loaded bacteria, and particle size amongst other factors. This research is part of our efforts to integrate data-driven or machine-learning based methods into on-chip microcapsule generation to automatically calculate encapsulation yield and efficiency during production.
Microneedles are minimally invasive devices that can have a range of applications in drug delivery. Our research is aimed at enhancing the functionality of microneedles for drug delivery and monitoring. Our objective is to develop methodologies and platforms that improve the efficacy of drug delivery while being minimally invasive to enable self-administration.
Our future goals are aimed at integrating microfluidic and nanotechnology methods to advance: