Amirreza Ataei, currently a PhD student at Institut Quantique in the Physics Department of Université de Sherbrooke with Louis Taillefer, has been working on transport measurement of quantum materials and also the miniaturization of thermoelectric and electric measurements in parallel and under pressure since he was a master’s student at the same institution. He wanted to explore many other materials with his setup and even develop the technique further to have a high-throughput capacity, but to conduct original research and perform more measurements, neither Amir nor the entire global community of condensed matter physics had access to many different materials with varied dopings or stoichiometries. He noticed a systematic problem: the synthesis of materials takes days or even weeks for each material, and a systematic measurement was usually lacking due to experimental challenges and limited access to precision measurement facilities. This bottleneck in his research inspired him to conceive the idea of a “network of microfurnaces” for the synthesis of many materials in parallel and integrate it with a “network of microanalyzers,” the proof of concept for which was achieved by his very own research.

To launch his startup, Amir turned to ACET, l’accélérateur d’entreprises technologiques (the accelerator of technology companies in Sherbrooke), which supported him in developing the business aspects of his company by addressing the question of what kind of value he could create. This support allowed him to protect his idea and also to have the opportunity to use the financial vehicle of SAFE (Simple Agreement for Future Equity). Financially, Amir received the Mitacs Accelerate Entrepreneur scholarship to start his project in addition to being able to rely on the support of Louis Taillefer and Institut Quantique for the use of laboratories for technological developments and to also dedicate time alongside his studies to build the company and develop collaborations while he still had a safety margin. Amir says, “It’s critical to have a safety margin against business competition and investor pressure when starting a company. I was also lucky to be able to balance my PhD and startup at the end of the pandemic, which allowed me to work in the lab at night or participate in remote business seminars to acquire new skills. This was an opportunity to hone my vision for an R&D-intensive startup with a viable business strategy.” Chemia Discovery Inc. was officially founded in October 2021.

Chemia is a startup that is developing high-throughput technologies for R&D of advanced materials. Here, we discuss the developments of one of their technologies, which is a miniaturized furnace for the synthesis of complex materials. Two furnace concepts have already been developed, each differing in terms of development and maintenance costs, as well as operational constraints: one system uses the Joule effect on a graphite plate containing several holes (each hole acting as a furnace), inspired by microtiter plates for biological research, and the other with a magnetic induction system that is explained in detail here. The latter was primarily developed by eight undergraduate students over 20 months as part of a final-year undergraduate project, defined and sponsored by Chemia at Université de Sherbrooke.

The first prototype of the induction furnace has undergone initial research that perfected the induction coil around a tungsten cylinder, which serves as the crucible. The furnace was equipped with a microcontroller for maintaining very precise temperature, and a dielectric liquid system for cooling the coil outside the furnace. The team then improved the temperature stability. The first prototype reached a stable temperature of 1000°C in several seconds within a sample space of approximately 10 mm³. The ultimate goal is to maintain a stable temperature for six minutes in a network of 10 microfurnaces using in-house-designed power supplies. For the network of microanalyzers, it is planned to measure at least six physicochemical properties, including transport, magnetization, and CO2 absorption either in parallel or consecutively with a short time interval during a single temperature sweep from the room temperature down to less than –200 °C in less than two hours. All six experiments will be systematically performed on each sample and on 10 samples in one experiment cycle. The advantage of integrating microfurnace and microanalyzer platforms is that one can carry out systematic or targeted experiments to elucidate correlations between various physical and chemical properties and identify the most effective stoichiometric tuning parameters.

In addition to the experimental high-throughput methodology, Chemia also employs its own ‘virtual lab’ based on cloud computing. Computational methods such as Density Functional Theory (DFT) are utilized to obtain approximate properties of materials, even if their synthesis or existence is not known a priori. For instance, the figure of merit for potential thermoelectric materials can be computed to identify leads and guide experimental research. Moreover, Grand Canonical Monte Carlo simulations provide insights into the interactions between gases and porous materials, which are especially relevant for discovering materials capable of selectively capturing carbon dioxide, an ongoing project at Chemia.

Chemia’s high-throughput computational platform was designed and implemented by Raphaël Robidas, a PhD student in computational chemistry at Université de Sherbrooke, the director of computational discovery at Chemia, and one of its shareholders. By leveraging cloud computing and extensive automation, computational research can instantly be scaled up to generate enormous volumes of data with minimal human effort. This approach is complementary to high-throughput syntheses and measurements.

As Chemia accumulates more experimental data and fills gaps in existing material databases by generating data with material-informed AI models (another Mitacs project supported by Chemia during summer 2024 with the participation of IVADO and McGill), it will be possible to further improve its research efficiency using various forms of data science and machine learning. One avenue that Chemia is exploring this summer is to use machine learning to leverage electronic band structures in order to predict properties of interest, thus bypassing computationally expensive calculations. Generative artificial intelligence also shows great promise in materials science, as demonstrated by Google Deepmind. This avenue is also on Chemia’s roadmap, despite the greater development challenges associated with it. However, the idea is to develop a self-reinforcing cycle that links or correlates AI-driven predictions with experimental and first-principles-based computational validations. This creates a virtuous feedback loop that can, in principle, continuously refine the parameters of AI models, improving their predictive accuracy for the physical properties of existing materials as well as new materials with novel structures. The company has started to carry out pilot projects which enables it to make suggestions for the range of unknown physical properties of any material that is available on Materials Project at the moment. If you’d like to explore the full range of innovative materials that could impact your research, covering nearly all existing inorganic materials, feel free to reach out to them. They are keen to test their AI models for material suggestions on research-worthy problems constrained by material properties, before they start the large commercialization phase.

It is also noteworthy that the cost of each experiment remains constant, regardless of the material’s complexity (i.e., the number and types of atoms in one unit cell), while the computational costs increase exponentially with material complexity. Nevertheless, the number of new materials and possible experiments is boundless. Thus, it is crucial to develop a synergistic approach between experimental and computational methods to enable a viable and effective material discovery process.

The three permanent members at Chemia are Amirreza Ataei, the CEO; Raphaël Robidas, the director of computational discovery; and Jean Ombeni, the product developer associate. Chemia has applied for and supported over 12 Mitacs internship units for seven interns from various universities across Québec, in addition to sponsoring an undergraduate project. They are in the process of forming multidisciplinary collaborations to further develop their technologies and demonstrate the use cases of novel materials in applications such as more energy-efficient sensing and gas absorption. This summer, Chemia has welcomed three interns from McGill, H.E.C., and Université de Sherbrooke to work on projects related to material simulations, market assessment, and robotics.

On the experimental side, their first proof of concept works for the synthesis and characterization of one sample. Some of the next steps include improving the quality of synthesized samples, implementing necessary automation, and a cost-efficient scale up of the experimental platform. On the computational side, two near-term milestones are increasing the precision and efficiency of computations and integrating with the experimental platform. Chemia is currently seeking collaborators, funders, and new partnerships with expertise and interest in artificial intelligence, physics, chemistry, and engineering.

Chemia plans for the initial phase of its materials R&D program with a particular focus on materials for clean energy; CO2 capture, thermoelectric materials, and materials with a high specific heat. Eventually, they aim to explore more complex materials in which electronic interactions are significant, such as quantum materials, materials that perform at the possible physical limits but are the most elusive.

Chemia is actively seeking to extend its collaborations with other universities across Québec, and to discuss various possibilities for short- and long-term collaborations with highly motivated and highly skilled professionals who are interested in supporting their mission, which is to accelerate clean energy technologies through accelerated R&D of advanced materials. If you are interested in knowing more or exploring the intersection of your interests, do not hesitate to get in touch with them and contact them at: Amirreza.Ataei@USherbrooke.ca, or info@ChemiaDiscovery.com, and Raphael.Robidas@ChemiaDiscovery.com.