The Banerjee Group
Areas of Interest:
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Theoretical Chemistry
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Artificial Intelligence / Machine Learning
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Catalysis
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Electrochemistry
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Quantum Materials
Expanding the Design Space for
Catalysis and Quantum Materials
Advancing Physical Chemistry Principles
and Chemical Theory-Informed AI
Research Directions:
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Fundamental limitations imposed by chemical and physical principles hinder the exploration of new materials and molecular chemistry. The recent growth in artificial intelligence (AI) is particularly well-suited to addressing this grand challenge. Toward this end, research in the Banerjee Group seeks to answer:
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What unexplored design spaces can help overcome the known fundamental limitations in chemistry?
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What new theories are required to enable these discoveries, and how can AI facilitate this process?
Additionally, it is possible to envision overcoming the limitations of a single chemical system by designing complex multicomponent systems in which each component works synergistically to compensate for the limitations of individual systems. The group focuses on:
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Developing predictive theories to design multicomponent chemical systems.
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Understanding how these multicomponent systems respond to changing conditions, such as variations in electrode potential.
Application:
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​The group applies its theoretical methods to catalysis, electrochemistry, recycling technologies, and novel quantum processes, with primary focus areas including (a) electrification of the chemical industry, (b) sustainable recycling, (c) photovoltaics, and (d) discovery of quantum materials. To address challenges in these domains, the group develops analytical theory, mathematical representations tailored for machine learning (ML) algorithms, and ML potentials (MLPs). Leveraging the power of AI/ML, we aim to discover new materials with targeted properties and model complex, multivariable chemical processes that are otherwise difficult to simulate.​
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Overall, the group aims to develop methods for simulating emergent processes across scales. As a fun analogy, the video below shows how winds create dynamic ripples – much like how surface fluctuations can influence material properties.
