Research

| Self-driving AI for Computational Chemistry Research

  We concentrate on automatically collecting text/image/video data and feeding this to the AI model to automatically conduct research.  We leverage various type of large language models to facilitate this process and work on fine-tuning the existing models for optimal performance. Moreover, we use these data to facilitate identifying best materials for experimental synthesis and tackle properties such as water/thermal stabilities that cannot be readily obtained from conventional molecular simulations.  

| Inverse Design of Nanomaterials

  We concentrate on constructing a user-desired inverse design model where properties are fed as inputs and the optimal materials are outputted.  Leveraging a large materials space in materials such as metal-organic frameworks, zeolites, perovskites, and polymers, we are developing various molecular simulations techniques as well as machine learning models to facilitate finding the ideal materials for the ideal process.

| Designing Multi-dimensional Composite Materials

  Many of the optimal materials these days are comprised of two different types of materials.  We fully leverage our techniques designed from our research lab to construct various different composite materials (e.g. MOF@MOF, MOF and polymers, MOF@COF) to optimize synergetic selections from a vast library of component materials.  Moreover, we study in-depth the mechanisms behind the interactions between the components to discover the source behind the synergetic properties.

| Energy Storage and CO2 Reduction/Transformation

  We investigate various different solutions to the energy and environmental related applications with focus on gas separations, storage, and CO2 reduction.  Many of the current solutions involve large-scale screening procedure, constructing new database of materials, as well as identifying/concentrating on few materials that show exceptional properties.  This type of research can facilitate collaboration between our group and our fellow experimental collaborators to accelerate novel materials synthesis and development.