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Our research interests lie in the energy field with the aim of discovering new materials to achieve more energy-efficient and cost-effective energy-related processes including separations, energy storage, etc. Reducing energy consumption, cost, and 2 emissions of many energy-related processes is currently one of the most prominent challenges. Recently, porous materials including zeolites, zeolitic imidazolate frameworks (ZIFs), metal-organic frameworks (MOFs), graphene-based materials, etc. have become of great interest to the scientific community for their potential in energy applications. Can we operate these processes with better energy efficiencies and at lower costs?

To achieve this, discovering new materials is essential. The total number of possible material candidates, however, could be hypothetically infinite. For instance, MOFs are highly tunable; one can design an optimal material by having the right combination of chemical compositions and structural topologies. 

Our group strives to use and develop computational approaches to accelerate the discovery of new materials to achieve more energy-efficient and cost-effective energy-related processes (e.g., separations, energy storage, and catalysis). Computational approaches allow us to efficiently and accurately study a large number of materials to identify the most promising ones, as well as provide a better atomic-level understanding of material properties, thereby accelerating the development of the new materials. In addition, to facilitate materials discovery, we aim to collaborate with researchers from different fields including materials synthesis/characterization, process engineering, quantum chemistry, etc., to synergistically push materials development forward. 

 We have three main research directions:

A.   Large-scale computational screenings: Use molecular simulations to study a large number of materials to identify promising ones.

B.   Atomistic understandings of material properties: Use computational approaches as powerful tools to achieve better understandings of material properties at an atomic level.

C.   Methodology development: Develop new methods and Integrate multi-scale computational techniques to achieve more accurate simulation predictions and more efficient computation screenings. 

A. Computational screenings

Nanoporous materials (e.g., zeolites, metal-organic frameworks, etc.) can potentially provide a more energy-efficient way for various energy-related applications such as gas separation and storage. The total number of possible materials can be achieved by changing structural topologies and chemical compositions, however, is tremendous. Fully characterizing all possible materials with experimental methods is therefore less feasible. In this respect, molecular simulations can play an important role in the discovery of new materials. By studying a large number of materials, computational studies can identify promising ones and obtain insights into structure-property relationships, thus largely facilitating the search for new materials.

One of the Dr. Lin’ past work studied >100,000 zeolites structures as adsorbents for carbon capture. Figure 1a (below) shows that this computational study identified many promising zeolite structures that can reduce the energy required for carbon capture compared to the current state-of-the-art amine technology (the green line shown in the left figure below represents the performance of the MEA amine technology). Figure 1b (below) illustrates the structural topologies of some promising zeolites.

There are many applications (see Figure 1c (below)) where novel materials may have a crucial role to play. Our research group therefore strives to extensively explore the potential of nanoporous materials using molecular simulation techniques in these applications.

Figure 1 ((a) and (b) are adopted from a Dr. Lin’s publication: Lin, L.-C. et al, Nature Material, 11, 633-641, 2012)

Some selected publications related to this topic are listed below:

1. Lin, L.-C., Berger, A.H., Martin, R.L., Kim, J. Swisher, J.A., Jariwala, K., Rycroft, C.H., Bhown, A.S., Deem, M.W., Haranczyk, M. & Smit, B. “In Silico Screening of Carbon-Capture Materials,” Nature Materials, 11, 633-641, 2012. 

2. *Kim, J., *Lin, L.-C., Swisher, J.A., Haranczyk, M & Smit, B. Prediction Large CO2 Adsorption in Aluminosilicate Zeolites for Postcombustion Carbon Dioxide Capture, J. Am. Chem. Soc., 134(46), 18940-18943, 2012. 

3. Kim, J., Maiti, A., Lin, L.-C., Stolaroff, J.K., Smit, B. & Aines, R.D. New Materials for Methane Capture from Dilute and Medium-concentration Sources,” Nature Communications, 4, 1694, 2013. 

4. Kim, J., Abouelnasr, M., Lin, L.-C. & Smit, B. Large-scale Screening of Zeolite Structures for CO2 Membrane Separation, J. Am. Chem.  Soc., 135 (20), 7545-7552, 2013. 


B. Atomistic understandings 

A detailed understanding of materials’ properties is of utmost importance to the rational design of better materials. Computational approaches (e.g., molecular simulations and quantum mechanical calculations) can be used as a powerful characterization tool to study materials at an atomic level. Our group strives to apply state-of-the-art computational techniques and work with experimentalists to help understand materials’ properties.

Some selected publications related to this topic are listed below:

1. Lin, L.-C., Kim, J., Kong, X., Scott, E., McDonald, T.M., Long, J.R., Reimer, J.A. & Smit, B. Understanding CO2 Dynamics in Metal-Organic Frameworks with Open Metal Sites, Angew. Chem. Int. Ed. 52, 4410-4413, 2013. ***Selected as the inside cover of the issue

2. Planas, N., Dzubak, A.L., Poloni, R., Lin, L.-C., McManus, A., McDonald, T.M., Neaton, J.B., Long, J.R., Smit, B. & Gagliardi, L. The Mechanism of Carbon Dioxide Adsorption in an Alkylamine-Functionalized Metal-Organic Framework, J. Am. Chem. Soc. 135, 7402-7405, 2013.

3. Janda, A.L., Vlaisavljevich, B., Lin, L.-C., Smit, B., & Bell, A.T., Effects of zeolite structural confinement on adsorption thermodynamics and reaction kinetics for monomolecular cracking and dehydrogenation of n-butane, J. Am. Chem. Soc. In press, 2016.

C. Methodology development

The accuracy of predictions made by molecular simulations is crucial for the computational identification of promising materials, which is largely governed by the reliability of adopted force field potentials. However, for many cases, commonly used force fields cannot yield accurate predictions of properties. For instance, the interactions of CO2 with open-metal sites MOFs, M-MOF-74s, are poorly described by universal force fields (UFF), leading to a highly under-estimated adsorption uptake at post-combustion flue gas conditions (see the right figure below). Herein, an efficient, systematic, and transferable methodology is required to generate accurate force fields. Moreover, to establish a predictive molecular simulation approach, it is essential to parameterize potential parameters from ab initio quantum chemical calculations (e.g., density functional theory (DFT)). 

Recently, we have proposed and developed a new methodology to parameterize force fields of CO2, N2, and H2O adsorbing in nanoporous materials (see Figure 2a (below)), and the obtained force fields can well reproduce experimentally measured data (see Figure 2b (below)). To use this methodology in screening studies, several key components, however, are still missing. Specifically, it is important to extend the methodology to be (1) applicable for all types of porous materials, (2) applicable for many other guest molecules, and (3) automatic.

Figure 2 (This figure is adopted from a Dr. Lin’s publication: Lin, L.-C. et al. JCTC, 10, 1477-1488, 2014)

Some selected publications related to this topic are listed below:

1. *Dzubak, A.L., *Lin, L.C., Kim, J., Swisher, J.A., Poloni, R., Maximoff, S.N., Smit, B. & Gagliardi, L.  Ab Initio Carbon Capture in Open-site Metal-Organic Frameworks, Nature Chemistry, 4, 810-816, 2012.

2. Lin, L.-C., Lee, K, Gagliardi, L., Neaton, J.B. & Smit, B.  Force Field Development from Electronic Structure Calculations with Periodic Boundary Conditions: Applications to Gaseous Adsorption and Transport in Metal-Organic Frameworks. J. Chem. Theory Comput., 10, 1477-1488, 2014.