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Accelerating Multiscale Materials Modeling with Machine Learning

Modine, N.A.; Stephens, John A.; Swiler, Laura P.; Thompson, Aidan P.; Vogel, Dayton J.; Cangi, Attila C.; Feilder, Lenz F.; Rajamanickam, Sivasankaran R.

The focus of this project is to accelerate and transform the workflow of multiscale materials modeling by developing an integrated toolchain seamlessly combining DFT, SNAP, LAMMPS, (shown in Figure 1-1) and a machine-learning (ML) model that will more efficiently extract information from a smaller set of first-principles calculations. Our ML model enables us to accelerate first-principles data generation by interpolating existing high fidelity data, and extend the simulation scale by extrapolating high fidelity data (102 atoms) to the mesoscale (104 atoms). It encodes the underlying physics of atomic interactions on the microscopic scale by adapting a variety of ML techniques such as deep neural networks (DNNs), and graph neural networks (GNNs). We developed a new surrogate model for density functional theory using deep neural networks. The developed ML surrogate is demonstrated in a workflow to generate accurate band energies, total energies, and density of the 298K and 933K Aluminum systems. Furthermore, the models can be used to predict the quantities of interest for systems with more number of atoms than the training data set. We have demonstrated that the ML model can be used to compute the quantities of interest for systems with 100,000 Al atoms. When compared with 2000 Al system the new surrogate model is as accurate as DFT, but three orders of magnitude faster. We also explored optimal experimental design techniques to choose the training data and novel Graph Neural Networks to train on smaller data sets. These are promising methods that need to be explored in the future.

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TYPE SAND Report YEAR 2022
OSTIDOI

Prediction of Reactive Nitrous Acid Formation in Rare-Earth MOFs via ab initio Molecular Dynamics

Angewandte Chemie - International Edition

Vogel, Dayton J.; Rimsza, Jessica R.; Nenoff, T.M.

Reactive gas formation in pores of metal–organic frameworks (MOFs) is a known mechanism of framework destruction; understanding those mechanisms for future durability design is key to next generation adsorbents. Herein, an extensive set of ab initio molecular dynamics (AIMD) simulations are used for the first time to predict competitive adsorption of mixed acid gases (NO2 and H2O) and the in-pore reaction mechanisms for a series of rare earth (RE)-DOBDC MOFs. Spontaneous formation of nitrous acid (HONO) is identified as a result of deprotonation of the MOF organic linker, DOBDC. The unique DOBDC coordination to the metal clusters allows for proton transfer from the linker to the NO2 without the presence of H2O and may be a factor in DOBDC MOF durability. This is a previously unreported mechanisms of HONO formation in MOFs. With the presented methodology, prediction of future gas interactions in new nanoporous materials can be achieved.

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TYPE Journal Article YEAR 2021
ScopusOSTIDOI

Near-Zero Power MOF-Based Sensors for NO2 Detection

Advanced Functional Materials

Small, Leo J.; Henkelis, Susan E.; Rademacher, David R.; Schindelholz, Mara E.; Krumhansl, James L.; Vogel, Dayton J.; Nenoff, T.M.

Detection and capture of toxic nitrogen oxides (NOx) is important for emissions control of exhaust gases and general public health. The ability to directly electrically detect trace (0.5–5 ppm) NO2 by a metal–organic framework (MOF)-74-based sensor at relatively low temperatures (50 °C) is demonstrated via changes in electrical properties of M-MOF-74, M = Co, Mg, Ni. The magnitude of the change is ordered Ni > Co > Mg and explained by each variant's NO2 adsorption capacity and specific chemical interaction. Ni-MOF-74 provides the highest sensitivity to NO2; a 725× decrease in resistance at 5 ppm NO2 and detection limit <0.5 ppm, levels relevant for industry and public health. Furthermore, the Ni-MOF-74-based sensor is selective to NO2 over N2, SO2, and air. Linking this fundamental research with future technologies, the high impedance of MOF-74 enables applications requiring a near-zero power sensor or dosimeter, with the active material drawing <15 pW for a macroscale device 35 mm2 with 0.8 mg MOF-74. This represents a 104–106× decrease in power consumption compared to other MOF sensors and demonstrates the potential for MOFs as active components for long-lived, near-zero power chemical sensors in smart industrial systems and the internet of things.

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TYPE Journal Article YEAR 2020
ScopusOSTIDOI

Luminescent Properties of DOBDC Containing MOFs: The Role of Free Hydroxyls

ACS Applied Materials and Interfaces

Henkelis, Susan E.; Rademacher, David R.; Vogel, Dayton J.; Valdez, Nichole R.; Rodriguez, Mark A.; Rohwer, Lauren E.; Nenoff, T.M.

A novel metal-organic framework (MOF), Mn-DOBDC, has been synthesized in an effort to investigate the role of both the metal center and presence of free linker hydroxyls on the luminescent properties of DOBDC (2,5-dihydroxyterephthalic acid) containing MOFs. Co-MOF-74, RE-DOBDC (RE-Eu and Tb), and Mn-DOBDC have been synthesized and analyzed by powder X-ray diffraction (PXRD) and the fluorescent properties probed by UV-Vis spectroscopy and density functional theory (DFT). Mn-DOBDC has been synthesized by a new method involving a concurrent facile reflux synthesis and slow crystallization, resulting in yellow single crystals in monoclinic space group C2/c. Mn-DOBDC was further analyzed by single-crystal X-ray diffraction (SCXRD), scanning electron microscopy-energy-dispersive spectroscopy (SEM-EDS), and photoluminescent emission. Results indicate that the luminescent properties of the DOBDC linker are transferred to the three-dimensional structures of both the RE-DOBDC and Mn-DOBDC, which contain free hydroxyls on the linker. In Co-MOF-74 however, luminescence is quenched in the solid state due to binding of the phenolic hydroxyls within the MOF structure. Mn-DOBDC exhibits a ligand-based tunable emission that can be controlled in solution by the use of different solvents.

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TYPE Journal Article YEAR 2020
ScopusOSTIDOI

Tuned Hydrogen Bonding in Rare-Earth Metal-Organic Frameworks for Design of Optical and Electronic Properties: An Exemplar Study of Y-2,5-Dihydroxyterephthalic Acid

ACS Applied Materials and Interfaces

Vogel, Dayton J.; Nenoff, T.M.; Rimsza, Jessica R.

Organic linkers in metal-organic framework (MOF) materials exhibit differences in hydrogen bonding (H-bonding), which can alter the geometric, electronic, and optical properties of the MOF. Density functional theory (DFT) simulations were performed on a photoluminescent Y-2,5-dihydroxyterephthalic acid (DOBDC) MOF with H-bonding concentrations between 0 and 100%; the H-bonds were located on both bidentate-and monodentate-bound DOBDC linkers. At 0% H-bond concentration in the framework, the lattice parameters contracted, the density increased, and simulated X-ray diffraction patterns shifted. Comparison with published experimental data identified that Y-DOBDC MOF structures must have a degree of H-bond concentration. The concentration of H-bonds in the system shifted the calculated band gap energy from 2.25 eV at 100% to 3.00 eV at 0%. The band gap energies also indicate a distinction of H-bonds formed on bidentate-coordinated linkers compared to those on monodentate linkers. Additionally, when the calculated optical spectra are compared with experimental data, the ligand-to-ligand charge-transfer luminescence in Y-DOBDC MOFs is expected to result from an average of 20-40% H-bonding with at least 50% of the bidentate linkers containing H-bonding. Therefore, the type of H-bonding within the DOBDC linker determines the electronic structure and the optical absorption of the MOF framework structure. Tuning of the H-bonding in rare-earth MOFs provides an opportunity to control the specific optical and adsorption properties of the MOF framework on the basis of reactions between the linker and the environment.

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TYPE Journal Article YEAR 2020
ScopusOSTIDOI
Results 1–25 of 37
Results 1–25 of 37