Predicting the Electronic Structure of Matter on Ultra-Large Scales
The long-standing problem of predicting the electronic structure of matter on ultra-large scales (beyond 100,000 atoms) is solved with machine learning.
The long-standing problem of predicting the electronic structure of matter on ultra-large scales (beyond 100,000 atoms) is solved with machine learning.
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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Angewandte Chemie - International Edition
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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Advanced Functional Materials
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.
ACS Applied Materials and Interfaces
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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ACS Applied Materials and Interfaces
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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ACS Applied Materials and Interfaces
Acid gases (e.g., NOx and SOx), commonly found in complex chemical and petrochemical streams, require material development for their selective adsorption and removal. Here, we report the NOx adsorption properties in a family of rare earth (RE) metal-organic frameworks (MOFs) materials. Fundamental understanding of the structure-property relationship of NOx adsorption in the RE-DOBDC materials platform was sought via a combined experimental and molecular modeling study. No structural change was noted following humid NOx exposure. Density functional theory (DFT) simulations indicated that H2O has a stronger affinity to bind with the metal center than NO2, while NO2 preferentially binds with the DOBDC ligands. Further modeling results indicate no change in binding energy across the RE elements investigated. Also, stabilization of the NO2 and H2O molecules following adsorption was noted, predicted to be due to hydrogen bonding between the framework ligands and the molecules and nanoconfinement within the MOF structure. This interaction also caused distinct changes in emission spectra, identified experimentally. Calculations indicated that this is due to the adsorption of NO2 molecules onto the DOBDC ligand altering the electronic transitions and the resulting photoluminescent properties, a feature that has potential applications in future sensing technologies.
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Physical Chemistry Chemical Physics
Here, we apply density functional theory (DFT) to investigate rare-earth metal organic frameworks (RE-MOFs), RE12(μ3-OH)16(C8O6H4)8(C8O6H5)4 (RE = Y, Eu, Tb, Yb), and characterize the level of theory needed to accurately predict structural and electronic properties in MOF materials with 4f-electrons. A two-step calculation approach of geometry optimization with spin-restricted DFT and large core potential (LCPs), and detailed electronic structures with spin-unrestricted DFT with a full valence potential + Hubbard U correction is investigated. Spin-restricted DFT with LCPs resulted in good agreement between experimental lattice parameters and optimized geometries, while a full valence potential is necessary for accurate representation of the electronic structure. The electronic structure of Eu-DOBDC MOF indicated a strong dependence on the treatment of highly localized 4f-electrons and spin polarization, as well as variation within a range of Hubbard corrections (U = 1-9 eV). For Hubbard corrected spin-unrestricted calculations, a U value of 1-4 eV maintains the non-metallic character of the band gap with slight deviations in f-orbital energetics. When compared with experimentally reported results, the importance of the full valence calculation and the Hubbard correction in correctly predicting the electronic structure is highlighted.