Filtering by
- All Subjects: Density Functional Theory
- Creators: Muhich, Christopher
- Creators: Adams, James
- Creators: Krause, Stephen
Graph neural networks (GNN) offer a potential method of bypassing the Kohn-Sham equations in density functional theory (DFT) calculations by learning both the Hohenberg-Kohn (HK) mapping of electron density to energy, allowing for calculations of much larger atomic systems and time scales and enabling large-scale MD simulations with DFT-level accuracy. In this work, we investigate the feasibility of GNNs to learn the HK map from the external potential approximated as Gaussians to the electron density 𝑛(𝑟), and the mapping from 𝑛(𝑟) to the energy density 𝑒(𝑟) using Pytorch Geometric. We develop a graph representation for densities on radial grid points and determine that a k-nearest neighbor algorithm for determining node connections is an effective approach compared to a distance cutoff model, having an average graph size of 6.31 MB and 32.0 MB for datasets with 𝑘 = 10 and 𝑘 = 50 respectively. Furthermore, we develop two GNNs in Pytorch Geometric, and demonstrate a decrease in training losses for a 𝑛(𝑟) to 𝑒(𝑟) of 8.52 · 10^14 and 3.10 · 10^14 for 𝑘 = 10 and 𝑘 = 20 datasets respectively, suggesting the model could be further trained and optimized to learn the electron density to energy functional.
Using DFT calculations and GAMESS computational software, porphine and its derivatives were analyzed for unique sites to accept the adsorbates As(III), As(V) and P(V) in order to compare resulting adsorption energies and determine if any of these molecules prefer arsenic oxyanions over phosphate. Pure porphine preferred As(III) over P(V) with a resulting adsorption energy of -0.7974 eV. Of the functionalized porphyrins tested, carboxyl porphyrin preferred As(V) over P(V) with a total adsorption energy of -0.7345 eV. Ethyl, methyl, chlorine and amino porphyrin all preferred As(III), with energies of -0.7934, -0.8239, -0.7602, and -0.8508 eV, respectively. Of the metalated porphyrins tested, copper and vanadium porphyrin preferred As(V) over P(V) with adsorption energies of -0.7645 and -2.0915 eV. Chromium, iron and magnesium porphyrin all preferred As(III) over P(V) with energies of -0.5993, -1.4539, and - 1.0790 eV, respectively.
A proof of principle demonstration of a resonator that can switch from a high-Q “on state” to a low-Q “off state” at reduced temperatures is demonstrated in (Al1-xFex)2O3 and La(Al1-xFex)O3. The Fe3+ ions are in a high spin state (S=5/2) and undergo electron paramagnetic resonance absorption transitions that increase the microwave loss of the system. Transitions occur between mJ states with a corresponding change in the angular momentum, J, by ±ħ (i.e., ΔmJ=±1) at small magnetic fields. The paramagnetic ions also have an influence on the dielectric and magnetic properties, which I explore in these systems along with another low loss complex perovskite material, Ca[(Al1-xFex)1/2Nb1/2]O3. I describe what constitutes an optimal microwave loss switchable material induced from EPR transitions and the mechanisms associated with the key properties.
As a first step to modeling the properties of high-performance microwave host lattices and ultimately their performance at microwave frequencies, a first-principles approach is used to determine the structural phase stability of various complex perovskites with a range of tolerance factors at 0 K and finite temperatures. By understanding the correct structural phases of these complex perovskites, the temperature coefficient of resonant frequency can be better predicted.
A strong understanding of these parameters is expected to open the possibility to produce new types of high-performance switchable filters, time domain MIMO’s, multiplexers, and demultiplexers.