Investigation of a Quantum Monte Carlo Protocol To Achieve High Accuracy and High-Throughput Materials Formation Energies

High-throughput calculations based on density functional theory (DFT) methods have been widely implemented in the scientific community. However, depending on both the properties of interest as well as particular chemical/structural phase space, accuracy even for correct trends remains a key challenge for DFT. In this work, we evaluate the use of quantum Monte Carlo (QMC) to calculate material formation energies in a high-throughput environment. We test the performance of automated QMC calculations on 21 compounds with high quality reference data from the Committee on Data for Science and Technology (CODATA) thermodynamic database. We compare our approach to different DFT methods as well as different pseudopotentials, showing that errors in QMC calculations can be progressively improved especially when correct pseudopotentials are used. We determine a set of accurate pseudopotentials in QMC via a systematic investigation of multiple available pseudopotential libraries. We show that using this simple automated recipe, QMC calculations can outperform DFT calculations over a wide set of materials. Out of 21 compounds tested, chemical accuracy has been obtained in formation energies of 11 structures using our QMC recipe, compared to none using DFT calculations.National Science Foundation (U.S.) (Grant DMR 1206242)National Science Foundation (U.S.) (Grant DMR 1352373)United States. Department of Energy (Award INCITE MAT307)United States. Department of Energy (Award INCITE MAT141)National Science Foundation (U.S.) (Grant XSEDE TG-DMR090027

Magnetism and Piezoelectricity in Stable Transition Metal Silicate Monolayers

Two-dimensional van der Waals (2D vdW) materials that display ferromagnetism and piezoelectricity have received increased attention. Despite numerous 2D materials have so far been reported as ferromagnetic, developing an air stable and transferable vdW material that is multiferroic has been challenging. To address this problem, we report our work on layered transition metal silicates that are derivatives of kaolinites and lizardites with transition metal substituting on Al$^{3+}$ and Mg$^{2+}$ sites using ab-initio calculations. Using Density Functional Theory (DFT), we show that these compounds are stable under varying O$_2$ partial pressure and can be synthesized using a surface assisted method. We show that these materials have finite out-of-plane piezoelectric response thanks to the lack of inversion symmetry and also they can be tailored to be ferrimagnetic with a non-zero net moment

QMCPACK: Advances in the development, efficiency, and application of auxiliary field and real-space variational and diffusion Quantum Monte Carlo

We review recent advances in the capabilities of the open source ab initio Quantum Monte Carlo (QMC) package QMCPACK and the workflow tool Nexus used for greater efficiency and reproducibility. The auxiliary field QMC (AFQMC) implementation has been greatly expanded to include k-point symmetries, tensor-hypercontraction, and accelerated graphical processing unit (GPU) support. These scaling and memory reductions greatly increase the number of orbitals that can practically be included in AFQMC calculations, increasing accuracy. Advances in real space methods include techniques for accurate computation of band gaps and for systematically improving the nodal surface of ground state wavefunctions. Results of these calculations can be used to validate application of more approximate electronic structure methods including GW and density functional based techniques. To provide an improved foundation for these calculations we utilize a new set of correlation-consistent effective core potentials (pseudopotentials) that are more accurate than previous sets; these can also be applied in quantum-chemical and other many-body applications, not only QMC. These advances increase the efficiency, accuracy, and range of properties that can be studied in both molecules and materials with QMC and QMCPACK

Low-energy electronic interactions in ferrimagnetic Sr2CrReO6 thin films

We reveal in this study the fundamental low-energy landscape in the ferrimagnetic Sr2CrReO6 double perovskite and describe the underlying mechanisms responsible for the three low-energy excitations below 1.4 eV. Based on resonant inelastic x-ray scattering and magnetic dynamics calculations, and experiments collected from both Sr2CrReO6 powders and epitaxially strained thin films, we reveal a strong competition between spin-orbit coupling, Hund's coupling, and the strain-induced tetragonal crystal field. We also demonstrate that a spin-flip process is at the origin of the lowest excitation at 200 meV, and we bring insights into the predicted presence of orbital ordering in this material. We study the nature of the magnons through a combination of ab initio and spin-wave theory calculations, and show that two nondegenerate magnon bands exist and are dominated either by rhenium or chromium spins. The rhenium band is found to be flat at about 200 meV ($\pm$25 meV) through X-L-W-U high-symmetry points and is dispersive toward $\Gamma$Comment: 6 figure

Large Scale Benchmark of Materials Design Methods

Lack of rigorous reproducibility and validation are major hurdles for scientific development across many fields. Materials science in particular encompasses a variety of experimental and theoretical approaches that require careful benchmarking. Leaderboard efforts have been developed previously to mitigate these issues. However, a comprehensive comparison and benchmarking on an integrated platform with multiple data modalities with both perfect and defect materials data is still lacking. This work introduces JARVIS-Leaderboard, an open-source and community-driven platform that facilitates benchmarking and enhances reproducibility. The platform allows users to set up benchmarks with custom tasks and enables contributions in the form of dataset, code, and meta-data submissions. We cover the following materials design categories: Artificial Intelligence (AI), Electronic Structure (ES), Force-fields (FF), Quantum Computation (QC) and Experiments (EXP). For AI, we cover several types of input data, including atomic structures, atomistic images, spectra, and text. For ES, we consider multiple ES approaches, software packages, pseudopotentials, materials, and properties, comparing results to experiment. For FF, we compare multiple approaches for material property predictions. For QC, we benchmark Hamiltonian simulations using various quantum algorithms and circuits. Finally, for experiments, we use the inter-laboratory approach to establish benchmarks. There are 1281 contributions to 274 benchmarks using 152 methods with more than 8 million data-points, and the leaderboard is continuously expanding. The JARVIS-Leaderboard is available at the website: https://pages.nist.gov/jarvis_leaderboar

Quantum Monte Carlo for accurate energies and materials design

Thesis: Ph. D., Massachusetts Institute of Technology, Department of Materials Science and Engineering, 2017.This electronic version was submitted by the student author. The certified thesis is available in the Institute Archives and Special Collections.Cataloged from student-submitted PDF version of thesis.Includes bibliographical references (pages 107-119).Quantum Monte Carlo (QMC) is an electronic structure calculation method that is capable of calculating incredibly accurate solutions of Schrödinger equation of quantum mechanics for real systems. However, QMC is computationally very expensive compared to density functional theory (DFT) method, such that its application has been limited. In addition, QMC is a stochastic (Monte Carlo) method, meaning that the way calculations are initialized, where a lot of user effort is invested, is crucial for getting accurate results. Computational expense can be justified if the data would be used repeatedly, however the lack of automatization is a severe problem, if QMC would be used in materials discovery. In Chapter 4, we show our automated calculation strategy for formation energy of periodic materials using QMC. We show that our method performs almost by an order of a magnitude more accurate, compared to high throughput DFT strategies having empirical corrections. Nevertheless, it would be beneficial to understand when DFT methods fail such that QMC is used only when the computational expense is justified. A single DFT functional rarely performs uniformly accurate accross different materials and properties due to nonsystematic errors. In Chapter 5, we investigate one specific example: dihydroazulene ring opening photoisomerization, where different substitutions on the ring opening moiety introduce isomerization enthalpy errors up to 0.8 eV. We show that GGA exchange is the main reason for failure in B3LYP, PBE and TPSSH functionals. However, performing a test, similar to the Chapter 5, on each chemical reaction can be an intimidating task where the benchmark set must be carefully devised by an expert in the field. In the absence of experiments, the DFT functional choice is still often done in heuristic way. In Chapter 6, we demonstrate how we can systematically analyze benchmark sets using machine learning to provide highly accurate reaction energies and provide DFT functional selection for different classes of materials when high accuracy calculations or experiments are not available. Our approach provides probabilities of getting accurate results for a reaction that is investigated using each DFT functional.by Kayahan Saritas.Ph. D

Accurate Isomerization Enthalpy and Investigation of the Errors in Density Functional Theory for Dihydroazulene/Vinylheptafulvene Photochromism Using Diffusion Monte Carlo

We investigate the isomerization enthalpy of the dihydroazulene/vinylheptafulvene (DHA/VHF) molecular photoswitch system derivatives using electronic structure calculation methods including density functional theory (DFT), quantum Monte Carlo (QMC), and coupled cluster (CCSD(T)). Recent efforts have focused on tuning the isomerization enthalpy of the photoswitch for solar thermal energy storage applications using substitutional functional groups on its five- and seven-membered carbon rings, predominantly using DFT for the energy predictions. However, using the higher accuracy QMC and CCSD(T) methods, we show that in many cases DFT incorrectly predicts the isomerization enthalpy, and the errors depend on the functional groups substituted and the choice of the DFT functional. Isomerization of the DHA to VHF molecule is an electrocyclic ring-opening reaction on the five-membered ring of the DHA isomer. We find that the DFT errors are correlated to the electrocyclic ring-opening reactions of cyclobutene and cyclo-1,3-hexadiene, such that the DFT error changes monotonically with the size of the carbon ring, although QMC and CCSD(T) results are in a good agreement irrespective of the ring size. Using the QMC and CCSD(T) isomerization enthalpies, we predict gravimetric energy densities of the DHA derivatives for solar thermal storage applications. Our results show that suitable substitutions on DHA can yield gravimetric storage densities as large as 732 kJ/kg. ©2017 American Chemical Society

Accurate Isomerization Enthalpy and Investigation of the Errors in Density Functional Theory for Dihydroazulene/Vinylheptafulvene Photochromism Using Diffusion Monte Carlo

We investigate the isomerization enthalpy of the dihydroazulene/vinylheptafulvene (DHA/VHF) molecular photoswitch system derivatives using electronic structure calculation methods including density functional theory (DFT), quantum Monte Carlo (QMC), and coupled cluster (CCSD­(T)). Recent efforts have focused on tuning the isomerization enthalpy of the photoswitch for solar thermal energy storage applications using substitutional functional groups on its five- and seven-membered carbon rings, predominantly using DFT for the energy predictions. However, using the higher accuracy QMC and CCSD­(T) methods, we show that in many cases DFT incorrectly predicts the isomerization enthalpy, and the errors depend on the functional groups substituted and the choice of the DFT functional. Isomerization of the DHA to VHF molecule is an electrocyclic ring-opening reaction on the five-membered ring of the DHA isomer. We find that the DFT errors are correlated to the electrocyclic ring-opening reactions of cyclobutene and cyclo-1,3-hexadiene, such that the DFT error changes monotonically with the size of the carbon ring, although QMC and CCSD­(T) results are in a good agreement irrespective of the ring size. Using the QMC and CCSD­(T) isomerization enthalpies, we predict gravimetric energy densities of the DHA derivatives for solar thermal storage applications. Our results show that suitable substitutions on DHA can yield gravimetric storage densities as large as 732 kJ/kg