39 Works

Solute transport database in Mg using ab initio and exact diffusion theory

Ravi Agarwal & Dallas R. Trinkle
This dataset demonstrate the improved solute transport in hcp Mg through exact diffusion theory:Green function approach. We report the database of 61 solutes consisting of solute diffusivity and solute drag ratio. We also report the results from previously used approximate models of diffusion namely 8-frequency and 13-frequency models. The parameters needed for the diffusion models i.e. binding energy, migration barrier and attempt frequency are obtained through density functional theory calculations

Dataset for A Blocked Linear Method for Optimizing Large Parameter Sets in Variational Monte Carlo

Luning Zhao & Eric Neuscamman
We present a modification to variational Monte Carlo’s linear method optimization scheme that addresses a critical memory bottleneck while maintaining compatibility with both the traditional ground state variational principle and our recently-introduced variational principle for excited states. For wave function ansatzes with tens of thou- sands of variables, our modification reduces the required memory per parallel process from tens of gigabytes to hundreds of megabytes, making the methodology a much bet- ter fit for modern...

Grain Structure, Grain-averaged Lattice Strains, and Macro-scale Strain Data for Superelastic Nickel-Titanium Shape Memory Alloy Polycrystal Loaded in Tension

Harshad M. Paranjape, Partha P. Paul, Hemant Sharma, Peter Kenesei, Jun-Sang Park, T.W. Duerig, L. Catherine Brinson & Aaron P. Stebner
A cylindrical dog bone specimen from NiTi shape memory alloy is loaded in tension at room temperature for eleven cycles. Maximum stress in each cycle is approximately 220 MPa. The experiment is performed in-situ at Sector 1, beam line 1ID-E of Advanced Photon Source, Argonne National Laboratory. Using far-field high-energy diffraction microscopy technique, grain centroids, grain-averaged lattice strain tensor, grain volume, and grain-averaged crystal orientation are obtained at the start of the first cycle and...

Characterizing the Unifying Thread in High Temperature Superconductors Using Realistic Simulations

Awadhesh Narayan, Brian Busemeyer & Lucas K. Wagner
This is a dataset collecting high accuracy quantum Monte Carlo (QMC) results for pnictide and cuprate compounds, some of which are high temperature superconductors. Our trial wavefunction consists of a Slater determinant augmented by a Jastrow factor. We construct the Slater determinant using orbitals from density functional theory (DFT). Our DFT calculations are done using the CRYSTAL package, with the PBE0 functional. We use Burkatzki-Filippi-Dolg pseudopotentials to replace the core electrons. We then use the...

CSLM-4 48h Coarsened PbSn (30 volume percent dendrites)

Thomas Cool & Peter Voorhees

CSLM-4 13h 30min Coarsened PbSn (30 volume percent dendrites)

Thomas Cool & Peter Voorhees

Dataset for Delayed Slater determinant update algorithms for high efficiency quantum Monte Carlo

Tyler McDaniel, Ed F. D'Azevedo, Ying Wai Li, Kwai Wong & Paul R. C. Kent
This dataset contains raw data, analysis/graphing scripts, and additional figures for "Delayed Slater determinant update algorithms for high efficiency quantum Monte Carlo" by T. McDaniel, E. F. D’Azevedo, Y. W. Li, K. Wong, and P. R. C. Kent.

Chemical vapor deposition of monolayer MoS2 directly on ultrathin Al2O3 for low-power electronics

Hadallia Bergeron, Vinod K. Sangwan, Julian J. McMorrow, Gavin P. Campbell, Itamar Balla, Xiaolong Liu, Michael J. Bedzyk, Tobin J. Marks & Mark C. Hersam
This data corresponds to the characterization of a transfer-free ultrathin heterostructure of a 2D semiconductor and high-k dielectric, and the resulting field-effect transistors. Monolayer MoS2 was grown directly via chemical vapor deposition on 20 nm of amorphous alumina deposited via atomic layer deposition on a silicon substrate. This method of integrating 2D MoS2 with a high-k dielectric results in superior performance in low-power electronics figures of merit. DOI: doi.org/10.1063/1.4975064

Combustion-Assisted Photonic Annealing of Printable Graphene Inks via Exothermic Binders

Ethan B. Secor, Theodore Z. Gao, Manuel H. Dos Santos, Shay G. Wallace, Karl W. Putz & Mark C. Hersam
Data corresponds to the demonstration of photonic curing of graphene/nitrocellulose patterns, in which the exothermic decomposition of nitrocellulose modifies and aids the annealing reaction. Few-layer graphene flakes are produced by liquid-phase exfoliation and stabilized by nitrocellulose to formulate inks suitable for direct write printing. Graphene thin films exhibit high conductivity and mechanical flexibility following the photonic annealing step, along with a porous microstructure. Characterization of the materials using Raman spectroscopy, Fourier transform infrared spectroscopy, scanning...

Dataset for Accuracy of ab initio electron correlation and electron densities in vanadium dioxide

Ilkka Kylanpaa, Janakiraman Balachandran, Panchapakesan Ganesh, Olle Heinonen, Paul R. C. Kent & Jaron T. Krogel
Dataset for "Accuracy of ab initio electron correlation and electron densities in vanadium dioxide" Ilkka Kylanpaa , Janakiraman Balachandran, Panchapakesan Ganesh , Olle Heinonen, Paul R. C. Kent, and Jaron T. Krogel (2017).

Size consistent excited states via algorithmic transformations between variational principles

Jacqueline A. R. Shea & Eric Neuscamman
We demonstrate that a broad class of excited state variational principles is not size consistent. In light of this difficulty, we develop and test an approach to excited state optimization that transforms between variational principles in order to achieve state selectivity, size consistency, and compatibility with quantum Monte Carlo. To complement our formal analysis, we provide numerical examples that confirm these properties and demonstrate how they contribute to a more black box approach to excited...

Fluctuation spectroscopy of step edges on Pt(111); Crossover from bulk to surface diffusion

Michal Ondrejcek, Wacek Swiech, Mahesh Rajappan, G. Yang & C. Peter Flynn
By step fluctuation spectroscopy, using low-energy electron microscopy LEEM, we investigate step energies and relaxation on clean Pt(111) surface at temperatures above half the melting temperature Tm (range 1190K

Atom Probe Tomography Analysis of Ag Doping in 2D Layered Material (PbSe)5(Bi2Se3)3

Xiaochen Ren, Arunima K. Singh, Lei Fang, Mercouri G. Kanatzidis, Francesca Tavazza, Albert V. Davydov & Lincoln J. Lauhon
This dataset contains the original APT data and analysis for the published paper in Nano Lett., 2016, 16 (10), pp 6064–6069.

Phase Field Benchmark I Dataset

Andrea M. Jokisaari, Peter W. Voorhees, Jonathan E. Guyer, James A. Warren & Olle Heinonen
This data set is that generated by the authors to create the publication below for the first set of phase field benchmark problems covering spinodal decomposition and Ostwald ripening. Please see the paper for details: A. M. Jokisaari, P. W. Voorhees, J. E. Guyer, J. Warren, O. G. Heinonen, Computational Materials Science 126 (2017) 139-151 (http://dx.doi.org/10.1016/j.commatsci.2016.09.022). You may also refer to the website, https://pages.nist.gov/chimad-phase-field/. Please contact O. G. Heinonen (heinonen@anl.gov) with questions, etc.

Umair

Khan Umair

Dataset of Synthetic X-ray Scattering Images for Classification Using Deep Learning

Kevin G. Yager, Julien Lhermitte, Dantong Yu, Boyu Wang, Ziqiao Guan & Jiliang Liu
This dataset contains a large number of example x-ray scattering images; each image is tagged with a variety of attributes describing the data features appearing in the image ('rings', 'anisotropic', etc.) or describing the underlying material ('BCC', 'FCC', etc.). The main purpose of this dataset is as a training set for machine-learning methods. The images were generated synthetically, using a combination of ad hoc methods (e.g. superimposing features such as rings and halos) and simple...

Simulated microstructures of gamma' precipitates in cobalt-based superalloys

Andrea M. Jokisaari, Shahab Naghavi, Chris Wolverton, Peter W. Voorhees & Olle G. Heinonen
This data set is that generated by the authors to create the publication below for the study on the equilibrium shapes of gamma' precipitates in novel Co-based superalloys. Please see the paper for details: A. M. Jokisaari, S. S. Naghavi, C. Wolverton, P. W. Voorhees, O. G. Heinonen, Predicting the morphologies of gamma prime precipitates in cobalt-based superalloys, submitted as a preprint to arXiv and accepted to Acta Materialia. Please contact O. G. Heinonen (heinonen@anl.gov)...

Dataset for Non-equilibrium BN-ZnO: Optical properties and excitonic effects from first principles

Xiao Zhang & André Schleife
This is the description file for the published data in the work [doi will be inserted once it’s published]. The calculations are performed in Vienna Ab initio Simulation Package (VASP) thus the inputs and outputs files are in VASP format. Some part of the calculations use our own code that is not published. The data for publication is structured as follows: 1. Data for structural relaxation: This folder contains the relevant inputs (VASP INCAR, KPOINTS,...

Coherent Band Excitations in CePd3

Hyowon Park

CSLM-4 95min Coarsened PbSn 30 volume percent dendrites

Thomas Cool & Peter Voorhees

X-ray Studies of Discrete Combinatorial Co-based Alloys

Michael J. Bedzyk

Probing the growth and melting pathways of a decagonal quasicrystal in real-time

Insung Han, Xianghui Xiao & Ashwin J. Shahani
This data was collected to study the principles of the growth and melting of a decagonal quasicrystal from a liquid. The composition of imaged sample is Al-9.55at%Ni-9.55at%Co, and the growth and melting of a decagonal quasicrystal were observed during the continuous slow cooling. The quasicrystalline phase shows weaker projection intensity because of more X-ray absorption resulting from its heavy elemental (Ni and Co) composition. This contrast difference allowed us to segment the quasicrystal from the...

Dataset for A New Generation of Effective Core Potentials for Correlated Calculations

M. Chandler Bennett, Cody A. Melton, Abdulgani Annaberdiyev, Guangming Wang, Luke Shulenburger & Lubos Mitas
Dataset includes all input and output files of calculations performed in the work "A new generation of effective core potentials for correlated calculations" as well as effective core potentials and correlation consistent basis sets generated in the study.

CSLM-4 10min Coarsened PbSn 30 volume percent dendrites

Thomas Cool & Peter Voorhees

Enhanced Conductivity, Adhesion, and Environmental Stability of Printed Graphene Inks with Nitrocellulose

Ethan B. Secor, Theodore Z. Gao, Ahmad E. Islam, Rahul Rao, Shay G. Wallace, Jian Zhu, Karl W. Putz, Benji Maruyama & Mark C. Hersam
Data corresponds to the demonstration of inkjet-printed graphene patterns using the polymer nitrocellulose as an effective ink stabilizer. Few-layer graphene flakes are produced by liquid-phase exfoliation and stabilized by nitrocellulose to formulate inks suitable for inkjet printing, blade coating, and spray coating. Graphene thin films exhibit high conductivity and mechanical flexibility following a thermal annealing step. Characterization of the materials using atomic force microscopy, Raman spectroscopy, Fourier transform infrared spectroscopy, scanning electron microscopy, thermal gravimetric...

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