51 Works

AFRL AM Modeling Challenge Series: Challenge 2 Data Description

Michael Groeber, Edwin Schwalbach, Sean Donegan, Michael Uchic, Michael Chapman, Shade Paul, William Musinski, Jonathan Miller, Todd Turner, Daniel Sparkman & Marie Cox

Dataset for An efficient hybrid orbital representation for quantum Monte Carlo calculations

Ye Luo, Kenneth P. Esler, Paul R. C. Kent & Luke Shulenburger

Dataset for Nanoscale Control of Oxygen Defects and Metal−Insulator Transition in Epitaxial Vanadium Dioxides

Yogesh Sharma, Janakiraman Balachandran, Changhee Sohn, Jaron T. Krogel, Panchapakesan Ganesh, Liam Collins, Anton V. Ievlev, Qian Li, Xiang Gao, Nina Balke, Olga S. Ovchinnikova, Sergei V. Kalinin, Olle Heinonen & Ho Nyung Lee
Dataset for "Nanoscale Control of Oxygen Defects and Metal−Insulator Transition in Epitaxial Vanadium Dioxides" Yogesh Sharma, Janakiraman Balachandran, Changhee Sohn, Jaron T. Krogel, Panchapakesan Ganesh, Liam Collins, Anton V. Ievlev, Qian Li, Xiang Gao, Nina Balke, Olga S. Ovchinnikova, Sergei V. Kalinin, Olle Heinonen, and Ho Nyung Lee (2018).

Influence of ruthenium in a model Co-Al-W superalloy

Daniel Sauza, Peter Bocchini, Ding-Wen Chung, David Dunand & David Seidman
The effect of 2 at.% Ru addition on a base Co-8.8Al-7.3W at.% superalloy, consisting of a gamma-(fcc) matrix with gamma’-(L12 structure) precipitates is studied using atom-probe tomography. Ru is found to partition to the gamma' precipitate after aging at 900C for 16h.

γ+γ’ Microstructures in the Co-Ta-V Ternary System

Fernando Reyes Tirado, Jacques Perrin Toinin & David Dunand
The Co-Ta-V ternary systems are investigated in a search for L12-ordered γ’ precipitation. Alloys are arc-melted, homogenized at 1250 °C, and aged at 900 °C for 2 h. The novel system displays metastable γ’ precipitates.

High and low thermal conductivity of amorphous macromolecules

Xu Xie, Kexin Yang, Dongyao Li, Tsung-Han Tsai, Jungwoo Shin, Paul V. Braun & David G. Cahill
Prior to the TDTR measurement, a thin layer of Al optical transducer (≈90 nm) was deposited (via magnetron sputtering) onto the sample. The water contents in the sample after Al coating were expected to be negligible, due to the long-time pumping in vacuum before deposition (90 °C baking for 2 h at 1× 10^-4 Torr, followed by pumping at <10^−7 Torr overnight). The Al coating prevents the water vapor from diffusing into the sample. To...

Multi-terminal memtransistors from polycrystalline monolayer molybdenum disulfide

Vinod K. Sangwan, Hong-Sub Lee, Hadallia Bergeron, Itamar Balla, Megan Beck, Kan-Sheng Chen & Mark C. Hersam
Data corresponds to the demonstration of the first memtransistor on monolayer MoS2. Polycrystalline monolayer MoS2 was grown by chemical vapor deposition with grain sizes of 3-5 microns. Memtransistor devices were fabricated on Si substrates coated with 300 nm thermal oxide by following custom-made photolithography and reactive ion etching recipes. Characterization of the devices using atomic force microscopy, electrostatic force microscopy, and cryogenic measurement revealed switching mechanism governed by a dynamically tunable Schottky barrier at contact....

Vacancy Mediated and Interstitial Solute Transport in Zr from Density Functional Theory Calculations

Abhinav C. P. Jain, Patrick A. Burr & Dallas R. Trinkle
The Interstitial folder contains the DFT dataset for the interstitial site and migration energies of all solutes, scripts required to extract the data and compute diffusivity. The Vacancy_Mediated folder contains the DFT dataset for the solute-vacancy binding and vacancy migration energies, scripts required to extract the data and compute diffusivity. The scripts/ directory in site Interstitial and Vacancy_Mediated folders contains the python and bash scripts, which extracts the input data for diffusion model from DFT...

Data for Overcoming the Overcoming the Memory Bottleneck in Auxiliary Field Quantum Monte Carlo Simulations with Interpolative Separable Density Fitting

Fionn D. Malone, Zhang Shuai & Morales. A Miguel
Data for "Overcoming the Memory Bottleneck in Auxiliary Field Quantum Monte Carlo Simulations with Interpolative Separable Density Fitting." ===================== In this dataset you will find: 1. The analysed data and plotting scripts necessary to reproduce the figures in the above paper. 2. The raw data produced from qmcpack calculations: - convergence/ (with respect to ISDF rank parameter c): - 2x2x2/: - DZ/ - TZ/ - 3x3x3/ - DZ/ - TZ/ - cold_curve/ (AFQMC results for...

Transfer of Rotationally Commensurate MoS2 from Epitaxial Graphene

Junmo Kang, Itamar Balla, Xiaolong Liu, Hadallia Bergeron, Soo Kim, Christopher Wolverton & Mark C. Hersam
This dataset corresponds to an accepted manuscript.

AFRL AM Modeling Challenge Series: Challenge 3 Data Package

Michael Groeber, Edwin Schwalbach, Sean Donegan, Michael Uchic, Michael Chapman, Paul Shade, William Musinski, Jonathan Miller, Todd Turner, Daniel Sparkman & Marie Cox

MIDAS Challenge Datasets

Michael A. Groeber & Edwin J Schwalbach

Phase Field Benchmark II Dataset

Andrea Jokisaari, Peter Voorhees, Jonathan Guyer, James Warren & Olle Heinonen

Orbital Symmetry and the Optical Response of Single-Layer MX Monochalcogenides

Gabriel Antonius, Diana Y. Qiu & Steven G. Louie
Optical absorption calculations in the GW+BSE framework for single-layer GaSe and GaTe in the hexagonal phase.

Spatially Heterogeneous Dynamics in a Metallic Glass Forming Liquid Imaged by Electron Correlation Microscopy

Pei Zhang, Jason Maldonis, Ze Liu, Jan Schroers & Paul Voyles
Supercooled liquids exhibit spatial heterogeneity in the dynamics of their fluctuating atomic arrangements. The length and time scales of the heterogeneous dynamics are central to the glass transition and influence nucleation and growth of crystals from the liquid. We report direct experimental visualization of the spatially heterogeneous dynamics as a function of temperature in the supercooled liquid state of a Pt- based metallic glass, using electron correlation microscopy with sub-nanometer resolution. An experimental four point...

BerkeleyGW 2018 Workshop Examples

Mauro Del Ben

Dataset for Polyelectrolyte Complexation of Oligonucleotides by Charged Hydrophobic – Neutral Hydrophilic Block Polymers

Alexander E. Marras, Jeffrey R. Vieregg, Jeffrey M. Ting, Jack D. Rubien & Matthew V. Tirrell
“Polyelectrolyte Complexation of Oligonucleotides by Charged Hydrophobic – Neutral Hydrophilic Block Polymers“ Alexander E. Marras, Jeffrey R. Vieregg, Jeffrey M. Ting, Jack D. Rubien, Matthew V. Tirrell Institute for Molecular Engineering, University of Chicago, Chicago, IL 60637 contact via twitter @AEMarras, @J_Ting1 or jvieregg@uchicago.edu preprint DOI: 10.26434/chemrxiv.7456322.v1 Files include background subtracted small angle X-ray scattering (SAXS) data from the Advanced Photon Source at Argonne National Laboratory. Data is organized by cation type (poly-l-lysine-PEG vs. poly-vinylbenzyltrimethyl-ammonium)...

Accelerated Discovery of Metallic Glasses through Iteration of Machine Learning and High-Throughput Experiments

Ren Fang, Logan Ward, Travis Williams, Kevin J. Laws, Christopher Wolverton, Jason Hattrick-Simpers & Apurva Mehta
This repository contains data supporting the manuscript: "Accelerated Discovery of Metallic Glasses through Iteration of Machine Learning and High-Throughput Experiments." It includes the raw x-ray diffraction measurements and scripts used to process that data. This dataset also contains the scripts necessary to build and test the machine learning models used in the work, and the output files generated from each of those scripts.

The Third Sandia Fracture Challenge

Sharlotte Kramer, Brad Boyce, Amanda Jones, Jhana Gearhart & Brad Salzbrenner
The Third Sandia Fracture Challenge (SFC3) is a collaborative effort for assessment of the state-of-the-art predictive capability in ductile failure. The Challenge is designed such that computational modelers are asked to predict ductile failure in an unfamiliar geometry using provided standard materials data. The SFC3, issued in December 2016, is centered on an additively manufactured 316L stainless steel geometry with through holes and internal cavities that could not be produced by conventional machining. The provided...

Far field high energy diffraction data for \"Study of slip activity in a Mg-Y alloy by in situ high energy X-ray diffraction microscopy and elastic viscoplastic self-consistent modeling\"

Leyun Wang, Zhonghe Huang, Huamiao Wang, Alireza Maldar, Sangbong Yi, Jun-Sang Park, Peter Kenesei, Erica Lilleodden & Xiaoqin Zeng
FF-HEDM data set (including the raw data) and reduced grain-by-grain information for several points along the stress-strain curve. These are GE image files.

Dateset for \"Auxiliary-field quantum Monte Carlo calculations of the structural properties of nickel oxide\"

Shuai Zhang, Fionn D. Malone & Miguel A. Morales

Data for Motif Extraction from Zr50Cu45Al5 Metallic Glass Models

Jason J. Maldonis, Arash Deghan Banadaki, Srikanth Patala & Paul M. Voyles

γ+γ’ Microstructures in the Co-Nb-V Ternary System

Fernando Reyes Tirado, Jacques Perrin Toinin & David Dunand
The Co-Nb-V ternary systems are investigated in a search for L12-ordered γ’ precipitation. Alloys are arc-melted, homogenized at 1250 °C, and aged at 900 °C for 2 h. The novel system displays metastable γ’ precipitates.

Atom Probe Tomography Reconstruction and Analysis for the Temporal Evolution of Co-Al-W Superalloys at 650˚C

Peter Bocchini, Ding-Wen Chung, David Dunand & David Seidman
Series of APT study for different aging time at 650C for Co-8.9Al-7.3W. Data were generated between 2012 to 2014. The temporal evolution of a γ(f.c.c.)/γ’(L12) Co-8.8Al-7.3W superalloy aged at 650 °C (10 min to 4096 h) is studied utilizing atom-probe tomography (APT). Results allows characterization of nucleation and coarsening kinetics of Co superalloys.

A Machine Learning Approach for Engineering Bulk Metallic Glass Alloys

Logan Ward, Stephanie C. O’Keeffe, Joesph Stevick, Glenton R. Jelbert, Muratahan Aykol & Chris Wolverton
This dataset contains the training data, software, and scripts necessary to replicate the machine learning models in a "A Machine Learning Approach for Engineering Bulk Metallic Glass Alloys."

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  • 2018
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