9 Works

Room Temperature Electrical Properties of Semiconductor Materials

Kevin Cruse, Eric Toberer & Elif Ertekin
These data describe room temperature properties of semiconductors (with particular attention paid toward electrical properties) with the intention of contributing to a machine learning model for electrical conductivity in thermoelectric candidates. These data were curated from 5 sources (scientific articles, online sources, and a semiconductor properties textbook). Much of the dataset is still sparse and is still being populated. It is expected that this dataset will help standardize room temperature electrical property information on semiconductors...

ZEOMICS: Zeolites and Microporous Structures Characterization

Eric First, Chrysanthos Gounaris, James Wei & Christodoulos Floudas
ZEOMICS is an automated computational method for characterizing the three-dimensional porous networks of microporous materials, such as zeolites. The original database was developed by Princeton University and includes information about topological features for 204 unique zeolite frameworks built from the International Zeolite Associations (IZA) structural database . Data is generated using several algorithmic steps applied to a structural CIF. The dataset includes information on pore size distributions, accessible surface area and volume as a function...

NiTiHf Shape Memory Alloys

Sen Liu, Benham Amin-Ahmadi, Branden Kappes, Xiaoli Zhang & Stebner Aaron
Because of the time necessary for performing experiments on high dimensionality design space in manufacturing processes, exploring the entire design space is often prohibitively costly and time-consuming. To accelerate the development of NiTiHf shape memory alloys, we have proposed a sequential learning design framework to strategically identify experimental candidates who maximize information gain using fewest possible experiments. A Kriging regression model scales to high-dimensional search space in terms of processing features, part properties and alloy...

Database-Driven Calculation of Semiconductor Branch-Point Energy for Heterojunction Design

Ethan Shapera & Andre Schleife
Heterojunctions are at the heart of many modern semiconductor devices with tremendous societal impact: Light-emitting diodes shape the future of energy-efficient lighting, solar cells are promising for renewable energy, and photoelectrochemistry seeks to optimize efficiency of the water-splitting reaction. Design of heterojunctions is difficult due to the limited number of materials for which band alignment is known, and the experimental and computational difficulties associated with obtaining this data. Band alignment based on branch-point energies (EBP)...

Dielectric and Piezoelectric Properties of Ceramics

Yachao Chen, Geoff Brennecka, Vanessa Meschke, Kevin Cruse, Kelsey Cannon, Mary Dougherty & Katie Fisk
Piezoelectric and ferroelectric properties are know to be closely associated with proximity to phase transitions, but attempts to identify general rules for identifying and exploiting such phase transitions have had limited success. By learning from a wide range of literature reports, we hope to identify relationships and descriptors that are more predictive than existing design rules based on things like crystal chemistry (such as tolerance factors) or empirical mixing rules. Initial efforts have focused on...

Cr-Fe-Ni Sigma Phase Finite Temperature Calculations

Matthew Feurer, Brandon Bocklund, Shunli Shang, Allison Beese & Zi-Kui Liu
The Cr-Fe-Ni system is of great technological importance and is a fundamental part of many key alloys. The sigma phase, much like other topologically close-packed phases, is a brittle phase that is detrimental to the properties of the alloys in which it forms. This work uses first-principles calculations based on density functional theory (DFT) to develop a description for the sigma phase using a 5 sublattice model with magnetic configurations considered. A high-throughput DFT workflow...

In-Situ Simultaneous Small Angle and Wide Angle X-ray Scattering of Nickel Carbide Nanoparticle Growth using Thermolysis of Nitrogen-containing and Nitrogen-free Nickel Salts in the Presence of Oleylamine

Samuel Gage, Lenson Pellouchoud, Amanda Fournier, Christopher Tassone & Ryan Richards
We have used simultaneous small angle x-ray scattering (SAXS) and wide angle x-ray scattering (WAXS) to monitor the structural evolution of NiC nanocrystals as a function of precursor salt. The combination of these techniques has enabled us to follow the nucleation and growth of these nanocrystals, as well as the phase evolution. We find that the precursor salt affect not only the growth kinetics, but also the microstructural evolution. While both salts produce NiC nanocrystals,...

DATA: Combined Machine Learning and CALPHAD Approach for Discovering Processing-Structure Relationships in Soft Magnetic Alloys

Rajesh Jha, Nirupam Chakraborti, David Diercks, Aaron Stebner & Cristian Ciobanu
Contains data files and figures plotted from these files that were included in this paper.Data was generated through:1. Precipitation model developed in Thermocalc for mean radius and volume fraction of Fe3Si nanocrystals during isothermal annealing of FINEMET alloy.2. Sobol's algorithm for testing precipitation model.Authors:Rajesh Jha, Nirupam Chakraborti, David R. Diercks, Aaron P. Stebner, Cristian V. Ciobanu,Colorado School of Mines, Golden, Colorado 80401, USA

Si-Vacancy complexes in Graphene

Maxim Ziatdinov, Ondrej Dyck, Sergei Kalinin & Bobby Sumpter
Scanning transmission electron microscopy of Si-vacancy complexes in monolayer graphene

Registration Year

  • 2019
  • 2018

Resource Types

  • Dataset