6 Works

Si-Vacancy complexes in Graphene

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

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)...

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,...

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...

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...

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

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  • 2018
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