487 citations · 1.7k across the 18 of their papers we have counts for
21 papers · 1 filter
Machine learning for impurity charge-state transition levels in semiconductors from elemental properties using multi-fidelity datasets
Maciej P. Polak, Ryan Jacobs, Arun Mannodi-Kanakkithodi +2
Quantifying charge-state transition energy levels of impurities in semiconductors is critical to understanding and engineering their optoelectronic properties for applications rang…
Discovery and Engineering of Low Work Function Perovskite Materials
Tianyu Ma, Ryan Jacobs, John Booske +1
Materials with low work functions are critical for an array of applications requiring the facile removal or efficient transport of electrons through a device. Perovskite oxides are…
Work Function Trends and New Low Work Function Boride and Nitride Materials for Electron Emission Applications
Tianyu Ma, Ryan Jacobs, John Booske +1
LaB6 has been used as a commercial electron emitter for decades. Despite the large number of studies on the work function of LaB6, there is no comprehensive understanding of work f…
Calibrated bootstrap for uncertainty quantification in regression models
Glenn Palmer, Siqi Du, Alexander Politowicz +7
Obtaining accurate estimates of machine learning model uncertainties on newly predicted data is essential for understanding the accuracy of the model and whether its predictions ca…
Solid phase epitaxial growth of the correlated-electron transparent conducting oxide SrVO3
Samuel D. Marks, Lin Lin, Peng Zuo +11
SrVO3 thin films with a high figure of merit for applications as transparent conductors were crystallized from amorphous layers using solid phase epitaxy (SPE). Epitaxial SrVO3 fil…
Opportunities and Challenges for Machine Learning in Materials Science
Dane Morgan, Ryan Jacobs
Advances in machine learning have impacted myriad areas of materials science, ranging from the discovery of novel materials to the improvement of molecular simulations, with likely…