H
Holden Parks
Researcher at Carnegie Mellon University
Publications - 9
Citations - 159
Holden Parks is an academic researcher from Carnegie Mellon University. The author has contributed to research in topics: Superlattice & Bilayer graphene. The author has an hindex of 3, co-authored 8 publications receiving 85 citations. Previous affiliations of Holden Parks include Lawrence Berkeley National Laboratory.
Papers
More filters
Journal ArticleDOI
Xi-cam: a versatile interface for data visualization and analysis
Ronald Pandolfi,Daniel B. Allan,Elke Arenholz,Luis Barroso-Luque,Stuart I. Campbell,Thomas A Caswell,Austin Blair,Francesco De Carlo,Sean Fackler,Amanda P. Fournier,Guillaume Freychet,Masafumi Fukuto,Dogˇa Gürsoy,Zhang Jiang,Harinarayan Krishnan,Dinesh Kumar,R. Joseph Kline,Ruipeng Li,Christopher Liman,Stefano Marchesini,Apurva Mehta,Alpha T. N'Diaye,Dilworth Y. Parkinson,Holden Parks,Lenson A Pellouchoud,Talita Perciano,Fang Ren,Shreya Sahoo,Joseph Strzalka,Daniel F. Sunday,Christopher J. Tassone,Daniela Ushizima,Singanallur Venkatakrishnan,Kevin G. Yager,Peter H. Zwart,James A. Sethian,Alexander Hexemer +36 more
TL;DR: The core of Xi-cam is an extensible plugin-based graphical user interface platform which provides users with an interactive interface to processing algorithms, and targets cross-facility and cross-technique collaborative development, in support of multi-modal analysis.
Journal ArticleDOI
Tunable angle-dependent electrochemistry at twisted bilayer graphene with moiré flat bands
Yun Yu,Kaidi Zhang,Holden Parks,Mohammad Babar,Stephen R. Carr,Isaac M. Craig,Madeline Van Winkle,A. Lyssenko,Takashi Taniguchi,Kenji Watanabe,Venkatasubramanian Viswanathan,D. Kwabena Bediako +11 more
TL;DR: In this paper , a strong twist-angle dependence of heterogeneous charge transfer kinetics at twisted bilayer graphene electrodes with the greatest enhancement observed near the "magic angle" (~1.1°).
Journal ArticleDOI
Uncertainty Quantification in First-Principles Predictions of Harmonic Vibrational Frequencies of Molecules and Molecular Complexes
TL;DR: In this article, the authors developed a method to quantify the uncertainty associated with density functional theory-predicted harmonic vibrational frequencies using the built-in error estimation capabilities of the Bayesian error estimation functional with van der Waals exchange-correlation functional.
Journal ArticleDOI
Machine learning enabled discovery of application dependent design principles for two-dimensional materials
TL;DR: In this paper, a large-scale search for high-performing candidate 2D materials is limited to calculating a few simple descriptors, usually with first-principles density functional theory calculations.