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Nicholas Marcella
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Mapping XANES spectra on structural descriptors of copper oxide clusters using supervised machine learning
Y Liu, N Marcella, J Timoshenko, A Halder, B Yang, L Kolipaka, M Pellin, ...
The Journal of Chemical Physics 151 (16), 2019
722019
Enhancing catalytic performance of dilute metal alloy nanomaterials
M Luneau, E Guan, W Chen, AC Foucher, N Marcella, T Shirman, ...
Communications chemistry 3 (1), 46, 2020
602020
Dilute alloys based on Au, Ag, or Cu for efficient catalysis: from synthesis to active sites
JD Lee, JB Miller, AV Shneidman, L Sun, JF Weaver, J Aizenberg, ...
Chemical Reviews 122 (9), 8758-8808, 2022
592022
Role of Lewis and Brønsted acidity in metal chloride catalysis in organic media: reductive etherification of furanics
H Nguyen, N Xiao, S Daniels, N Marcella, J Timoshenko, A Frenkel, ...
ACS Catalysis 7 (10), 7363-7370, 2017
522017
Experimental and theoretical structural investigation of AuPt nanoparticles synthesized using a direct electrochemical method
AS Lapp, Z Duan, N Marcella, L Luo, A Genc, J Ringnalda, AI Frenkel, ...
Journal of the American Chemical Society 140 (20), 6249-6259, 2018
412018
Decoding reactive structures in dilute alloy catalysts
N Marcella, JS Lim, AM Płonka, G Yan, CJ Owen, JES van der Hoeven, ...
Nature communications 13 (1), 832, 2022
392022
Neural network assisted analysis of bimetallic nanocatalysts using X-ray absorption near edge structure spectroscopy
N Marcella, Y Liu, J Timoshenko, E Guan, M Luneau, T Shirman, ...
Physical Chemistry Chemical Physics 22 (34), 18902-18910, 2020
372020
Latent representation learning for structural characterization of catalysts
PK Routh, Y Liu, N Marcella, B Kozinsky, AI Frenkel
The Journal of Physical Chemistry Letters 12 (8), 2086-2094, 2021
362021
Solving the structure of “single-atom” catalysts using machine learning–assisted XANES analysis
S Xiang, P Huang, J Li, Y Liu, N Marcella, PK Routh, G Li, AI Frenkel
Physical Chemistry Chemical Physics 24 (8), 5116-5124, 2022
232022
Probing Active Sites in CuxPdy Cluster Catalysts by Machine-Learning-Assisted X-ray Absorption Spectroscopy
Y Liu, A Halder, S Seifert, N Marcella, S Vajda, AI Frenkel
ACS Applied Materials & Interfaces 13 (45), 53363-53374, 2021
232021
Structural and valence state modification of cobalt in CoPt nanocatalysts in redox conditions
AC Foucher, N Marcella, JD Lee, DJ Rosen, R Tappero, CB Murray, ...
ACS nano 15 (12), 20619-20632, 2021
202021
Dynamical Change of Valence States and Structure in NiCu3 Nanoparticles during Redox Cycling
AC Foucher, N Marcella, JD Lee, R Tappero, CB Murray, AI Frenkel, ...
The Journal of Physical Chemistry C 126 (4), 1991-2002, 2022
142022
New role of Pd hydride as a sensor of surface Pd distributions in Pd− Au catalysts
E Guan, AC Foucher, N Marcella, T Shirman, M Luneau, AR Head, ...
ChemCatChem 12 (3), 717-721, 2020
142020
Speciation of Nanocatalysts Using X-ray Absorption Spectroscopy Assisted by Machine Learning
PK Routh, N Marcella, AI Frenkel
The Journal of Physical Chemistry C 127 (12), 5653-5662, 2023
82023
Z-Contrast Enhancement in Au–Pt Nanocatalysts by Correlative X-ray Absorption Spectroscopy and Electron Microscopy: Implications for Composition Determination
Y Liu, M Xie, N Marcella, AC Foucher, EA Stach, MR Knecht, AI Frenkel
ACS Applied Nano Materials 5 (7), 8775-8782, 2022
32022
Neural network based analysis of multimodal bond distributions using extended x-ray absorption fine structure spectra
N Marcella, S Lam, VS Bryantsev, S Roy, AI Frenkel
Physical Review B 109 (10), 104201, 2024
12024
Unraveling the Catalytic Effect of Hydrogen Adsorption on Pt Nanoparticle Shape-Change
CJ Owen, N Marcella, Y Xie, J Vandermause, AI Frenkel, RG Nuzzo, ...
arXiv preprint arXiv:2306.00901, 2023
12023
Decoding Reactive Structures in Bimetallic Catalysts
NJ Marcella
State University of New York at Stony Brook, 2021
12021
Iterative Bragg peak removal on X-ray absorption spectra with automatic intensity correction
R Shimogawa, N Marcella, CR O'Connor, TS Kim, C Reece, I Lubomirsky, ...
Journal of Synchrotron Radiation 31 (3), 2024
2024
Decoding the Pair Distribution Function of Uranium in Molten Fluoride Salts from X-Ray Absorption Spectroscopy Data by Machine Learning
K Zheng, N Marcella, AL Smith, AI Frenkel
The Journal of Physical Chemistry C, 2024
2024
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