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The Journal of Physical Chemistry Letters|February 23, 2021
Latent Representation Learning for Structural Characterization of CatalystsPrahlad K Routh, Yang Liu, Nicholas Marcella, et al.ACS Applied Materials & Interfaces|July 13, 2021
Probing Active Sites in Cu<sub></sub>Pd<sub></sub> Cluster Catalysts by Machine-Learning-Assisted X-ray Absorption SpectroscopyYang Liu, Avik Halder, Soenke Seifert, et al.Journal of Synchrotron Radiation|April 9, 2024
Iterative Bragg peak removal on X-ray absorption spectra with automatic intensity correctionRyuichi Shimogawa, Nicholas Marcella, Christopher R O'Connor, et al.Physical Chemistry Chemical Physics : PCCP|February 14, 2022
Solving the structure of "single-atom" catalysts using machine learning - assisted XANES analysisShuting Xiang, Peipei Huang, Junying Li, et al.Journal of the American Chemical Society|May 12, 2018
Experimental and Theoretical Structural Investigation of AuPt Nanoparticles Synthesized Using a Direct Electrochemical MethodAliya S Lapp, Zhiyao Duan, Nicholas Marcella, et al.ACS Nano|November 15, 2021
Structural and Valence State Modification of Cobalt in CoPt Nanocatalysts in Redox ConditionsAlexandre C Foucher, Nicholas Marcella, Jennifer D Lee, et al.The Journal of Chemical Physics|November 3, 2019
Mapping XANES spectra on structural descriptors of copper oxide clusters using supervised machine learningYang Liu, Nicholas Marcella, Janis Timoshenko, et al.Physical Chemistry Chemical Physics : PCCP|May 13, 2020
Neural network assisted analysis of bimetallic nanocatalysts using X-ray absorption near edge structure spectroscopyNicholas Marcella, Yang Liu, Janis Timoshenko, et al.Communications Chemistry|January 27, 2023
Enhancing catalytic performance of dilute metal alloy nanomaterialsMathilde Luneau, Erjia Guan, Wei Chen, et al.Nature Communications|February 12, 2022
Decoding reactive structures in dilute alloy catalystsNicholas Marcella, Jin Soo Lim, Anna M Płonka, et al.Pageof 2