Neural network assisted analysis of bimetallic nanocatalysts using X-ray absorption near edge structure spectroscopy

Marcella, N; Liu, Y.; Timoshenko, J.; Guan, E.; Luneau, M.; Shirman, T.; Plonka, A.; van der Hoeven, J.; Aizenberg, J.; Friend, C.; Frenkel, A.

doi:10.1039/D0CP02098B

Neural network assisted analysis of bimetallic nanocatalysts using X-ray absorption near edge structure spectroscopy

Journal Article · 01 January 2022 · Physical Chemistry Chemical Physics. PCCP

DOI:https://doi.org/10.1039/D0CP02098B· OSTI ID:1690064

Marcella, N; Liu, Y.; Timoshenko, J.; Guan, E.; Luneau, M.; Shirman, T.; Plonka, A.; van der Hoeven, J.; Aizenberg, J.; Friend, C.; Frenkel, A.

Research Organization:: Brookhaven National Lab. (BNL), Upton, NY (United States)

Sponsoring Organization:: ~OTHER

DOE Contract Number:: SC0012704

OSTI ID:: 1690064

Report Number(s):: BNL-220392-2020-JACI

Journal Information:: Physical Chemistry Chemical Physics. PCCP, Vol. 22, Issue 34

Country of Publication:: United States

Language:: English

References (52)

Pd–Au bimetallic catalysts: understanding alloy effects from planar models and (supported) nanoparticles Gao, Feng; Goodman, D. Wayne Chemical Society Reviews, Vol. 41, Issue 24 https://doi.org/10.1039/c2cs35160a	journal	January 2012
Importance of electronic ligand effects in metal alloy catalysts Burch, Robert Accounts of Chemical Research, Vol. 15, Issue 1 https://doi.org/10.1021/ar00073a004	journal	January 1982
Synthesis, catalysis, surface chemistry and structure of bimetallic nanocatalysts Tao, Franklin (Feng) Chemical Society Reviews, Vol. 41, Issue 24 https://doi.org/10.1039/c2cs90093a	journal	January 2012
Ligand and ensemble effects in adsorption on alloy surfaces Liu, P.; Nørskov, J. K. Physical Chemistry Chemical Physics, Vol. 3, Issue 17 https://doi.org/10.1039/b103525h	journal	January 2001
Machine-Learning Methods Enable Exhaustive Searches for Active Bimetallic Facets and Reveal Active Site Motifs for CO ₂ Reduction Ulissi, Zachary W.; Tang, Michael T.; Xiao, Jianping ACS Catalysis, Vol. 7, Issue 10 https://doi.org/10.1021/acscatal.7b01648	journal	August 2017
Complex structural dynamics of nanocatalysts revealed in Operando conditions by correlated imaging and spectroscopy probes Li, Y.; Zakharov, D.; Zhao, S. Nature Communications, Vol. 6, Issue 1 https://doi.org/10.1038/ncomms8583	journal	June 2015
Structural Characterization of Carbon-Supported Platinum−Ruthenium Nanoparticles from the Molecular Cluster Precursor PtRu ₅ C(CO) ₁₆ Nashner, Michael S.; Frenkel, Anatoly I.; Adler, David L. Journal of the American Chemical Society, Vol. 119, Issue 33 https://doi.org/10.1021/ja971039f	journal	August 1997
Noncrystalline-to-Crystalline Transformations in Pt Nanoparticles Li, Long; Wang, Lin-Lin; Johnson, Duane D. Journal of the American Chemical Society, Vol. 135, Issue 35 https://doi.org/10.1021/ja405497p	journal	August 2013
Evolution of Structure and Chemistry of Bimetallic Nanoparticle Catalysts under Reaction Conditions Tao, Feng; Grass, Michael E.; Zhang, Yawen Journal of the American Chemical Society, Vol. 132, Issue 25 https://doi.org/10.1021/ja101502t	journal	June 2010
Reaction-Driven Restructuring of Rh-Pd and Pt-Pd Core-Shell Nanoparticles Tao, F.; Grass, M. E.; Zhang, Y. Science, Vol. 322, Issue 5903 https://doi.org/10.1126/science.1164170	journal	November 2008
Revealing the Atomic Restructuring of Pt–Co Nanoparticles Xin, Huolin L.; Alayoglu, Selim; Tao, Runzhe Nano Letters, Vol. 14, Issue 6 https://doi.org/10.1021/nl500553a	journal	May 2014
Critical review: Effects of complex interactions on structure and dynamics of supported metal catalysts Frenkel, Anatoly I.; Cason, Michael W.; Elsen, Annika Journal of Vacuum Science & Technology A: Vacuum, Surfaces, and Films, Vol. 32, Issue 2 https://doi.org/10.1116/1.4820493	journal	March 2014
Applications of extended X-ray absorption fine-structure spectroscopy to studies of bimetallic nanoparticle catalysts Frenkel, Anatoly I. Chemical Society Reviews, Vol. 41, Issue 24 https://doi.org/10.1039/c2cs35174a	journal	January 2012
Effects of surface disorder on EXAFS modeling of metallic clusters Yevick, Aaron; Frenkel, Anatoly I. Physical Review B, Vol. 81, Issue 11 https://doi.org/10.1103/PhysRevB.81.115451	journal	March 2010
Probing the Limits of Conventional Extended X-ray Absorption Fine Structure Analysis Using Thiolated Gold Nanoparticles Chill, Samuel T.; Anderson, Rachel M.; Yancey, David F. ACS Nano, Vol. 9, Issue 4 https://doi.org/10.1021/acsnano.5b00090	journal	February 2015
Solving the Structure and Dynamics of Metal Nanoparticles by Combining X-Ray Absorption Fine Structure Spectroscopy and Atomistic Structure Simulations Timoshenko, J.; Duan, Z.; Henkelman, G. Annual Review of Analytical Chemistry, Vol. 12, Issue 1 https://doi.org/10.1146/annurev-anchem-061318-114929	journal	June 2019
Parameter-free calculations of X-ray spectra with FEFF9 Rehr, John J.; Kas, Joshua J.; Vila, Fernando D. Physical Chemistry Chemical Physics, Vol. 12, Issue 21 https://doi.org/10.1039/b926434e	journal	January 2010
X-ray-absorption spectroscopy and n -body distribution functions in condensed matter. I. Theory Filipponi, Adriano; Di Cicco, Andrea; Natoli, Calogero Renzo Physical Review B, Vol. 52, Issue 21 https://doi.org/10.1103/PhysRevB.52.15122	journal	December 1995
MXAN : a new software procedure to perform geometrical fitting of experimental XANES spectra Benfatto, M.; Congiu-Castellano, A.; Daniele, A. Journal of Synchrotron Radiation, Vol. 8, Issue 2 https://doi.org/10.1107/S0909049500015338	journal	March 2001
FitIt: New software to extract structural information on the basis of XANES fitting Smolentsev, G.; Soldatov, A. V. Computational Materials Science, Vol. 39, Issue 3 https://doi.org/10.1016/j.commatsci.2006.08.007	journal	May 2007
“Inverting” X-ray Absorption Spectra of Catalysts by Machine Learning in Search for Activity Descriptors Timoshenko, Janis; Frenkel, Anatoly I. ACS Catalysis, Vol. 9, Issue 11 https://doi.org/10.1021/acscatal.9b03599	journal	September 2019
Probing Atomic Distributions in Mono- and Bimetallic Nanoparticles by Supervised Machine Learning Timoshenko, Janis; Wrasman, Cody J.; Luneau, Mathilde Nano Letters, Vol. 19, Issue 1 https://doi.org/10.1021/acs.nanolett.8b04461	journal	December 2018
Neural Network Approach for Characterizing Structural Transformations by X-Ray Absorption Fine Structure Spectroscopy Timoshenko, Janis; Anspoks, Andris; Cintins, Arturs Physical Review Letters, Vol. 120, Issue 22 https://doi.org/10.1103/PhysRevLett.120.225502	journal	May 2018
Supervised Machine-Learning-Based Determination of Three-Dimensional Structure of Metallic Nanoparticles Timoshenko, Janis; Lu, Deyu; Lin, Yuewei The Journal of Physical Chemistry Letters, Vol. 8, Issue 20 https://doi.org/10.1021/acs.jpclett.7b02364	journal	October 2017
Application of the ratio method of EXAFS analysis to disordered systems Bunker, Grant Nuclear Instruments and Methods in Physics Research, Vol. 207, Issue 3 https://doi.org/10.1016/0167-5087(83)90655-5	journal	April 1983
Solving the structure of nanoparticles by multiple-scattering EXAFS analysis Frenkel, A. I. Journal of Synchrotron Radiation, Vol. 6, Issue 3 https://doi.org/10.1107/S0909049598017786	journal	May 1999
Estimation of mean size and shape of small metal particles by EXAFS Jentys, Andreas Physical Chemistry Chemical Physics, Vol. 1, Issue 17 https://doi.org/10.1039/a904654b	journal	January 1999
In situ coarsening study of inverse micelle-prepared Pt nanoparticles supported on γ-Al2O3: pretreatment and environmental effects Matos, J.; Ono, L. K.; Behafarid, F. Physical Chemistry Chemical Physics, Vol. 14, Issue 32 https://doi.org/10.1039/c2cp41339f	journal	January 2012
Tuning the Structure of Pt Nanoparticles through Support Interactions: An in Situ Polarized X-ray Absorption Study Coupled with Atomistic Simulations Ahmadi, M.; Timoshenko, J.; Behafarid, F. The Journal of Physical Chemistry C, Vol. 123, Issue 16 https://doi.org/10.1021/acs.jpcc.9b00945	journal	March 2019
Subnanometer Substructures in Nanoassemblies Formed from Clusters under a Reactive Atmosphere Revealed Using Machine Learning Timoshenko, Janis; Halder, Avik; Yang, Bing The Journal of Physical Chemistry C, Vol. 122, Issue 37 https://doi.org/10.1021/acs.jpcc.8b07952	journal	August 2018
Cluster Assemblies Produced by Aggregation of Preformed Ag Clusters in Ionic Liquids Roese, Stefanie; Kononov, Alexander; Timoshenko, Janis Langmuir, Vol. 34, Issue 16 https://doi.org/10.1021/acs.langmuir.7b03984	journal	March 2018
Mapping XANES spectra on structural descriptors of copper oxide clusters using supervised machine learning Liu, Yang; Marcella, Nicholas; Timoshenko, Janis The Journal of Chemical Physics, Vol. 151, Issue 16 https://doi.org/10.1063/1.5126597	journal	October 2019
Aqueous Au-Pd colloids catalyze selective CH ₄ oxidation to CH ₃ OH with O ₂ under mild conditions Agarwal, Nishtha; Freakley, Simon J.; McVicker, Rebecca U. Science, Vol. 358, Issue 6360 https://doi.org/10.1126/science.aan6515	journal	September 2017
Bimetallic dendrimer-encapsulated nanoparticles as catalysts: a review of the research advances Peng, Xiaohong; Pan, Qinmin; Rempel, Garry L. Chemical Society Reviews, Vol. 37, Issue 8 https://doi.org/10.1039/b716441f	journal	January 2008
Achieving High Selectivity for Alkyne Hydrogenation at High Conversions with Compositionally Optimized PdAu Nanoparticle Catalysts in Raspberry Colloid-Templated SiO ₂ Luneau, Mathilde; Shirman, Tanya; Foucher, Alexandre C. ACS Catalysis, Vol. 10, Issue 1 https://doi.org/10.1021/acscatal.9b04243	journal	November 2019
Palladium–gold single atom alloy catalysts for liquid phase selective hydrogenation of 1-hexyne Liu, Jilei; Shan, Junjun; Lucci, Felicia R. Catalysis Science & Technology, Vol. 7, Issue 19 https://doi.org/10.1039/C7CY00794A	journal	January 2017
Dilute Pd/Au Alloy Nanoparticles Embedded in Colloid-Templated Porous SiO 2 : Stable Au-Based Oxidation Catalysts Luneau, Mathilde; Shirman, Tanya; Filie, Amanda Chemistry of Materials, Vol. 31, Issue 15 https://doi.org/10.1021/acs.chemmater.9b01779	journal	July 2019
Effects of Pd on Catalysis by Au: CO Adsorption, CO Oxidation, and Cyclohexene Hydrogenation by Supported Au and Pd–Au Catalysts Ward, Timothy; Delannoy, Laurent; Hahn, Ruth ACS Catalysis, Vol. 3, Issue 11 https://doi.org/10.1021/cs400569v	journal	October 2013
Core Shell Inversion during Nucleation and Growth of Bimetallic Pt/Ru Nanoparticles Nashner, Michael S.; Frenkel, Anatoly I.; Somerville, David Journal of the American Chemical Society, Vol. 120, Issue 32 https://doi.org/10.1021/ja980638z	journal	August 1998
Structural Rearrangement of Bimetallic Alloy PdAu Nanoparticles within Dendrimer Templates to Yield Core/Shell Configurations ^† Knecht, Marc R.; Weir, Michael G.; Frenkel, Anatoly I. Chemistry of Materials, Vol. 20, Issue 3 https://doi.org/10.1021/cm0717817	journal	February 2008
Solving the 3D structure of metal nanoparticles Frenkel, Anatoly Zeitschrift für Kristallographie - Crystalline Materials, Vol. 222, Issue 11/2007 https://doi.org/10.1524/zkri.2007.222.11.605	journal	January 2007
Short range order in bimetallic nanoalloys: An extended X-ray absorption fine structure study Frenkel, Anatoly I.; Wang, Qi; Sanchez, Sergio I. The Journal of Chemical Physics, Vol. 138, Issue 6 https://doi.org/10.1063/1.4790509	journal	February 2013
Deep Learning of Atomically Resolved Scanning Transmission Electron Microscopy Images: Chemical Identification and Tracking Local Transformations Ziatdinov, Maxim; Dyck, Ondrej; Maksov, Artem ACS Nano, Vol. 11, Issue 12 https://doi.org/10.1021/acsnano.7b07504	journal	October 2016
A Deep Learning Approach to Identify Local Structures in Atomic-Resolution Transmission Electron Microscopy Images Madsen, Jacob; Liu, Pei; Kling, Jens Advanced Theory and Simulations, Vol. 1, Issue 8 https://doi.org/10.1002/adts.201800037	journal	July 2018
Ab Initio Quality NMR Parameters in Solid-State Materials Using a High-Dimensional Neural-Network Representation Cuny, Jérôme; Xie, Yu; Pickard, Chris J. Journal of Chemical Theory and Computation, Vol. 12, Issue 2 https://doi.org/10.1021/acs.jctc.5b01006	journal	January 2016
Identifying the Atomic-Level Effects of Metal Composition on the Structure and Catalytic Activity of Peptide-Templated Materials Merrill, Nicholas A.; McKee, Erik M.; Merino, Kyle C. ACS Nano, Vol. 9, Issue 12 https://doi.org/10.1021/acsnano.5b04665	journal	October 2015
Modular Design of Advanced Catalytic Materials Using Hybrid Organic-Inorganic Raspberry Particles Shirman, Elijah; Shirman, Tanya; Shneidman, Anna V. Advanced Functional Materials, Vol. 28, Issue 27 https://doi.org/10.1002/adfm.201704559	journal	December 2017
New Role of Pd Hydride as a Sensor of Surface Pd Distributions in Pd−Au Catalysts Guan, Erjia; Foucher, Alexandre C.; Marcella, Nicholas ChemCatChem, Vol. 12, Issue 3 https://doi.org/10.1002/cctc.201901847	journal	December 2019
Enhancing catalytic performance of dilute metal alloy nanomaterials Luneau, Mathilde; Guan, Erjia; Chen, Wei Communications Chemistry, Vol. 3, Issue 1 https://doi.org/10.1038/s42004-020-0293-2	journal	April 2020
Structure of the methanol synthesis catalyst determined by in situHERFD XAS and EXAFS Kleymenov, Evgeny; Sa, Jacinto; Abu-Dahrieh, Jehad Catal. Sci. Technol., Vol. 2, Issue 2 https://doi.org/10.1039/C1CY00277E	journal	January 2012
The Nuclearity of the Active Site for Methane to Methanol Conversion in Cu-Mordenite: A Quantitative Assessment Pappas, Dimitrios K.; Martini, Andrea; Dyballa, Michael Journal of the American Chemical Society, Vol. 140, Issue 45 https://doi.org/10.1021/jacs.8b08071	journal	October 2018
Linking the evolution of catalytic properties and structural changes in copper–zinc nanocatalysts using operando EXAFS and neural-networks Timoshenko, Janis; Jeon, Hyo Sang; Sinev, Ilya Chemical Science, Vol. 11, Issue 14 https://doi.org/10.1039/D0SC00382D	journal	January 2020

Similar Records

Neural network assisted analysis of bimetallic nanocatalysts using X-ray absorption near edge structure spectroscopy

Journal Article · 2020 · Physical Chemistry Chemical Physics. PCCP · OSTI ID:1677655

Marcella, Nicholas; Liu, Yang; Timoshenko, Janis; +8 more

Neural network assisted analysis of bimetallic nanocatalysts using X-ray absorption near edge structure spectroscopy

Journal Article · 2020 · Phys. Chem. Chem. Phys. · OSTI ID:1659316

Marcella, Nicholas; Liu, Yang; Timoshenko, Janis; +7 more

Neural network assisted analysis of bimetallic nanocatalysts using X-ray absorption near edge structure spectroscopy

Journal Article · 2020 · Physical Chemistry Chemical Physics. PCCP · OSTI ID:1845278

Marcella, Nicholas; Liu, Yang; Timoshenko, Janis; +8 more

Related Subjects

99 GENERAL AND MISCELLANEOUS

Neural network assisted analysis of bimetallic nanocatalysts using X-ray absorption near edge structure spectroscopy

Citation Formats

References (52)

Similar Records

Related Subjects