Machine Learning-Guided Discovery of Underlying Decisive Factors and New Mechanisms for the Design of Nonprecious Metal Electrocatalysts

[1]  Jianguo Liu,et al.  Designing AI-aided analysis and prediction models for nonprecious metal electrocatalyst-based proton exchange membrane fuel cells. , 2020, Angewandte Chemie.

[2]  Changpeng Liu,et al.  Single-Atom Cr-N4 Sites Designed for Durable Oxygen Reduction Catalysis in Acid Media. , 2019, Angewandte Chemie.

[3]  Evan C. Wegener,et al.  Highly active atomically dispersed CoN4 fuel cell cathode catalysts derived from surfactant-assisted MOFs: carbon-shell confinement strategy , 2019, Energy & Environmental Science.

[4]  Yadong Li,et al.  Design of N-Coordinated Dual-Metal Sites: A Stable and Active Pt-Free Catalyst for Acidic Oxygen Reduction Reaction. , 2017, Journal of the American Chemical Society.

[5]  Juan Herranz,et al.  Iron-based cathode catalyst with enhanced power density in polymer electrolyte membrane fuel cells. , 2011, Nature communications.

[6]  D. Cullen,et al.  Thermally Driven Structure and Performance Evolution of Atomically Dispersed Fe-N4 Sites for Oxygen Reduction. , 2019, Angewandte Chemie.

[7]  Zhen Wu,et al.  Towards online optimisation of solid oxide fuel cell performance: Combining deep learning with multi-physics simulation , 2020 .

[8]  J. Goodwin,et al.  Pt Alloy Electrocatalysts for Proton Exchange Membrane Fuel Cells: A Review , 2013 .

[9]  Zhengdong Cheng,et al.  Accelerated Design of Catalytic Water-Cleaning Nanomotors via Machine Learning. , 2019, ACS applied materials & interfaces.

[10]  Bowen Wang,et al.  AI-based optimization of PEM fuel cell catalyst layers for maximum power density via data-driven surrogate modeling , 2020 .

[11]  Branko N. Popov,et al.  Studies of oxygen reduction reaction active sites and stability of nitrogen-modified carbon composite catalysts for PEM fuel cells , 2010 .

[12]  M. O'keeffe,et al.  Colossal cages in zeolitic imidazolate frameworks as selective carbon dioxide reservoirs , 2008, Nature.

[13]  F. Kang,et al.  Seeded growth of branched iron–nitrogen-doped carbon nanotubes as a high performance and durable non-precious fuel cell cathode , 2020, Carbon.

[14]  Yide Liu,et al.  Applying machine learning to boost the development of high-performance membrane electrode assembly for proton exchange membrane fuel cells , 2021 .

[15]  Frédéric Jaouen,et al.  Heat-treated Fe/N/C catalysts for O2 electroreduction: are active sites hosted in micropores? , 2006, The journal of physical chemistry. B.

[16]  Yuyan Shao,et al.  Single Atomic Iron Catalysts for Oxygen Reduction in Acidic Media: Particle Size Control and Thermal Activation. , 2017, Journal of the American Chemical Society.

[17]  Karren L. More,et al.  Direct atomic-level insight into the active sites of a high-performance PGM-free ORR catalyst , 2017, Science.

[18]  Xien Liu,et al.  Atomic Fe Dispersed on N‐Doped Carbon Hollow Nanospheres for High‐Efficiency Electrocatalytic Oxygen Reduction , 2018, Advanced materials.

[19]  Michael O’Keeffe,et al.  Exceptional chemical and thermal stability of zeolitic imidazolate frameworks , 2006, Proceedings of the National Academy of Sciences.

[20]  D. Cullen,et al.  Atomically dispersed manganese catalysts for oxygen reduction in proton-exchange membrane fuel cells , 2018, Nature Catalysis.

[21]  Yadong Li,et al.  Isolated Single Iron Atoms Anchored on N-Doped Porous Carbon as an Efficient Electrocatalyst for the Oxygen Reduction Reaction. , 2017, Angewandte Chemie.

[22]  Changpeng Liu,et al.  Identification of binuclear Co2N5 active sites for oxygen reduction reaction with more than one magnitude higher activity than single atom CoN4 site , 2018 .

[23]  Zachary W. Ulissi,et al.  Accelerated discovery of CO2 electrocatalysts using active machine learning , 2020, Nature.

[24]  Yuyan Shao,et al.  Nitrogen‐Coordinated Single Cobalt Atom Catalysts for Oxygen Reduction in Proton Exchange Membrane Fuel Cells , 2018, Advanced materials.

[25]  Deborah J. Jones,et al.  Effect of Furfuryl Alcohol on Metal Organic Framework-based Fe/N/C Electrocatalysts for Polymer Electrolyte Membrane Fuel Cells , 2014 .

[26]  T. Kondo,et al.  Active sites of nitrogen-doped carbon materials for oxygen reduction reaction clarified using model catalysts , 2016, Science.

[27]  Cheng Wang,et al.  Directly converting Fe-doped metal–organic frameworks into highly active and stable Fe-N-C catalysts for oxygen reduction in acid , 2016 .

[28]  Zhang-peng Tian,et al.  Pythagorean fuzzy multiple criteria decision analysis based on Shapley fuzzy measures and partitioned normalized weighted Bonferroni mean operator , 2018, Int. J. Intell. Syst..

[29]  Kalyan Veeramachaneni,et al.  AI^2: Training a Big Data Machine to Defend , 2016, 2016 IEEE 2nd International Conference on Big Data Security on Cloud (BigDataSecurity), IEEE International Conference on High Performance and Smart Computing (HPSC), and IEEE International Conference on Intelligent Data and Security (IDS).

[30]  R. Yıldırım,et al.  Assessment of critical materials and cell design factors for high performance lithium-sulfur batteries using machine learning , 2020 .

[31]  Omar K Farha,et al.  Metal-organic framework materials as catalysts. , 2009, Chemical Society reviews.

[32]  Haoquan Zheng,et al.  PVP-assisted transformation of a metal-organic framework into Co-embedded N-enriched meso/microporous carbon materials as bifunctional electrocatalysts. , 2018, Chemical communications.

[33]  Yao Zhang,et al.  Identifying degradation patterns of lithium ion batteries from impedance spectroscopy using machine learning , 2020, Nature Communications.

[34]  Lirong Zheng,et al.  Fe–N–C electrocatalyst with dense active sites and efficient mass transport for high-performance proton exchange membrane fuel cells , 2019, Nature Catalysis.

[35]  Jin Zhao,et al.  Climbing the Apex of the ORR Volcano Plot via Binuclear Site Construction: Electronic and Geometric Engineering. , 2019, Journal of the American Chemical Society.

[36]  Jun Wang,et al.  ZIF-8 derived graphene-based nitrogen-doped porous carbon sheets as highly efficient and durable oxygen reduction electrocatalysts. , 2014, Angewandte Chemie.

[37]  Yuen Wu,et al.  Negative pressure pyrolysis induced highly accessible single sites dispersed on 3D graphene frameworks for enhanced oxygen reduction. , 2020, Angewandte Chemie.

[38]  Kui Jiao,et al.  Multi-physics-resolved digital twin of proton exchange membrane fuel cells with a data-driven surrogate model , 2020 .

[39]  A. Shorrocks.  Decomposition procedures for distributional analysis: a unified framework based on the Shapley value , 2013 .

[40]  R. Yıldırım,et al.  Data mining in photocatalytic water splitting over perovskites literature for higher hydrogen production , 2019, Applied Catalysis B: Environmental.

[41]  Stefano Ermon,et al.  Closed-loop optimization of fast-charging protocols for batteries with machine learning , 2020, Nature.

[42]  Y. Ishikawa,et al.  In Search of the Active Site in Nitrogen-Doped Carbon Nanotube Electrodes for the Oxygen Reduction Reaction , 2010 .

[43]  K. Amine,et al.  Nitrogen-coordinated single iron atom catalysts derived from metal organic frameworks for oxygen reduction reaction , 2019, Nano Energy.

[44]  D. Cullen,et al.  High-performance fuel cell cathodes exclusively containing atomically dispersed iron active sites , 2019, Energy & Environmental Science.

[45]  R. Jasinski,et al.  A New Fuel Cell Cathode Catalyst , 1964, Nature.

[46]  Fei Gao,et al.  Data-driven proton exchange membrane fuel cell degradation predication through deep learning method , 2018, Applied Energy.

[47]  Stefan Palkovits,et al.  Using Artificial Intelligence To Forecast Water Oxidation Catalysts , 2019, ACS Catalysis.

[48]  Yun Wang,et al.  Coexisting Single‐Atomic Fe and Ni Sites on Hierarchically Ordered Porous Carbon as a Highly Efficient ORR Electrocatalyst , 2020, Advanced materials.

[49]  M. E. Günay,et al.  Exploring the critical factors of algal biomass and lipid production for renewable fuel production by machine learning , 2021 .

[50]  Dan Zhao,et al.  Iron imidazolate framework as precursor for electrocatalysts in polymer electrolyte membrane fuel cells , 2012 .