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Wang X, Li M, Wang P, Sun D, Ding L, Li H, Tang Y, Fu G. Spin-Selective Coupling in Mott-Schottky Er 2 O 3 -Co Boosts Electrocatalytic Oxygen Reduction. SMALL METHODS 2023:e2300100. [PMID: 37029579 DOI: 10.1002/smtd.202300100] [Citation(s) in RCA: 5] [Impact Index Per Article: 5.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Subscribe] [Scholar Register] [Received: 01/26/2023] [Revised: 03/15/2023] [Indexed: 06/19/2023]
Abstract
Alkaline oxygen reduction reaction (ORR) is critical to electrochemical energy conversion technology, yet the rational breaking of thermodynamic inhibition for ORR through spin regulation remains a challenge. Herein, a Mott-Schottky catalyst consisting of Er2 O3 -Co particles uniformly implanted into carbon nanofibers (Er2 O3 -Co/CNF) is designed for enhancing ORR via spin-selective coupling. The optimized Er2 O3 -Co/CNF affords a high half-wave potential (0.835 V vs reversible hydrogen electrode, RHE) and onset potential (0.989 VRHE ) for the ORR surpassing individual Co/CNF and Er2 O3 /CNF. Theoretical calculations reveal the introduction of Er2 O3 optimizes the electronic structure of Co through Er(4f)-O(2p)-Co(3d) gradient orbital coupling, resulting in significantly enhanced ORR performance. Through gradient orbital coupling, the induced spin-up hole in Co 3d states endows the Er-O-Co unit active site with a spin-selective coupling channel for electron transition. This favors the decrease of the energy gap in the potential-limiting step, thus achieving a high theoretical limiting potential of 0.77 VRHE for the Er2 O3 -Co. Moreover, the potential practicability of Er2 O3 -Co/CNF as an air-cathode is also demonstrated in Zn-air batteries. This work is believed to provide, new perspectives for the design of efficient ORR electrocatalysts by engineering spin-selective coupling induced by rare-earth oxides.
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Affiliation(s)
- Xuan Wang
- Jiangsu Key Laboratory of New Power Batteries, Jiangsu Collaborative Innovation Center of Biomedical Functional Materials, School of Chemistry and Materials Science, Nanjing Normal University, Nanjing, 210023, China
| | - Meng Li
- Jiangsu Key Laboratory of New Power Batteries, Jiangsu Collaborative Innovation Center of Biomedical Functional Materials, School of Chemistry and Materials Science, Nanjing Normal University, Nanjing, 210023, China
| | - Pu Wang
- Jiangsu Key Laboratory of New Power Batteries, Jiangsu Collaborative Innovation Center of Biomedical Functional Materials, School of Chemistry and Materials Science, Nanjing Normal University, Nanjing, 210023, China
| | - Dongmei Sun
- Jiangsu Key Laboratory of New Power Batteries, Jiangsu Collaborative Innovation Center of Biomedical Functional Materials, School of Chemistry and Materials Science, Nanjing Normal University, Nanjing, 210023, China
| | - Linfei Ding
- Advanced Analysis and Testing Center, Nanjing Forestry University, Nanjing, 210037, China
| | - Hao Li
- Advanced Institute for Materials Research (WPI-AIMR), Tohoku University, Sendai, 980-8577, Japan
| | - Yawen Tang
- Jiangsu Key Laboratory of New Power Batteries, Jiangsu Collaborative Innovation Center of Biomedical Functional Materials, School of Chemistry and Materials Science, Nanjing Normal University, Nanjing, 210023, China
| | - Gengtao Fu
- Jiangsu Key Laboratory of New Power Batteries, Jiangsu Collaborative Innovation Center of Biomedical Functional Materials, School of Chemistry and Materials Science, Nanjing Normal University, Nanjing, 210023, China
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Houston PL, Nandi A, Bowman JM. A Machine Learning Approach for Rate Constants. III. Application to the Cl( 2P) + CH 4 → CH 3 + HCl Reaction. J Phys Chem A 2022; 126:5672-5679. [PMID: 35960874 DOI: 10.1021/acs.jpca.2c04376] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/28/2022]
Abstract
The temperature dependence of the thermal rate constant for the reaction Cl(3P) + CH4 → HCl + CH3 is calculated using a Gaussian Process machine learning (ML) approach to train on and predict thermal rate constants over a large temperature range. Following procedures developed in two previous reports, we use a training data set of approximately 40 reaction/potential surface combinations, each of which is used to calculate the corresponding database of rate constant at approximately eight temperatures. For the current application, we train on the entire data set and then predict the temperature dependence of the title reaction employing a "split" data set for correction at low and high temperatures to capture both tunneling and recrossing. The results are an improvement on recent RPMD calculations compared to accurate quantum ones, using the same high-level ab initio potential energy surface. Both tunneling at low temperatures and significant recrossing at high temperatures are observed to influence the rate constants. The recrossing effects, which are not described by TST and even sophisticated tunneling corrections, do appear in experiment at temperatures above around 600 K. The ML results describe these effects and in fact merge at 600 K with RPMD results (which can describe recrossing), and both are close to experiment at the highest experimental temperatures. These results are in accord with a recent high-level experiment-theory study of this reaction.
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Affiliation(s)
- Paul L Houston
- Department of Chemistry and Chemical Biology, Cornell University, Ithaca, New York 14853, United States.,Department of Chemistry and Biochemistry, Georgia Institute of Technology, Atlanta, Georgia 30332, United States
| | - Apurba Nandi
- Cherry L. Emerson Center for Scientific Computation and Department of Chemistry, Emory University, Atlanta, Georgia 30322, United States
| | - Joel M Bowman
- Cherry L. Emerson Center for Scientific Computation and Department of Chemistry, Emory University, Atlanta, Georgia 30322, United States
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Klippenstein SJ. Spiers Memorial Lecture: theory of unimolecular reactions. Faraday Discuss 2022; 238:11-67. [DOI: 10.1039/d2fd00125j] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/21/2022]
Abstract
One hundred years ago, at an earlier Faraday Discussion meeting, Lindemann presented a mechanism that provides the foundation for contemplating the pressure dependence of unimolecular reactions. Since that time, our...
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Hansen AS, Bhagde T, Moore KB, Moberg DR, Jasper AW, Georgievskii Y, Vansco MF, Klippenstein SJ, Lester MI. Watching a hydroperoxyalkyl radical (•QOOH) dissociate. Science 2021; 373:679-682. [PMID: 34353951 DOI: 10.1126/science.abj0412] [Citation(s) in RCA: 13] [Impact Index Per Article: 4.3] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/18/2021] [Accepted: 06/22/2021] [Indexed: 11/02/2022]
Abstract
A prototypical hydroperoxyalkyl radical (•QOOH) intermediate, transiently formed in the oxidation of volatile organic compounds, was directly observed through its infrared fingerprint and energy-dependent unimolecular decay to hydroxyl radical and cyclic ether products. Direct time-domain measurements of •QOOH unimolecular dissociation rates over a wide range of energies were found to be in accord with those predicted theoretically using state-of-the-art electronic structure characterizations of the transition state barrier region. Unimolecular decay was enhanced by substantial heavy-atom tunneling involving O-O elongation and C-C-O angle contraction along the reaction pathway. Master equation modeling yielded a fully a priori prediction of the pressure-dependent thermal unimolecular dissociation rates for the •QOOH intermediate-again increased by heavy-atom tunneling-which are required for global models of atmospheric and combustion chemistry.
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Affiliation(s)
- Anne S Hansen
- Department of Chemistry, University of Pennsylvania, Philadelphia, PA 19104, USA
| | - Trisha Bhagde
- Department of Chemistry, University of Pennsylvania, Philadelphia, PA 19104, USA
| | - Kevin B Moore
- Chemical Sciences and Engineering Division, Argonne National Laboratory, Lemont, IL 60439, USA
| | - Daniel R Moberg
- Chemical Sciences and Engineering Division, Argonne National Laboratory, Lemont, IL 60439, USA
| | - Ahren W Jasper
- Chemical Sciences and Engineering Division, Argonne National Laboratory, Lemont, IL 60439, USA
| | - Yuri Georgievskii
- Chemical Sciences and Engineering Division, Argonne National Laboratory, Lemont, IL 60439, USA
| | - Michael F Vansco
- Department of Chemistry, University of Pennsylvania, Philadelphia, PA 19104, USA
| | - Stephen J Klippenstein
- Chemical Sciences and Engineering Division, Argonne National Laboratory, Lemont, IL 60439, USA.
| | - Marsha I Lester
- Department of Chemistry, University of Pennsylvania, Philadelphia, PA 19104, USA.
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