电化学（中英文） ›› 2022, Vol. 28 ›› Issue (2): 2108511. doi: 10.13208/j.electrochem.210851
所属专题： “理论计算模拟”专题文章； “电催化和燃料电池”专题文章； iSAIEC 2023； “AI for Electrochemistry”专题文章
• 综述 • 上一篇
李吉利1, 李晔飞1,*(
), 刘智攀1,2,*()
收稿日期:2021-11-04
修回日期:2021-12-21
出版日期:2022-02-28
发布日期:2022-01-02
Ji-Li Li1, Ye-Fei Li1,*(), Zhi-Pan Liu1,2,*()
Received:2021-11-04
Revised:2021-12-21
Published:2022-02-28
Online:2022-01-02
Contact:
*Ye-Fei Li, E-mail:
摘要：
电化学中的理论计算模拟对于从原子水平理解电化学过程中的机制至关重要,它可以弥补许多实验上无法解释的现象,如果能在原子尺度上确定理解反应的活性中心,得到电极或电催化剂结构的演变过程,建立反应的微观机理,从根本上解决电极氧化和腐蚀的问题,提高电化学催化剂的活性和稳定性,从而设计更高效的电催化剂。然而,电化学的理论计算模拟中仍然存在诸多问题,例如,溶剂化效应的实现、电极/电解质（金属/溶液）界面之间合适的模拟模型和方法、电化学过程中的结构演化以及如何降低结构计算的计算代价等。在这里,我们回顾了电化学建模方法的最新进展以及我们小组通过使用修正的泊松-玻尔兹曼连续介质溶剂化模型模拟溶剂化效应对溶剂化效应和模型进行改进。同时为了减少计算代价,我们更关注机器学习在电化学模拟中的应用,主要分为两个部分,即通过快速对多种不同组分的能量进行计算并筛选出合适组分,但是无法得到实际的结构演变情况。另一个是通过快速结构取样得到不同组分不同的结构变化能够更为直观的获得结构的演变过程,从而揭示反应的机理。我们以本课题组开发的SSW-NN的方法为例,总结了基于机器学习的原子模拟在电化学方面的应用,介绍了SSW-NN,模拟电化学反应条件下电极和电催化剂的氧化和腐蚀,并阐明了催化剂结构的活性和稳定性。
李吉利, 李晔飞, 刘智攀. 电化学理论模拟方法的发展及其在铂基燃料电池中的应用[J]. 电化学（中英文）, 2022, 28(2): 2108511.
Ji-Li Li, Ye-Fei Li, Zhi-Pan Liu. Recent Advances in Electrochemical Kinetics Simulations and Their Applications in Pt-based Fuel Cells[J]. Journal of Electrochemistry, 2022, 28(2): 2108511.
Figure 1.
(A) Gouy-Chapman-Stern representation of electric double layer[10]. (B) The periodic slab employed with the double-reference method to determine the potential[29]. Reproduced with permission of Ref. 10 (A) and Ref. 29 (B). Copyright with 2014 American Chemical Society and Copyright with 2007 Springer Science Business Media, LLC. (color on line)
Figure 2.
Contour plots of total electrostatic potential for formate-adsorbed Pt(111) (A) without and (B) with the continuum solvation shell; (C) MD snapshot for the formate-adsorbed Pt(111)/H2O system taken after 10 ps NVT simulation at 300 K[16]. Reproduced with permission of Ref 16. Copyright with 2009 American Chemical Society. (color on line)
Figure 3.
(A) Illustration of the SSW global optimization. (B) Scheme for the Behlar NN architecture[39]. (C) Procedure for generating the training dataset using SSW global optimization. Reproduced with permission of Ref. 39 (B). Copyright with 2017 Royal Society of Chemistry. (color on line)
Figure 4.
(A) Free energy profiles for ORR on Pt(111) at 0.8 V and the structural snapshots of *O2, *OOH, *O, TS1, TS2, and TS3. (B) Plots for the free energy barrier (ΔGa) vs. potential (U) of two reaction pathways for ORR on Pt(111). (C) Tafel curve and the contributions from two reaction pathways. The insert in (C) is the I-V curve with the maximum limiting current at the low potentials being ~ -3.9 mA·cm-2 as determined from experiment[42]. Reproduced with permission of Ref 42 (A) and Ref 42 (B-C). Copyright with 2012 American Chemical Society and Copyright with 2012 American Chemical Society. (color on line)
Figure 5.
Free energy diagram and the stable structures for each stage. (A) The O coverage; (B) The quasidifferential oxygen adsorption energy[44]; (C-D) Formation free energy of the phase-II (ΔGII) and the phase-III (ΔGII) as described in Reactions (3.9) and (3.10)[44]; (E) Structures for the surface adsorption phase (the phase-I), subsurface O phase (the phase-II), and surface vacancy phase (the phase-III) for the 0.625 ML O, 0.67 ML O and 1 ML O covered Pt(111), Pt(211), and Pt(100) surfaces at 1.2 V, respectively. Blue balls: subsurface Pt; yellow balls: surface Pt; red balls: O[44]. (F) Atomic model of Pt(730) plane with a high density of stepped surface atoms[4]. (G) Surface phase diagram of Pt(111) and Pt2M (M = Sc, Ti, Zr, Nb, Mo, Pd, Ag) alloys[45]. (H) Schematic free energy profile for the O-OH dissociation pathway for ORR on Pt(111) and Pt2Mo(111)[45]. Reproduced with permission of Ref. 44 (A-E), Ref. 4 (F), Ref. 45 (G) and Ref. 45 (H). Copyright with 2010 American Chemical Society, Copyright with 2007 The American Asso-ciation for the Advancement of Science,Copyright with 2011 Royal Society of Chemistry and Copyright with 2011 Royal Society of Chemistry. (color on line)
Figure 6.
(A) The size vs. shape diagram for Pt nanoparticles from experiment (black) and theory (blue)[46]. (B) Calculated MA of Pt nanoparticles[46]. (C) Surface composition of Pt201 by combining thermodynamics and the steady-state kinetics analysis using DFT/CM-MPB calculations[46]. Blue balls: Pt; red balls: O. Reproduced with permission of Ref. 46(A-C). Copyright with 2013 Royal Society of Chemistry. (color on line)
Figure 7.
Structures and energetic profiles for the evolution of Pt3Ni(111) under ORR conditions at 0.9 V vs. RHE. (A) Atomic str-uctures of intermediate states. The atoms above the (111) surface plane are depicted in the ball-and-stick style, while other atoms are depicted in the CPK style. (B) Energetic profiles for the evolution of Pt3Ni(111). Colors in (A): Blue balls are Pt; Violet balls are Ni; Red balls are O. (color on line)
| [1] |
Yang Z G, Zhang J L, Kintner-Meyer M C W, Lu X C, Choi D, Lemmon J P, Liu J. Electrochemical energy storage for green grid[J]. Chem. Rev., 2011, 111(5):3577-3613.
doi: 10.1021/cr100290v URL |
| [2] |
Jukk K, Alexeyeva N, Ritslaid P, Kozlova J, Sammelselg V, Tammeveski K. Electrochemical reduction of oxygen on heat-treated Pd nanoparticle/multi-walled carbon nano-tube composites in alkaline solution[J]. Electrocatalysis, 2013, 4(1):42-48.
doi: 10.1007/s12678-012-0117-y URL |
| [3] |
Gasteiger H A, Markovic N M. Just a dream-or future reality[J]. Science, 2009, 324(5923):48-49.
doi: 10.1126/science.1172083 pmid: 19342578 |
| [4] |
Tian N, Zhou Z Y, Sun S G, Ding Y, Wang Z L. Synjournal of tetrahexahedral platinum nanocrystals with high-index facets and high electro-oxidation activity[J]. Science, 2007, 316(5825):732-735.
pmid: 17478717 |
| [5] |
Stamenkovic V R, Mun B S, Mayrhofer K J J, Ross P N, Markovic N M. Effect of surface composition on electronic structure, stability, and electrocatalytic properties of Pt-transition metal alloys: Pt-skin versus Pt-skeleton surfaces[J]. J. Am. Chem. Soc., 2006, 128(27):8813-8819.
pmid: 16819874 |
| [6] |
Gasteiger H A, Kocha S S, Sompalli B, Wagner F T. Activity benchmarks and requirements for Pt, Pt-alloy, and non-Pt oxygen reduction catalysts for PEMFCs[J]. Appl. Catal. B, 2005, 56(1):9-35.
doi: 10.1016/j.apcatb.2004.06.021 URL |
| [7] |
Zhu J, Hu L, Zhao P, Lee L Y S, Wong K Y. Recent advances in electrocatalytic hydrogen evolution using nanoparticles[J]. Chem. Rev., 2020, 120(2):851-918.
doi: 10.1021/acs.chemrev.9b00248 URL |
| [8] |
Lim B, Jiang M J, Camargo P H C, Cho E C, Tao J, Lu X M, Zhu Y M, Xia Y N. Pd-Pt bimetallic nanodendrites with high activity for oxygen reduction[J]. Science, 2009, 324(5932):1302-1305.
doi: 10.1126/science.1170377 URL |
| [9] |
Zhang J, Sasaki K, Sutter E, Adzic R R. Stabilization of platinum oxygen-reduction electrocatalysts using gold clusters[J]. Science, 2007, 315(5809):220-222.
pmid: 17218522 |
| [10] |
Fang Y H, Liu Z P. Tafel kinetics of electrocatalytic reactions: from experiment to first-principles[J]. ACS Catal., 2014, 4(12):4364-4376.
doi: 10.1021/cs501312v URL |
| [11] |
Gouy M. Sur la constitution de la charge électrique à la surface d'un électrolyte[J]. J. Phys. Theor. Appl., 1910, 9(1):457-468.
doi: 10.1051/jphystap:019100090045700 URL |
| [12] |
Chapman D L, LI. A contribution to the theory of electrocapillarity[J]. Philos. Mag., 1913, 25(148):475-481.
doi: 10.1080/14786440408634187 URL |
| [13] | Stern O. Zur theorie der elektrolytischen doppelschicht[J]. Elektrochem. Angew. Phys. Chem., 1924, 30(21-22):508-516. |
| [14] |
Furuya N, Shibata M. Structural changes at various Pt single crystal surfaces with potential cycles in acidic and alkaline solutions[J]. J. Electroanal. Chem., 1999, 467(1):85-91.
doi: 10.1016/S0022-0728(99)00077-7 URL |
| [15] | Basdogan Y, Maldonado A M, Keith J A. Advances and challenges in modeling solvated reaction mechanisms for renewable fuels and chemicals[J]. Wires Comput. Mol. Sci., 2020, 10(2):e1446. |
| [16] |
Wang H F, Liu Z P. Formic acid oxidation at Pt/H2O interface from periodic DFT calculations integrated with a continuum solvation model[J]. J. Phys. Chem. C, 2009, 113(40):17502-17508.
doi: 10.1021/jp9059888 URL |
| [17] |
Li Y F, Liu Z P, Liu L, Gao W. Mechanism and activity of photocatalytic oxygen evolution on titania anatase in aqueous surroundings[J]. J. Am. Chem. Soc., 2010, 132(37):13008-13015.
doi: 10.1021/ja105340b URL |
| [18] |
Fang Y H, Liu Z P. Electrochemical reactions at the electrode/solution interface: theory and applications to water electrolysis and oxygen reduction[J]. Sci. China Chem., 2010, 53(3):543-552.
doi: 10.1007/s11426-010-0047-6 URL |
| [19] |
Shang C, Liu Z P. Stochastic surface walking method for structure prediction and pathway searching[J]. J. Chem. Theory Comput., 2013, 9(3):1838-1845.
doi: 10.1021/ct301010b URL |
| [20] |
Shang C, Liu Z P. Constrained broyden minimization combined with the dimer method for locating transition state of complex reactions[J]. J. Chem. Theory Comput., 2010, 6(4):1136-1144.
doi: 10.1021/ct9005147 URL |
| [21] |
Artrith N, Urban A, Ceder G. Constructing first-principles phase diagrams of amorphous LixSi using machine-learning-assisted sampling with an evolutionary algorithm[J]. J. Chem. Phys., 2018, 148(24):241711.
doi: 10.1063/1.5017661 URL |
| [22] |
Wales D J, Doye J P K. Global optimization by basin-hopping and the lowest energy structures of lennard-Jones clusters containing up to 110 atoms[J]. J. Phys. Chem. A, 1997, 101(28):5111-5116.
doi: 10.1021/jp970984n URL |
| [23] |
Hart G L W, Mueller T, Toher C, Curtarolo S. Machine learning for alloys[J]. Nat. Rev. Mater., 2021, 6(8):730-755.
doi: 10.1038/s41578-021-00340-w URL |
| [24] |
Norskov J K, Rossmeisl J, Logadottir A, Lindqvist L, Kit-chin J R, Bligaard T, Jonsson H. Origin of the overpotential for oxygen reduction at a fuel-cell cathode[J]. J. Phys. Chem. B, 2004, 108(46):17886-17892.
doi: 10.1021/jp047349j URL |
| [25] |
Lozovoi A Y, Alavi A, Kohanoff J, Lynden-Bell R M. Ab initio simulation of charged slabs at constant chemical potential[J]. J. Chem. Phys., 2001, 115(4):1661-1669.
doi: 10.1063/1.1379327 URL |
| [26] |
Nörskov J K, Bligaard T, Rossmeisl J, Christensen C H. Towards the computational design of solid catalysts[J]. Nat. Chem., 2009, 1(1):37-46.
doi: 10.1038/nchem.121 URL |
| [27] |
Filhol J S, Neurock M. Elucidation of the electrochemical activation of water over Pd by first principles[J]. Angew. Chem. Int. Ed., 2006, 45(3):402-406.
doi: 10.1002/(ISSN)1521-3773 URL |
| [28] |
Reiss H, Heller A. The absolute potential of the standard hydrogen electrode: a new estimate[J]. J. Phys. Chem, 1985, 89(20):4207-4213.
doi: 10.1021/j100266a013 URL |
| [29] |
Janik M J, Taylor C D, Neurock M. First principles analysis of the electrocatalytic oxidation of methanol and carbon monoxide[J]. Top. Catal., 2007, 46(3):306-319.
doi: 10.1007/s11244-007-9004-9 URL |
| [30] |
Fattebert J L, Gygi F. Density functional theory for efficient ab initio molecular dynamics simulations in solution[J]. J. Comput. Chem., 2002, 23(6):662-666.
pmid: 11939598 |
| [31] |
Fattebert J L, Gygi F. Linear-scaling first-principles mol-ecular dynamics with plane-waves accuracy[J]. Phys. Rev. B, 2006, 73(11):115124.
doi: 10.1103/PhysRevB.73.115124 URL |
| [32] |
Fang Y H, Liu Z P. Surface phase diagram and oxygen coupling kinetics on flat and stepped Pt surfaces under electrochemical potentials[J]. J. Phys. Chem. C, 2009, 113(22):9765-9772.
doi: 10.1021/jp901091a URL |
| [33] |
Fang Y H, Wei G F, Liu Z P. Theoretical modeling of electrode/electrolyte interface from first-principles periodic continuum solvation method[J]. Catal. Today, 2013, 202:98-104.
doi: 10.1016/j.cattod.2012.04.055 URL |
| [34] |
Shang C, Zhang X J, Liu Z P. Stochastic surface walking method for crystal structure and phase transition pathway prediction[J]. Phys. Chem. Chem. Phys., 2014, 16(33):17845-17856.
doi: 10.1039/C4CP01485E URL |
| [35] |
Wei G F, Liu Z P. Restructuring and hydrogen evolution on Pt nanoparticle[J]. Chem. Sci., 2015, 6(2):1485-1490.
doi: 10.1039/C4SC02806F URL |
| [36] |
Li Y F, Liu Z P. Particle size, shape and activity for photocatalysis on titania anatase nanoparticles in aqueous surroundings[J]. J. Am. Chem. Soc., 2011, 133(39):15743-15752.
doi: 10.1021/ja206153v URL |
| [37] |
Zhang X J, Shang C, Liu Z P. Stochastic surface walking reaction sampling for resolving heterogeneous catalytic reaction network: A revisit to the mechanism of water-gas shift reaction on Cu[J]. J. Chem. Phys., 2017, 147(15):152706.
doi: 10.1063/1.4989540 URL |
| [38] |
Behler J. First principles neural network potentials for reactive simulations of large molecular and condensed systems[J]. Angew. Chem. Int. Ed., 2017, 56(42):12828-12840.
doi: 10.1002/anie.201703114 URL |
| [39] |
Huang S D, Shang C, Zhang X J, Liu Z P. Material discovery by combining stochastic surface walking global optimization with a neural network[J]. Chem. Sci., 2017, 8(9):6327-6337.
doi: 10.1039/C7SC01459G URL |
| [40] | Huang S D, Shang C, Kang P L, Zhang X J, Liu Z P. LASP: Fast global potential energy surface exploration[J]. Wires. Comput. Mol. Sci., 2019, 9(6):e1415. |
| [41] |
Hansen H A, Rossmeisl J, Nörskov J K. Surface pourbaix diagrams and oxygen reduction activity of Pt, Ag and Ni(111) surfaces studied by DFT[J]. Phys. Chem. Chem. Phys., 2008, 10(25):3722-3730.
doi: 10.1039/b803956a pmid: 18563233 |
| [42] |
Wei G F, Fang Y H, Liu Z P. First principles tafel kinetics for resolving key parameters in optimizing oxygen electrocatalytic reduction catalyst[J]. J. Phys. Chem. C, 2012, 116(23):12696-12705.
doi: 10.1021/jp3034616 URL |
| [43] |
He Q G, Yang X F, Chen W, Mukerjee S, Koel B, Chen S W. Influence of phosphate anion adsorption on the kinetics of oxygen electroreduction on low index Pt(hkl) single crystals[J]. Phys. Chem. Chem. Phys., 2010, 12(39):12544-12555.
doi: 10.1039/c0cp00433b URL |
| [44] |
Fang Y H, Liu Z P. Toward anticorrosion electrodes: site-selectivity and self-acceleration in the electrochemical corrosion of platinum[J]. J. Phys. Chem. C, 2010, 114(9):4057-4062.
doi: 10.1021/jp9111734 URL |
| [45] |
Wei G F, Liu Z P. Towards active and stable oxygen reduction cathodes: a density functional theory survey on Pt2M skin alloys[J]. Energy Environ. Sci., 2011, 4(4):1268-1272.
doi: 10.1039/c0ee00762e URL |
| [46] |
Wei G F, Liu Z P. Optimum nanoparticles for electrocatalytic oxygen reduction: the size, shape and new design[J]. Phys. Chem. Chem. Phys., 2013, 15(42):18555-18561.
doi: 10.1039/c3cp53758g URL |
| [47] |
Leontyev I N, Belenov S V, Guterman V E, Haghi-Ashtiani P, Shaganov A P, Dkhil B. Catalytic activity of carbon-supported Pt nanoelectrocatalysts. Why reducing the size of Pt nanoparticles is not always beneficial[J]. J. Phys. Chem. C, 2011, 115(13):5429-5434.
doi: 10.1021/jp1109477 URL |
| [48] |
Fang Y H, Song D D, Li H X, Liu Z P. Structure and activity of potential-dependent Pt(110) surface phases revealed from machine-learning atomic simulation[J]. J. Phys. Chem. C, 2021, 125(20):10955-10963.
doi: 10.1021/acs.jpcc.1c02222 URL |
| [49] |
Stamenkovic V R, Fowler B, Mun B S, Wang G, Ross P N, Lucas C A, Markovic N M. Improved oxygen reduction activity on Pt3Ni(111) via increased surface site avai-lability[J]. Science, 2007, 315(5811):493-497.
doi: 10.1126/science.1135941 pmid: 17218494 |
| [1] | 王锋, 程俊. 机器学习加速氧化还原电位和酸度常数计算[J]. 电化学（中英文）, 2024, 30(2): 2307181-. |
| [2] | 朱振威, 邱景义, 王莉, 曹高萍, 何向明, 王京, 张浩. 人工智能在锂离子电池研发中的应用[J]. 电化学（中英文）, 2022, 28(12): 2219003-. |
| 阅读次数 | ||||||
|
全文 |
|
|||||
|
摘要 |
|
|||||
