51
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A theoretical investigation on the influence of anatase support and vanadia dispersion on the oxidative dehydrogenation of propane to propene. ACTA ACUST UNITED AC 2013. [DOI: 10.1016/j.molcata.2013.08.011] [Citation(s) in RCA: 16] [Impact Index Per Article: 1.3] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/24/2022]
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52
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Tuning the catalytic performance of carbon nanotubes by tuning the conjugation between the π orbitals of carbon nanotubes and the active oxygenic functional groups. CHINESE JOURNAL OF CATALYSIS 2013. [DOI: 10.1016/s1872-2067(12)60627-5] [Citation(s) in RCA: 7] [Impact Index Per Article: 0.6] [Reference Citation Analysis] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 11/18/2022]
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53
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Zhang XJ, Shang C, Liu ZP. From Atoms to Fullerene: Stochastic Surface Walking Solution for Automated Structure Prediction of Complex Material. J Chem Theory Comput 2013; 9:3252-60. [PMID: 26584000 DOI: 10.1021/ct400238j] [Citation(s) in RCA: 54] [Impact Index Per Article: 4.5] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/28/2022]
Abstract
It is of general concern whether the automated structure prediction of unknown material without recourse to any knowledge from experiment is ever possible considering the daunting complexity of potential energy surface (PES) of material. Here we demonstrate that the stochastic surface walking (SSW) method can be a general and promising solution to this ultimate goal, which is applied to assemble carbon fullerenes containing up to 100 atoms (including 60, 70, 76, 78, 80, 84, 90, 96, and 100 atoms) from randomly distributed atoms, a long-standing challenge in global optimization. Combining the SSW method with a parallel replica exchange algorithm, we can locate the global minima (GM) of these large fullerenes efficiently without being trapped in numerous energy-nearly degenerate isomers. Detailed analyses on the SSW trajectories allow us to rationalize how and why the SSW method is able to explore the highly complex PES, which highlights the abilities of SSW method for surmounting the high barrier and the preference of SSW trajectories to the low energy pathways. The work demonstrates that the parallel SSW method is a practical tool for predicting unknown materials.
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Affiliation(s)
- Xiao-Jie Zhang
- Shanghai Key Laboratory of Molecular Catalysis and Innovative Materials, Department of Chemistry, Key Laboratory of Computational Physical Science (Ministry of Education), Fudan University , Shanghai 200433, China
| | - Cheng Shang
- Shanghai Key Laboratory of Molecular Catalysis and Innovative Materials, Department of Chemistry, Key Laboratory of Computational Physical Science (Ministry of Education), Fudan University , Shanghai 200433, China
| | - Zhi-Pan Liu
- Shanghai Key Laboratory of Molecular Catalysis and Innovative Materials, Department of Chemistry, Key Laboratory of Computational Physical Science (Ministry of Education), Fudan University , Shanghai 200433, China
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54
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Leng J, Gao W, Shang C, Liu ZP. Efficient softest mode finding in transition states calculations. J Chem Phys 2013; 138:094110. [DOI: 10.1063/1.4792644] [Citation(s) in RCA: 5] [Impact Index Per Article: 0.4] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/14/2022] Open
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55
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Fang YH, Wei GF, Liu ZP. Theoretical modeling of electrode/electrolyte interface from first-principles periodic continuum solvation method. Catal Today 2013. [DOI: 10.1016/j.cattod.2012.04.055] [Citation(s) in RCA: 60] [Impact Index Per Article: 5.0] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 10/28/2022]
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56
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Shang C, Liu ZP. Stochastic Surface Walking Method for Structure Prediction and Pathway Searching. J Chem Theory Comput 2013; 9:1838-45. [DOI: 10.1021/ct301010b] [Citation(s) in RCA: 178] [Impact Index Per Article: 14.8] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/28/2022]
Affiliation(s)
- Cheng Shang
- Shanghai Key Laboratory of Molecular Catalysis and
Innovative Materials, Department of Chemistry, Key Laboratory of Computational
Physical Science (Ministry of Education), Fudan University, Shanghai
200433, China
| | - Zhi-Pan Liu
- Shanghai Key Laboratory of Molecular Catalysis and
Innovative Materials, Department of Chemistry, Key Laboratory of Computational
Physical Science (Ministry of Education), Fudan University, Shanghai
200433, China
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57
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Wei GF, Liu ZP. Optimum nanoparticles for electrocatalytic oxygen reduction: the size, shape and new design. Phys Chem Chem Phys 2013; 15:18555-61. [DOI: 10.1039/c3cp53758g] [Citation(s) in RCA: 42] [Impact Index Per Article: 3.5] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/16/2022]
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58
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Nikodem A, Matveev AV, Zheng BX, Rösch N. Efficient Two-Step Procedures for Locating Transition States of Surface Reactions. J Chem Theory Comput 2012; 9:588-99. [DOI: 10.1021/ct300728a] [Citation(s) in RCA: 7] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/16/2022]
Affiliation(s)
- Astrid Nikodem
- Department Chemie and Catalysis
Research Center, Technische Universität München, 85747
Garching, Germany
| | - Alexei V. Matveev
- Department Chemie and Catalysis
Research Center, Technische Universität München, 85747
Garching, Germany
| | - Bo-Xiao Zheng
- Department Chemie and Catalysis
Research Center, Technische Universität München, 85747
Garching, Germany
- Department
of Chemistry and
Key Laboratory of Organic Optoelectronics and Molecular Engineering
of Ministry of Education, Tsinghua University, Beijing 100084, China
| | - Notker Rösch
- Department Chemie and Catalysis
Research Center, Technische Universität München, 85747
Garching, Germany
- Institute of High Performance
Computing, 1 Fusionopolis Way, #16-16 Connexis, Singapore 138632,
Singapore
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59
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Chen D, Fang YH, Liu ZP. Searching for active binary rutile oxide catalyst for water splitting from first principles. Phys Chem Chem Phys 2012; 14:16612-7. [PMID: 22941355 DOI: 10.1039/c2cp42149f] [Citation(s) in RCA: 13] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/21/2022]
Abstract
Water electrolysis is an important route to large-scale hydrogen production using renewable energy, in which the oxygen evolution reaction (OER: 2H(2)O → O(2) + 4H(+) + 4e(-)) causes the largest energy loss in traditional electrocatalysts involving Ru-Ir mixed oxides. Following our previous mechanistic studies on the OER on RuO(2)(110) (J. Am. Chem. Soc. 2010, 132, 18214), this work aims to provide further insight into the key parameters relevant to the activity of OER catalysts by investigating a group of rutile-type binary metal oxides, including RuNiO(2), RuCoO(2), RuRhO(2), RuIrO(2) and OsIrO(2). Two key aspects are focused on, namely the surface O coverage at the relevant potential conditions and the kinetics of H(2)O activation on the O-covered surfaces. The O coverage for all the oxides investigated here is found to be 1 ML at the concerned potential (1.23 V) with all the exposed metal cations being covered by terminal O atoms. The calculated free energy barrier for the H(2)O dissociation on the O covered surfaces varies significantly on different surfaces. The highest OER activity occurs at RuCoO(2) and RuNiO(2) oxides with a predicted activity about 500 times higher than pure RuO(2). On these oxides, the surface bridging O near the terminal O atom has a high activity for accepting the H during H(2)O splitting. It is concluded that while the differential adsorption energy of the terminal O atom influences the OER activity to the largest extent, the OER activity can still be tuned by modifying the electronic structure of surface bridging O.
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Affiliation(s)
- Dong Chen
- Shanghai Key Laboratory of Molecular Catalysis and Innovative Materials, Department of Chemistry, Fudan University, Shanghai 200433, China
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60
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Shang C, Liu ZP. Constrained Broyden Dimer Method with Bias Potential for Exploring Potential Energy Surface of Multistep Reaction Process. J Chem Theory Comput 2012; 8:2215-22. [DOI: 10.1021/ct300250h] [Citation(s) in RCA: 47] [Impact Index Per Article: 3.6] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/28/2022]
Affiliation(s)
- Cheng Shang
- Shanghai Key Laboratory of Molecular Catalysis and
Innovative Materials, Department of Chemistry, Key Laboratory of Computational
Physical Science (Ministry of Education), Fudan University, Shanghai
200433, China
| | - Zhi-Pan Liu
- Shanghai Key Laboratory of Molecular Catalysis and
Innovative Materials, Department of Chemistry, Key Laboratory of Computational
Physical Science (Ministry of Education), Fudan University, Shanghai
200433, China
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61
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Mechanism and kinetics for methanol synthesis from CO2/H2 over Cu and Cu/oxide surfaces: Recent investigations by first-principles-based simulation. ACTA ACUST UNITED AC 2011. [DOI: 10.1007/s11458-011-0250-9] [Citation(s) in RCA: 6] [Impact Index Per Article: 0.4] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 10/17/2022]
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62
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Shang C, Liu ZP. Origin and Activity of Gold Nanoparticles as Aerobic Oxidation Catalysts in Aqueous Solution. J Am Chem Soc 2011; 133:9938-47. [DOI: 10.1021/ja203468v] [Citation(s) in RCA: 185] [Impact Index Per Article: 13.2] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 02/07/2023]
Affiliation(s)
- Cheng Shang
- Shanghai Key Laboratory of Molecular Catalysis and Innovative Materials, Department of Chemistry, Key Laboratory for Computational Physical Sciences (Ministry of Education), Fudan University, Shanghai 200433, China
| | - Zhi-Pan Liu
- Shanghai Key Laboratory of Molecular Catalysis and Innovative Materials, Department of Chemistry, Key Laboratory for Computational Physical Sciences (Ministry of Education), Fudan University, Shanghai 200433, China
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63
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Schlegel HB. Geometry optimization. WILEY INTERDISCIPLINARY REVIEWS-COMPUTATIONAL MOLECULAR SCIENCE 2011. [DOI: 10.1002/wcms.34] [Citation(s) in RCA: 186] [Impact Index Per Article: 13.3] [Reference Citation Analysis] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 11/07/2022]
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64
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Fang YH, Liu ZP. Mechanism and Tafel Lines of Electro-Oxidation of Water to Oxygen on RuO2(110). J Am Chem Soc 2010; 132:18214-22. [DOI: 10.1021/ja1069272] [Citation(s) in RCA: 424] [Impact Index Per Article: 28.3] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/28/2022]
Affiliation(s)
- Ya-Hui Fang
- Shanghai Key Laboratory of Molecular Catalysis and Innovative Materials, Department of Chemistry, Key Laboratory of Computational Physical Science (Ministry of Education), Fudan University, Shanghai 200433, People’s Republic of China
| | - Zhi-Pan Liu
- Shanghai Key Laboratory of Molecular Catalysis and Innovative Materials, Department of Chemistry, Key Laboratory of Computational Physical Science (Ministry of Education), Fudan University, Shanghai 200433, People’s Republic of China
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65
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Li YF, Liu ZP, Liu L, Gao W. Mechanism and Activity of Photocatalytic Oxygen Evolution on Titania Anatase in Aqueous Surroundings. J Am Chem Soc 2010; 132:13008-15. [DOI: 10.1021/ja105340b] [Citation(s) in RCA: 280] [Impact Index Per Article: 18.7] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/29/2022]
Affiliation(s)
- Ye-Fei Li
- Shanghai Key Laboratory of Molecular Catalysis and Innovative Materials, Department of Chemistry, Key Laboratory for Computational Physical Sciences, Ministry of Education, Fudan University, Shanghai 200433, China, and School of Mathematical Sciences, Fudan University, Shanghai 200433, China
| | - Zhi-Pan Liu
- Shanghai Key Laboratory of Molecular Catalysis and Innovative Materials, Department of Chemistry, Key Laboratory for Computational Physical Sciences, Ministry of Education, Fudan University, Shanghai 200433, China, and School of Mathematical Sciences, Fudan University, Shanghai 200433, China
| | - LuLu Liu
- Shanghai Key Laboratory of Molecular Catalysis and Innovative Materials, Department of Chemistry, Key Laboratory for Computational Physical Sciences, Ministry of Education, Fudan University, Shanghai 200433, China, and School of Mathematical Sciences, Fudan University, Shanghai 200433, China
| | - Weiguo Gao
- Shanghai Key Laboratory of Molecular Catalysis and Innovative Materials, Department of Chemistry, Key Laboratory for Computational Physical Sciences, Ministry of Education, Fudan University, Shanghai 200433, China, and School of Mathematical Sciences, Fudan University, Shanghai 200433, China
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