定向Monte Carlo格点搜索算法用于氧化铝团簇(Al2O3)n (n=1~50)的结构搜索

doi:10.6023/A21050207

摘要/Abstract

氧化铝纳米团簇在众多技术应用中日益受到重视, 找到其最优结构对进一步的研究非常重要. 本工作提出了一种定向Monte Carlo格点搜索算法用于搜索不同氧化铝晶体(α, θ和δ)内的不同尺寸的氧化铝纳米团簇的结构, 并对结构进行了分析比较. 通过定向移动策略, 定向Monte Carlo格点搜索中每一步都是“有效”移动, 极大地增加了搜索效率. 研究结果发现α氧化铝团簇形成一种多层结构, θ和δ氧化铝团簇形成一种单层薄膜结构. θ和δ氧化铝团簇的二阶能量差分存在奇偶震荡, 偶数尺寸的氧化铝团簇具有相对更高的稳定性. 通过相对能量比较发现相同尺寸下θ和δ氧化铝团簇薄膜结构比α氧化铝团簇结构更稳定, 在对这种薄膜进行第一性原理计算后进一步验证这种薄膜具有良好的稳定性和抗氧化性.

关键词: 氧化铝团簇, 定向Monte Carlo, 结构搜索, 稳定性, 单层薄膜结构

Alumina nanoclusters have attracted increasing attention in many technical applications due to their excellent properties in optics, electricity, thermodynamics, chemical reactions and other aspects. Therefore, it is very important to find the optimal structure for further research. In this paper, we use the directional Monte Carlo lattice search algorithm combined with Woodley's potential function to investigate the stable structures of different sizes of alumina nanoclusters in different crystal forms (α, θ and δ). In our algorithm, the lattice was chosen from supercells which the primitive lattice cell from the inorganic crystal structure database (ICSD) was duplicated to generate large supercells of α, θ and δ phases. The initial random structure generated in the lattice, then the selective probability for all chosen and empty atoms is calculated based on the Boltzmann distribution of energy. In the directional Monte Carlo exchange, at elevated temperatures, the system has enough energy to cross energy barriers and find the basins, and at low temperatures, it converges to around the global minimum. After structure searching, we analyze and compare the stable structures of different crystal forms. The results show that the α-alumina clusters consist of multiple (Al₂O₃)₁ and form a multilayer structure, as the size increased, hexagonal aluminum began to form inside the cluster. The θ and δ alumina clusters form a stable monolayer thin film structure, with the increase of size, the monolayer film structure can still be maintained. To further study the relative stability of the cluster structure, we introduced a second-order energy difference. The second-order energy difference of θ and δ alumina clusters has obvious odd-even oscillation, and the even size alumina clusters have relatively higher stability due to better symmetry. α-Alumina is the most stable crystalline phase in the bulk phase, so we take the α-alumina clusters as the benchmark to compare the relative energy of alumina clusters with different crystal types. Through the comparison of relative energy, we found that the thin film structure of θ and δ alumina clusters under the same size is more stable than that of the α-alumina clusters. Therefore, we further carried out first-principles calculations on this film structure, and we found that this film structure has good kinetic and thermodynamic stability and good oxidation resistance.

Key words: alumina cluster, directional Monte Carlo, structure search, stabilization, monolayer thin film structure

引用此文

孙稷, 易玖琦, 程龙玖. 定向Monte Carlo格点搜索算法用于氧化铝团簇(Al₂O₃)_n (n=1~50)的结构搜索[J]. 化学学报, 2021, 79(9): 1154-1163.

Ji Sun, Jiuqi Yi, Longjiu Cheng. Directional Monte Carlo Lattice Search Algorithm for the Structure Search of Alumina Clusters (Al₂O₃)_n (n=1~50)[J]. Acta Chimica Sinica, 2021, 79(9): 1154-1163.

导出引用 EndNote|Reference Manager|ProCite|BibTeX|RefWorks

分享此文

图/表 14

参数	A/(eV•Å¹²)	ρ/Å	B/eV	C/(eV•Å⁶)
Al³⁺-Al³⁺	1.0		0.0	0.00
Al³⁺-O^2-	10.0	0.2649	2409.505	0.00
O^2--O^2-	1.0	0.1490	22764.000	27.88

表1. Al2O3的Buckingham势参数

Table 1. Buckingham interatomic pair potential parameters for Al2O3

图1. α-Al2O3, θ-Al2O3和δ-Al2O3三种晶型晶胞结构, 铝原子和氧原子分别由蓝灰色和红色表示, 本工作中所有结构都是用VESTA (visualization for electronic and structural analysis)绘制的[41]

Figure 1. α-Al2O3, θ-Al2O3 and δ-Al2O3 crystal cell structure, aluminum atoms and oxygen atoms are represented by blue gray and red respectively. All structures in this work have been rendered with VESTA

图2. 定向Monte Carlo格点算法流程图

Figure 2. The flow chart of the directed Monte Carlo lattice algorithm

图3. (a), (b)和(c)分别为α-(Al2O3)n n=10, 30和50时, 定向Monte Carlo和传统Monte Carlo的性能对比. 其中黑色曲线和红色曲线分别为10次独立的定向Monte Carlo和基于Markov过程Monte Carlo的最低能量结构的平均能量下降趋势

Figure 3. (a), (b) and (c) show the performance comparison of directional Monte Carlo and traditional Monte Carlo when α-(Al2O3)n n=10, 30 and 50, respectively. The black curve and the red curve respectively show the change of the average energy of the 10 directional Monte Carlo and the lowest energy structure based on Markov process Monte Carlo with the step size (MC steps)

图4. 对(Al2O3)n三种不同降温策略的收敛性比较, 其中(a) n=10, (b) n=30, (c) n=50

Figure 4. Comparison of convergence of three different cooling strategies for (Al2O3)n, where (a) n=10, (b) n=30, and (c) n=50

图5. α-(Al2O3)n的团簇结构, (a), (b)和(c)分别为n=30, 50和1时的结构. (d)和(e)为(a)虚线内截取的部分结构

Figure 5. The structure of α-(Al2O3)n cluster, (a), (b) and (c) are the structure when n=30, 50 and 1, respectively. (d) and (e) are the partial structure intercepted from the dotted line in (a)

图6. (a), (b)和(c)分别为θ-(Al2O3)n (n=8, 32和48)不同晶面的结构, (d), (e)和(f)分别为δ-Al2O3 (n=8, 32和48)不同晶面的结构

Figure 6. (a), (b) and (c) are the structures of different crystal faces of θ-(Al2O3)n (n=8, 32 and 48), and (d), (e) and (f) are the structures of different crystal faces of δ-Al2O3 (n=8, 32 and 48), respectively

图7. (a), (b)和(c)分别为θ-(Al2O3)n、δ-(Al2O3)n和α-(Al2O3)n (n=1~50)团簇的二阶能量差分, (d)为n=1~50时θ-(Al2O3)n和δ-(Al2O3)n与α-(Al2O3)n相对能量比较

Figure 7. The second order energy difference of (a) θ-(Al2O3)n, (b) δ-(Al2O3)n and (c) α-(Al2O3)n (n=1~50) clusters, respectively. Figure (d) shows the relative energy comparison of θ-(Al2O3)n and δ-(Al2O3)n with α-(Al2O3)n at (n=1~50)

图8. (a), (b)和(c)分别为θ, δ和α氧化铝部分具有较大二阶差分能的稳定结构

Figure 8. (a), (b) and (c) are the stable structures of θ, δ and α alumina with large second order difference energies, respectively

图9. θ-Al2O3单层结构的单胞左视图(a), 主视图(b), 俯视图(c). 其中红色的表示O, 灰绿色的表示Al

Figure 9. Single cell left view (a), main view (b), top view (c) of θ-Al2O3 monolayer structure. The red is O, and the gray green is Al

图10. θ-Al2O3单层在第一布里渊区内的声子色散曲线

Figure 10. Phonon dispersion curve of θ-Al2O3 monolayer in the first Brillouin region

图12. θ-Al2O3单层与氧气分子进行分子动力学模拟, 模拟时长为5 ps

Figure 12. The θ-Al2O3 monolayer was simulated with oxygen molecules in molecular dynamics, during a timescale of 5 ps

图13. 左图(a)从其体相中剥离单层的过程示意图, 右图(b)不同剥离距离条件下的剥离能

Figure 13. Diagram of the process of stripping a single layer from its body phase on the left (a), peel energy under different peel distances on the right (b)

参考文献 55

[1]	Brey, W. S.; Krieger, K. A. J. Am. Chem. Soc. 1949, 71, 3637. doi: 10.1021/ja01179a016
[2]	Ernst, M.; Lurot, F.; Schrotter, J.-C. Appl. Catal. B-Environ. 2004, 47, 15. doi: 10.1016/S0926-3373(03)00290-X
[3]	Qin, Y. Acta Phys.-Chim. Sin. 2019, 35, 1305. (in Chinese) doi: 10.3866/PKU.WHXB201906082
	( 覃勇, 物理化学学报, 2019, 35, 1305.)
[4]	Lukin, E. S.; Tarasova, S. V.; Korolev, A. V. Glass Ceram. 2001, 58, 105. doi: 10.1023/A:1010999432041
[5]	Schembri, V.; Heijmen, B. J. M. Med. Phys. 2007, 34, 2113. pmid: 17654914
[6]	Martínez, A.; Sansores, L. E.; Salcedo, R.; Tenorio, F. J.; Ortiz, J. V. J. Phys. Chem. A 2002, 106, 10630. doi: 10.1021/jp0213102
[7]	Turco, R. P.; Toon, O. B.; Whitten, R. C.; Cicerone, R. J. Nature 1982, 298, 830. doi: 10.1038/298830a0
[8]	Magg, N.; Giorgi, J. B.; Schroeder, T.; Bäumer, M.; Freund, H.-J. J. Phys. Chem. B 2002, 106, 8756. doi: 10.1021/jp0204556
[9]	Silva, F. T.; Silva, M. X.; Belchior, J. C. Front. Chem. 2019, 7, 707. doi: 10.3389/fchem.2019.00707
[10]	Jäger, M.; Schäfer, R.; Johnston, R. L. Nanoscale 2019, 11, 9042. doi: 10.1039/c9nr02031d pmid: 31025685
[11]	Yañez, O.; Báez-Grez, R.; Inostroza, D.; Rabanal-León, W. A.; Pino-Rios, R.; Garza, J.; Tiznado, W. J. Chem. Theory Comput. 2019, 15, 1463. doi: 10.1021/acs.jctc.8b00772
[12]	Zhou, L.-Q.; Yan, Z.-H.; Yue, Z.-Y.; Liang, X.-Q.; Zhao, J.-J. J. At. Mol. Phys. 2017, 34, 441. (in Chinese)
	( 周丽琴, 闫兆鸿, 岳子渝, 梁晓庆, 赵纪军, 原子与分子物理学报, 2017, 34, 441.)
[13]	Zhao, J.; Shi, R.; Sai, L.; Huang, X.; Su, Y. Mol. Simulat. 2016, 42, 809. doi: 10.1080/08927022.2015.1121386
[14]	Zhou, Y.; Zhao, Z.; Cheng, D. Comput. Phys. Commun. 2020, 247, 106945. doi: 10.1016/j.cpc.2019.106945
[15]	Mai, G.; Hong, Y.; Fu, S.; Lin, Y.; Hao, Z.; Huang, H.; Zhu, Y. Swarm Evol. Comput. 2020, 57, 100710. doi: 10.1016/j.swevo.2020.100710
[16]	Li, M.-S.; Huang, X.-Y.; Liu, H.-S.; Liu, B.-X.; Wu, Y.; Ai, F.-R. Acta Chim. Sinica 2013, 71, 1053. (in Chinese) doi: 10.6023/A13020193
	( 李孟山, 黄兴元, 柳和生, 柳炳祥, 武燕, 艾凡荣, 化学学报, 2013, 71, 1053.) doi: 10.6023/A13020193
[17]	Liu, T.-D.; Chen, J.-R.; Hong, W.-P.; Shao, G.-F.; Wang, T. N.; Zheng, J.-W.; Wen, Y.-H. Acta Phys. Sin. 2013, 62, 192. (in Chinese)
	( 刘暾东, 陈俊仁, 洪武鹏, 邵桂芳, 王婷娜, 郑骥文, 文玉华, 物理学报, 2013, 62, 192.)
[18]	Wang, Y.-C.; Lv, J.; Ma, Y.-M. Chin. Sci. Bull. 2015, 60, 2580. (in Chinese) doi: 10.1360/N972015-00575
	( 王彦超, 吕健, 马琰铭, 科学通报, 2015, 60, 2580.)
[19]	Gao, P.-Y.; Lv, J.; Wang, Y.-C.; Ma, Y.-M. Physics 2017, 46, 582. (in Chinese)
	( 高朋越, 吕健, 王彦超, 马琰铭, 物理, 2017, 46, 582.)
[20]	Zhang, J.; Dolg, M. Phys. Chem. Chem. Phys. 2015, 17, 24173. doi: 10.1039/c5cp04060d pmid: 26327507
[21]	Zhang, J.; Dolg, M. Phys. Chem. Chem. Phys. 2016, 18, 3003. doi: 10.1039/c5cp06313b pmid: 26738568
[22]	Zhang, J.; Glezakou, V.-A.; Rousseau, R.; Nguyen, M.-T. J. Chem. Theory Comput. 2020, 16, 3947. doi: 10.1021/acs.jctc.9b01107 pmid: 32364725
[23]	Wang, Q.-W.; Li, X.-Q.; Chen, H.-J.; Zhang, J.-W. 2017, 34, 1040. (in Chinese)
	( 王全武, 李喜全, 陈恒杰, 张家伟, 原子与分子物理学报, 2017, 34, 1040.)
[24]	Shao, X.; Cheng, L.; Cai, W. J. Comput. Chem. 2004, 25, 1693. doi: 10.1002/(ISSN)1096-987X
[25]	Shao, X.; Yang, X.; Cai, W. J. Comput. Chem. 2008, 29, 1772. doi: 10.1002/jcc.20938
[26]	Wu, X.; He, C. Chem. Phys. 2012, 405, 100. doi: 10.1016/j.chemphys.2012.06.015
[27]	Wu, X.; Cheng, W. J. Chem. Phys. 2014, 141, 124110. doi: 10.1063/1.4896152
[28]	Wei, D.; Ma, W.; Wu, X.; Cheng, L. Chem. Phys. 2021, 543, 111097. doi: 10.1016/j.chemphys.2021.111097
[29]	Siddique, N.; Adeli, H. Int. J. Artif. Intell. Tools 2016, 25, 1630001. doi: 10.1142/S0218213016300015
[30]	Karabin, M.; Stuart, S. J. J. Chem. Phys. 2020, 153, 114103. doi: 10.1063/5.0018725 pmid: 32962382
[31]	Rondina, G. G.; Da Silva, J. L. F. J. Chem Inf. Model. 2013, 53, 2282. doi: 10.1021/ci400224z
[32]	Huang, R.; Bi, J.-X.; Li, L.; Wen, Y.-H. J. Chem Inf. Model. 2020, 60, 2219. doi: 10.1021/acs.jcim.0c00130 pmid: 32203652
[33]	Liu, T.-D.; Li, Z.-P.; Ji, Q.-S.; Shao, G.-F.; Fan, T.-E.; Wen, Y.-H. Acta Phys. Sin. 2017, 66, 57. (in Chinese)
	( 刘暾东, 李泽鹏, 季清爽, 邵桂芳, 范天娥, 文玉华, 物理学报, 2017, 66, 57.)
[34]	Northby, J. A. J. Chem. Phys. 1987, 87, 6166. doi: 10.1063/1.453492
[35]	Rahm, J. M.; Erhart, P. Nano Lett. 2017, 17, 5775. doi: 10.1021/acs.nanolett.7b02761
[36]	He, C.-C.; Liao, J.-H.; Yang, X.-B. Acta Phys. Sin. 2017, 66, 85. (in Chinese)
	( 何长春, 廖继海, 杨小宝, 物理学报, 2017, 66, 85.)
[37]	Gutiérrez, G.; Johansson, B. Phys. Rev. B 2002, 65, 104202. doi: 10.1103/PhysRevB.65.104202
[38]	Woodley, S. M. Proc. R. Soc. A 2011, 467, 2020. doi: 10.1098/rspa.2011.0009
[39]	Bush, T. S.; Gale, J. D.; Catlow, C. R. A.; Battle, P. D. J. Mater. Chem. 1994, 4, 831. doi: 10.1039/jm9940400831
[40]	Romero, D.; Barrón, C.; Gómez, S. Comput. Phys. Commun. 1999, 123, 87. doi: 10.1016/S0010-4655(99)00259-3
[41]	Momma, K.; Izumi, F. J. Appl. Crystallogr. 2011, 44, 1272. doi: 10.1107/S0021889811038970
[42]	Lewis, J.; Schwarzenbach, D.; Flack, H. D. Acta Crystallogr. Sect. A 1982, 38, 733. doi: 10.1107/S0567739482001478
[43]	Zhou, R.-S.; Snyder, R. L. Acta Crystallogr. Sect. B 1991, 47, 617. doi: 10.1107/S0108768191002719
[44]	Repelin, Y.; Husson, E. Mater. Res. Bull. 1990, 25, 611. doi: 10.1016/0025-5408(90)90027-Y
[45]	Yu, K.; Wang, X.; Chen, L.; Wang, L. J. Chem. Phys. 2019, 151, 214105. doi: 10.1063/1.5127913
[46]	Paleico, M. L.; Behler, J. J. Chem. Phys. 2020, 152, 094109. doi: 10.1063/1.5142363
[47]	Kresse, G.; Furthmüller, J. Phys. Rev. B 1996, 54, 11169. pmid: 9984901
[48]	Kresse, G.; Furthmüller, J. Comput. Mater. Sci. 1996, 6, 15. doi: 10.1016/0927-0256(96)00008-0
[49]	Perdew, J. P.; Burke, K.; Ernzerhof, M. Phys. Rev. Lett. 1996, 77, 3865. pmid: 10062328
[50]	Monkhorst, H. J.; Pack, J. D. Phys. Rev. B 1976, 13, 5188. doi: 10.1103/PhysRevB.13.5188
[51]	Togo, A.; Tanaka, I. Scr. Mater. 2015, 108, 1. doi: 10.1016/j.scriptamat.2015.07.021
[52]	Grimme, S.; Antony, J.; Ehrlich, S.; Krieg, H. J. Chem. Phys. 2010, 132, 154104. doi: 10.1063/1.3382344
[53]	Laurens, G.; Amans, D.; Lam, J.; Allouche, A.-R. Phys. Rev. B 2020, 101, 045427. doi: 10.1103/PhysRevB.101.045427
[54]	Van den Bossche, M.; Noguera, C.; Goniakowski, J. Nanoscale 2020, 12, 6153. doi: 10.1039/c9nr10487a pmid: 32133480
[55]	McHale, J. M.; Auroux, A.; Perrotta, A. J.; Navrotsky, A. Science 1997, 277, 788. doi: 10.1126/science.277.5327.788

定向Monte Carlo格点搜索算法用于氧化铝团簇(Al₂O₃)_n (n=1~50)的结构搜索

Directional Monte Carlo Lattice Search Algorithm for the Structure Search of Alumina Clusters (Al₂O₃)_n (n=1~50)

RichHTML

PDF

PDF (Mobile)

可视化

摘要/Abstract

引用此文

分享此文

图/表 14

参考文献 55

相关文章 15

编辑推荐

相关统计

本文评价

[1]	苑志祥, 张浩, 胡思伽, 张波涛, 张建军, 崔光磊. 离子聚合原位固态化构建高安全锂电池固态聚合物电解质的研究进展^★[J]. 化学学报, 2023, 81(8): 1064-1080.
[2]	高丰琴, 刘洋, 张引莉, 蒋育澄. 羧基功能化Fe₃O₄固定化酶反应器的构筑及性能研究[J]. 化学学报, 2023, 81(4): 338-344.
[3]	查汉, 房进, 闫翎鹏, 杨永珍, 马昌期. 有机太阳能电池热失效机制及三元共混提升其热稳定性研究进展[J]. 化学学报, 2023, 81(2): 131-145.
[4]	刘彦甫, 李世麟, 荆亚楠, 肖林格, 周惠琼. 有机太阳能电池性能衰减机理研究进展[J]. 化学学报, 2022, 80(7): 993-1009.
[5]	许宁, 乔庆龙, 刘晓刚, 徐兆超. 基于抑制扭转的分子内电荷转移(TICT)提升有机小分子荧光染料亮度及光稳定性^※[J]. 化学学报, 2022, 80(4): 553-562.
[6]	戴敏, 雷钢铁, 张钊, 李智, 曹湖军, 陈萍. 五氧化二钒促进MgH₂/Mg室温吸氢^※[J]. 化学学报, 2022, 80(3): 303-309.
[7]	田宋炜, 周丽雪, 张秉乾, 张建军, 杜晓璠, 张浩, 胡思伽, 苑志祥, 韩鹏献, 李素丽, 赵伟, 周新红, 崔光磊. 聚环氧乙烷聚合物电解质基高电压固态锂金属电池的研究进展[J]. 化学学报, 2022, 80(10): 1410-1423.
[8]	龚政, 张意, 吕华, 崔树勋. 脯氨酸聚酯的单链力学性质[J]. 化学学报, 2022, 80(1): 7-10.
[9]	吕泽伟, 韩敏芳, 孙再洪, 孙凯华. 固体氧化物燃料电池运行初期电化学性能演变机制[J]. 化学学报, 2021, 79(6): 763-770.
[10]	苗俊辉, 丁自成, 刘俊, 王利祥. 小分子给体/高分子受体型有机太阳能电池研究进展[J]. 化学学报, 2021, 79(5): 545-556.
[11]	刘长安, 洪士博, 李蓓. 石墨烯在甘油/尿素剥离液中的稳定行为的分子动力学模拟研究[J]. 化学学报, 2021, 79(4): 530-538.
[12]	赵添堃, 王鹏, 姬明宇, 李善家, 杨明俊, 蒲秀瑛. Salan钛双齿配合物的Sonogashira合成后修饰反应研究[J]. 化学学报, 2021, 79(11): 1385-1393.
[13]	边洋爽, 刘凯, 郭云龙, 刘云圻. 功能性可拉伸有机电子器件的研究进展[J]. 化学学报, 2020, 78(9): 848-864.
[14]	张晋维, 李平, 张馨凝, 马小杰, 王博. 水稳定性金属有机框架材料的水吸附性质与应用[J]. 化学学报, 2020, 78(7): 597-612.
[15]	张静, 汤功奥, 曾誉, 王保兴, 刘力玮, 吴强, 杨立军, 王喜章, 胡征. 可溶性氧化-还原介质促进分级结构碳纳米笼的锂氧电池性能[J]. 化学学报, 2020, 78(6): 572-576.