Probing Structure, Thermochemistry, Electron Affinity and Magnetic Moment of Erbium-Doped Silicon Clusters ErSin (n = 3–10) and Their Anions with Density Functional Theory

Zhang, Yanpeng; Yang, Jucai; Cheng, Lin

doi:10.1007/s10876-018-1336-z

Cited by 17 publications

(7 citation statements)

References 41 publications

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“…Yang et al used ABCluster to study metal‐doped silicon clusters

MS i_{n}^{q}

( q = 0, − 1, n ≤ 20, M = Sc, Y, Ti, Zr, and some lanthanides) [91, 116, 208–220]. The computed photoelectron spectroscopies using GMs agree well with experimental ones.…”

Section: Applicationsmentioning

confidence: 84%

Global optimization of chemical cluster structures: Methods, applications, and challenges

Zhang

Glezakou

2020

Int J of Quantum Chemistry

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Chemical clusters are relevant to many applications in catalysis, separations, materials, and energy sciences. Experimentally, the structure of clusters is difficult to determine, but it is very important in understanding their chemistry and properties. Computational methods can be used to examine cluster structure, however finding the most stable structure is not simple, particularly as the cluster size increases. Global optimization techniques have long been used to tackle the problem of the most stable structure, but such approaches would have to look for a global minimum, while sampling local minima over the whole potential energy surface as well. In this review, the state‐of‐the‐art theory of global optimization theory is summarized. First, the definition, significance, relation to experiments, and a brief history of global optimization is presented. We then discuss, in more detail, three versatile global optimization methods: the basin hopping, the artificial bee colony algorithm, and the genetic algorithm. We close with some representative application examples of global optimization of clusters since 2016 and the challenges, open questions and opportunities in this field.

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“…Yang et al used ABCluster to study metal‐doped silicon clusters

MS i_{n}^{q}

( q = 0, − 1, n ≤ 20, M = Sc, Y, Ti, Zr, and some lanthanides) [91, 116, 208–220]. The computed photoelectron spectroscopies using GMs agree well with experimental ones.…”

Section: Applicationsmentioning

confidence: 84%

Global optimization of chemical cluster structures: Methods, applications, and challenges

Zhang

Glezakou

2020

Int J of Quantum Chemistry

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“…One example is that ABCluster was used to search the GMs of lanthanide (Ln) doped silicon cluster anions as large as LnSi 20 − , and the calculated photoelectron spectroscopy from these GMs agree well with the experimental ones. [48][49][50][51][52][53][54][55][56][57] Another example is that several authors searched the GMs of clusters consisting of atmosphere related molecules like water, ammonia, nitric acid, hydroxymethanesulfonic acid, sulfuric anhydride, and pentoxide−iodic acid. [58][59][60][61][62][63][64][65][66][67][68][69][70] Using GMs of different sizes, atmospheric cluster dynamics equations can be solved 71 and a lot of atmospheric chemical phenomena were successfully explained.…”

Section: Introductionmentioning

confidence: 99%

NWPEsSe: An Adaptive-Learning Global Optimization Algorithm for Nanosized Cluster Systems

Zhang

Glezakou

Rousseau

et al. 2020

J. Chem. Theory Comput.

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Global optimization constitutes an important and fundamental problem in theoretical studies in many chemical fields, such as catalysis, materials or separations problems. In this paper, a novel algorithm has been developed for the global optimization of large systems including neat and ligated clusters in gas phase, and supported clusters in periodic boundary conditions. The method is based on an updated artificial bee colony (ABC) algorithm method, that allows for adaptive-learning during the search process. The new algorithm is tested against four classes of systems of diverse chemical nature: gas phase Au 55 , ligated Au 8 2+ , Au 8 supported on graphene oxide and defected rutile, and a large cluster assembly [Co 6 Te 8 (PEt 3 ) 6 ][C 60 ] , with sizes ranging between 1 to 3 nm and containing up to 1300 atoms. Reliable global minima (GMs) are obtained for all cases, either confirming published data or reporting new lower energy structures. The algorithm and interface to other codes in the form of an independent program, Northwest Potential Energy Search Engine (NWPEsSe), is freely available and it provides a powerful and efficient approach for global optimization of nanosized cluster systems.

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“…Second, the “substitutional structure” method was employed, in which a Tb atom was substituted for a Si atom in the most stable structure of Si n + 1 0/− . Third, geometry structures presented in the previous literatures were utilized. Then, all the low‐lying geometries were reoptimized at the B3LYP/BS‐II level (BS‐II: cc‐pVTZ for Si and Stuttgart RSC ECP for Tb).…”

Section: Computational Detailsmentioning

confidence: 99%

“…By simulating the experimental observations of photoelectron spectroscopy (PES) of RESi n − (RE = Tb, Ho, Lu, 6 ≤ n ≤ 20) [12][13][14] and RESi n − (3 ≤ n ≤ 13, RE = Ho, Gd, Pr, Sm, Eu, Yb) clusters. [15,16] Some theoretical investigations have been achieved, such as LaSi n (n ≤ 21), [17,18] PrSi n (n ≤ 21), [19,20] PMSi n (n = 3-10), [21] SmSi n (n ≤ 10), [22,23] EuSi n (n ≤ 13), [24,25] GdSi n (n ≤ 17), [26,27] DySi n (3 ≤ n ≤ 10), [28] HoSi n (n ≤ 20), [29][30][31][32] ErSi n (n = 3-10), [33] TmSi n (n = 3-10), [34] YbSi n (n ≤ 13), [35][36][37] LuSi n (n ≤ 12), [38,39] and TbSi n (n = 2-13). [40] The experimental observation and theoretical simulation results show that (a) PES of RESi n − species can be classified into three molds (A, B, and AB) according to their appearances.…”

mentioning

confidence: 99%

Structural stability and evolution of terbium‐doped silicon clusters and influence of 4f → 5d electronic transition mechanism on magnetism and appearance of photoelectron spectroscopy for TbSi_n^0/− (n = 6‐18) clusters

Yang

Cheng

2019

Int J of Quantum Chemistry

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The global minimal structures of terbium-doped Si clusters and their anions TbSi n 0/− (n = 6-18) are confirmed by employing the ABCluster unbiased global search technique combined with a B2PLYP double-hybrid density functional and comparing consistency of simulated and experimental photoelectron spectroscopy (PES). The results demonstrated that structural evolution patterns for neutral clusters prefer Tb-substitutional to Tb-encapsulated configuration starting from n = 16. While for the corresponding anionic clusters, the growth pattern adopts Tb-linked structures to encapsulated motif. The Natural Population Analysis revealed that the 4f electrons of Tb atom in TbSi n 0/− (n = 6-18) clusters participate in bonding. The way to participate in bonding is one 4f electron transition to 5d orbital ([Xe]6s 2 4f 9 ! [Xe]6s 2 4f 8 5d 1), which significantly affects the cluster's magnetism and appearance of PES. The total magnetic moments of neutral TbSi n and the corresponding anions maintain at 7 μB and 6 μB, respectively, which are larger than that of an isolated Tb atom. The HOMO-LUMO energy gap, relative stability, and chemical bonding analysis demonstrated that superatomic TbSi 16 − cluster is a magic cluster with fine thermodynamic and moderate chemical stability. K E Y W O R D S terbium-doped Si clusters, structural evolution patterns, cluster's magnetism 1 | INTRODUCTION Rare earth (RE) is known as the industrial "gold." RE-doped semiconductors such as silicon exhibits novel light electron magnetic and chemical properties and yields interesting features that are extremely useful in broad applications, from microelectronic industries to energy, materials, and chemical industries. For instance, erbium silicides are the excellent silicon-based photonic source: the light emitting diode, fiber amplifier, or device of the photomedicine. [1] NdFeB magnets are widely used in small size direct current motor, hard disks, mobile phones, battery-powered tools, and other electronic products. [2,3] RE silicides play a vital role in refining, desulfurization, neutralizing low-melting harmful impurities, and improving the properties of steels. [4] Terbium silicide is an ideal device, which has immeasurable potential in field emission cathode, hydrogen storage material, internal photoemission infrared detector, and so forth. It is also used in semiconductor industry as large-scale integrated circuits, Ohmic contacts, and rectifying contacts, owing to the interfaces of terbium and silicon have good lattice matching, sharp interfaces, low Schottky barrier heights, high conductivity, and excellent thermal stability. [5,6] Furthermore, terbium silicides can be formed by a self-assembly process, which is a powerful tool overcoming the miniaturization limit of traditional lithography-based fabrication methods of electronic devices like

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Probing Structure, Thermochemistry, Electron Affinity and Magnetic Moment of Erbium-Doped Silicon Clusters ErSin (n = 3–10) and Their Anions with Density Functional Theory

Cited by 17 publications

References 41 publications

Global optimization of chemical cluster structures: Methods, applications, and challenges

Global optimization of chemical cluster structures: Methods, applications, and challenges

NWPEsSe: An Adaptive-Learning Global Optimization Algorithm for Nanosized Cluster Systems

Structural stability and evolution of terbium‐doped silicon clusters and influence of 4f → 5d electronic transition mechanism on magnetism and appearance of photoelectron spectroscopy for TbSi_n^0/− (n = 6‐18) clusters

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Probing Structure, Thermochemistry, Electron Affinity and Magnetic Moment of Erbium-Doped Silicon Clusters ErSin (n = 3–10) and Their Anions with Density Functional Theory

Cited by 17 publications

References 41 publications

Global optimization of chemical cluster structures: Methods, applications, and challenges

Global optimization of chemical cluster structures: Methods, applications, and challenges

NWPEsSe: An Adaptive-Learning Global Optimization Algorithm for Nanosized Cluster Systems

Structural stability and evolution of terbium‐doped silicon clusters and influence of 4f → 5d electronic transition mechanism on magnetism and appearance of photoelectron spectroscopy for TbSin0/− (n = 6‐18) clusters

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Structural stability and evolution of terbium‐doped silicon clusters and influence of 4f → 5d electronic transition mechanism on magnetism and appearance of photoelectron spectroscopy for TbSi_n^0/− (n = 6‐18) clusters