Computational Materials Science最新文献_第2页

Effects of interstitial oxygen on ω transformations and twin formation in bcc NbTaTiHf multi-principal element alloy from first-principles 从第一性原理看间隙氧对bcc NbTaTiHf多主元素合金ω转变和孪晶形成的影响

IF 3.3 3区材料科学 Q2 MATERIALS SCIENCE, MULTIDISCIPLINARY

Computational Materials Science

Pub Date : 2026-02-03 DOI: 10.1016/j.commatsci.2026.114569

Pedro P.P.O. Borges, Robert O. Ritchie, Mark Asta

Transformation- and twinning-induced plasticity (TRIP and TWIP) have been reported to contribute to the low-temperature deformation of some body-centered cubic (bcc) multi-principal element alloys (MPEAs) containing large fractions of group IV transition metals. The influence of interstitial solutes on the mechanisms underlying these forms of plasticity, however, remains unclear. Using first-principles calculations, we study the effects of interstitial O atoms on the relative stability of bcc and

ω

phases and on unstable and twin boundary stacking fault energy profiles in a representative bcc MPEA with high group-IV elemental fraction: NbTaTiHf. We find that O additions generally promote the relaxation of

ω

configurations back to their parent bcc structure, therefore inhibiting

ω

transformation. Calculations of the Rice parameter for bulk bcc and

ω

phases, as well as bcc-

ω

interfaces, further show that

ω

formation is a potent embrittlement factor, an effect that is enhanced by O additions, suggesting that the formation of bcc-

ω

interfaces is energetically preferred over the formation of the bulk

ω

phase. By contrast, the Rice parameter for twin boundaries indicates that these interfaces do not embrittle the material, even with O atoms at twin boundaries, providing a more favorable pathway for plastic deformation compared to

ω

transformation.

相变和孪晶诱导塑性（TRIP和TWIP）是导致含有大量IV族过渡金属的体心立方（bcc）多主元素合金（mpea）低温变形的主要原因。然而，间隙溶质对这些可塑性形成机制的影响尚不清楚。利用第一性原理计算方法，研究了具有代表性的具有高iv族元素分数的NbTaTiHf bcc MPEA中，O原子对bcc相和ω相相对稳定性以及对不稳定和双边界层错能分布的影响。我们发现O的加入通常会促进ω构型的弛豫，从而抑制ω的转变。对大块bcc和ω相以及bcc-ω界面的Rice参数计算进一步表明，ω的形成是一个强有力的脆化因素，O的加入增强了这一效应，这表明bcc-ω界面的形成在能量上优于大块ω相的形成。相比之下，孪晶界的Rice参数表明，即使在孪晶界处有O原子，这些界面也不会使材料发生脆化，与ω相变相比，这为塑性变形提供了更有利的途径。

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引用次数: 0

A thermodynamically consistent phase-field framework for viscoelastic fatigue fracture with dissipated-energy-driven toughness degradation 具有耗散能驱动韧性退化的粘弹性疲劳断裂的热力学一致相场框架

IF 3.3 3区材料科学 Q2 MATERIALS SCIENCE, MULTIDISCIPLINARY

Computational Materials Science

Pub Date : 2026-02-03 DOI: 10.1016/j.commatsci.2026.114538

Ming Yuan , Jianqiu Zhou , Jiaxin Cui , Changqing Miao

Viscoelastic materials, widely used in mechanical systems, are prone to fatigue damage under cyclic loading, where the evolution of such damage has been shown to be closely linked to internal energy dissipation. In this paper, a thermodynamically consistent phase-field modeling framework is developed to simulate fatigue crack behavior in viscoelastic materials, in which a toughness degradation mechanism driven by the history-dependent dissipated energy is introduced to characterize the progressive reduction of fracture resistance under cyclic loading. The proposed model, implemented in COMSOL Multiphysics, accurately reproduces experimentally observed crack paths reported in the literature, and the predicted crack growth behavior follows the Paris law. Simulation analyses on dumbbell-shaped and single-edge notched specimens further reveal that the viscoelastic dissipation mechanism governs distinct crack evolution patterns under different loading frequencies: lower frequencies induce greater energy dissipation per cycle, leading to significant damage accumulation and crack growth within fewer cycles but over longer durations; whereas higher frequencies result in greater energy input per unit time, promoting earlier crack initiation and faster propagation. Additional simulations on a three-dimensional C-shaped structure further illustrate the model's numerical robustness and extendibility to more complex geometries.

粘弹性材料是一种广泛应用于机械系统的材料，在循环载荷作用下容易产生疲劳损伤，而这种损伤的演变与内部能量耗散密切相关。本文建立了一个热动力学一致相场模型框架来模拟粘弹性材料的疲劳裂纹行为，其中引入了由历史相关耗散能驱动的韧性退化机制来表征循环加载下断裂抗力的逐步降低。该模型在COMSOL Multiphysics中实现，准确再现了文献中报道的实验观察到的裂纹路径，预测的裂纹扩展行为遵循巴黎定律。对哑铃形和单边缺口试件的模拟分析进一步揭示了不同加载频率下粘弹性耗散机制支配着不同的裂纹演化模式：频率越低，每循环能量耗散越大，导致损伤累积和裂纹扩展显著，循环次数越少，持续时间越长；而频率越高，单位时间内的能量输入越大，裂纹萌生越早，扩展越快。在三维c形结构上的额外仿真进一步说明了该模型的数值鲁棒性和可扩展性，可用于更复杂的几何形状。

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引用次数: 0

Enhanced oxygen evolution activity in NiFe layered double hydroxides via Ce doping and oxygen vacancy engineering 通过Ce掺杂和氧空位工程增强NiFe层状双氧水化物的析氧活性

IF 3.3 3区材料科学 Q2 MATERIALS SCIENCE, MULTIDISCIPLINARY

Computational Materials Science

Pub Date : 2026-02-03 DOI: 10.1016/j.commatsci.2026.114564

Je-hyun Lee, Taihoon Kim, Yong-Chae Chung

The overall pace of water electrolysis is governed by the comparatively slow oxygen evolution step, and rational electronic-structure control of transition-metal hydroxides offers a direct route to accelerate OER kinetics. Using density-functional theory (DFT), this study elucidates how cerium (Ce) doping and oxygen vacancies (V_o) jointly reshape the electronic structure and the oxygen-evolution pathway of NiFe layered double hydroxide (NiFe-LDH). Ce substitution downshifts the O-2p and Ni/Fe-3d bands, stabilizing metal–oxygen bonding, while hybridization among Ce-4f, O-2p, and Ni/Fe-3d (a d–p–f network) drives electron redistribution. The presence of V_o promotes polaronic charge transfer via hopping rather than band-like conduction. In this context, the electronic structure is consistent with metal-centered localized states associated with oxygen vacancies and Ce dopants, rather than band-like itinerant carriers. These electronic rearrangements mitigate antibonding interactions in M–O bonds, enhance electronic connectivity for polaron hopping, and reduce the highest computed free-energy barrier along the sequence of surface-bound intermediates in the oxygen-evolution pathway. Across the compositions and defect configurations examined, the barriers decrease, and the preferred active site shifts from Ni to Fe when V_o is present. Overall, dopant-triggered d–p–f electronic redistribution, coupled with defect-mediated charge control, offers a practical handle for regulating the reactivity of transition-metal hydroxide catalysts.

水电解的总体速度受相对较慢的析氧步骤控制，合理控制过渡金属氢氧化物的电子结构为加快OER动力学提供了直接途径。本研究利用密度泛函理论（DFT）阐明了铈（Ce）掺杂和氧空位（Vo）如何共同重塑NiFe层状双氢氧化物（NiFe- ldh）的电子结构和析氧途径。Ce取代降低了O-2p和Ni/Fe-3d带，稳定了金属-氧键，而Ce-4f、O-2p和Ni/Fe-3d之间的杂化（d-p-f网络）驱动了电子再分布。Vo的存在促进极化电荷通过跳变而不是带状传导转移。在这种情况下，电子结构符合与氧空位和Ce掺杂剂相关的金属中心局域态，而不是带状流动载流子。这些电子重排减轻了M-O键的反键相互作用，增强了极化子跳跃的电子连连接性，并降低了在氧演化途径中沿表面结合中间体序列计算的最高自由能势垒。在所检查的成分和缺陷构型中，当存在Vo时，势垒降低，首选活性位点从Ni转移到Fe。总的来说，掺杂剂触发的d-p-f电子重分布，加上缺陷介导的电荷控制，为调节过渡金属氢氧化物催化剂的反应性提供了一个实用的方法。

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引用次数: 0

Prediction of new Ti-N phases using machine learned interatomic potential 利用机器学习原子间势预测新的Ti-N相

IF 3.3 3区材料科学 Q2 MATERIALS SCIENCE, MULTIDISCIPLINARY

Computational Materials Science

Pub Date : 2026-02-03 DOI: 10.1016/j.commatsci.2026.114532

Pradeep Kumar Rana, Atharva Vyawahare, Rohit Batra, Satyesh K. Yadav

Ti-N material system have range of compounds with different stoichiometry like Ti₂N, Ti₃N₂, Ti₆N₅, Ti₄N₃ along with Ti ,TiN and solid solutions of N in Ti with a maximum of 23% solubility. In this work, we develop an interatomic potential based on moment tensor potential (MTP) that could reliably predict mechanical properties and thermodynamic stability of all experimentally reported Ti-N phases. Taking into account the structural similarity and dissimilarity of various Ti-N system, choice of training dataset was crucial for development of the potential. Root mean square error (RMSE) in prediction of total energy using MTP potential compared to one calculated using Density Functional Theory (DFT) for training dataset is 2.1 meV/atom and for testing dataset is 6.8 meV/atom. Mean percentage error in prediction of elastic constant was compared to DFT. Our developed potential performs better than existing MEAM and M3GNet potential for Ti-N system. The developed potential was used to predict new intermediate phases in Ti-N system which have similar structures as that of experimentally reported Ti-N phases. A maximum deviation of 30 meV/atom from the convex hull plot of formation energy at 0K was observed for all predicted structures in the Ti-N system. Thus we show that structures with all N/Ti ratios from 0 to 1 can be thermodynamically stable.

Ti-N材料体系中含有Ti2N、Ti3N2、Ti6N5、Ti4N3等不同化学计量的化合物以及Ti、TiN和N在Ti中的固溶体，溶解度最高可达23%。在这项工作中，我们开发了一个基于矩张量势（MTP）的原子间势，可以可靠地预测所有实验报道的Ti-N相的力学性能和热力学稳定性。考虑到各种Ti-N系统的结构相似性和差异性，训练数据集的选择对潜力的开发至关重要。使用MTP势预测总能量的均方根误差（RMSE）与使用密度泛函理论（DFT）计算的总能量相比，训练数据集为2.1 meV/原子，测试数据集为6.8 meV/原子。对弹性常数预测的平均百分比误差与DFT进行了比较。我们开发的Ti-N体系电位优于现有的MEAM和M3GNet电位。利用发展势预测了Ti-N体系中具有与实验报道的Ti-N相相似结构的新中间相。在Ti-N体系中，所有预测结构与0K时形成能凸包图的最大偏差为30 meV/原子。因此，我们证明了所有N/Ti比从0到1的结构都可以是热力学稳定的。

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引用次数: 0

Scalable machine learning models for predicting quantum transport in disordered 2D hexagonal materials 预测无序二维六边形材料中量子输运的可扩展机器学习模型

IF 3.3 3区材料科学 Q2 MATERIALS SCIENCE, MULTIDISCIPLINARY

Computational Materials Science

Pub Date : 2026-02-02 DOI: 10.1016/j.commatsci.2026.114561

Seyed Mahdi Mastoor, Ayda Baghervand, Amirhossein Ahmadkhan Kordbacheh

We introduce scalable machine learning models to predict two key electronic properties of disordered two-dimensional hexagonal nanomaterials: the transmission coefficient T(E) and the average local density of states (average-LDOS). Using a tight-binding Hamiltonian combined with the Non-Equilibrium Green’s Function formalism, the dataset of more than 400,000 unique nanoribbon configurations across graphene, germanene, silicene, and stanene with varying geometries, impurity concentrations, and energy levels was generated. A central contribution of this work is the development of a geometry-driven and physically interpretable feature space that enables generalization across material classes and system sizes. Random Forest regression and classification models are systematically evaluated in terms of accuracy, stability, and extrapolation ability. Regression consistently outperforms classification in capturing continuous transport behavior on in-domain data, while extrapolation performance degrades, revealing the limitations of tree-based models in unseen regimes. This study demonstrates a data-driven and transferable framework for accelerating quantum transport prediction in 2D nanostructures with disorder, providing new insights into structure–property relationships and guiding future development of physics-informed learning models for materials science.

我们引入可扩展的机器学习模型来预测无序二维六边形纳米材料的两个关键电子性质：透射系数T(E)和平均局域态密度（average- ldos）。使用紧密结合的哈密顿量和非平衡格林函数形式，生成了超过400,000个独特的纳米带配置的数据集，这些纳米带分布在石墨烯、锗烯、硅烯和斯坦烯中，具有不同的几何形状、杂质浓度和能级。这项工作的一个核心贡献是开发了一个几何驱动的和物理上可解释的特征空间，它可以跨材料类别和系统大小进行泛化。随机森林回归和分类模型在准确性，稳定性和外推能力方面进行了系统的评估。在捕捉域内数据的连续传输行为方面，回归一直优于分类，而外推的性能下降，揭示了基于树的模型在未知状态下的局限性。本研究展示了一个数据驱动和可转移的框架，用于加速二维无序纳米结构中的量子输运预测，为结构-性质关系提供了新的见解，并指导了材料科学物理知识学习模型的未来发展。

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引用次数: 0

A crystal plasticity approach for understanding the effect of microstructure and crystallographic texture on mechanisms of low cycle fatigue 用晶体塑性方法来理解微观组织和晶体织构对低周疲劳机制的影响

IF 3.3 3区材料科学 Q2 MATERIALS SCIENCE, MULTIDISCIPLINARY

Computational Materials Science

Pub Date : 2026-02-02 DOI: 10.1016/j.commatsci.2026.114544

Aayush Trivedi , Jalaj Kumar , Mehdi Salem , Alankar Alankar

This study analyzes the effect of crystallographic orientations on fatigue nucleation in Ti alloys. Uniaxial low cycle fatigue tests were performed on additively manufactured Ti–6Al–4V specimens at various strain amplitudes. Slip system activity and orientations were examined using a crystal plasticity model implemented in the Massively Parallel Object Oriented Simulation Environment (MOOSE). Gumbel distributions of Fatigue Indicator Parameters (FIPs) increase proportionally with strain amplitude, while FIPs strongly correlate with cycles to failure. Interestingly, the contribution of shear on basal and prismatic slip systems is strain-dependent, verified through FIP projections on Inverse Pole Figure (IPF) maps. Our analyses show that evolution of backstress and threshold stress on prismatic slips plays the key role. Incorporating

< c + a >

pyramidal slips captured tension–compression asymmetry under cyclic loading, enabling accurate representation of slip competition. Finally, idealized microstructures demonstrate design strategies for fatigue-resistant Ti alloys.

本文分析了晶体取向对钛合金疲劳形核的影响。对增材制造的Ti-6Al-4V试样进行了不同应变幅值下的单轴低周疲劳试验。利用大规模并行面向对象仿真环境（MOOSE）中实现的晶体塑性模型来检测滑移系统的活动和方向。疲劳指示参数（FIPs）的Gumbel分布随着应变幅值的增大而增大，而FIPs与失效周期密切相关。有趣的是，剪切对基底和棱柱滑移系统的贡献是应变依赖的，这一点通过逆极图（IPF）图上的FIP投影得到了验证。分析表明，滑移体的背应力和阈值应力的演化起着关键作用。结合<；c+a>；锥体滑移捕获循环加载下的拉压不对称，能够准确地表示滑移竞争。最后，理想化的显微组织展示了抗疲劳钛合金的设计策略。

{"title":"A crystal plasticity approach for understanding the effect of microstructure and crystallographic texture on mechanisms of low cycle fatigue","authors":"Aayush Trivedi , Jalaj Kumar , Mehdi Salem , Alankar Alankar","doi":"10.1016/j.commatsci.2026.114544","DOIUrl":"10.1016/j.commatsci.2026.114544","url":null,"abstract":"<div><div>This study analyzes the effect of crystallographic orientations on fatigue nucleation in Ti alloys. Uniaxial low cycle fatigue tests were performed on additively manufactured Ti–6Al–4V specimens at various strain amplitudes. Slip system activity and orientations were examined using a crystal plasticity model implemented in the Massively Parallel Object Oriented Simulation Environment (MOOSE). Gumbel distributions of Fatigue Indicator Parameters (FIPs) increase proportionally with strain amplitude, while FIPs strongly correlate with cycles to failure. Interestingly, the contribution of shear on basal and prismatic slip systems is strain-dependent, verified through FIP projections on Inverse Pole Figure (IPF) maps. Our analyses show that evolution of backstress and threshold stress on prismatic slips plays the key role. Incorporating <span><math><mrow><mo><</mo><mi>c</mi><mo>+</mo><mi>a</mi><mo>></mo></mrow></math></span> pyramidal slips captured tension–compression asymmetry under cyclic loading, enabling accurate representation of slip competition. Finally, idealized microstructures demonstrate design strategies for fatigue-resistant Ti alloys.</div></div>","PeriodicalId":10650,"journal":{"name":"Computational Materials Science","volume":"266 ","pages":"Article 114544"},"PeriodicalIF":3.3,"publicationDate":"2026-02-02","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"146186283","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"材料科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0

The effect of vacancy defects on the stability of atomic metallic hydrogen: A deep neural network molecular dynamics study 空位缺陷对原子金属氢稳定性的影响：深度神经网络分子动力学研究

IF 3.3 3区材料科学 Q2 MATERIALS SCIENCE, MULTIDISCIPLINARY

Computational Materials Science

Pub Date : 2026-02-01 DOI: 10.1016/j.commatsci.2026.114515

Jingsong Zhang , Chuanguo Zhang , Guo Chen , Xianlong Wang

In this study, we carried out systematic molecular dynamics simulations to investigate the dynamics of vacancy clusters and how vacancies affect the stability of the atomic metallic hydrogen (Cs-IV phase). These simulations were enabled by the development of a deep neural network potential for hydrogen, which is applicable across a wide range of pressures (<700 GPa) and temperatures (<4000 K). The results highlight three main points. First, vacancy clusters in the Cs-IV phase exhibit rapid dissociation, with complete breakdown occurring within 25 ps. Second, the diffusion coefficient of vacancies in the Cs-IV phase is comparable to that of liquid hydrogen molecules and increases with elevated temperature and pressure. Third, although high-concentration (>0.49%) vacancy defects narrow the temperature-pressure stability range of Cs-IV phase, their low aggregation tendency and high diffusivity render this effect negligible under practical conditions. This study offers practical guidance for the synthesis and preservation of atomic metallic hydrogen, as it elucidates the limited nucleation rate of vacancies, their relatively high diffusion coefficient, and the negligible effect of vacancies on the material's stability under practical conditions.

在这项研究中，我们进行了系统的分子动力学模拟来研究空位团簇的动力学以及空位如何影响原子金属氢（Cs-IV相）的稳定性。这些模拟是通过氢的深度神经网络潜力的开发实现的，该网络适用于广泛的压力（700 GPa）和温度（4000 K）。研究结果突出了三个要点。首先，Cs-IV相中的空位团簇解离迅速，在25ps内发生完全击穿。其次，Cs-IV相中空位的扩散系数与液氢分子相当，并且随着温度和压力的升高而增大。第三，虽然高浓度（>0.49%）空位缺陷使Cs-IV相的温压稳定范围变窄，但其低聚集倾向和高扩散率使得这种影响在实际条件下可以忽略不计。该研究阐明了在实际条件下，空位的成核速率有限，扩散系数较高，对材料稳定性的影响可以忽略不计，对原子金属氢的合成和保存具有实际指导意义。

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引用次数: 0

A neuroevolution potential for predicting the lattice thermal conductivity of structurally disordered γ-Ga2O3 预测结构无序γ-Ga2O3晶格热导率的神经进化潜力

IF 3.3 3区材料科学 Q2 MATERIALS SCIENCE, MULTIDISCIPLINARY

Computational Materials Science

Pub Date : 2026-02-01 DOI: 10.1016/j.commatsci.2026.114555

Fangwei Yang , Haoran Sun , Xiaoxin Yang , Xu Li , Gang Yang

In recent years, the lattice thermal conductivity of γ-Ga₂O₃ with a defective spinel structure has attracted widespread attention from both industry and academia. However, due to its inherent structural disorder, accurately predicting its thermal conductivity using first-principles methods remains challenging. To overcome this challenge, this study developed a machine-learning interatomic potential applicable to multiple γ-Ga₂O₃ configurations, based on the neuroevolution potential framework combined with a multi-round active-learning strategy. Using this potential, the thermal conductivity of different γ-Ga₂O₃ configurations along various crystallographic directions was calculated. The results show that, within the same structure, the thermal conductivity along the [100] and [010] directions is essentially the same, while it is significantly lower along the [001] direction. Furthermore, the thermal conductivity of all configurations originates primarily from low-frequency phonons in the 0–6 THz range. The highly disordered structure intensifies phonon scattering and significantly reduces the group velocity, resulting in limited actual contribution of high-frequency phonons to thermal transport. Additionally, different configurations exhibit high similarity in phonon transport characteristics, resulting in relatively small differences in thermal conductivity among them.

近年来，具有缺陷尖晶石结构的γ-Ga2O3晶格导热性能受到了业界和学术界的广泛关注。然而，由于其固有的结构无序性，使用第一性原理方法准确预测其导热系数仍然具有挑战性。为了克服这一挑战，本研究基于神经进化势框架结合多轮主动学习策略，开发了一种适用于多种γ-Ga2O3构型的机器学习原子间势。利用该势，计算了不同构型γ-Ga2O3沿不同结晶方向的热导率。结果表明，在同一结构内，沿[100]和[010]方向的导热系数基本相同，而沿[001]方向的导热系数明显较低。此外，所有构型的热导率主要来源于0-6太赫兹范围内的低频声子。高度无序的结构加剧了声子散射，显著降低了群速度，导致高频声子对热输运的实际贡献有限。此外，不同构型的声子输运特性具有较高的相似性，导致它们之间的导热系数差异相对较小。

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引用次数: 0

Perspective: Multi-shot LLMs are useful for literature summaries, but humans should remain in the loop 观点：多镜头法学硕士对文献总结很有用，但人类应该留在循环中

IF 3.3 3区材料科学 Q2 MATERIALS SCIENCE, MULTIDISCIPLINARY

Computational Materials Science

Pub Date : 2026-02-01 DOI: 10.1016/j.commatsci.2026.114517

Edward Kim , Jason Hattrick-Simpers

引用次数: 0

Atomic-scale response of surface-defective CdSe quantum dot to electron injection 表面缺陷CdSe量子点对电子注入的原子尺度响应

IF 3.3 3区材料科学 Q2 MATERIALS SCIENCE, MULTIDISCIPLINARY

Computational Materials Science

Pub Date : 2026-02-01 DOI: 10.1016/j.commatsci.2026.114547

Xiangyu Huo , Shuangli Yue , Xian Wang , Donghui Xu , Li Zhang , Mingli Yang

The long-term stability of blue-emitting quantum dots (QDs) remains a challenge for their use in electroluminescent applications. While surface defects are common in colloidal QDs because of their long-chain ligands, electron accumulation is one of the key features during device operation. In this contribution, we investigate the early-stage response of CdSe QDs to accumulated electrons, with a particular focus on the role of surface defects and their evolution upon electron injection. First-principles calculations and ab initio molecular dynamics simulations reveal that the injected electrons preferentially localize at under-coordinated Cd atoms rather than distributing uniformly across the QD, making these defect-associated surface metal atoms partially or fully reduced depending on the number of injected electrons. This leads to a surface reconstruction and consequently to remarkable changes in the electronic and optical properties. Moreover, the electron localization tends to occur at these specific defective sites. The formation energy variations of defects and the formation of in-gap states are found to be responsible for the localization of injected electrons. These findings provide fundamental insights into charge-induced surface processes in CdSe QDs, and highlight the role of surface defects in mediating electron localization and structural rearrangements. They provide a mechanistic basis for future studies on improving the stability of blue-emitting QDs.

蓝光量子点（QDs）在电致发光应用中的长期稳定性仍然是一个挑战。由于胶体量子点具有长链配体，因此表面缺陷在胶体量子点中很常见，而电子积累是器件运行过程中的关键特征之一。在这篇文章中，我们研究了CdSe量子点对累积电子的早期响应，特别关注了表面缺陷的作用及其在电子注入中的演变。第一性原理计算和从头算分子动力学模拟表明，注入的电子优先定位在欠配位的Cd原子上，而不是均匀地分布在整个量子点上，使得这些缺陷相关的表面金属原子根据注入电子的数量部分或完全减少。这导致了表面重建，从而导致了电子和光学性质的显著变化。此外，电子定位往往发生在这些特定的缺陷位点。发现缺陷的形成能量变化和隙内态的形成是注入电子局域化的主要原因。这些发现为CdSe量子点中电荷诱导的表面过程提供了基本的见解，并强调了表面缺陷在介导电子定位和结构重排中的作用。这为进一步研究提高蓝色发光量子点的稳定性提供了机理基础。

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引用次数: 0