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Strain-induced resonances in the dynamical quadratic magnetoelectric response of multiferroics (多鐵動力學二次磁電響應中的應變感應共振)
S. Omid Sayedaghaee, Charles Paillard1, Sergey Prosandeev, Bin Xu and Laurent Bellaiche
npj Computational Materials 6:60(2020)
doi:s41524-020-0311-z
Published online:21 May2020

Abstract| Full Text | PDF OPEN

摘要:近年來,對磁電(ME)效應——這一多鐵材料中鐵電有序與磁有序間交叉耦合的研究興趣經歷了重大的復興。近期大量的工作不僅研究了利用磁場(或電場)對極化(或磁化)的交叉控制來設計傳感器,驅動器,換能器和存儲設備,更旨在清楚地理解ME響應的來源以及與之相關的新穎效應。在這里,我們推導出解析模型用于理解多鐵體系中ME效應的驚人和新穎的動力學,并通過原子模擬進一步確認該現象的存在。具體而言,揭示了應變可以導致電聲磁振子的存在,其為一種聲學和光學聲子與磁振子混合的新型準粒子。該粒子可導致共振,從而顯著增強了磁電響應。而且,在本工作之前,尚未有工作討論變頻磁場導致動態二次ME響應,此為二次諧波過程。這些過程表明處理此類系統時應考慮非線性的是十分重要的。 

Abstract:For the last few years, the research interest in magnetoelectric (ME) effect, which is the cross-coupling between ferroelectric and magnetic ordering in multiferroic materials, has experienced a significant revival. The extensive recent studies are not only conducted towards the design of sensors, actuators, transducers, and memory devices by taking advantage of the cross-control of polarization (or magnetization) by magnetic (or electric) fields, but also aim to create a clearer picture in understanding the sources of ME responses and the novel effects associated with them. Here we derive analytical models allowing to understand the striking and novel dynamics of ME effects in multiferroics and further confirm it with atomistic simulations. Specifically, the role of strain is revealed to lead to the existence of electroacoustic magnons, a new quasiparticle that mixes acoustic and optical phonons with magnons, which results in resonances and thus a dramatic enhancement of magnetoelectric responses. Moreover, a unique aspect of the dynamical quadratic ME response under a magnetic field with varying frequencies, which is the second harmonic generation (SHG), has not been discussed prior to the present work. These SHGs put emphasis on the fact that nonlinearities should be considered while dealing with such systems.

Editorial Summary

Strain matters: resonance enhanced dynamic quadratic magnetoelectric effect應變生新花:共振增強動態二次磁電效應

本研究發現了應變可以誘導多鐵體系中動態二次磁電耦合響應的共振增強。由美國阿肯色大學Bellaiche教授領導的國際團隊基于唯象模型和分子動力學模擬研究了應變對于多鐵體系中的動態二次磁電耦合響應的影響。他們首先構建了多鐵體系應變、磁和電多場耦合的唯象朗道模型,并基于該模型的推導得到了二次磁電系數隨外場頻率的變化關系。他們發現,當體系允許應變存在時,體系中會出現一種新的元激發準粒子,即電聲磁振子,其為聲學/光學聲子與磁振子耦合態。該準粒子導致二次磁電系數在某些頻率會極大的增強,發生所謂共振現象。為證實上述結果,他們基于典型多鐵體系BiFeO3的等效哈密頓量開展了分子動力學模擬。通過施加不同頻率的交變外場,他們發現在應變允許發生時的確觀察到磁電系數的共振增強,而當應變不能發生時,共振增強消失,從而證實了唯象模型的結果。該研究提出一種全新的強磁電響應的物理機制,且可以單相材料中實現,不僅豐富磁電耦合的物理圖像,而且有望用于實現新型磁電耦合器件。 

Stain induced resonant enhancement of dynamic quadratic magnetoelectric (ME) response in multiferroics was discovered. An international team led by Professor L. Bellaiche from the University of Arkansas studied the role of strain on the dynamic quadratic ME coupling in multiferroic systems based on phenomenological model and molecular dynamics simulations. They first proposed a phenomenological Landau model to describe the coupling of strain, magnetic and electric variants in multiferroic system. By derivation of this model, the relationship between the dynamic quadratic ME coefficient and the frequency of external field was obtained. They found that when strain exists, a new kind of elementary excitation, namely electroacoustic magnon, will appear in the system, which is the coupling state of acoustic/optical phonon and magnon. This excitation results in a dramatic enhancement of the quadratic ME coefficient at certain frequencies, resulting in the so-called resonance phenomenon. To confirm the above results, they carried out molecular dynamics simulations based on the effective Hamiltonian of BiFeO3. By applying alternating external fields of different frequencies, they found that the resonance enhancement of ME coefficient can be observed when  strain was allowed, while it disappears when the strain is clamped, which confirms the results of the phenomenological model. This study proposes a new mechanism of ME response, which can be realized in single-phase materials. It not only enriches the physics of ME coupling, but is also expected to be used to realize new ME devices.

Simulating Raman spectra by combining first-principles and empirical potential approaches with application to defective MoS2(第一性原理結合經驗勢方法模擬拉曼光譜并應用于缺陷MoS2的研究)
Zhennan KouArsalan HashemiMartti J. PuskaArkady V. Krasheninnikov & Hannu-Pekka Komsa
npj Computational Materials 6:59(2020)
doi:s41524-020-0320-y
Published online:15 May 2020

Abstract| Full Text | PDF OPEN

摘要:二維過渡金屬雙硫屬化合物在光電、催化或傳感器件中的成功應用,很大程度上依賴于材料的質量,即厚度均勻性、晶界的存在以及點缺陷的類型和濃度。拉曼光譜是探測這些因素的一個強大而無損的工具,但光譜的解釋,特別是不同貢獻的區分并不簡單。與模擬光譜進行比較是有益的,但對于有缺陷的材料系統,由于所涉及的尺寸太大,第一性原理模擬通常在計算上過于昂貴。在此,本研究提出了一種第一性原理和經驗勢結合的方法來模擬缺陷材料的拉曼光譜,并將其應用于具有MoS空位隨機分布的單層MoS2中。我們研究了在何種程度上可以區分空穴類型,并提供隨缺陷濃度變化時拉曼光譜演化的起源分析。我們將模擬光譜應用于聲子局域模型(之前實驗中使用的模型)來評估缺陷濃度。結果顯示,該模型的最簡單形式不足以完全捕獲峰形,但是當聲子局域類型與完整的聲子譜聯系起來的時候,該模型獲得的結果與實驗數據有很好的一致性。 

Abstract:Successful application of two-dimensional transition metal dichalcogenides in optoelectronic, catalytic, or sensing devices heavily relies on the materials’ quality, that is, the thickness uniformity, presence of grain boundaries, and the types and concentrations of point defects. Raman spectroscopy is a powerful and nondestructive tool to probe these factors but the interpretation of the spectra, especially the separation of different contributions, is not straightforward. Comparison to simulated spectra is beneficial, but for defective systems first-principles simulations are often computationally too expensive due to the large sizes of the systems involved. Here, we present a combined first-principles and empirical potential method for simulating Raman spectra of defective materials and apply it to monolayer MoS2 with random distributions of Mo and S vacancies. We study to what extent the types of vacancies can be distinguished and provide insight into the origin of different evolutions of Raman spectra upon increasing defect concentration. We apply our simulated spectra to the phonon confinement model used in previous experiments to assess defect concentrations, and show that the simplest form of the model is insufficient to fully capture peak shapes, but a good match is obtained when the type of phonon confinement and the full phonon dispersion relation are accounted for.

Editorial Summary

Simulating Raman spectra in defective MoS2: by first-principles and empirical potential approaches模擬缺陷MoS2的拉曼光譜:第一性原理結合經驗勢方法

該研究展示了一種基于經驗勢和第一性原理計算的方法,用于模擬缺陷材料的拉曼光譜,其中經驗勢用于評估缺陷系統的振動模式,然后與第一性原理計算得到的拉曼張量進行結合。來自芬蘭阿爾托大學應用物理系的Hannu-Pekka Komsa領導的團隊,構建了該組合方法,并研究了在何種程度上可以區分空位類型,最后探討了隨缺陷濃度增加時拉曼光譜不同演化的機理。這種方法不僅能可靠地模擬拉曼光譜,還可深入了解缺陷系統中振動模式的物理內涵,以及如何用拉曼光譜對它們進行探測。作者利用該方法研究了單層MoS2中的空位缺陷,捕獲了缺陷對突出峰位移和不對稱展寬的影響,其結果與實驗數據定性一致。此外,他們使用聲子局域模型來擬合其模擬的拉曼光譜,以評估該模型在缺陷材料中的適用性。結果發現,當同時考慮完整的聲子色散關系和局域類型時,該模型非常有效。通過本研究發現,只要有適當的經驗勢,就可以有效地評估缺陷系統的拉曼光譜。 

A method for simulating Raman spectra of defective materials based on a combination of empirical potentials and first-principles calculations is demonstrated, in which the empirical potentials are used to evaluate the vibrational modes of the defective system, which are then combined with Raman tensors evaluated from the first-principles calculations. A team led by Hannu-Pekka Komsa from the Department of Applied Physics, Aalto University, Finland, had constructed this combined method and studied to what extent the types of vacancies can be distinguished, and finally provided insight into the origin of different evolutions of Raman spectra upon increasing defect concentration. This approach allows them to not only reliably simulate Raman spectra, but also gain insights into the physics of vibrational modes in defective systems and how they can be probed with Raman spectroscopy. The authors used this method to study vacancies in monolayer MoS2 and captured the effect of defects on the shifts and on the asymmetric broadening of the prominent peaks, with the results being in a qualitative agreement with experimental data. They then used the phonon confinement model to fit their simulated Raman spectra to assess the applicability of the model in the context of defective materials. They found it to work well when the full dispersion relation and the type of confinement are accounted for. The approach presented here allows for efficient evaluation of the Raman spectra of defective systems provided that an appropriate empirical potential is available.

Predicting synthesizable multi-functional edge reconstructions in two-dimensional transition metal dichalcogenides(預測二維過渡金屬雙鹵化物中可合成的多功能邊緣重構)
Guoxiang HuVictor FungXiahan SangRaymond R. Unocic & P. Ganesh
npj Computational Materials 6:120(2020)
doi:s41524-020-0327-4
Published online:13 August 2020

Abstract| Full Text | PDF OPEN

摘要:二維(2D)過渡金屬雙硫屬化合物(TMDC)由于其獨特的多樣性和可調性,尤其是其邊緣特性,已經引起了人們極大的興趣。除了常規六邊形2D材料常見的扶手椅邊和鋸齒形邊緣外,通過對合成條件的精細調控,可以實現更復雜的邊緣重構。然而目前缺乏對整個可合成的邊緣重構家族的研究。本研究開發了一種集成計算方法,整合了構型生成、力的弛豫以及電子結構計算等流程,以系統、有效地發現的重構邊緣和篩選其功能特性。以MoS2為模型系統,對數百條重構邊緣進行篩選,發現超過160條重構邊緣比傳統邊緣更穩定。更令人興奮的是,我們發現了9個新的可合成的重構邊緣,具有熱力學穩定性,此外還成功地再現了3個最近合成的邊緣結構。我們還發現預測的重構邊緣具有多功能特性(與常規邊緣相比,還具有接近最佳的析氫活性),是析氫反應(HER)的理想選擇,并且具有半金屬性,且磁矩變化很大,使其特別適合納米自旋電子應用。我們的工作揭示了在2D TMDC中存在大量可合成的重構邊緣,并打開了2D材料“本征”邊緣工程多功能性的材料設計新范式。 

Abstract:Two-dimensional (2D) transition metal dichalcogenides (TMDCs) have attracted tremendous interest as functional materials due to their exceptionally diverse and tunable properties, especially in their edges. In addition to the conventional armchair and zigzag edges common to hexagonal 2D materials, more complex edge reconstructions can be realized through careful control over the synthesis conditions. However, the whole family of synthesizable, reconstructed edges remains poorly studied. Here, we develop a computational approach integrating ensemble-generation, force-relaxation, and electronic-structure calculations to systematically and efficiently discover additional reconstructed edges and screen their functional properties. Using MoS2 as a model system, we screened hundreds of edge-reconstruction to discover over 160 reconstructed edges to be more stable than the conventional ones. More excitingly, we discovered nine new synthesizable reconstructred edges with record thermodynamic stability, in addition to successfully reproducing three recently synthesized edges. We also find our predicted reconstructed edges to have multi-functional properties—they show near optimal hydrogen evolution activity over the conventional edges, ideal for catalyzing hydrogen-evolution reaction (HER) and also exhibit half-metallicity with a broad variation in magnetic moments, making them uniquely suitable for nanospintronic applications. Our work reveals the existence of a wide family of synthesizable, reconstructed edges in 2D TMDCs and opens a new materials-by-design paradigm of ‘intrinsic’ edge engineering multifunctionality in 2D materials.

Editorial Summary

2D transition metal dichalcogenides: Predicting synthesizable multi-functional edge reconstructions二維過渡金屬雙鹵化物:預測可合成的多功能邊緣重構

由于2D過渡金屬雙硫屬化合物(TMDC中整個可合成的重構邊緣家族仍然未知,該研究開發出了一種集成計算方法,可以快速有效地發現2D TMDC體系中更多可合成的功能性邊緣,為計算篩選和發現其他功能重構的TMDC邊緣提供了獨特的機會。來自美國橡樹嶺國家實驗室納米材料科學中心的Guoxiang HuP. Ganesh共同領導的研究團隊,從構型文件生成開始,使用力場方法,篩選了材料的穩定邊緣。并使用基于DFT的電子結構計算,進一步細化了所獲得的穩定邊緣,以生成相圖并篩選其功能特性。以MoS2為例,篩選出了2H1TMoS2625個邊緣構型,并預測了穩定的邊緣以指導實驗合成。隨后,他們研究了這些邊緣的功能特性,發現許多這些內在可調的邊緣重構,對于析氫反應來說是接近最佳的。因此,他們的研究為預測??2D材料的可合成功能邊緣提供了一個全面而經濟的計算方案,并為實驗研究人員提供了有用的指導。許多研究已經通過Edisonian方法中的外部摻雜來調控了TMDCs的催化、電子和磁性能,但這項研究的優點是發現了一系列“本征”(基于金屬/硫屬元素比)可調材料。該研究成功開啟了一種新的材料設計范式,可搜索和發現其他具有特定多功能的、有潛在邊緣多型性的2D“本征”邊緣重構家族,并適用于納米尺度的廣泛應用。 

Due to the whole family of synthesizable reconstructed edges in 2D TMDCs remains largely unknown, a computational approach to rapidly and efficiently discover more synthesizable functional edges in the family of 2D TMDCs is developed, which presents a unique opportunity to computationally screen and discover additional functional reconstructed TMDC edges. A team co-led by Guoxiang Hu and P. Ganesh from the Center for Nanophase Materials Sciences, Oak Ridge National Laboratory, USA, starting with configuration ensemble generations, screened for stable edges using a computationally affordable force-field method. The obtained stable edges are then further refined with DFT based electronic-structure calculations to generate phase diagrams and screen for their functional properties. Using MoS2 as an example, the authors screened 625 edge configurations for 2H and 1T MoS2 phases, and predicted stable edges to guide the experimental synthesis. Subsequently they studied the functional properties of these edges and discovered many of these intrinsically tunable edge reconstructions to be near-optimal for hydrogen evolution reaction. Their study thus provides a comprehensive yet affordable computational scheme for predicting synthesizable functional edges of 2D materials and provides useful guidelines to experimental researchers. Many studies have investigated tuning the catalytic, electronic and magnetic properties of TMDCs by external doping in an Edisonian approach, but the merit of this study is to discover a family of ‘intrinsically’ (based on the metal/chalcogen ratio) tunable materials with widely varying functional properties. Success of this study opens a new materials-by-design paradigm to search and discover other families of 2D ‘intrinsic’ edge reconstructions with specific multi-functionalities, with potential edge polytypism, for a wide range of nanoscale applications.

Perfect short-range ordered alloy with line-compound-like properties in the ZnSnN2:ZnO system (ZnSnN2ZnO系統中具有線化合物性質的完美短程有序合金)
Jie PanJacob J. CordellGarritt J. TuckerAndriy ZakutayevAdele C. Tamboli & Stephan Lany
npj Computational Materials 6:120(2020)
doi:s41524-020-0331-8
Published online:13 August 2020

Abstract| Full Text | PDF OPEN

摘要:我們提出了一種新的固體材料相,它是一種無序的固溶體,但具有許多有序線化合物的特征。這些新的物理現象源于完美的短程序,從而保留了局域八隅律規則。我們采用第一性原理計算、模型哈密頓量的蒙特卡羅模擬和基于短程序擴展的固溶模型對雙亞晶格混合半導體合金(ZnSnN21-xZnO2x開展模擬。我們證明,這種獨特的固溶體必須在“幻術”組分中出現,其電子特征沒有無序引起的電荷局域化,因此具有類似有序相的優良載流子傳輸。有趣的是,該相具有傳統固溶體模型(如規則溶體和帶隙彎曲模型等)沒有的奇異性。在熱力學上,該合金相的形成焓急劇降低(類似線化合物),但仍需要長程無序帶來的熵才能在實驗溫度下穩定該化合物。 

Abstract:We present a new solid-state material phase which is a disordered solid solution but offers many ordered line-compound features. The emergent physical phenomena are rooted in the perfect short-range order which conserves the local octet rule. We model the dual-sublattice-mixed semiconductor alloy (ZnSnN2)1?x(ZnO)2x(ZnSnN2)1?x(ZnO)2x using first-principles calculations, Monte-Carlo simulations with a model Hamiltonian, and an extension of the regular solution model by incorporating short-range order. We demonstrate that this unique solid solution, occurring at a “magic” composition, can provide an electronically pristine character without disorder-induced charge localization and, therefore, a superior carrier transport similar to ordered phases. Interestingly, this phase shows singularities that are absent in the conventional solid-solution models, such as the regular solution and band-gap bowing model. Thermodynamically, this alloy phase has a sharply reduced enthalpy at its composition (like a line compound), but it still requires the entropy from long-range disorder to be stabilized at experimentally accessible temperatures.

Editorial Summary

Singularity in solid solution: disordered structure but ordered properties固溶體的奇異點:具有有序化合物性能的無序固溶體

本文通過計算預測了一種具有固溶體結構特征但類似有序化合物物理性能的新奇固體相。來自美國可再生能源實驗室(NREL)的團隊基于綜合利用多種計算模型,即固溶體模型、蒙特卡洛模擬和第一性原理,針對雙亞晶格混合半導體合金(ZnSnN21-xZnO2x的相結構開展了研究。該體系可以看成是由ON四面體組合而成。他們首先提出了一種用于描述短程有序的參量,基于該參量構建了描述該化合物形成焓的經驗表達式。進而基于該能量表達式開展蒙特卡洛模擬,由此獲得所有固溶體組分(0<x<0.5)能量最低的結構,并開展密度泛函計算精確計算這些結構的能量。有趣的是,他們發現x=0.25成為所謂“幻數”組分。在該組分,混合焓隨組分變化的曲線出現明顯奇異點。分析表明,該組分對應的結構具有完美的短程有序,即所有四面體內部都滿足八隅律,就是說八面體內陰陽離子化合價之和為零。然而八面體間的連接仍然是無序的。因此該體系處于短程有序長程無序的特殊狀態。更有意義的是,對該體系電子結構分析表明,該組分結構的帶隙明顯偏離正常固溶體模型預測結果,且能帶邊緣的電子態具有很強的離域性,這是有序化合物的典型特征,其電輸運性能應明顯優于無序固溶體。通過進一步理論計算,研究人員證明了上述新奇化合物存在的可能性并預測可能存在的溫度區間。該工作的意義在于,提出了在多元固溶體中可能存在特別的短程有序長程無序結構,其具有類型有序化合物的物理性質。這一發現為新型功能材料設計提供新思路和更廣闊的搜索空間。 

A novel solid phase with the characteristics of solid solution like structure but ordered compound like physical properties was predicted. A team from the National Renewable Energy Laboratory (NREL) utilized a set of calculation models, namely solid solution model, Monte Carlo simulation and density functional theory calculation to study the phase structure of (ZnSnN2)1-x(ZnO)2x, a dual-sublattice-mixed semiconductor alloy. This system can be regarded as a combination of O and N tetrahedrons. The authors first proposed an order parameter to describe the short-range order, based on which an empirical expression describing the formation enthalpy of the compound was constructed. Based on the energy expression, Monte Carlo simulations were carried out to obtain the structures for each composition (0 < x < 0.5). Then density functional calculations were carried out to determine the energy of these structures accurately. Interestingly, they found that x = 0.25 becomes a so-called "magic number" composition. In this component, a singularity appears in the curve of the enthalpy of mixing with the component. The analysis shows that the corresponding structure of the component has perfect short-range order, that is, all tetrahedrons satisfy the local octet rule, i.e. the sum of the valence of cation and anion within one tetrahedron is zero. While the connection between octahedrons is still disordered. Therefore, the system is in a special state with short-range order but long-range disorder. More importantly, the analysis of the electronic structure shows that the band gap of the structures with the “magic” composition deviate from the predicted results of the normal solid solution model, and the electronic states at the edge of the energy band exhibit strong delocalization, which is a typical characteristic of ordered compounds and could lead to superior electrical transport properties over that of disordered solid solutions. By further theoretical calculation, the researchers demonstrated the possibility of the existence of these novel compounds and predicted the possible temperature range. The significance of this work lies in the prediction that special short-range ordered but long-range disordered structures may exist in multicomponent solid solutions, which could exhibit physical properties of typical ordered compounds. This study provides a broader space for new material design and discovery.

Machine learning for accelerating the discovery of high-performance donor/acceptor pairs in non-fullerene organic solar cells (機器學習助力高性能非富勒烯有機太陽能電池供體/受體材料的開發)
Yao Wu, Jie Guo, Rui Sun & Jie Min
npj Computational Materials 6:120(2020)
doi:s41524-020-00388-2
Published online:13 August 2020

Abstract| Full Text | PDF OPEN

摘要:通過人工智能、計算機科學和材料的合成與優化有機結合,可以大幅促進高性能有機光伏材料的開發。在這個過程中,機器學習模型與算法的選擇發揮著至關重要的作用。本研究以565組供體/受體對的數據為訓練集通過五種常見算法構建了機器學習模型,并評估了這些模型應用于指導材料設計和供體/受體配對物篩選的可靠性,結果顯示基于隨機森林(RF)和提升回歸樹(BRT)算法的模型表現優異。因此本研究進一步利用RF和BRT模型對3200萬組供體/受體對進行性能預測和篩選,并從該數據庫中選出六組供體/受體對進行合成與器件表征,從而獲得它們的實驗光電轉化效率。實驗驗證結果顯示,基于RF的機器學習模型更適合用于有機光伏材料的高通量篩選。這為材料的設計和供體/受體配對物的選擇提供了新的思路,從而加速有機太陽能電池的發展。 

Abstract:Integrating artificial intelligence (AI) and computer science together with current approaches in material synthesis and optimization will act as an effective approach for speeding up the discovery of high-performance photoactive materials in organic solar cells (OSCs). Yet, like model selection in statistics, the choice of appropriate machine learning (ML) algorithms plays a vital role in the process of new material discovery in databases. In this study, we constructed five common algorithms, and introduced 565 donor/acceptor (D/A) combinations as training data sets to evaluate the practicalities of these ML algorithms and their application potential when guiding material design and D/A pairs screening. Thus, the best predictive capabilities are provided by using the random forest (RF) and boosted regression trees (BRT) approaches beyond other ML algorithms in the data set. Furthermore, >32 million D/A pairs were screened and calculated by RF and BRT models, respectively. Among them, six photovoltaic D/A pairs are selected and synthesized to compare their predicted and experimental power conversion efficiencies. The outcome of ML and experiment verification demonstrates that the RF approach can be effectively applied to high-throughput virtual screening for opening new perspectives to design of materials and D/A pairs, thereby accelerating the development of OSCs.

Editorial Summary

Donor/acceptor pairs screening:in organic solar cells有機太陽能電池供體-受體材料的配對:需要“紅娘”!

傳統有機光伏材料研究方法包括對化學合成、供體/受體材料匹配和器件制備進行精細控制及優化,需要大量的資源投入和較長的研究周期,限制了有機光伏產業的發展與實際商業應用。近日,武漢大學閔杰研究員課題組以被文獻報道過的565組基于非富勒烯小分子受體材料和聚合物給體材料的供體/受體對數據庫,采用ASCII碼字符串的表達方式將供體/受體材料的化學結構進行轉化成二進制機器語言,并與其相關光伏參數一起作為訓練集和驗證集,分別采用線性回歸(LR)、多類邏輯回歸(MLR)、提升回歸樹(BRT)、人工神經網絡(ANN)和隨機森林(RF)算法構建機器學習模型(如圖1所示),可對供體、受體材料以及活性層供體/受體對的適配性進行快速的評估和篩選。研究人員對五種典型的算法模型進行評估發現,基于RF和BRT模型的預測結果與測試集中真實值的皮爾森相關系數(r)均超過了0.7,說明該兩種模型是進行這類機器學習的最佳表達方式。進一步,研究人員通過原有數據集并結合RF和BRT模型,分別篩選和計算出了3200萬個給受體對。為了驗證上述模型是否能夠有效地指導設計新的有機光伏體系,研究人員從該數據庫中選出六組易于合成且具有高效率的給受體對,并進行了材料合成、器件制備與表征。研究結果表明,相較于BRT,RF機器學習模型預測的結果和實驗結果之間具有更高的一致性,從而驗證了RF模型的高通量虛擬篩選與預測能力。這體現了機器學習方法在解決有機光伏材料問題方面強大的能力,將大大加快高性能有機光伏材料及其供體/受體對的探索過程。 

The traditional research lifecycle of organic photovoltaic (OPV) materials is tedious and laborious process which contains materials design and synthesis, device characterization and optimization and performance evaluation, hampering the development of organic photovoltaic. Recently, Prof. Min’s group collected data of 565 donor/acceptor (D/A) pairs with nonfullerene small molecule acceptors and polymer donors as training and testing set to construct five machine learning (ML) methods. These methods which were based on five common algorithms, linear regression (LR), multinomial logistic regression (MLR), boosted regression trees (BRT), artificial neural network (ANN) and random forest (RF), can be used to fast screening and evaluation of new promising materials and donor or acceptor counterparts. According to the predicted results of testing set, the researchers found that ML models based on RF and BRT algorithms performed well with high Pearson’s coefficient of over 0.7. What’s more, the RF and BRT models were used to screen 3.2 million D/A pairs automatically generated by the original dataset, among which six D/A pairs were selected, synthesized and characterized to further evaluate the applicability of these ML methods in OPV. The experiment results correlated better to the predicted results of RF methods compared to that of BRT methods, which indicated superiority of RF method in high throughput virtual screening of OPV materials. This work demonstrates machine learning as a powerful tool to solve problems in OSCs, which will accelerate the discovery of high-performance D/A combinations to a large extent.

Fundamental electronic structure and multiatomic bonding in 13 biocompatible high-entropy alloys (13種生物相容性高熵合金的基本電子結構和多原子鍵合)
Wai-Yim ChingSaro SanJamieson BrechtlRidwan SakidjaMiqin Zhang & Peter K. Liaw
npj Computational Materials 6:45(2020)
doi:s41524-020-0321-x
Published online:06 May 2020

Abstract| Full Text | PDF OPEN

摘要:高熵合金(HEA)由于其諸多獨特性能和潛在應用而備受關注。在此獨特的復雜多組分合金類別中,原子間相互作用的性質尚未得到充分認識或開發。本研究報告了一種理論建模技術,可以對其電子結構和原子間鍵合進行深入分析,并根據量子力學指標,即總鍵序密度(TBOD)和部分鍵序密度(PBOD),的使用來預測HEA性能。將該理論建模技術應用于13種生物相容性多組分HEA的研究,得到了許多新穎而有價值的結果,包括使用價電子數不足、對大晶格畸變進行量化、利用實驗數據驗證機械性能、對孔隙率進行建模以降低楊氏模量等。這項研究概述了應用HEA的路線圖作生物醫學用材料的合理設計方法。 

Abstract:High-entropy alloys (HEAs) have attracted great attention due to their many unique properties and potential applications. The nature of interatomic interactions in this unique class of complex multicomponent alloys is not fully developed or understood. We report a theoretical modeling technique to enable in-depth analysis of their electronic structures and interatomic bonding, and predict HEA properties based on the use of the quantum mechanical metrics, the total bond order density (TBOD) and the partial bond order density (PBOD). Application to 13 biocompatible multicomponent HEAs yields many new and insightful results, including the inadequacy of using the valence electron count, quantification of large lattice distortion, validation of mechanical properties with experiment data, modeling porosity to reduce Young’s modulus. This work outlines a road map for the rational design of HEAs for biomedical applications.

Editorial Summary

Fundamental electronic structure and multiatomic bonding:biocompatible high-entropy alloys生物相容性高熵合金:基本電子結構和多原子鍵合

該研究通過使用先進的大型超胞建模方法研究了13種受生物啟發的HEA的電子結構、原子間鍵合和機械性能,得到了許多對開發和應用生物相容性高熵合金(HEA)至關重要的新認識。來自美國密蘇里大學堪薩斯城分校物理與天文學系的陳慧妍領導的團隊,報道了他們針對HEA的形成理論及其潛在應用方面所面臨的挑戰,所作的有關電子結構、原子間鍵合以及總鍵序密度(TBOD)和部分鍵序密度(PBOD)的研究結果。他們指出,使用TBODPBOD作為評估多組分合金基本性能的關鍵指標時,具有特別的優點:無論HEA的原子種類、組成或大小如何,都可以直接將它們進行相互比較。而且,該方法還可應用于其他材料系統,只需每對原子間的所有原子間鍵合,再通過單胞的體積作標準化即可。此特性與基于焓評估的方法中所使用的基態能有很大不同,后者在評估不同組成的多組分HEA性能時計算繁重且耗時。 

The electronic structures, interatomic bonding, and mechanical properties of the 13 bioinspired HEAs are investigated through advanced modeling using large supercells yielding many new and insightful results critical to the development and application of biocompatible HEAs. A team led by Wai-Yim Ching from the Department of Physics and Astronomy, University of Missouri Kansas City, USA, presented the electronic structure, interatomic bonding, and the application of total bond order density (TBOD) and partial bond order density (PBOD) in addressing the challenges for fundamental understanding on the theory of formation of HEAs and its potential applications. They pointed out the special merits of using TBOD and PBOD as key metrics for assessing the fundamental properties of multicomponent alloys. They can be directly compared with each other irrespective of their atomic species, composition, or size. Moreover, they can be applied to other materials systems as long as all interatomic bonding between every pair of atoms are included and normalized by the volume of the cell. This characteristic is very different from other techniques based on ground state energies used in the enthalpy evaluation, which can be quite onerous and time consuming for multi-component HEAs with different compositions.

Fifth-degree elastic energy for predictive continuum stress-strain relations and elastic instabilities under large strain and complex loading in silicon (大變形任意載荷下可預測材料不同失穩條件的五階連續介質模型)
Hao ChenNikolai A. Zarkevich, Valery I. Levitas, Duane D. Johnson & Xiancheng Zhang
npj Computational Materials 6:115(2020)
doi:s41524-020-00382-8
Published online:04 August 2020

Abstract| Full Text | PDF OPEN

摘要:材料在復雜載荷下會有大變形,并經常伴有彈性失穩的相變過程。這種過程在簡單體系和復雜體系內都被觀察到。這里,基于對大量DFT計算結果的擬合,五階連續介質力學模型被發展來擬合任意載荷下材料失穩條件。該模型的柯西應力-拉格朗日應變曲線可以很好重現第一性原理計算結果。并且該模型準確的預測了任意載荷下材料的臨界失穩應力,包括多軸正應力和剪切應力下的失穩應力。這個模型將為連續介質力學模擬材料在任意載荷下大變形失穩提供了理論基礎。 

Abstract:Materials under complex loading develop large strains and often phase transformation via an elastic instability, as observed in both simple and complex systems. Here, we represent a material (exemplified for Si I) under large Lagrangian strains within a continuum description by a -order elastic energy found by minimizing error relative to density functional theory (DFT) results. The Cauchy stress-Lagrangian strain curves for arbitrary complex loadings are in excellent correspondence with DFT results, including the elastic instability driving the Si III phase transformation (PT) and the shear instabilities. PT conditions for Si I II under action of cubic axial stresses are linear in Cauchy stresses in agreement with DFT predictions. Such continuum elastic energy permits study of elastic instabilities and orientational dependence leading to different PTs, slip, twinning, or fracture, providing a fundamental basis for continuum physics simulations of crystal behavior under extreme loading.

Editorial Summary

Fifth-degree elastic energy for predictive continuum stress-strain relations and elastic instabilities under large strain and complex loading in silicon準確預測材料在任意載荷下失效的大變形彈性理論

任意載荷下,材料失效的臨界應力具有很大的不同,例如靜水壓下,材料失穩的壓強可以到100GPa,而在多方向剪切應力下材料失穩可能只需100-200MPa,可以達到3個量級差。然而目前針對材料失穩的連續介質模型大多基于能量或者最大剪切應力,并不能完全覆蓋材料任意并不完善任意載荷。該研究基于連續介質理論提出了基于拉格朗日應變的五階大變形模型,該模型能夠準確獲得硅在任意載荷下的材料失效應力。來自中國華東理工大學的陳浩講師和其博士導師美國愛荷華州立大學航空航天工程和機械工程系的Valery I. Levitas教授團隊,以及愛荷華州立大學材料學院的Duane D. Johnson教授團隊合作,采用第一性原理計算得到了單晶硅材料在任意載荷下的失穩應力,擬合了提出的大變形彈性理論,發現該彈性理論可以精確給出硅材料任意載荷下的失穩應力。該研究為在連續介質框架下研究精確模擬材料在任意載荷下的失穩條件提供了理論基礎,由于不同載荷可以導致不同的失穩模式,比如剪切應力下發生塑性變形,而在正應力下發生相變。因此該模型為連續介質力學提供了模擬任意載荷下導致不同失效模式的可能性。 

Materials under complex loading develop large strains and often phase transformation via an elastic instability, as observed in both simple and complex systems. Here, we represent a material (exemplified for Si I) under large Lagrangian strains within a continuum description by a 5th-order elastic energy found by minimizing error relative to density functional theory (DFT) results. The Cauchy stress-Lagrangian strain curves for arbitrary complex loadings are in excellent correspondence with DFT results, including the elastic instability driving the Si I to Si II phase transformation and the shear instabilities. Phase transformation conditions for Si I to Si II under action of cubic axial stresses are linear in Cauchy stresses in agreement with DFT predictions. Such continuum elastic energy permits study of elastic instabilities and orientational dependence leading to different phase transformations, slip, twinning, or fracture, providing a fundamental basis for continuum physics simulations of crystal behavior under extreme loading.

EPIC STAR: a reliable and efficient approach for phonon- and impurity-limited charge transport calculations (EPIC STAR:一種可靠且高效的方法,用于聲子和雜質限制的電荷輸運計算)
Tianqi DengGang WuMichael B. SullivanZicong Marvin WongKedar HippalgaonkarJian-Sheng Wang & Shuo-Wang Yang
npj Computational Materials 6:46(2020)
doi:s41524-020-0316-7
Published online:7 May 2020

Abstract| Full Text | PDF OPEN

摘要:本研究提出了一種計算效率高的第一性原理方法,以預測半導體本征電荷輸運性質。利用短程電子-聲子散射的廣義Eliashberg函數和長程電子-聲子和電子-雜質散射的解析表達式,實現了不需要經驗參數即可快速可靠地預測載流子遷移率和電子熱電性能。該方法被命名為“能量依賴性聲子-和雜質-限制的載流子散射近似(EPIC STAR)”方法。通過對幾種代表性半導體的實驗測量和其他理論方法的比較,驗證了該方法的有效性,得到了極性和非極性、各向同性和各向異性材料的定量一致性。該方法的效率和魯棒性有助于實現自動化預測和無監督預測,從而可對半導體材料進行高通量篩選和新材料發現,以作導電、熱電和其他電子學方面的應用。 

Abstract:A computationally efficient first-principles approach to predict intrinsic semiconductor charge transport properties is proposed. By using a generalized Eliashberg function for short-range electron–phonon scattering and analytical expressions for long-range electron–phonon and electron–impurity scattering, fast and reliable prediction of carrier mobility and electronic thermoelectric properties is realized without empirical parameters. This method, which is christened “Energy-dependent Phonon- and Impurity-limited Carrier Scattering Time AppRoximation (EPIC STAR)” approach, is validated by comparing with experimental measurements and other theoretical approaches for several representative semiconductors, from which quantitative agreement for both polar and non-polar, isotropic and anisotropic materials is achieved. The efficiency and robustness of this approach facilitate automated and unsupervised predictions, allowing high-throughput screening and materials discovery of semiconductor materials for conducting, thermoelectric, and other electronic applications.

Editorial Summary

EPIC STAR: a reliable and efficient approach for phonon- and impurity-limited charge transport calculationsEPIC STAR:一種可靠且高效的方法,用于聲子和雜質限制的電荷輸運計算

  該研究提出了一種計算效率高的第一性原理方法,以預測半導體本征電荷輸運性質。來自新加坡科學技術研究局高性能計算研究所的Gang WuShuo-Wang Yang共同領導的團隊,通過引入廣義Eliashberg函數并加入光學聲子極化、雜質散射和自由載流子屏蔽等過程,經過密度泛函微擾理論的計算,使該方法在計算量很小的情況下,尤其對非極性和極性半導體都能實現高保真度。該研究論證了極性光學聲子散射的重要性,這表明在研究極性半導體的電子性質時,在沒有考慮極性光學聲子散射時,需格外小心。通過與Si、GaAs、Mg2SiNbFeSb的實驗和理論結果進行的比較,作者驗證了這一方法的可靠性,并揭示了NaInSe2是一種潛在的新型熱電材料。隨著近年來高通量DFPT計算發展,該方法提出的方法可廣泛應用于高遷移率半導體和高性能熱電光伏材料的高通量篩選。 

A swift and automation-friendly approach for intrinsic and impurity-limited charge transport property prediction from first-principles is proposed. A team co-led by Gang Wu and Shuo-Wang Yang from the Institute of High Performance Computing, Agency for Science, Technology and Research, Singapore, by introducing generalized Eliashberg function and adding polar optical phonon contribution, impurity scattering, and free carrier screening, enabled the new approach to achieve high fidelity especially for both non-polar and polar semiconductors with very small computational cost after calculations by density functional perturbation theory (DFPT). They demonstrated the importance of polar optical phonon scattering, which suggests that care should be taken when the electronic properties of polar semiconductors are studied without polar optical phonon scattering. The authors verified this approach by comparing with previous experimental and theoretical results for Si, GaAs, Mg2Si, and NbFeSb, and also revealed NaInSe2 as a potential new thermoelectric material. As high-throughput DFPT computations have been demonstrated recently, this methodology can be widely applied for reliable high-throughput screening of high mobility semiconductors and high-performance thermoelectric and photovoltaic materials.

Efficient training of ANN potentials by including atomic forces via Taylor expansion and application to water and a transition-metal oxide (通過包括通過泰勒展開產生的原子力并應用于水和過渡金屬氧化物中,有效地訓練ANN勢)
April M. CooperJohannes KastnerAlexander Urban & Nongnuch Artrith
npj Computational Materials 6:54(2020)
doi:s41524-020-0323-8
Published online:13 May 2020

Abstract| Full Text | PDF OPEN

摘要:基于人工神經網絡(ANN)的經驗勢函數可以實現針對復雜材料的高精度(接近第一原理)大規模的原子模擬。對于分子動力學模擬,準確的能量和原子間作用力是先決條件,然而這需要同時基于電子結構計算得到的能量和力進行ANN訓練。本工作,我們基于總能量的泰勒展開,提出了一種同時基于能量和力信息來訓練ANN勢的有效替代方法。通過將力信息轉換為近似能量,可以避免傳統力訓練方法中計算量隨原子數量二次方增長的關系,從而可以利用包含復雜原子結構的參考數據集進行訓練。以不同系統為例,如水分子團簇、液態水和鋰過渡金屬氧化物,我們證明了所提出的力訓練方法相對于僅依靠能量訓練的方案具有顯著提升。在訓練中包含力信息可減少構建ANN勢所需的參考數據集的大小,增加勢函數的可移植性,并整體提升力預測的精度。對于水團簇,與所有力分量的顯式訓練相比,泰勒展開方法可降低約50?%的誤差,而計算成本卻要低得多。因此,這樣的力訓練方法,簡化了用于模擬復雜材料能量和力的ANN勢的構造過程,正如本研究在水和過渡金屬氧化物中證明的情形那樣。 

Abstract:Artificial neural network (ANN) potentials enable the efficient large-scale atomistic modeling of complex materials with near first-principles accuracy. For molecular dynamics simulations, accurate energies and interatomic forces are a prerequisite, but training ANN potentials simultaneously on energies and forces from electronic structure calculations is computationally demanding. Here, we introduce an efficient alternative method for the training of ANN potentials on energy and force information, based on an extrapolation of the total energy via a Taylor expansion. By translating the force information to approximate energies, the quadratic scaling with the number of atoms exhibited by conventional force-training methods can be avoided, which enables the training on reference datasets containing complex atomic structures. We demonstrate for different materials systems, clusters of water molecules, bulk liquid water, and a lithium transition-metal oxide that the proposed force-training approach provides substantial improvements over schemes that train on energies only. Including force information for training reduces the size of the reference datasets required for ANN potential construction, increases the transferability of the potential, and generally improves the force prediction accuracy. For a set of water clusters, the Taylor-expansion approach achieves around 50% of the force error improvement compared to the explicit training on all force components, at a much smaller computational cost. The alternative force-training approach thus simplifies the construction of general ANN potentials for the prediction of accurate energies and interatomic forces for diverse types of materials, as demonstrated here for water and a transition-metal oxide.

Editorial Summary

Transferring force into energy: accelerating construction of the machine learning potential變力為能量:加速機器學習勢函數構建

  該研究提出一種基于原子間作用力信息來高效訓練高精度神經網絡經驗勢函數的方法。來自美國、德國和英國的聯合研究團隊,提出將力信息轉換為近似能量,由此構建機器學習經驗勢的新方法?;诘谝恍栽砑蠙C器學習,訓練經驗勢對于大規模材料模擬來說十分重要。準確的經驗勢需要同時擬合體系能量和原子間作用力。而作用力的作為能量一階導數,擬合比較復雜,其計算量與原子數目成二次方關系。 

  作者將作用力轉化為能量巧妙的繞開了上述問題,由此可以采用較大體系的數據集開展訓練。計算結果表明,與直接采用作用力訓練勢函數的方法相比,該方法不僅將勢函數的精度提升了50%,同時計算效率明顯提升。為進一步驗證該方法的有效性,作者選取了三個具體的模型體系,即水分子團簇、液態水和復雜金屬氧化物開展勢函數訓練。他們發現,該方法可以顯著降低訓練所需的數據集大??;具有很好的可移植性,可以準確預測數據集之外的新體系;可以同時提升作用力預測的準確性。簡而言之,該方法簡化了神經網絡經驗勢的構造過程,有望推廣應用于任意類型的材料中。

An efficient training method for high-precision artificial neural network (ANN) empirical potential has been proposed based on the information of interatomic forces. 

The joint research team from the United States, Germany and the United Kingdom proposed this new method to by Taylor extrapolation of the total energy with inter-atomic forces. Empirical interatomic potential trained by machine learning based on first principles is important for large-scale material simulation. Accurate empirical potential requires simultaneous fitting of the total energy and interatomic forces. The force, as the first derivative of energy, is more complex to fit, as the computational cost is quadratic with the number of atoms. By translating the force information into energy, the authors bypass this problem. They found that compared with the conventional training method directly by force, the accuracy of potential can be improved by 50% by the newly proposed method with the calculation efficiency significantly improved. To further validify this method, three specific model systems, namely water molecular clusters, liquid water and complex metal oxides, are selected to train the potential. The results showed that this method can significantly reduce the size of the data set needed for training; it has good transferability as could accurately predict the new structure outside the data set; it can also improve the accuracy of force prediction. In short, this method simplifies the construction process of ANN potential, and is expected to be applied to any kind of materials.

Design of two-dimensional carbon-nitride structures by tuning the nitrogen concentration (基于氮濃度的調控實現二維氮化碳結構的設計)
Saiyu Bu, Nan Yao, Michelle A. Hunter, Debra J. Searles & Qinghong Yuan
npj Computational Materials 6:128(2020)
doi:s41524-020-00393-5
Published online:21 August 2020

Abstract| Full Text | PDF OPEN

摘要:氮摻雜石墨烯(NG)的性質與本征石墨烯的顯著差異使其在物理、化學、生物和材料科學等領域中具有更廣泛的應用。近些年NG的研究引起了越來越多的關注。然而,目前大多數實驗制備的NG通常氮濃度較低且多種類型的氮混合摻雜,限制了不同類型NG優異的物理和化學性質的應用。在本研究工作中,我們運用第一性原理計算與局域粒子群優化算法相結合的方法,探索了不同C/N比率下二維氮化碳(C1-xNx)可能的穩定結構?;诶碚撚嬎愕玫降牟煌Y構的C1-xNx的形成能,得出了低氮摻雜濃度下C1-xNx結構中同時含有石墨氮和吡啶氮的結論,并且發現低氮摻雜濃度的C1-xNx結構的形成能要比高N摻雜濃度的結構的形成能低得多,這意味著合成低氮摻雜濃度的NGs在能量上更為有利。這一系列結果解釋了實驗中觀察到的NG中石墨氮和吡啶氮的共存以及實驗中氮摻雜濃度過低的現象。計算還表明,如果氮摻雜濃度大于0.25,則C1-xNx結構中吡啶氮占優勢。進一步,我們提出了通過控制C和N源的前驅體以及生長溫度來克服低N摻雜濃度和N混合摻雜的限制,實現NGs的可控制備的實驗設想。 

Abstract:Nitrogen-doped graphene (NG) has attracted increasing attention because its properties are significantly different to pristine graphene, making it useful for various applications in physics, chemistry, biology, and materials science. However, the NGs that can currently be fabricated using most experimental methods always have low N concentrations and a mixture of N dopants, which limits the desirable physical and chemical properties. In this work, first principles calculations combined with the local particle-swarm optimization algorithm method were applied to explore possible stable structures of 2D carbon nitrides (C1-xNx) with various C/N ratios. It is predicted that C1-xNx structures with low N-doping concentration contain both graphitic and pyridinic N based on their calculated formation energies, which explains the experimentally observed coexistence of graphitic and pyridinic N in NG. However, pyridinic N is predominant in C1-xNx when the N concentration is above 0.25. In addition, C1-xNx structures with low N-doping concentration were found to have considerably lower formation energies than those with a high N concentration, which means synthesized NGs with low N-doping concentration are favorable. Moreover, we found the restrictions of mixed doping and low N concentration can be circumvented by using different C and N feedstocks, and by growing NG at lower temperatures.

Editorial Summary

Structure of nitrogen-doped graphene: How to tune it?氮摻雜石墨烯的結構調控:路在何方?

對石墨烯進行氮摻雜是打開石墨烯帶隙,提高其自由載流子密度,拓展石墨烯應用的重要方法之一。然而目前實驗上合成的氮摻雜石墨烯(NG)中氮原子的摻雜比率普遍較低,摻雜的氮原子通常以吡啶氮、吡咯氮、石墨氮等多種形式共存,并且摻雜氮原子在石墨烯的面內排列無序,這些特點極大地限制了NG的實際應用。本研究基于理論計算,揭示了NG中氮摻雜濃度低和各種類型氮混合摻雜的本質原因,并提出可通過控制前驅體種類、反應溫度和壓強對NG的氮摻雜濃度和類型進行調控的設想。
來自華東師范大學精密光譜科學與技術國家重點實驗室的博士生補賽玉(昆士蘭大學交流學生)及其導師袁清紅研究員與澳大利亞昆士蘭大學澳大利亞生物工程及納米科技研究所的Debra J. Searles教授等人,采用第一性原理計算與粒子群優化算法相結合的方法,對不同氮摻雜濃度的NG的穩定結構和能量進行了研究,揭示了目前NG合成中氮摻雜濃度低和不同類型氮原子混合摻雜的原因,提出了調控氮原子摻雜濃度和類型的有效方法。研究發現,NG的穩定結構與其中的氮原子濃度密切相關,低氮摻雜濃度下,NG中的石墨氮和吡啶氮具有相近的形成能,因而更易形成石墨氮和吡啶氮共摻雜的結構。隨著氮原子摻雜濃度的增加,石墨氮摻雜石墨烯的形成能要高于吡啶氮摻雜石墨烯的形成能,因而更易形成吡啶氮摻雜的石墨烯結構。特別是,當N原子摻雜濃度高于0.25時,NG中以吡啶氮摻雜為主。此外,該項研究還表明,低氮摻雜濃度的NG具有更低的形成能。這一系列研究結果解釋了目前實驗上NG中氮原子摻雜濃度低,以及多種類型的氮混合摻雜的實驗現象?;诶碚撗芯拷Y果,研究人員進一步提出可通過控制NG合成過程中的前驅體種類、生長溫度和壓強等實現碳和氮原子化學勢的調控,從而實現NG中氮原子的摻雜類型和濃度的調控。該研究通過對不同氮摻雜濃度下NG的結構和能量進行研究,為NG的可控合成提供了理論依據
。

Nitrogen doping of graphene is one of the important methods to open the bandgap of graphene, increasing its carrier density, making graphene active catalysts for many reactions, and thus expand the applications of graphene. However, the doping ratio of nitrogen atoms in experimentally synthesized nitrogen-doped graphene (NG) is generally low. Moreover, the doped nitrogen atoms usually coexist in various forms such as pyridinic, pyrrolic, and graphitic N, and the doped N atoms are usually randomly distributed in graphene. The uncontrollable doping greatly limits the applications of NG and thus understanding the mechanism of N doping in graphene and finding out potential means for the controllable doping is highly desired. In this work, based on theoretical calculations, we revealed the inherent reasons of low doping concentration and co-doping of different types of N centers, and proposed effective methods to control the N doping concentration and the type of nitrogen-dopants.  

Saiyu Bu, a PhD student from State Key Laboratory of Precision Spectroscopy, East China Normal University, (she was also a visiting student at The University of Queensland) and her supervisor Prof. Qinghong Yuan, together with Professor Debra J. Searles, from the Australian Institute of Bioengineering and Nanotechnology, The University of Queensland, Australia, et al., studied the stable structures and formation energies of NG with different doping concentration and types , revealed the reasons for the low nitrogen doping concentration and mixed doping of different types of nitrogen centers in the synthesized NG, and proposed methods to regulate the concentration and/or type of N dopant. It was found that the stable structures of NGs are highly dependent on their N doping concentration. At low N doping concentration, pyridinic N and graphitic N doped in graphene have similar formation energies, thus the NGs are more likely to be co-doped with both pyridinic and graphitic N centers. With the increase of doping concentration, the formation energy of graphitic N doped graphene becomes higher than that of pyridinic N doped graphene, leading to the preference of pyridinic N centers. Moreover, it is found that NGs with low a N concentration have lower formation energies and thus better stability. The theoretical calculations explained the current experimental observations of NGs with low N concentration and co-dopants of graphitic and pyridinic N centers. On the basis of the calculation results, the researchers proposed that the structure of NG can be well modulated by controlling the N and C feedstock, growth temperature and pressure etc.  

This study provides theoretical guideline for the synthesis of NG in a manner.
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