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Enregistrement W3025740981 · doi:10.1149/ma2020-0110835mtgabs

Van Der Waals Growth of III-V Semiconductors on Graphene

2020· article· en· W3025740981 sur OpenAlexaff
Nima Nateghi, Samik Mukherjee, Dhan Cardinal, Robert M. Jacobberger, Austin J. Way, Marı́a de la Mata, Richard Martel, P. Desjardins, Jordi Arbiol, Michael S. Arnold, Oussama Moutanabbir

Notice bibliographique

RevueECS Meeting Abstracts · 2020
Typearticle
Langueen
DomaineEngineering
ThématiqueNanowire Synthesis and Applications
Établissements canadiensRegroupement Québécois sur les Matériaux de PointeUniversité de MontréalPolytechnique MontréalTAV College
Organismes subventionnairesnon disponible
Mots-clésGraphenevan der Waals forceSemiconductorNucleationMaterials scienceBand gapDangling bondNanotechnologyEpitaxyOptoelectronicsCondensed matter physicsChemical physicsChemistrySiliconPhysics

Résumé

récupéré en direct d'OpenAlex

Recent discovery of graphene and its unique properties has attracted a great deal of interest in implementing this material in a variety of new devices, targeting applications in ultra-fast electronics, quantum information, carbon-free energy conversion, optoelectronics, and bio-integrated technologies [1,2]. However, graphene lacks a controlled non-zero bandgap, which prevents its large-scale application in electronic and energy conversion devices. To overcome this limitation, we exploit direct integration of III-V semiconductors on graphene through van der Waals epitaxy. Known for their efficient light emission and high charge carrier mobilities, III-V semiconductors are at the core of numerous technologies including high-efficiency solar cells, lasers, light emitting diodes, and ultra-fast transistors, to name a few [3]. Due to lack of dangling bonds on graphene’s surface, in epitaxial growth of III-V semiconductors on graphene the crystals follow the order of graphene lattice through van der Waals forces. Initially, two nucleation and growth processes were suggested for such van der Waals epitaxy: (1) nucleation starts at defect sites on graphene [4], and (2) nucleation starts on specific sites on graphene lattice, which are the favorable adsorption sites for III/V adatoms [5]. The latter growth mechanism limits the epitaxial growth of the III-V crystals in four different relative orientations (with different strain values) [5]. Recently, density functional theory calculations followed by homoepitaxial growth of InP, GaP, and GaAs through several layers of graphene suggested another determining factor in van der Waals epitaxial growth: long-range interaction between the III-V substrate under graphene and the III-V structures grown on graphene [6]. In this talk, we demonstrate the low-pressure metal-organic vapor phase deposition (MOCVD) of InAs, GaAs, InP, and GaP islands on single layer graphene sheets grown on copper foils and transferred on SiO 2 /Si (100), as well as graphene sheets directly grown on Ge (100), (110), and (111) substrates. We show that regardless of the nature of the substrate under graphene, III-V crystals grow mostly on graphene defect sites and their morphology can be somewhat controlled through controlling the growth parameters. We then show the effect of long-range forces between Ge and III-V structures on growth morphology, which results in significant coalescence and growth of tens of micron large islands on graphene/Ge as opposed to parasitic crystals grown on graphene/SiO 2 . In what follows, we provide a brief summary of our observations in both systems. All III-V semiconductors grown on graphene/SiO 2 /Si showed very similar growth morphology and crystal structure. Plan-view and cross-sectional scanning electron microscopy (SEM), micro-Raman spectroscopy, powder and high-resolution X-ray diffraction (XRD), along with cross-sectional transmission electron microscopy (TEM) and nanoscale cathodoluminescence analysis revealed formation of 1D, 2D, and 3D structures in zinc-blende, wurtzite, and polytypic (mixed zinc-blende/wurtzite) phases. We have recently demonstrated that polytypic InP crystals form a type II homojunction with potential applications in optoelectronic devices [7]. XRD analysis of the growth time evolution of texture, as well as growth rate and crystal size evolution analysis of the crystals using atomic force microscopy (AFM) suggested a growth mechanism similar to selected area MOCVD growth [7], which is widely used to grow nanostructures and devices. This enabled us to have some degree of control over the growth morphology (single crystals, polycrystals, nanowires) through controlling the growth parameters such as growth temperature, rate and time. Similar 1D, 2D, and 3D structure were grown on graphene/Ge (100), (110), (111). However, the size and crystalline quality of the islands have significantly improved for growth on Ge substrates. Moreover, two-step growth (nucleation at low temperature (450 °C) and growth at higher temperature (600 °C)) lead to coalescence of the crystals and formation of tens of microns large islands with smooth surface (roughness ~ 1nm from AFM data) on graphene/Ge, while no significant improvement in growth morphology was observed for growth on graphene/SiO 2 . These observations suggest a strong sensitivity of the morphology of the deposited films on the nature of the substrate below the graphene monolayers. This provides insight to control the properties of such hybrid systems and will pave the path to engineering a new class of electronic and optoelectronic devices by combining the advantages of semiconductors and graphene. References [1] K. S. Novoselov et al. , Nature 490 , 192 (2012). [2] A.K. Geim, IV Grigorieva, Nature 99 , 419 (2013) [3] O. Moutanabbir, U. Gosele, Annu. Rev. Mater. Res. 40 , 469 (2010). [4] Y. G. Hong et al ., ACS Nano 5 , 7576 (2011). [5] A. M. Munshi et al. , NanoLetters 7 , 713 (2013). [6] Y. Kim et al. , Nature 544 , 340 (2017). [7] S. Mukherjee et al. , Adv. Funct. Mater. 28 , 1705592 (2018). Figure 1

Récupéré en direct depuis OpenAlex et désinversé. Les résumés ne sont pas conservés dans cette base de données : les index inversés représentent 8,6 Go des 9,3 Go de texte de la base, et le serveur dispose de 13 Go libres.

Comment cette classification a été obtenuedéplier

Prédiction distillée sur la base complète

Imitation des enseignants

Ni prévalence calibrée, ni vérité terrain. Validation humaine à venir. Apprise à partir de 10 348 étiquettes directes de Codex et de 10 348 étiquettes directes de Gemma. Le mode candidate est l'union des têtes enseignantes seuillées; le consensus est leur intersection. Ces sorties portent le statut machine_predicted_unvalidated et ne sont ni des étiquettes humaines ni des étiquettes directes de modèles de pointe.

score de la tête « metaresearch » (Codex)0,000
score de la tête « metaresearch » (Gemma)0,000
Version: codex-gemma-dda1882f352aStatut de validation: machine_predicted_unvalidated
Catégories candidatesaucune
Catégories consensuellesaucune
DomaineSignal candidat: aucune · Signal consensuel: aucune
Devis d'étudeSignal candidat: Expérimental (laboratoire) · Signal consensuel: Expérimental (laboratoire)
GenreSignal candidat: Empirique · Signal consensuel: Empirique
Score de désaccord entre enseignants0,099
Score d'incertitude au seuil0,504

Scores Codex et Gemma par catégorie

CatégorieCodexGemma
Métarecherche0,0000,000
Méta-épidémiologie (sens strict)0,0000,000
Méta-épidémiologie (sens large)0,0000,000
Bibliométrie0,0000,000
Études des sciences et des technologies0,0000,000
Communication savante0,0000,000
Science ouverte0,0000,000
Intégrité de la recherche0,0000,000
Charge utile insuffisante (le modèle a refusé de juger)0,0000,000

Scores machine (provisoires)

Les deux têtes enseignantes du modèle étudiant, lues sur ce travail. Un score ordonne la base pour la relecture; il n'affirme jamais une catégorie, et le statut de validation accompagne chaque rangée tel quel.

Scores de référence d'un modèle non mature (critères de maturité non atteints, 7 itérations). Un score ordonne; il n'affirme jamais une catégorie.

Tête enseignante Opus0,018
Tête enseignante GPT0,219
Écart entre enseignants0,201 · la distance entre les deux têtes enseignantes sur ce seul travail
Statut de validationscore_only:v0-immature-baseline · tel quel depuis la passe de notation : score_only signifie que le nombre peut ordonner les travaux, et qu'aucune étiquette de catégorie n'en découle

Classification

machine, non validée

Prédiction automatique; un appel candidat d’une seule tête enseignante, pas un consensus.

Les modèles n’ont appliqué aucune catégorie : rien dans la taxonomie ne correspondait à ce travail.
Devis d'étudeExpérimental (laboratoire)
Domainenon disponible
GenreEmpirique

Le détail, modèle par modèle et score par score, se trouve en fin de page sous « Comment cette classification a été obtenue ».

En bref

Citations1
Publié2020
Routes d'admission1
Résumé présentoui

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