(Invited) Isotopically Programmed Group IV Semiconductors: A Versatile Platform for Quantum Technologies
Notice bibliographique
Résumé
The introduction of stable isotopes as an additional degree of freedom in the growth of semiconductor films and quantum structures provides a wealth of opportunities to manipulate their basic properties, design an entirely new class of devices, and highlight subtle but important nanoscale and quantum phenomena. In this presentation, I will describe the historical context and outline the recent progress in the area of isotopically engineering group IV semiconductors with focus on nanoscale and quantum structures and devices. This ability to isotopically program semiconductor structures has been a powerful paradigm to investigate and manipulate some of the important physical properties of semiconductors and exploit them in innovative device structures [1-13]. Isotopes of an element differ in the number of neutrons in the nucleus. This creates differences between the isotopes in their lattice dynamics and nuclear properties. For instance, the slight difference in zero-point motion leads to a difference in atomic volume between the isotope atoms, which influences the lattice constant [3]. Also, the difference in electron-phonon coupling between crystals of different isotopic composition was found to affect the electronic band gap [4]. The nuclear spin is another significant difference between stable isotopes. For instance, natural silicon (Si) has three stable isotopes: 28 Si, 29 Si, and 30 Si, with isotopic abundances of 92.23%, 4.67%, and 3.10%, respectively. Among these three isotopes, only 29 Si has a nuclear spin of ½, whereas 28 Si and 30 Si are nuclear spin-free. This property has been crucial in the realization of Si-based quantum information devices [5-8]. One of the most drastic isotope related effect in semiconductors is found in phonon properties [9-13]. Mass fluctuation induced by isotope disorder acts as a substitutional defect in a crystal thus affecting the phonon mean free path and consequently the phononic thermal conductivity. Measurements on isotopically pure Ge [9] and Si [10] crystals showed an enhanced thermal conductivity as compared to their natural counterparts. Also, lower thermal conductivity was recently demonstrated in Si isotope superlattices [11]. All the properties of semiconductor stable isotopes have been investigated and exploited in bulk materials or thin films. Herein, we will describe the new opportunities emerging from the combinations of the isotope effects with size-related effects in nanoscale materials [14-18]. More specifically, we will discuss phonon engineering in metal catalyzed silicon nanowires with tailor-made isotopic compositions grown using isotopically enriched silane and german precursors 28 SiH 4 , 29 SiH 4 , 30 SiH 4 , 74 GeH 4 and 76 GeH 4 , with purity better than 99.9%. Isotopically mixed nanowires 28 Si x 30 Si 1-x with a composition close to the highest mass disorder ( x ~ 0.5) were used as a playground to elucidate the interplay between nanoscale interface phenomena and heat transport [16]. We will show how isotopically engineered nanowire homo-junctions can be introduced to realize innovative phononic devices such as thermal diodes and thermal transistors. Additionally, we will also discuss the use of nuclear spin-full 29 Si to engineer novel quantum devices in nuclear spin-free SiGe nanostructures. Finally, atomistic-level investigations of isotopically programmed nanoscale materials will be presented based on laser-assisted atom probe tomography [15,17]. References [1] M. Cardona et al., Rev. Moden Phys. 77, 1173 (2005). [2] E. E. Haller, MRS Bull. 31, 547 (2006). [3] M. Hu et al., M. Phys. Rev. B 67, 113306 (2003). [4] G. Davis et al., Semicond. Sci. Technol. 7, 1271 (1992). [5] A. M. Tyryshkin et al., Nat. Mater. 11, 143 (2012). [6] D. R. McCamey et al., Science 330, 1652 (2010). [7] S. Simmons et al., Nature 470, 69 (2011). [8] K. M. Itoh, Solid State Commun. 133, 747 (2005). [9] V. I. Ozhogin et al., J. Exp. Theor. Phys. Lett. 63, 490 (1996). [10] R. K. Kremer et al., J. Solid State Commun. 131, 499 (2004). [11] H. Bracht et al., New J. Phys. 16, 015021 (2014). [12] M. Nakajima et al., Phys. Rev. B 63, 161304 (2001). [13] D. Morelli et al., Phys. Rev. B 66, 195304 (2002). [14] O. Moutanabbir et al., Phys. Rev. Lett. 105, 026101 (2010) [15] O. Moutanabbir et al., Appl. Phys. Lett. 98, 013111 (2011). [16] S. Mukherjee et al., Nano Letters 15, 3885 (2015). [17] S. Mukherjee et al., Nano Letters 16, 1335 (2016). [18] S. Mukherjee et al., Nano Letters, under review (2018).
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Comment cette classification a été obtenuedéplier
Prédiction distillée sur la base complète
Imitation des enseignantsNi 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.
Scores Codex et Gemma par catégorie
| Catégorie | Codex | Gemma |
|---|---|---|
| Métarecherche | 0,000 | 0,001 |
| Méta-épidémiologie (sens strict) | 0,000 | 0,000 |
| Méta-épidémiologie (sens large) | 0,000 | 0,000 |
| Bibliométrie | 0,000 | 0,000 |
| Études des sciences et des technologies | 0,000 | 0,000 |
| Communication savante | 0,000 | 0,000 |
| Science ouverte | 0,000 | 0,000 |
| Intégrité de la recherche | 0,000 | 0,000 |
| Charge utile insuffisante (le modèle a refusé de juger) | 0,000 | 0,000 |
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.
score_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 découleClassification
machine, non validéePrédiction automatique; un appel candidat d’une seule tête enseignante, pas un consensus.
Le détail, modèle par modèle et score par score, se trouve en fin de page sous « Comment cette classification a été obtenue ».