Strain-Mitigated Two Dimensional Based Electronics for Integrated Wearable Sensor-Systems
Notice bibliographique
Résumé
The ability to fabricate incredibly sophisticated integrated circuits at low cost rendered modern electronics more affordable, efficient, and functional. This monumental advance in technology would usher in the age of the Internet-of-things and transform wearable electronics from a largely academic pursuit into an everyday reality around which a robust and rapidly growing industry has formed. However, even the highly connected wearable electronics of today leave much to be desired with respect to their compatibility with soft tissues such as skin. More specifically, the poor compliance of the rigid, silicon-based integrated circuits conventionally used in the construction of these devices with the soft, curvilinear surfaces of the human body can result in high impedances at the skin-sensor interface which in turn contribute to low signal-to-noise ratios as well as poor sensitivity and accuracy. Motion artifacts originating from the poor conformability of such devices only exacerbate these problems. This mechanical mismatch represents a significant hurdle in the effort to move away from the conventional reactive approach to healthcare towards a more proactive approach that leverages ‘truly’ wearable sensors to improve health outcomes. Transistors are the building blocks upon which the vast majority of modern electronics are built. Although single transistors can be used to amplify or otherwise control electronic signals using only a small input signal, most of their functionality comes in the form of integrated circuits (ICs) consisting of many connected transistors. Conventional techniques for fabricating ICs exploit the rigidity of the semiconducting silicon substrate to ensure the device performance is consistent throughout the circuit. In contrast, integrated circuits for highly compliant wearable electronics that can conform even to microscopic features of the skin[1,2] face the inherent challenge of maintaining their electrical performance under mechanical deformations. As is the case with most sensors, the front-end circuitry for these devices (responsible for conveying the information contained in the signal – either wirelessly or without wires – to the end user) requires reliable and performant integrated circuits. Of course, integrating soft, ultra-thin sensors with the rigid silicon-based integrated circuits results in a mechanical mismatch with mechanical failure at the interface where the two components meet being the most likely scenario. Instead, here we present an approach which uses two-dimensional (2D) transistors in a specially designed strain-neutralizing configuration which circumvents much of the difficulties associated with the aforementioned mismatch. The extraordinary properties of 2D materials—particularly their excellent mechanical flexibility, ultimate thinness, optical transparency, and favorable transport properties for realizing electronics—make them prime candidates for replacing conventional silicon-based transistor circuits in next-generation wearable applications. Using finite-element analysis we have designed and simulated a compliant, strain-insensitive substrate which can resist uniaxial applied strains upwards of 35%. Moreover, simulations of the electronic band structure of the transistors under applied strain is used to optimize the circuit design and further minimize the effect of strain in the transistors. These electronic and mechanical simulations are used together in the configuration and subsequent fabrication of fully integrated strain-neutralized 2D transistors compatible with state-of-the-art soft stretchable wearable sensors. [1]S. Kabiri Ameri et al., “Graphene electronic tattoo sensors,” ACS Nano, 11, 7634–7641, 2017. [2] S. Kabiri Ameri et al., “Imperceptible electrooculography graphene sensor system for human–robot interface”, npj 2D Materials and Applications, 2, 1-7, 2018.
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 machine sur la base complète
Imitation des enseignantsNi prévalence calibrée, ni vérité terrain. Validation humaine à venir. Le volet Gemma est une étiquette directe du modèle pour chaque travail de la base, lue sur la notice réduite au titre. Le volet Codex est un classifieur appris des 10 348 étiquettes directes de Codex et calibré sur les taux pondérés de l'échantillon; les champs sans appui suffisant ne portent aucun appel Codex. Le mode candidate est l'union des deux volets; le consensus est leur intersection. Ces sorties portent le statut machine_predicted_unvalidated et ne sont pas des étiquettes humaines.
Scores du classifieur distillé par catégorie (deux têtes)
| 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 | 0,001 | 0,001 |
| Science ouverte | 0,001 | 0,001 |
| Intégrité de la recherche | 0,001 | 0,001 |
| Charge utile insuffisante (le modèle a refusé de juger) | 0,005 | 0,002 |
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 source (Gemma direct ou Codex distillé), 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 ».