Micro-light-emitting diodes (micro-LEDs) are the key to next-generation display technology. However, since the driving circuits are typically composed of Si devices, numerous micro-LED pixels must be transferred from their GaN substrate to bond with the Si field-effect transistors (FETs). This process is called massive transfer, which is arguably the largest obstacle preventing the commercialization of micro-LEDs. We combined GaN devices with emerging graphene transistors and for the first-time designed, fabricated, and measured a monolithic integrated device composed of a GaN micro-LED and a graphene FET connected in series. The p-electrode of the micro-LED was connected to the source of the driving transistor. The FET was used to tune the work current in the micro-LED. Meanwhile, the transparent electrode of the micro-LED was also made of graphene. The operation of the device was demonstrated in room temperature conditions. This research opens the gateway to a new field where other two-dimensional (2D) materials can be used as FET channel materials to further improve transfer properties. The 2D materials can in principle be grown directly onto GaN, which is reproducible and scalable. Also, considering the outstanding properties and versatility of 2D materials, it is possible to envision fully transparent micro-LED displays with transfer-free active matrices (AM), alongside an efficient thermal management solution.
In this paper, we propose a multi-agent framework to deal with situations involving uncertain or inconsistent information located in a distributed environment which cannot be combined into a single knowledge base. To this end, we introduce an inquiry dialogue approach based on a combination of possibilistic logic and a formal argumentation-based theory, where possibilistic logic is used to capture uncertain information, and the argumentation-based approach is used to deal with inconsistent knowledge in a distributed environment. We also modify the framework of earlier work, so that the system is not only easier to implement but also more suitable for educational purposes. The suggested approach is implemented in a clinical decision-support system in the domain of dementia diagnosis. The approach allows the physician to suggest a hypothetical diagnosis in a patient case, which is verified through the dialogue if sufficient patient information is present. If not, the user is informed about the missing information and potential inconsistencies in the information as a way to provide support for continuing medical education. The approach is presented, discussed, and applied to one scenario. The results contribute to the theory and application of inquiry dialogues in situations where the data are uncertain and inconsistent.
Currently, applying graphene on GaN based electronic devices requires the troublesome, manual, lengthy, and irreproducible graphene transfer procedures, making it not feasible for real applications. Here, a semiconductor industry compatible...
This paper presents ACKTUS, a semantic web platform for modeling and managing knowledge integrated in support systems for health care, and for designing the interaction with the end user applications. A key purpose is to allow the domain experts to collaboratively model the knowledge content and tailor interaction to users. Therefore, the development has been done in a process of participatory action research where domain experts have contributed to the design and re-design of ACKTUS while they have been modeling the content and behavior of end-user applications. The ontology that serves as the knowledge structure in the system integrates the user model, modality values, clinical practice guidelines and preferences, in the form of schemes and scheme-nodes (arguments) in an argumentation framework, partly by integrating the argument interchange format. User studies have shown that ACKTUS can be used for the intended purpose by domain professionals not familiar with knowledge engineering tasks. Moreover, the platform functions as a research infrastructure for health researchers in their development and evaluation of new ICT-based interventions targeting improved health.
scite is a Brooklyn-based organization that helps researchers better discover and understand research articles through Smart Citations–citations that display the context of the citation and describe whether the article provides supporting or contrasting evidence. scite is used by students and researchers from around the world and is funded in part by the National Science Foundation and the National Institute on Drug Abuse of the National Institutes of Health.
hi@scite.ai
10624 S. Eastern Ave., Ste. A-614
Henderson, NV 89052, USA
Copyright © 2024 scite LLC. All rights reserved.
Made with 💙 for researchers
Part of the Research Solutions Family.