Browsing by Author "Volin, Ulrika"

Now showing 1 - 3 of 3
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    Atomic layer deposition of Zr-sandwiched ZnO thin films for transparent thermoelectrics
    (IOP Publishing Ltd., 2023-01-15) Koskinen, Tomi; Volin, Ulrika; Tossi, Camilla; Raju, Ramesh; Tittonen, Ilkka; Department of Electronics and Nanoengineering; Ilkka Tittonen Group; Department of Electronics and Nanoengineering
    Atomic layer deposited (ALD) transparent thermoelectric materials enable the introduction of energy harvesting and sensing devices onto surfaces of various shapes and sizes in imperceptible manner. Amongst these materials, ZnO has shown promising results in terms of both thermoelectric and optical characteristics. The thermoelectric performance of ZnO can be further optimized by introducing extrinsic doping, to the realization of which ALD provides excellent control. Here, we explore the effects of sandwiching of ZrO2 layers with ZnO on glass substrates. The room-temperature thermoelectric power factor is maximised at 116μW m−1 K−2 with samples containing a 2% nominal percentage of ZrO2. The addition of ZrO2 layers is further shown to reduce the thermal conductivity, resulting in a 20.2% decrease from the undoped ZnO at 2% doping. Our results contribute to increasing the understanding of the effects of Zr inclusion in structural properties and growth of ALD ZnO, as well as the thermal and thermoelectric properties of Zr-doped ZnO films in general.
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    Biocompatibility of carbon-based nanomaterials
    (2020-12-21) Volin, Ulrika; Pande, Ishan; Sähkötekniikan korkeakoulu; Turunen, Markus
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    Designing a supply market intelligence model to maximize business value
    (2024-08-21) Volin, Ulrika; Espigares, Inmaculada; Perustieteiden korkeakoulu; Vuori, Natalia
    This thesis investigates the role of Market Intelligence (MI) and Supply Market Intelligence (SMI) in enhancing decision-making processes within a strategic sourcing team at a large global telecom company. Through qualitative research involving semi-structured interviews with team members from four business units, the study identifies significant challenges in the current MI processes, including inefficiency, issues with data validity, and poor communication practices. The findings reveal a need for a more structured and centralized MI approach, emphasizing the importance of a dedicated team and a standardized data platform to facilitate timely and informed decision-making. The research proposes the integration of AI to streamline data collection and processing, thereby improving the overall efficiency of the MI process. This study contributes to the existing literature by extending previous research on MI and offering practical solutions tailored to the unique challenges faced by the telecom industry. Future research directions are suggested to further explore the implementation of advanced technologies in MI practices.