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Luca Boarino

Researcher at Polytechnic University of Turin

Publications -  218
Citations -  3546

Luca Boarino is an academic researcher from Polytechnic University of Turin. The author has contributed to research in topics: Porous silicon & Silicon. The author has an hindex of 27, co-authored 213 publications receiving 2977 citations. Previous affiliations of Luca Boarino include Katholieke Universiteit Leuven.

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Monolithic cells for solar fuels

TL;DR: This tutorial review provides an overview of synthesis techniques which could be used to realise monolithic multifunctional membrane-electrode assemblies, such as Layer-by-Layer (LbL) deposition, Atomic Layer Deposition (ALD), and porous silicon (porSi) engineering.
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NO2 monitoring at room temperature by a porous silicon gas sensor

TL;DR: In this article, a study on reactivity of p + porous silicon layers (PSL) to different gas atmosphere has been carried out, where three different processes to insure good electrical contact are proposed and discussed.
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Self-limited single nanowire systems combining all-in-one memristive and neuromorphic functionalities

TL;DR: This work reports for the first time a single crystalline nanowire based model system capable of combining all memristive functions – non-volatile bipolar memory, multilevel switching, selector and synaptic operations imitating Ca2+ dynamics of biological synapses.
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Polymer Distributed Bragg Reflectors for Vapor Sensing

TL;DR: In this paper, a new strategy to achieve fast and responsive hybrid distributed Bragg reflectors for environmental vapor sensing was established, and easily processable zinc oxide-polystyrene nanocomposites were fabricated to grow high quality multilayers with large gas permeability and dielectric contrast.
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In materia reservoir computing with a fully memristive architecture based on self-organizing nanowire networks.

TL;DR: In this paper, the authors report on in materia reservoir computing in a fully memristive architecture based on self-organized nanowire networks, where functional synaptic connectivity with nonlinear dynamics and fading memory properties is exploited.