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- Artini, Cristina, et al.
(författare)
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Roadmap on thermoelectricity
- 2023
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Ingår i: Nanotechnology. - : IOP Publishing Ltd. - 0957-4484 .- 1361-6528. ; 34:29
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Tidskriftsartikel (refereegranskat)abstract
- The increasing energy demand and the ever more pressing need for clean technologies of energy conversion pose one of the most urgent and complicated issues of our age. Thermoelectricity, namely the direct conversion of waste heat into electricity, is a promising technique based on a long-standing physical phenomenon, which still has not fully developed its potential, mainly due to the low efficiency of the process. In order to improve the thermoelectric performance, a huge effort is being made by physicists, materials scientists and engineers, with the primary aims of better understanding the fundamental issues ruling the improvement of the thermoelectric figure of merit, and finally building the most efficient thermoelectric devices. In this Roadmap an overview is given about the most recent experimental and computational results obtained within the Italian research community on the optimization of composition and morphology of some thermoelectric materials, as well as on the design of thermoelectric and hybrid thermoelectric/photovoltaic devices.
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| 2. |
- Celeste, Arcangelo, et al.
(författare)
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Enhancement of Functional Properties of Liquid Electrolytes for Lithium-Ion Batteries by Addition of Pyrrolidinium-Based Ionic Liquids with Long Alkyl-Chains
- 2020
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Ingår i: Batteries and Supercaps. - : Wiley. - 2566-6223. ; 3:10, s. 1059-1068
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Tidskriftsartikel (refereegranskat)abstract
- Three ionic liquid belonging to the N-alkyl-N-methylpyrrolidinium bis(trifluoromethanesulfonyl) imides (Pyr(1),nTFSI with n=4,5,8) have been added as co-solvent to two commonly used electrolytes for Li-ion cells: (a) 1 M lithium hexafluorophosphate (LiPF6) in a mixture of ethylene carbonate (EC) and linear like dimethyl carbonate (DMC) in 1 : 1 v/v and (b) 1 M lithium bis-(trifluoromethanesulfonyl)imide (LiTFSI) in EC : DMC 1 : 1 v/v. These electrolyte formulations (classified as P and T series containing LiPF6 or LiTFSI salts, respectively) have been analyzed by comparing ionic conductivities, transport numbers, viscosities, electrochemical stability as well as vibrational properties. In the case of the Pyr(1,5)TFSI and Pyr(1,8)TFSI blended formulations, this is the first ever reported detailed study of their functional properties in Li-ion cells electrolytes. Overall, P-electrolytes demonstrate enhanced properties compared to the T-ones. Among the various P electrolytes those containing Pyr(1,4)TFSI and Pyr(1,5)TFSI limit the accumulation of irreversible capacity upon cycling with satisfactory performance in lithium cells.
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| 3. |
- Ribes, Stefano, 1992, et al.
(författare)
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Machine Learning-Based Classification of Hardware Trojans in FPGAs Implementing RISC-V Cores
- 2024
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Ingår i: International Conference on Information Systems Security and Privacy. - 2184-4356. ; 1, s. 717-724
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Konferensbidrag (refereegranskat)abstract
- Hardware Trojans (HTs) pose a severe threat to integrated circuits, potentially compromising electronic devices, exposing sensitive data, or inducing malfunction. Detecting such malicious modifications is particularly challenging in complex systems and commercial CPUs, where they can occur at various design stages, from initial HDL coding to the final hardware implementation. This paper introduces a machine learningbased strategy for the detection and classification of HTs within RISC-V soft cores implemented in FieldProgrammable Gate Arrays (FPGAs). Our approach comprises a systematic methodology for comprehensive data collection and estimation from FPGA bitstreams, enabling us to extract insights ranging from hardware performance counters to intricate metrics like design clock frequency and power consumption. Our ML models achieve perfect accuracy scores when analyzing features related to both synthesis, implementation results, and performance counters. We also address the challenge of identifying HTs solely through performance counters, highlighting the limitations of this approach. Additionally, our work emphasizes the significance of Implementation Features (IFs), particularly circuit timing, in achieving high accuracy in HT detection.
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