For the cooling part, efforts have been focused on the development of the two microfluidic solutions (self-adaptive fins and valves ). The performance of the proposed solutions has been numerically assessed and experimentally validated through the WP2 proof of concept. Indeed, in a first stage, the capacity of the Self-Adaptive fins to locally boost the heat transfer, demonstrated numerically, has been experimentally validated. In a second stage, a series of tests have been carried out at fixed flow rate to characterize the cell array cooling solutions with and without microvalves. The result demonstrated that the STREAMS cooling scheme allows to reduce drastically one of the major drawback of microchannel cooling devices: the pressure drops. Moreover, a time dependent and non-uniform heat load scenario has been applied. The analysis of these results demonstrated that all the objectives defined for the STREAMS cooling solution have been reached.
For the thermal map monitoring, the micro-thermal sensors (µTES) have been processed from two thermoelectric (TE) materials: SiGe (used as reference) and nanostructured materials (QDSL: Quantum Dots Superlattices, integrating TiSi2 nanoparticles inside a SiGe matrix). This is the first time that such nanostructured materials QDSL are integrated into a TE device. It was shown that all QDSL-based µTES offer higher performances than SiGe-based µTES. The main objective of WP3 dealed with the “integration of IC compatible passive heat flux sensors (sensitivity up to Se = 100 mV/K) at the interposer level to anticipate thermal map variation (time response ~ 200 ms and lateral spatial resolution ~ 500 μm)”. All results obtained from SiGe and QDSL-based µTESs fit with the objectives of project STREAMS: sensitivity higher than 100 mV/K, response time lower than 4 ms and a lateral spatial resolution equal to 500 µm. Finally, performances of µTESs developed in project STREAMS go over performances of the SoA. For example, the sensitivity density of STREAMS µTES is six times higher than the one of commercial µTES, making these µTES a reference in thermal sensors.
For the energy harvesting part, the objectives were to take advantage of the thermal gradient coming from chips to harvest thermal energy and to use this energy to make the active cooling system as much energy-autonomous as possible. Two sub-tasks have been achieved: to develop, implement and embed a high performance thermoelectric generator and to develop, implement and embed a power management interface circuit to power local functionalities. µTEGs and PMU are fully functionnal, but not together because of an issue not fully determined. For the µTEG, a generated power of 680 µW has been measured for a temperature difference corresponding to 8K, while the target was 1 mW. But it should be considered that the objectives of WP4 are also linked to the development and implementation of new cooling solutions, which are the objectives of WP2. At the beginning of the project, it was decided by the consortium, as well as by the reviewers, to focus on the success of this work package WP2. A traded-off between achieving high cooling performance (WP2) and high power generation by the µTEGs (WP4) thus needed to be performed. Due to this trade-off, optimal conditions for thermal energy harvesting and thus to achieve a temperature difference of 15K, i.e. a high temperature difference, are not feasible. Nevertheless, the power generated by the µTEG developed in this project is considerable. Indeed, compared to the state-of-the-art, our µTEG present the highest useful electrical power density compared to other Si-based µTEGs. Results obtained are very promising.
