The MetaboliQs project is working to leverage room-temperature diamond quantum dynamics to enable safe multimodal cardiac imaging which can help better diagnosis of Cardiovascular Diseases .

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Project Progress and Achievements: May 2020

Researchers' summary

The main achievements in this first project period are summarized below in three building blocks:

Building block 1

Quantum-grade Diamonds: For overgrown diamond layers, the consortium has been able to achieve the highest coherence in NV (nitrogen-vacancy) ensembles. In addition, they have developed large-scale dense nanostructuring of these diamonds with excellent surface quality as well as achieved large-scale diamonds with high purity (quantum-grade diamonds of huge size).

With respect to these NV ensembles, the project has achieved the first of a kind shallow NitrogenVacancy NV layer (nanometric NV layer) and has further developed the NV activation through different processes (tuning the electron energies/ doses) to attain insight into NV creation, high NV concentration and purity. 

Building block 2

Diamond Polarizer As for hardware, the project consortium has developed two stand-alone operational polarizers for NV (nitrogen-vacancy) experiments. They have also produced aligned near-surface diamond stack with excellent properties by using an iterative process and accomplished novel pulse sequences as well as demonstrated polarization enhancement (5x fold) on optimized diamonds compared to state-of-the-art dynamic nuclear polarization (DNP) sequences. 

Building block 3

Applications of Technology The development of a cryogenically-cooled radiofrequency coil has permitted an outstanding increase in imaging sensitivity (7-fold increase) with respect to the current state-of-the-art room temperature detection setups. The consortium 
has developed a novel image acquisition strategy, developing new sequences for full-body fast imaging.

Finally, project partners have developed a comprehensive simulation framework to synthesize hyperpolarized metabolic data, test image reconstruction and data analysis schemes. In view of the increasing importance of Machine Learning in data analysis, the availability of realistic data including their ground truth is of utmost importance. Using data synthesis, large sets of training data can be easily generated and made available. 

More information 

Find more information about what MetaboliQs has achieved here

To mark the mid-point of the Quantum Technologies Flagship’s eighteen-month ramp-up phase in May 2020, a mid-term review was published with information about the achievements of all the projects. Read it here.