Accelerating colloidal quantum dot innovation with algorithms and automation
Journal article
Howes, P., Munyebvu, N., Lane, E. and Grisan, E. (2022). Accelerating colloidal quantum dot innovation with algorithms and automation. Materials Advances. https://doi.org/10.1039/d2ma00468b
| Authors | Howes, P., Munyebvu, N., Lane, E. and Grisan, E. |
|---|---|
| Abstract | Quantum dots (QDs) have received an immense amount of research attention and investment in the four decades since their discovery, and fantastic progress has been made. However, they are complex materials exhibiting distinctive behaviors, and they have been slow to proliferate in real- world applications. QDs occupy an intermediate state of matter, being neither bulk nor molecular materials. Their unique and useful properties arise exactly because of this, but massive challenges in product and device stability and reproducibility also follow as a consequence. Chief amongst the many challenges faced in bringing QD-based devices to market are managing heavy-metal content and device instability. In this review, the possibility of using emerging data-driven methodologies from artificial intelligence (AI) and machine learning (ML) to expedite the translation of QDs from the lab bench to impactful energy-related applications is explored. These approaches will help us go from scarce and patchy knowledge of highly complex parameter spaces to accurate and broad ’maps’, intelligently targeted synthesis and advanced quality control. |
| Keywords | nanoparticles; machine learning; automation; microfluidics |
| Year | 2022 |
| Journal | Materials Advances |
| Publisher | Royal Society of Chemistry (RSC) |
| Digital Object Identifier (DOI) | https://doi.org/10.1039/d2ma00468b |
| Web address (URL) | https://pubs.rsc.org/en/content/articlelanding/2022/MA/D2MA00468B |
| Publication dates | |
| 12 Aug 2022 | |
| Publication process dates | |
| Accepted | 30 Aug 2022 |
| Deposited | 22 Aug 2022 |
| Publisher's version | License File Access Level Open |
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Peruffo, A., Corain, L., Bombardi, C., Centelleghe, C., Grisan, E., Graïc, J-M, Bontempi, P., Grandis, A. and Cozzi, B. (2019). The motor cortex of the sheep: laminar organization, projections and diffusion tensor imaging of the intracranial pyramidal and extrapyramidal tracts. Brain Structure and Function. 224 (5), pp. 1933-1946. https://doi.org/10.1007/s00429-019-01885-xBuilding a reduced dictionary of relevant perfusion patterns from CEUS data for the classification of testis lesions
Favaron, T., Huang, D.Y., Christensen-Jeffries, K., Eckersley, R., Sidhu, P.S. and Grisan, E. (2019). Building a reduced dictionary of relevant perfusion patterns from CEUS data for the classification of testis lesions. 2019 IEEE 16th International Symposium on Biomedical Imaging. Venice, Italy 08 - 11 Apr 2019 Institute of Electrical and Electronics Engineers (IEEE). https://doi.org/10.1109/ISBI.2019.8759528Deep Convolutional Neural Network for Survival Estimation of Amyotrophic Lateral Sclerosis patients
Grisan, E., Zandon`a, A. and Di Camillo, B. (2019). Deep Convolutional Neural Network for Survival Estimation of Amyotrophic Lateral Sclerosis patients. European Symposium on Artificial Neural Networks, Computational Intelligence and Machine Learning. Bruges, Belgium 24 - 26 Apr 2019 i6doc.Prediction of Adverse Glycemic Events from Continuous Glucose Monitoring Signal
Gadaleta, M., Facchinetti, A., Grisan, E. and Rossi, M. (2019). Prediction of Adverse Glycemic Events from Continuous Glucose Monitoring Signal. IEEE Journal of Biomedical and Health Informatics. 23 (2). https://doi.org/10.1109/JBHI.2018.2823763Sparse Image Reconstruction for Contrast Enhanced Cardiac Ultrasound using Diverging Waves
Stanziola, A., Toulemonde, M., Papadopoulou, V., Corbett, R., Duncan, N., Grisan, E. and Tang, M-X. (2019). Sparse Image Reconstruction for Contrast Enhanced Cardiac Ultrasound using Diverging Waves. IEEE International Ultrasonics Symposium 2019. Glasgow 09 2009 - 06 Oct 2019 Institute of Electrical and Electronics Engineers (IEEE).Super resolution ultrasound image filtering with machine learning to reduce the localization error
Harput, S., Fong, L.H., Stanziola, A., Zhang, G., Toulemonde, M., Zhou, J., Christensen-Jeffries, K., Brown, J., Eckersley, R., Grisan, E., Dunsby, C. and Tang, M. (2019). Super resolution ultrasound image filtering with machine learning to reduce the localization error. IEEE International Ultrasonics Symposium 2019. Glasgow 09 2009 - 06 Oct 2019 Institute of Electrical and Electronics Engineers (IEEE).MicroRNA Detection by DNA-Mediated Liposome Fusion
Jumeaux, C., Wahlsten, O., Block, S., Kim, E., Chandrawati, R., Howes, P., Höök, F. and Stevens, M. M. (2018). MicroRNA Detection by DNA-Mediated Liposome Fusion. ChemBioChem. 19 (5), pp. 434 - 438. https://doi.org/10.1002/cbic.201700592Temporal Convolution Networks for Real-Time Abdominal Fetal Aorta Analysis with Ultrasound
Savioli, N., Visentin, S., Cosmi, E., Grisan, E., Lamata, P. and Montana, G. (2018). Temporal Convolution Networks for Real-Time Abdominal Fetal Aorta Analysis with Ultrasound. Artificial Neural Networks and Machine Learning – ICANN 2018. Rhodes, Greece 04 - 07 Oct 2018 Springer. https://doi.org/10.1007/978-3-030-01421-6_15Bright, near infrared emitting PLGA-PEG dye-doped CN-PPV nanoparticles for imaging applications
Kemal, E., Abelha, T. F., Urbano, L., Peters, R., Owen, D. M., Howes, P., Green, M. and Dailey, L. A. (2017). Bright, near infrared emitting PLGA-PEG dye-doped CN-PPV nanoparticles for imaging applications. RSC Advances. (25), pp. 15255-15264. https://doi.org/10.1039/c6ra25004aQuantitative imaging by pixel-based contrast-enhanced ultrasound reveals a linear relationship between synovial vascular perfusion and the recruitment of pathogenic IL-17A-F+IL-23+ CD161+ CD4+ T helper cells in psoriatic arthritis joints
Fiocco, U, Stramare, R, Martini, V, Coran, A, Caso, F, Costa, L, Felicetti, M, Rizzo, G, Tonietto, M, Scanu, A, Oliviero, F, Raffeiner, B, Vezzù, M, Lunardi, F, Scarpa, R, Sacerdoti, D, Rubaltelli, L, Punzi, L, Doria, A and Grisan, E (2017). Quantitative imaging by pixel-based contrast-enhanced ultrasound reveals a linear relationship between synovial vascular perfusion and the recruitment of pathogenic IL-17A-F+IL-23+ CD161+ CD4+ T helper cells in psoriatic arthritis joints. Clinical Rheumatology. 36 (2), pp. 391-399. https://doi.org/10.1007/s10067-016-3500-xBoosting the Battery Life of Wearables for Health Monitoring Through the Compression of Biosignals
Hooshmand, M, Zordan, D, Del Testa, D, Grisan, E and Rossi, M (2017). Boosting the Battery Life of Wearables for Health Monitoring Through the Compression of Biosignals. IEEE Internet of Things Journal. 4, pp. 1647-1662. https://doi.org/10.1109/JIOT.2017.2689164Detection of a slow-flow component in contrast-enhanced ultrasound of the synovia for the differential diagnosis of arthritis
Rizzo, G, Tonietto, M, Castellaro, M, Raffeiner, B, Coran, A, Fiocco, U, Stramare, R and Grisan, E (2017). Detection of a slow-flow component in contrast-enhanced ultrasound of the synovia for the differential diagnosis of arthritis. SPIE Medical Imaging. Orlando, FL, USA 11 - 16 Feb 2017 SPIE. https://doi.org/10.1117/12.2250818Improving the quantification of contrast enhanced ultrasound using a Bayesian approach
Rizzo, G, Tonietto, M, Castellaro, M, Raffeiner, B, Coran, A, Fiocco, U, Stramare, R and Grisan, E (2017). Improving the quantification of contrast enhanced ultrasound using a Bayesian approach. SPIE Medical Imaging. Orlando, FL , USA 16 2016 - 11 Feb 2017 SPIE. https://doi.org/10.1117/12.2250195Superpixel-based classification of gastric chromoendoscopy images
Boschetto, D and Grisan, E (2017). Superpixel-based classification of gastric chromoendoscopy images. SPIE Medical Imaging. Orlando, FL, USA 11 - 16 Feb 2017 SPIE. https://doi.org/10.1117/12.2254187Boosted learned kernels for data-driven vesselness measure
Grisan, E (2017). Boosted learned kernels for data-driven vesselness measure. Proceedings Volume 10137, Medical Imaging 2017: Biomedical Applications in Molecular, Structural, and Functional Imaging; 101370Z (2017). Orlando, FL, USA 11 - 16 Feb 2017 SPIE. https://doi.org/10.1117/12.2250370Cortical Thickness variability in Multiple Sclerosis: The role of lesion segmentation and filling
Palombit, A, Castellaro, M, Calabrese, M, Romualdi, C, Pizzini, FB, Montemezzi, S, Grisan, E and Bertoldo, A (2017). Cortical Thickness variability in Multiple Sclerosis: The role of lesion segmentation and filling. 2017 IEEE 14th International Symposium on Biomedical Imaging (ISBI 2017). Melbourne, VIC, Australia 18 - 21 Apr 2017 pp. 792-795 https://doi.org/10.1109/ISBI.2017.7950637From macro to nano: Linking quantitative CEUS perfusion parameters to CD4+ T cells subtypes in spondyloarthtitis
Grisan, E, Rizzo, G, Tonietto, M, Coran, A, Raffeiner, B, Scanu, A, Martini, V, Stramare, R and Fiocco, U (2017). From macro to nano: Linking quantitative CEUS perfusion parameters to CD4+ T cells subtypes in spondyloarthtitis. 2017 IEEE 14th International Symposium on Biomedical Imaging (ISBI 2017). Melbourne, VIC, Australia 17 - 21 Apr 2017 Institute of Electrical and Electronics Engineers (IEEE). pp. 899-902 https://doi.org/10.1109/ISBI.2017.7950661Grade and location of power doppler are predictive of damage progression in rheumatoid arthritis patients in clinical remission by anti-tumour necrosis factor α
Raffeiner, B, Grisan, E, Botsios, C, Stramare, R, Rizzo, G, Bernardi, L, Punzi, L, Ometto, F and Doria, A (2017). Grade and location of power doppler are predictive of damage progression in rheumatoid arthritis patients in clinical remission by anti-tumour necrosis factor α. Rheumatology (United Kingdom). 56, pp. 1320-1325. https://doi.org/10.1093/rheumatology/kex084