Welcome to the NanoEngineering Research group at the Cambridge Graphene Centre (CGC).
Our work encompasses Engineering, Physics, Chemistry, Materials Science and Nanotechnology, exploiting 0D, 1D and 2D nanomaterials for (opto)electronics, photonics, sensors and energy devices. We are also interested in computation-enabled smart devices, where algorithms are playing an increasingly important role in their performance and reliability. Exploiting the unique characteristics of various nanomaterials and synergies between them, supported by advanced learning algorithms is the theme of our ambitious multidisciplinary research, with a view towards real world applications.
We are always looking for MPhil and PhD candidates with *excellent academic results* and research backgrounds in 1) organic/electrochemical transducers 2) low-dimensional material-based devices for IR detection and imaging 3) computational approaches to nanomaterial-based sensors and 4) 3D printing of complex structures. International postdoctoral researchers and fellows for long term (12 months or more) collaborative research visits are very welcome. We strongly encourage student and visitor applications from under-represented groups, regardless of disability, race, religion or belief, sex or sexual orientation. If you are interested, please get in touch with Tawfique directly to learn more about our future plans in the above research areas.
Latest news
Recent Highlights
Real-time, noise and drift resilient formaldehyde sensing at room temperature with aerogel filaments
Z Chen, B Zhou, M Xiao, T Bhowmick, P K Kannan, L G Occhipinti, J W Gardner, T Hasan
Science Advances, 2024, 10, eadk6856
* This work is covered in University of Cambridge Research News as "Sensors made from 'frozen smoke' can detect toxic formaldehyde in homes and offices".
DOI: 10.1126/sciadv.adk6856
Miniaturized spectrometers with a tunable van der Waals junction
H H Yoon, H A Fernandez, F Nigmatulin, W Cai, Z Yang, H Cui, F Ahmed, X Cui, M G Uddin, E D Minot, H Lipsanen, K Kim, P Hakonen, T Hasan, Z Sun
Science, 2022, 378, 296
* This work is covered in University of Cambridge Research News as "Artificial intelligence powers record-breaking all-in-one miniature spectrometers".
DOI: 10.1126/science.add8544
Single-transistor neuron with excitatory-inhibitory spatiotemporal dynamics applied for neuronal oscillations
H Li, J Hu, A Chen, C Wang, L Chen, F Tian, J Zhou, Y Zhao, J Chen, Y Tong, K P Loh, Y Xu, Y Zhang, T Hasan, B Yu
Advanced Materials, 2022, 2207371
DOI: 10.1002/adma.202207371
Inkjet-printed rGO/binary metal oxide sensor for predictive gas sensing in a mixed environment
O Ogbeide, G Bae, W Yu, E Morrin, Y Song, W Song, Y Li, B-L Su, K-S An, T Hasan
Advanced Functional Materials, 2022, 32, 2113348
* A video introduction of the work by the author can be watched here.
DOI: 10.1002/adfm.202113348