Outputs (692)

Inhomogeneous Galactic chemical evolution: modelling ultra-faint dwarf galaxies of the Large Magellanic Cloud (2023)
Journal Article
Alexander, R. K., Vincenzo, F., Ji, A. P., Richstein, H., Jordan, C. J., & Gibson, B. K. (2023). Inhomogeneous Galactic chemical evolution: modelling ultra-faint dwarf galaxies of the Large Magellanic Cloud. Monthly notices of the Royal Astronomical Society, 522(4), 5415-5433. https://doi.org/10.1093/mnras/stad1312

Ultra-faint dwarf galaxies (UFDs) are among the oldest and most metal-poor galaxies in the cosmos, observed to contain no gas and a high dark matter mass fraction. Understanding the chemical abundance dispersion in such extreme environments could she... Read More about Inhomogeneous Galactic chemical evolution: modelling ultra-faint dwarf galaxies of the Large Magellanic Cloud.

Capillary Assembly of Anisotropic Particles at Cylindrical Fluid-Fluid Interfaces (2023)
Journal Article
Eatson, J. L., Gordon, J. R., Cegielski, P., Giesecke, A. L., Suckow, S., Rao, A., Silvestre, O. F., Liz-Marzán, L. M., Horozov, T. S., & Buzza, D. M. A. (2023). Capillary Assembly of Anisotropic Particles at Cylindrical Fluid-Fluid Interfaces. Langmuir : the ACS journal of surfaces and colloids, 39(17), 6006–6017. https://doi.org/10.1021/acs.langmuir.3c00016

The unique behavior of colloids at liquid interfaces provides exciting opportunities for engineering the assembly of colloidal particles into functional materials. The deformable nature of fluid-fluid interfaces means that we can use the interfacial... Read More about Capillary Assembly of Anisotropic Particles at Cylindrical Fluid-Fluid Interfaces.

Organic copolymer lasing from single defect microcavity fabricated using laser patterning (2023)
Journal Article
Claronino, P., Jayaprakash, R., Jessewitsch, T., Kilbride, R. C., Thornber, T., Muravitskaya, A., Oliver, R. D., Scherf, U., Bouillard, J. S. G., Adawi, A. M., & Lidzey, D. G. (2023). Organic copolymer lasing from single defect microcavity fabricated using laser patterning. Journal of Materials Chemistry C, https://doi.org/10.1039/d2tc05360h

Reducing the lasing threshold in optically pumped organic lasers is a necessary component of the drive to develop an organic laser diode, as this may help mitigate the losses associated with electrical contacts and charge injection. In this study we... Read More about Organic copolymer lasing from single defect microcavity fabricated using laser patterning.

Empirical constraints on the nucleosynthesis of nitrogen (2023)
Journal Article
Johnson, J. W., Weinberg, D. H., Vincenzo, F., Bird, J. C., & Griffith, E. J. (2023). Empirical constraints on the nucleosynthesis of nitrogen. Monthly notices of the Royal Astronomical Society, 520(1), 782-803. https://doi.org/10.1093/mnras/stad057

We derive empirical constraints on the nucleosynthetic yields of nitrogen by incorporating N enrichment into our previously developed and empirically tuned multizone galactic chemical evolution model. We adopt a metallicity-independent (‘primary’) N... Read More about Empirical constraints on the nucleosynthesis of nitrogen.

Three-dimensional topological magnetic monopoles and their interactions in a ferromagnetic meta-lattice (2023)
Journal Article
Rana, A., Liao, C.-T., Iacocca, E., Zou, J., Pham, M., Lu, X., Cating Subramanian, E.-E., Hung Lo, Y., Ryan, S. A., Bevis, C. S., Karl Jr, R. M., Glaid, A. J., Rable, J., Mahale, P., Hirst, J., Ostler, T., Liu, W., O’Leary, C. M., Yu, Y.-S., Bustillo, K., …Miao, J. (2023). Three-dimensional topological magnetic monopoles and their interactions in a ferromagnetic meta-lattice. Nature nanotechnology, 18, 227–232. https://doi.org/10.1038/s41565-022-01311-0

Topological magnetic monopoles (TMMs), also known as hedgehogs or Bloch points, are three-dimensional (3D) nonlocal spin textures that are robust to thermal and quantum fluctuations due to the topology protection1-4. Although TMMs have been observed... Read More about Three-dimensional topological magnetic monopoles and their interactions in a ferromagnetic meta-lattice.

Impact of newly measured 26Al(n, p)26Mg and 26Al(n, α)23Na reaction rates on the nucleosynthesis of 26Al in stars (2023)
Journal Article
Battino, U., Lederer-Woods, C., Pignatari, M., Soós, B., Lugaro, M., Vescovi, D., Cristallo, S., Woods, P. J., & Karakas, A. (2023). Impact of newly measured 26Al(n, p)26Mg and 26Al(n, α)23Na reaction rates on the nucleosynthesis of 26Al in stars. Monthly notices of the Royal Astronomical Society, 520(2), 2436-2444. https://doi.org/10.1093/mnras/stad106

The cosmic production of the short-lived radioactive nuclide 26Al is crucial for our understanding of the evolution of stars and galaxies. However, simulations of the stellar sites producing 26Al are still weakened by significant nuclear uncertaintie... Read More about Impact of newly measured 26Al(n, p)26Mg and 26Al(n, α)23Na reaction rates on the nucleosynthesis of 26Al in stars.

Boosting hydrogen production of uniform CuCo-ZIF nanododecahedrons by bimetal node and glycerol (2023)
Journal Article
Wang, Q., Teng, Y., Ma, B., Zhang, X., Yuan, X., Li, Z., Jiang, W., Teng, F., Ruan, W., & Ibhadon, A. O. (2023). Boosting hydrogen production of uniform CuCo-ZIF nanododecahedrons by bimetal node and glycerol. Materials Today Chemistry, 28, Article 101359. https://doi.org/10.1016/j.mtchem.2022.101359

Compared with fossil fuels reforming to hydrogen, electrolytic water to hydrogen is highly energy-intensive. It is still a big challenge to decrease the cost of electrolytic water to hydrogen. Herein, we investigate the electrocatalytic activity of u... Read More about Boosting hydrogen production of uniform CuCo-ZIF nanododecahedrons by bimetal node and glycerol.

Stark Effect Control of the Scattering Properties of Plasmonic Nanogaps (2022)
Journal Article
Pagnotto, D., Muravitskaya, A., Benoit, D. M., Bouillard, J. S. G., & Adawi, A. M. (2023). Stark Effect Control of the Scattering Properties of Plasmonic Nanogaps. ACS Applied Optical Materials, 1(1), 500–506. https://doi.org/10.1021/acsaom.2c00135

The development of actively tunable plasmonic nanostructures enables real-time and on-demand enhancement of optical signals. This is an essential requirement for a wide range of applications such as sensing and nanophotonic devices. Here we show that... Read More about Stark Effect Control of the Scattering Properties of Plasmonic Nanogaps.

Pharmacogenomics of GLP-1 receptor agonists: a genome-wide analysis of observational data and large randomised controlled trials (2022)
Journal Article
Dawed, A. Y., Mari, A., Brown, A., McDonald, T. J., Li, L., Wang, S., Hong, M. G., Sharma, S., Robertson, N. R., Mahajan, A., Wang, X., Walker, M., Gough, S., Hart, L. M., Zhou, K., Forgie, I., Ruetten, H., Pavo, I., Bhatnagar, P., Jones, A. G., …Jonsson, A. (2023). Pharmacogenomics of GLP-1 receptor agonists: a genome-wide analysis of observational data and large randomised controlled trials. Lancet Diabetes and Endocrinology, 11(1), 33-41. https://doi.org/10.1016/S2213-8587%2822%2900340-0

Background: In the treatment of type 2 diabetes, GLP-1 receptor agonists lower blood glucose concentrations, body weight, and have cardiovascular benefits. The efficacy and side effects of GLP-1 receptor agonists vary between people. Human pharmacoge... Read More about Pharmacogenomics of GLP-1 receptor agonists: a genome-wide analysis of observational data and large randomised controlled trials.

Machine learning-based predictions of gamma passing rates for virtual specific-plan verification based on modulation maps, monitor unit profiles, and composite dose images (2022)
Journal Article
Quintero, P., Benoit, D., Cheng, Y., Moore, C., & Beavis, A. (2022). Machine learning-based predictions of gamma passing rates for virtual specific-plan verification based on modulation maps, monitor unit profiles, and composite dose images. Physics in Medicine and Biology, 67(24), Article 245001. https://doi.org/10.1088/1361-6560/aca38a

Machine learning (ML) methods have been implemented in radiotherapy to aid virtual specific-plan verification protocols, predicting gamma passing rates (GPR) based on calculated modulation complexity metrics because of their direct relation to dose d... Read More about Machine learning-based predictions of gamma passing rates for virtual specific-plan verification based on modulation maps, monitor unit profiles, and composite dose images.