Projects per year
Organisation profile
Organisation profile
Welcome to the National Computational Infrastructure (NCI). The NCI is home to the Southern Hemisphere’s most highly-integrated supercomputer and filesystems, Australia’s highest performance research cloud, and one of the nation’s largest data catalogues—all supported by an expert team.
NCI is supported by the Australian Government’s National Collaborative Research Infrastructure Strategy, with operational funding provided through a formal collaboration incorporating CSIRO, Bureau of Meteorology, The Australian National University, Geoscience Australia the Australian Research Council, and a number of research intensive universities and medical research institutes.
Visit the National Computational Infrastructure Facility website for further information.
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Dive into the research topics where National Computational Infrastructure is active. These topic labels come from the works of this organisation's members. Together they form a unique fingerprint.
Collaborations and top research areas from the last five years
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Tuning catalyst reaction environments towards photoreforming of wastewater
Yin, Z. (PI) & Smith, S. (CoI)
19/02/24 → 18/02/27
Project: Research
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AuScope NCIRS 2023 - NCI HPC and Data Innovation ANU
Evans, B. (PI)
1/07/23 → 30/07/25
Project: Research
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Research output
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Acceleration of Self-Consistent Field Calculations Using Basis Set Projection and Many-Body Expansion as Initial Guess Methods
Yu, F. C. Y., Seidl, C., Palethorpe, E. & Barca, G. M. J., 11 Feb 2025, In: Journal of Chemical Theory and Computation. 21, 3, p. 1230-1248 19 p.Research output: Contribution to journal › Article › peer-review
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Accessible hybrid conferences are possible and affordable at large scale
Moss, V. A., Venugopal, R., Govender, K., Hotan, A. W., Kobayashi, R., Rees, G. A., Tasker, E. J., Vertue, D. G., Le Jeune, A., Kerrison, E. F., Roux, J., Blumenthal, K., Ekers, R. D., Peel, M. W., Takalana, C. M., Barocci-Faul, S., Benkhaldoun, Z., Binneman, A., Breytenbach, H. & Chibueze, J. O. & 6 others, , Jan 2025, In: Nature Astronomy. 9, 1, p. 6-10 5 p., 7324.Research output: Contribution to journal › Comment/debate › peer-review
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Advancing Sustainable Aviation Fuel Design: Machine Learning for High-Energy-Density Liquid Polycyclic Hydrocarbons
Rijal, D., Vasilyev, V. & Wang, F., 30 Jan 2025, In: Energy and Fuels. 39, 6, p. 3243-3255 13 p.Research output: Contribution to journal › Article › peer-review
3 Citations (Scopus)