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Nghia T. Vo

Researcher at National University of Singapore

Publications -  35
Citations -  1409

Nghia T. Vo is an academic researcher from National University of Singapore. The author has contributed to research in topics: Computer science & Thermal runaway. The author has an hindex of 18, co-authored 31 publications receiving 928 citations.

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I12: the Joint Engineering, Environment and Processing (JEEP) beamline at Diamond Light Source.

TL;DR: JEEP is a high-energy (50–150 keV) multi-purpose beamline offering polychromatic and monochromatic modes, enabling in situ studies using radiography, tomography, energy-dispersive diffraction, monochROMatic and white-beam two-dimensional diffraction/scattering and small-angle X-ray scattering.
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Characterising thermal runaway within lithium-ion cells by inducing and monitoring internal short circuits.

TL;DR: In this paper, an internal short circuiting device was used for controlled, on-demand, initiation of thermal runaway in lithium-ion batteries, allowing analysis of the nucleation and propagation of failure within 18 650 cells through the use of high-speed X-ray imaging at 2000 frames per second.
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Identifying the Cause of Rupture of Li-Ion Batteries during Thermal Runaway

TL;DR: For the first time, the mechanisms that lead to the most catastrophic type of cell failure, rupture, and explosion are identified and elucidated in detail and are expected to guide the development of safer commercial cell designs.
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Reliable method for calculating the center of rotation in parallel-beam tomography

TL;DR: This work proposes an alternative technique which is based on the Fourier analysis of the sinogram which shows excellent performance particularly on challenging data.
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Superior techniques for eliminating ring artifacts in X-ray micro-tomography

TL;DR: Three techniques for tackling severe ring artifacts in reconstructed images of synchrotron-based X-ray micro-tomography systems are proposed, which are easy to implement; do not generate extra stripe artifacts and void-center artifacts; and give superior quality on challenging data sets and in comparison with other techniques.