• Membrane Journal
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• v.30 no.3
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• pp.173-180
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• 2020

As the demand for fossil fuels continues to increase worldwide, carbon dioxide (CO₂) concentration in the air has increased over the centuries. The way to reduce CO₂ emissions to the atmosphere, carbon capture and sequestration (CCS) technology have been developed that can be applied to power plants and factories, which are primary emission sources. According to the climate change mitigation policy, direct air capture (DAC) in air, referred to as "negative emission" technology, has a low CO₂ concentration of 0.04%, so it is focused on adsorbent research, unlike conventional CCS technology. In the DAC field, chemical adsorbents using CO₂ absorption, solid absorbents, amine-functionalized materials, and ion exchange resins have been studied. Since the absorbent-based technology requires a high-temperature heat treatment process according to the absorbent regeneration, the membrane-based CO₂ capture system has a great potential Membrane-based system is also expected for indoor CO₂ ventilation systems and immediate CO₂ supply to smart farming systems. CO₂ capture efficiency should be improved through efficient process design and material performance improvement.

• Nuclear Engineering and Technology
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• v.49 no.6
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• pp.1259-1268
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• 2017

The alpha eigenvalue problem in multigroup neutron diffusion is studied with particular attention to the theoretical analysis of the model. Contrary to previous literature results, the existence of eigenvalue and eigenflux clustering is investigated here without the simplification of a unique fissile isotope or a single emission spectrum. A discussion about the negative decay constants of the neutron precursors concentrations as potential eigenvalues is provided. An in-hour equation is derived by a perturbation approach recurring to the steady state adjoint and direct eigenvalue problems of the effective multiplication factor and is used to suggest proper detection criteria of flux clustering. In spite of the prior work, the in-hour equation results give a necessary and sufficient condition for the existence of the eigenvalue-eigenvector pair. A simplified asymptotic analysis is used to predict bands of accumulation of eigenvalues close to the negative decay constants of the precursors concentrations. The resolution of the problem in one-dimensional heterogeneous problems shows numerical evidence of the predicted clustering occurrences and also confirms previous theoretical analysis and numerical results.

• Nuclear Engineering and Technology
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• v.52 no.6
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• pp.1327-1333
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• 2020

The global warming phenomenon emerges from the issue of climate change, which attracts the attention of intellectuals towards clean energy sources from dirty energy sources. Among clean sources, nuclear energy is getting immense attention among policymakers. However, the role of nuclear energy in pollution emissions reduction has remained inconclusive and demand for further investigation. Therefore, the current study contributes to extend knowledge by investigating the nexus between nuclear energy, economic growth, and CO₂ emissions in a developing country context such as Pakistan for the period between 1973 and 2017. The auto-regressive distributive lag model summarizes the nuclear energy has negative effect on environmental pollution as it releases carbon emission in the environment. Moreover, vector error correction Granger causality provides evidence for bidirectional causality between nuclear energy and carbon emissions. These interesting findings provide new insight, and policy guidelines provided based on these results.