RIETVELD TEXTURE REFINEMENT ANALYSIS OF LINDE TYPE A ZEOLITE FROM X-RAY DIFFRACTION DATA

Autor: SAMA M. AL-JUBOURI, BASMA I. WAISI, STUART M. HOLMES

Publikováno v: Journal of Engineering Science and Technology, Vol 13, Iss 12, Pp 4066-4077 (2018)

Rietveld method was used to conduct a texture refinement analysis for Linde type A zeolite prepared by hydrothermal conditions of 100 ºC for 4 h. Material Analysis Using Diffraction software, which is an open access/user-friendly software, was used

Externí odkaz: https://doaj.org/article/cbbd872183314529b26ff6aa6d32693b

Synthesis of Phosphonated Graphene Oxide by Electrochemical Exfoliation to Enhance the Performance and Durability of High-temperature Proton Exchange Membrane Fuel cells

Autor: Jianuo Chen, Zunmin Guo, Maria Perez-Page, Yifeng Jia, Ziyu Zhao, Stuart M. Holmes

Publikováno v: Chen, J, Guo, Z, Perez-Page, M, Jia, Y, Zhao, Z & Holmes, S 2023, ' Synthesis of Phosphonated Graphene Oxide by Electrochemical Exfoliation to Enhance the Performance and Durability of High-temperature Proton Exchange Membrane Fuel cells ', Journal of Energy Chemistry, vol. 76, pp. 448-458 . https://doi.org/10.1016/j.jechem.2022.09.028

The doping of functionalized graphene oxide (GO) in the membranes becomes a promising method for improving the performance of high-temperature proton exchange membrane fuel cells (HT-PEMFC). Phosphonated graphene oxide (PGO) with a P/O ratio of 8.5%

Externí odkaz: https://explore.openaire.eu/search/publication?articleId=doi_dedup___::09851529032b5576dc22ebc390fa29d3
https://research.manchester.ac.uk/en/publications/5273ab78-72df-4cc4-a9d5-fcbe14f02fd9

Discrete-Particle Model to Optimize Operational Conditions of Proton-Exchange Membrane Fuel-Cell Gas Channels

Autor: Vahid Niasar, Daniel Niblett, Stuart M. Holmes

Publikováno v: ACS Applied Energy Materials

Operation of proton-exchange membrane fuel cells is highly deteriorated by mass transfer loss, which is a result of spatial and temporal interaction between airflow, water flow, channel geometry, and its wettability. Prediction of two-phase flow dyna

Externí odkaz: https://explore.openaire.eu/search/publication?articleId=doi_dedup___::4e63bf3d6f59a0517f63ad9b87f0b2ea
https://doi.org/10.1021/acsaem.1c01391

The performance and durability of high-temperature proton exchange membrane fuel cells enhanced by single-layer graphene

Autor: Jianuo Chen, Josh J. Bailey, Liam Britnell, Maria Perez-Page, Madhumita Sahoo, Zhe Zhang, Andrew Strudwick, Jennifer Hack, Zunmin Guo, Zhaoqi Ji, Philip Martin, Dan J.L. Brett, Paul R. Shearing, Stuart M. Holmes

Publikováno v: Chen, J, Bailey, J J, Britnell, L, Perez-Page, M, Sahoo, M, Zhang, Z, Strudwick, A, Hack, J, Guo, Z, Ji, Z, Martin, P, Brett, D J L, Shearing, P R & Holmes, S M 2022, ' The performance and durability of high-temperature proton exchange membrane fuel cells enhanced by single-layer graphene ', Nano Energy, vol. 93, 106829 . https://doi.org/10.1016/j.nanoen.2021.106829

Single-layer graphene (SLG) obtained by chemical vapor deposition is applied between membrane and electrodes by a wet chemical transfer method to study its effect on the performance and durability of polybenzimidazole membranes in high-temperature pr

Externí odkaz: https://explore.openaire.eu/search/publication?articleId=doi_dedup___::605c23b1c26ff4c43aa140211e6a2cfb
https://pure.qub.ac.uk/en/publications/ac35a050-72ab-42a0-a048-7d6229924126

Lab-based X-ray micro-computed tomography coupled with machine-learning segmentation to investigate phosphoric acid leaching in high-temperature polymer electrolyte fuel cells

Autor: Josh J. Bailey, Paul R. Shearing, Jennifer Hack, Stuart M. Holmes, Jianuo Chen, Maria Perez-Page, Dan J. L. Brett

Publikováno v: Bailey, J J, Chen, J, Hack, J, Perez-Page, M, Holmes, S M, Brett, D J L & Shearing, P R 2021, ' Lab-based X-ray micro-computed tomography coupled with machine-learning segmentation to investigate phosphoric acid leaching in high-temperature polymer electrolyte fuel cells ', Journal of Power Sources, vol. 509, 230347 . https://doi.org/10.1016/j.jpowsour.2021.230347
Bailey, J J, Chen, J, Hack, J, Perez-page, M, Holmes, S M, Brett, D J L & Shearing, P R 2021, ' Lab-based X-ray micro-computed tomography coupled with machine-learning segmentation to investigate phosphoric acid leaching in high-temperature polymer electrolyte fuel cells ', Journal of Power Sources, vol. 509, 230347 . https://doi.org/10.1016/j.jpowsour.2021.230347

A machine-learning approach is used to segment 14 X-ray computed-tomography datasets acquired by lab-based scanning of laser-milled, high-temperature polymer electrolyte fuel cell samples mounted in a 3D-printed sample holder. Two modes of operation,

Externí odkaz: https://explore.openaire.eu/search/publication?articleId=doi_dedup___::b1e85eaee8864dcdd826fc3ea05337ce
https://pure.qub.ac.uk/en/publications/7418cc9e-062f-4e16-a25c-5f717baf7c3d