Durable Thin‐Film Porous Transport Electrodes for High Current Density PEM Water Electrolysis
Water electrolysis using porous transport electrodes with sputter‐deposited, ionomer‐free thin films of rutile IrO2 catalyst suppresses Ir dissolution by >10x over other forms of IrOx. The rutile IrO2 catalyst prepared by this readily scalable electrode synthesis method provides stable cell operation at 3 A cm−2 while using low Ir loading (0.4 mg Ir cm−
James L. Young +18 more
wiley +1 more source
A Novel Metal Foam‐Supported Solid Oxide Fuel Cell With High Specific Power
Solid oxide fuel cells (SOFCs) employing metal foam supports with an ultrahigh porosity of 90% and average pore size of 100 µm are successfully fabricated. The metal foam architecture significantly enhances gas diffusion coefficients, effectively reducing concentration polarization while simultaneously decreasing areal mass.
Jingbo Ma +4 more
wiley +1 more source
Integrated laboratory workflow for proton exchange membrane fuel cell fabrication and testing. [PDF]
Hesham H +6 more
europepmc +1 more source
This study addresses the critical issue of delamination between YSZ and GDC electrolytes in SOECs, which is caused by Thermal deformation disparity. A novel YSZ‐GDC composite interlayer, fabricated using a simple dip‐coating method, is introduced to solve this problem. This layer effectively suppresses delamination by mitigating thermal stress.
Rustam Yuldashev +4 more
wiley +1 more source
pH-dependent redox hydrogen pump for electrochemical direct air capture of CO<sub>2</sub>. [PDF]
Zhang X +6 more
europepmc +1 more source
Multi-time scaling optimization for electric station considering uncertainties of renewable energy and EVs. [PDF]
Zhou L +5 more
europepmc +1 more source
Composite Bifunctional Electrocatalyst for the Oxygen Reduction and Evolution Reactions
Casey E. Beall +11 more
doaj +1 more source
Pd/MnO<sub>2</sub>:Pd/C Electrocatalysts for Efficient Hydrogen and Oxygen Electrode Reactions in AEMFCs. [PDF]
Cruz-Reyes I +5 more
europepmc +1 more source
AI-driven multi-objective optimization of FCHEV sizing and energy management considering degradation and vehicle dynamics under realistic machine learning-based traffic conditions. [PDF]
Montazeri-Gh M, Mostashiri A.
europepmc +1 more source

