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A new catalyst design, pseudo-high entropy alloy (HEA), was proposed and demonstrated for high performance water electrolysis. Pseudo-HEAs, defined as single-phase four-element alloys of molar configurational entropy greater than 1.36R, are in general easier to design and prepare for enhanced electrocatalytic efficiency as compared with traditional HEAs of five or more elements. A carbon armored pseudo-HEA catalyst, FeCoNiMo@C, was synthesized with a simple two-stage thermal conversion of FeCoNiMo-MOF, grown in situ on a nickel foam (NF) substrate, to exhibit outstanding catalytic efficiency and stability toward water electrolysis in alkaline media. It delivered 10 and 500 mA cm−2 at ultra-low overpotentials of 55 and 233 mV, respectively for the hydrogen evolution reaction and 204 and 273 mV, respectively for the oxygen evolution reaction. The FeCoNiMo@C/NF//FeCoNiMo@C/NF couple achieved ultra-low cell voltages of 1.488 V@10 mA cm−2 and 1.725 V@500 mA cm−2 for full cell water splitting and ultra-stability at an industrially applicable high current density of 500 mA cm−2 with a minor decay of 3.4% over 50 h. The success was attributed to the atomic scale synergy between constituent atoms, Fe, Co, Ni and Mo, atomically dispersed in the pseudo-HEA. [ABSTRACT FROM AUTHOR]

Significance: Consistent and accurate probe placement is a crucial step towards enhancing the reproducibility of longitudinal and group-based functional neuroimaging studies. While the selection of headgear is central to these efforts, there does not currently exist a standardized design that can accommodate diverse probe configurations and experimental procedures., Aim: We aim to provide the community with an open-source software pipeline for conveniently creating low-cost, 3-D printable neuroimaging head caps with anatomically significant landmarks integrated into the structure of the cap., Approach: We utilize our advanced 3-D head mesh generation toolbox and 10-20 head landmark calculations to quickly convert a subject's anatomical scan or an atlas into a 3-D printable head cap model. The 3-D modeling environment of the open-source Blender platform permits advanced mesh processing features to customize the cap. The design process is streamlined into a Blender add-on named "NeuroCaptain"., Results: Using the intuitive user interface, we create various head cap models using brain atlases, and share those with the community. The resulting mesh-based head cap designs are readily 3-D printable using off-the-shelf printers and filaments while accurately preserving the head topology and landmarks., Conclusions: The methods developed in this work result in a widely accessible tool for community members to design, customize and fabricate caps that incorporate anatomically derived landmarks. This not only permits personalized head cap designs to achieve improved accuracy, but also offers an open platform for the community to propose standardizable head caps to facilitate multi-centered data collection and sharing.