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Record W4416601054 · doi:10.1149/ma2025-02391833mtgabs

Low-Cost Nanostructured Cathode Electrocatalysts and Supports for Water Electrolysis in Acidic and Alkaline Media

2025· article· W4416601054 on OpenAlexaff
Kang‐Hoon Choi, Ahmed Abdulla Ahmed Almaazmi, Sasha Omanovic

Bibliographic record

VenueECS Meeting Abstracts · 2025
Typearticle
Language
FieldEnergy
TopicElectrocatalysts for Energy Conversion
Canadian institutionsMcGill University
Fundersnot available
KeywordsHydrogen productionElectrolysis of waterElectrolysisHydrogenCatalysisElectrochemistryAlkaline water electrolysisWater splittingNanocompositeCarbon fibers

Abstract

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Hydrogen production via water electrolysis in an acidic medium relies heavily on noble-metal-based electrocatalysts like platinum and iridium, which are highly efficient but expensive and scarce. Further, alkaline water electrolysis in anion-exchange-membrane water electrolysers necessities electrodes of higher specific electrochemical activity. To transition to a hydrogen economy, where hydrogen serves as a clean energy carrier, replacing fossil fuels in industries like transportation, ammonia production, and steel manufacturing, cost reductions in hydrogen production are essential. By developing cost-effective and efficient non-precious metal catalysts and better catalyst supports, large-scale green hydrogen production via water electrolysis can become more viable, reducing dependence on fossil fuels and lowering carbon emissions across multiple sectors. This aligns with global efforts to decarbonize heavy industries and promote renewable energy integration. Herein, we present our recent works (i) on the development of cost-effective cathode electrocatalysts for hydrogen evolution in an acidic medium, based on Ni-W nanocomposite materials, and (ii) on the development of carbon-based support for cathodes used in an alkaline water electrolysers based on hollow multiactivity carbon spheres (HMCS). Ni-W and Ni-W-Ru nanocomposite electrocatalysts were synthesized via a sequential, optimized three-step process to enhance hydrogen evolution reaction (HER) performance in acidic media. Initially, Ni–W nanocomposite materials were prepared using a single-step solution combustion synthesis (SCS) method. Optimization of the fuel-to-oxidant ratio established φ = 9 as ideal. The Ni 0.9 W 0.1 alloy phase with minimal oxide impurities, tested in 0.5 M H 2 SO 4 demonstrated the superior HER performance, correlating directly with higher proportions of metallic Ni and W states (Figure 1a, green). However, residual carbon impurities limited catalytic efficiency. To mitigate this limitation, an additional annealing step under a 10 vol.% H 2 /Ar reductive atmosphere was introduced. Among the various compositions evaluated, Ni 0.7 W 0.3 exhibited optimal HER performance, achieving a Tafel slope of 100 mV dec −1 , exchange current density of 677 μA cm − 2 , and an overpotential (η 10 ) of −143 mV at 10 mA cm − 2 (Figure 1a, blue). The enhanced catalytic activity was attributed to a synergistic interaction between metallic Ni–W, metallic tungsten, and oxygen-deficient tungsten oxide phases. To further enhance electrocatalytic efficiency toward the level of noble-metal-based catalysts, Ru was incorporated with Ni 0.7 W 0.3 , forming (Ni 0.7 W 0.3 ) 1−x Ru x electrocatalysts with low Ru loadings (x ≤ 0.10). The analysis revealed a heterogeneous structure consisting of an interconnected network of both spherical and irregularly shaped nanoparticles, with uniform elemental distribution of Ni, W, and Ru. Structural analyses confirmed the presence of metallic Ru and Ni 0.9 W 0.1 phases along with oxygen-deficient WO 2 . The (Ni 0.7 W 0.3 ) 0.96 Ru 0.04 catalyst displayed comparable HER activity ( η 10 = -109.3 mV) to the commercial 5 wt.% Ru/C (η 10 = -109.8 mV), despite containing only half of the Ru content (2.48 wt.%). Moreover, (Ni 0.7 W 0.3 ) 0.95 Ru 0.05 , containing 3.77 wt.% Ru, outperformed the commercial 5 wt.% Ru/C benchmark with an even lower η 10 of -99.2 mV (Figure 1a, red). Furthermore, all synthesized (Ni 0.7 W 0.3 ) 1−x Ru x electrocatalysts exhibited superior exchange current densities and mass activities compared to the commercial 5 wt.% Ru/C catalyst. In fact, the (Ni 0.7 W 0.3 ) 0.98 Ru 0.02 catalyst exhibited a remarkable mass activity of 2.07 A mg Ru −1 at an overpotential of −125 mV, nearly twice that of the commercial 5 wt.% Ru/C catalyst (1.04 A mg Ru −1 ). The remarkable catalytic activity was attributed to synergistic electronic interactions between Ru, Ni, and W phases, enhancing HER kinetics. Additionally, the high specific surface area and porous three-dimensional nanostructure maximized active site exposure. This research demonstrates that engineering ternary metallic interactions and structural characteristics in Ni-W-Ru nanocomposites effectively enhances HER performance, offering a promising and cost-effective alternative to conventional noble-metal catalysts in acidic media. In the context of alkaline water electrolysis, we successfully synthesized HMCS as a support for nickel nanoparticles in cathodes (Figure 1b,c). The HMCS exhibited a high specific surface area (up to 284 ± 10 m²g -1 ), facilitating the formation of a Ni/HMCS electrocatalyst with significantly enhanced HER activity compared to pure Ni. This result highlights HMCS as a promising metal-catalyst support. Notably, the non-activated Ni/HMCS outperformed the activated Ni/HMCS in HER performance. Figure 1

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How this classification was reachedexpand

Full frame machine prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.

metaresearch head score (Codex)0.000
metaresearch head score (Gemma)0.000
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Bench or experimental · Consensus signal: Bench or experimental
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.001
Threshold uncertainty score0.002

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0010.000

Machine scores (provisional)

The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.

Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.

Opus teacher head0.006
GPT teacher head0.227
Teacher spread0.221 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designBench or experimental
Domainnot available
GenreEmpirical

How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".

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Citations0
Published2025
Admission routes1
Has abstractyes

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