Table · dataset · 2026
Hierarchical Morphology Engineering of Silicon Micropillars Dictates Interfacial Kinetics for Room-Temperature Hydrogen Sensing
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The precise construction of three-dimensional (3D) hierarchical architectures on silicon substrates is highly desirable for amplifying surface-dominated physicochemical interactions.
Description
However, traditional top-down microfabrication typically yields inherently smooth sidewalls, restricting active site density and causing the “premature saturation” of interfacial reactions. Herein, we report a controllable morphology engineering strategy via one-step metal-assisted chemical etching (MACE) to fabricate hierarchical silicon micropillars (HMPs) with in situ sculpted nanoscale rough sidewalls.
To elucidate the impact of this hierarchical morphology on interfacial kinetics, we employed Pd-modified HMPs for room-temperature H<sub>2</sub> sensing as a proof-of-concept model. This custom architecture effectively bypasses the morphological bottlenecks of traditional smooth micropillars (SMPs). The optimized Pd/HMPs sensor achieved a response of up to 628% toward 1% H<sub>2</sub>a > 6-fold enhancement over its SMPs counterpartwith a low detection limit of 200 ppb.
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Intriguingly, the sensor exhibits an anomalous humidity-enhanced sensing behavior under low-humidity conditions, revealing a unique synergistic mechanism jointly governed by local surface charge modulation and proton-assisted interfacial transport. This work establishes a versatile paradigm for constructing complex on-chip silicon architectures and offers fundamental insights into how morphology governs interfacial kinetics.
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Where it is published
- DOI doi.org/10.1021/acs.langmuir.6c03618.s001 ↗
DOI / persistent id · from zivahub uct ac za
Catalogue records · 1
- OAI-PMH record api.figshare.com/v2/oai?verb=GetRecord&metadataPrefix=oai_dc&identifier=oai%3Af… ↗
metadata API · from zivahub uct ac za
Topics
Provenance · 1 source records, 12 field assertions
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|---|---|---|---|
| ZivaHub | oai:figshare.com:article/34024834 | 12 d ago | JSON v1 |
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