Lab-on-device investigation of phase transition in MoOx semiconductors

Precise tuning of phase transition material properties enables multifunctional devices for information processing and energy conversion, but controlling on-device phase transitions and monitoring microscopic mechanisms remains challenging. Here, we develop a lab-on-device system for molybdenum oxide to probe operando hydrogenation mechanisms through in situ electrical and spectral characterization with density functional theory calculations, revealing threshold-driven proton dynamics that govern the transition between nonvolatile memory operation and catalytic hydrogen evolution. Moderate proton intercalation (flux < 10<sup>17 </sup>cm<sup>-2</sup>) achieves a five-order conductance modulation under ambient conditions via polaron formation and stoichiometric optimization (H/Mo up to 22%, Mo/O approaching ideal ratios), outperforming oxygen vacancy engineering. Beyond this threshold (flux ~10<sup>17</sup> cm<sup>-2</sup>), intensive proton intercalation triggers electric-to-chemical energy conversion, directly linking proton history to catalytic activity. Leveraging these principles, we achieve nonvolatile electrochemical memory with linear synaptic and accumulative neuronal functionalities, and demonstrate an all electrochemical random-access memory neural network hardware that executes memory-efficient rank-order coding for sparse signals even under noisy conditions.

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Publication Details

Journal
Nature Communications
Published
2025-05-23
DOI
https://doi.org/10.1038/s41467-025-60050-7
Citations
6
Primary Topic
Advanced Memory and Neural Computing
Type
article
Field-Weighted Citation Impact
4.38

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article

Lab-on-device investigation of phase transition in MoOx semiconductors

Yang Chai, Younian Tang, Chunzhen Yang, Huixin Xiu et al.
6 citations
Nature Communications
Advanced Memory and Neural Computing
4.38
article

Lab-on-device investigation of phase transition in MoOx semiconductors

Yang Chai, Younian Tang, Chunzhen Yang, Huixin Xiu, Xiaoci Liang, Bin Xi, Chuan Liu, Jialiang Wang, Mengye Wang, Dongyue Su
article en
6 citations

Abstract

Precise tuning of phase transition material properties enables multifunctional devices for information processing and energy conversion, but controlling on-device phase transitions and monitoring microscopic mechanisms remains challenging. Here, we develop a lab-on-device system for molybdenum oxide to probe operando hydrogenation mechanisms through in situ electrical and spectral characterization with density functional theory calculations, revealing threshold-driven proton dynamics that govern the transition between nonvolatile memory operation and catalytic hydrogen evolution. Moderate proton intercalation (flux < 10<sup>17 </sup>cm<sup>-2</sup>) achieves a five-order conductance modulation under ambient conditions via polaron formation and stoichiometric optimization (H/Mo up to 22%, Mo/O approaching ideal ratios), outperforming oxygen vacancy engineering. Beyond this threshold (flux ~10<sup>17</sup> cm<sup>-2</sup>), intensive proton intercalation triggers electric-to-chemical energy conversion, directly linking proton history to catalytic activity. Leveraging these principles, we achieve nonvolatile electrochemical memory with linear synaptic and accumulative neuronal functionalities, and demonstrate an all electrochemical random-access memory neural network hardware that executes memory-efficient rank-order coding for sparse signals even under noisy conditions.

Nature CommunicationsVol. 16(1)
Hong Kong Polytechnic University (HK), University of Shanghai for Science and Technology (CN), Sun Yat-sen University (CN)
National Natural Science Foundation of China, National Key Research and Development Program of China, Basic and Applied Basic Research Foundation of Guangdong Province
Affordable and clean energy
Openalex Percentile: Top 6%
Advanced Memory and Neural Computing
4.38
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