Enhancements of electric field and afterglow of non-equilibrium plasma by Pb(ZrxTi1−x)O3 ferroelectric electrode

Xu, Yijie; Liu, Ning; Lin, Ying; Mao, Xingqian; Zhong, Hongtao; Chang, Ziqiao; Shneider, Mikhail N.; Ju, Yiguang

doi:10.1038/s41467-024-47230-7

Cited by 4 publications

(1 citation statement)

References 42 publications

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“…These improvements are postulated to arise from the intricate but poorly-understood synergies between the plasma and catalyst [13,14]. Despite extensive experimental efforts on investigating the role of factors such as electric field [15], surface charges [16][17][18], surface reactions involving excited species [8], atoms, and photons [19,20], amongst others, there remain significant gaps in the fundamental understanding of plasma-catalyst interactions, let alone designing efficient catalysts tailored for plasma catalysis [21]. On the other hand, first-principles studies, particularly density functional theory (DFT), have proven useful for the investigation of plasma-catalyst interactions.…”

Section: Introductionmentioning

confidence: 99%

Interpretable Attention-based Transfer Learning in Plasma Catalysis: A Study on the Role of Surface Charge

Mesbah,

Shao,

Lele

et al. 2024

Preprint

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Low-temperature plasma catalysis holds promise for electrification of energy-intensive chemical processes such as methane reforming and ammonia synthesis. However, fundamental understanding of plasma-catalyst interactions, essential for catalyst design and screening for plasma catalysts, remains largely limited. Recent work has demonstrated the importance of first-principles studies, including density functional theory (DFT), for elucidating the role of electro- and photo-effects such as electric field and charge in plasma catalysis. The availability of increasing amounts of DFT data in thermal catalysis presents a unique opportunity for plasma catalysis research to efficiently leverage this existing first-principles knowledge of thermal catalysis towards investigating plasma-catalyst interactions. To this end, this paper investigates interpretable transfer learning from thermal to plasma catalysis, with a focus on the role of surface charge. Pre-trained attention-based graph neural networks (GNNs) from the Open Catalysis Project, trained using millions of thermal catalysis DFT data points, are structurally adapted to account for surface charge effects and fine-tuned using plasma catalysis DFT data of single metal atoms on Al$_2$O$_3$ support and adsorbates involved in plasma-catalytic ammonia synthesis. Not only the fine-tuned attention-based GNN model provides a high test accuracy for predicting adsorption energies and atomic forces in plasma catalysis, but also shows adequate extrapolation for unseen single metal atoms in the plasma catalysis data used for the model fine-tuning. To distinguish the effects of surface charge from other dissimilarities in DFT data of thermal and plasma catalysis, a dual-model framework is presented that relies on two pre-trained GNNs, one of which is specifically tasked to capture surface charge effects using an attention mechanism that provides interpretable insights into their role. Lastly, it is demonstrated how the attention-based GNNs developed for single metal atoms can be efficiently adapted for predicting adsorption energies and atomic forces for metal clusters in plasma catalysis. This work highlights the vast potential of interpretable transfer learning from thermal catalysis to plasma catalysis to mitigate excessive computational requirements of first-principles studies in plasma catalysis, towards accelerating fundamental research in this domain.

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Section: Introductionmentioning

confidence: 99%

Interpretable Attention-based Transfer Learning in Plasma Catalysis: A Study on the Role of Surface Charge

Mesbah,

Shao,

Lele

et al. 2024

Preprint

View full text Add to dashboard Cite

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Kinetics of low temperature plasma assisted NH3/H2 oxidation in a nanosecond-pulsed discharge

Liu,

Mei,

Mao

et al. 2024

Proceedings of the Combustion Institute

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Characterization of gliding arc plasma ignition in aeroengine swirl combustion chamber

Zhang,

Yu,

et al. 2024

Physics of Fluids

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Gliding arc plasma-enhanced combustion is a relatively new combustion technology. This paper describes a gliding arc plasma combustion dome that improves the ignition characteristics of aeroengines. The ignition characteristics are studied using an experimental platform consisting of a single-combustion-dome swirl combustion chamber. A flame spontaneous radiation imaging technique is adopted to collect the C2* groups formed during the ignition process. We focus on the ignition mode, flame kernel propagation mechanism, ignition delay time, and ignition boundary of the gliding arc ignition process. The gliding arc ignition process has five stages with different characteristics: flame kernel stabilization, flame kernel expansion, intense combustion, combustion decay, and stable combustion. During the flame kernel propagation stage, the main flame kernel in the combustion dome splits into flame kernel 1, located in the recirculation zone of the upper wall, and flame kernel 2, located in the recirculation zone of the lower wall under the action of airflow. The main flame kernel reflects the direct action of the gliding arc. Unconsumed energy and active particles included in the main flame kernel are added to flame kernels 1 and 2 through sporadic splitting of the main kernel. This promotes the expansion rate of the fire nucleus in the combustion chamber. Compared with electric spark ignition, gliding arc plasma-enhanced combustion significantly widens the ignition boundary and shortens the ignition delay time of the combustion chamber. The ignition delay time can be shortened by up to 81.53% under an inlet flow rate of 55 m/s and a residual gas coefficient of 3; the ignition boundary can be widened by a maximum of 115.9% under an inlet flow rate of 5 m/s.

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Enhancements of electric field and afterglow of non-equilibrium plasma by Pb(ZrxTi1−x)O3 ferroelectric electrode

Cited by 4 publications

References 42 publications

Interpretable Attention-based Transfer Learning in Plasma Catalysis: A Study on the Role of Surface Charge

Interpretable Attention-based Transfer Learning in Plasma Catalysis: A Study on the Role of Surface Charge

Kinetics of low temperature plasma assisted NH3/H2 oxidation in a nanosecond-pulsed discharge

Characterization of gliding arc plasma ignition in aeroengine swirl combustion chamber

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