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Author | Cai, Y.; Mei, D.; Chen, Y.; Bogaerts, A.; Tu, X. | ||||
Title | Machine learning-driven optimization of plasma-catalytic dry reforming of methane | Type | A1 Journal Article | ||
Year | 2024 | Publication | Journal of Energy Chemistry | Abbreviated Journal | Journal of Energy Chemistry |
Volume | 96 | Issue | Pages | 153-163 | |
Keywords | A1 Journal Article; Plasma catalysis Machine learning Process optimization Dry reforming of methane Syngas production; Plasma, laser ablation and surface modeling Antwerp (PLASMANT) ; | ||||
Abstract | This study investigates the dry reformation of methane (DRM) over Ni/Al2O3 catalysts in a dielectric barrier discharge (DBD) non-thermal plasma reactor. A novel hybrid machine learning (ML) model is developed to optimize the plasma-catalytic DRM reaction with limited experimental data. To address the non-linear and complex nature of the plasma-catalytic DRM process, the hybrid ML model integrates three well-established algorithms: regression trees, support vector regression, and artificial neural networks. A genetic algorithm (GA) is then used to optimize the hyperparameters of each algorithm within the hybrid ML model. The ML model achieved excellent agreement with the experimental data, demonstrating its efficacy in accurately predicting and optimizing the DRM process. The model was subsequently used to investigate the impact of various operating parameters on the plasma-catalytic DRM performance. We found that the optimal discharge power (20 W), CO2/CH4 molar ratio (1.5), and Ni loading (7.8 wt%) resulted in the maximum energy yield at a total flow rate of 51 mL/min. Furthermore, we investigated the relative significance of each operating parameter on the performance of the plasmacatalytic DRM process. The results show that the total flow rate had the greatest influence on the conversion, with a significance exceeding 35% for each output, while the Ni loading had the least impact on the overall reaction performance. This hybrid model demonstrates a remarkable ability to extract valuable insights from limited datasets, enabling the development and optimization of more efficient and selective plasma-catalytic chemical processes. | ||||
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Publisher | Place of Publication | Editor | |||
Language | Wos | Publication Date ![]() |
2024-04-25 | ||
Series Editor | Series Title | Abbreviated Series Title | |||
Series Volume | Series Issue | Edition | |||
ISSN | 2095-4956 | ISBN | Additional Links | ||
Impact Factor | 13.1 | Times cited | Open Access | ||
Notes | This project received funding from the European Union’s Hori- zon 2020 research and innovation program under the Marie Sklodowska-Curie grant agreement No. 813393. | Approved | Most recent IF: 13.1; 2024 IF: 2.594 | ||
Call Number | PLASMANT @ plasmant @ | Serial | 9124 | ||
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Author | Khan, S.U.; Matshitse, R.; Borah, R.; Nemakal, M.; Moiseeva, E.O.; Dubinina, T.V.; Nyokong, T.; Verbruggen, S.W.; De Wael, K. | ||||
Title | Coupling of phthalocyanines with plasmonic gold nanoparticles by click chemistry for an enhanced singlet oxygen based photoelectrochemical sensing | Type | A1 Journal article | ||
Year | 2024 | Publication | ChemElectroChem | Abbreviated Journal | |
Volume | Issue | Pages | 1-11 | ||
Keywords | A1 Journal article; Antwerp Electrochemical and Analytical Sciences Lab (A-Sense Lab); Antwerp engineering, PhotoElectroChemistry & Sensing (A-PECS) | ||||
Abstract | Coupling photosensitizers (PSs) with plasmonic nanoparticles increases the photocatalytic activity of PSs as the localized surface plasmon resonance (LSPR) of plasmonic nanoparticles leads to extreme concentration of light in their vicinity known as the near-field enhancement effect. To realize this in a colloidal phase, efficient conjugation of the PS molecules with the plasmonic nanoparticle surface is critical. In this work, we demonstrate the coupling of phthalocyanine (Pc) molecules with gold nanoparticles (AuNPs) in the colloidal phase via click chemistry. This conjugated Pc-AuNPs colloidal system is shown to enhance the photocatalytic singlet oxygen (1O2) production over non-conjugated Pcs and hence improve the photoelectrochemical detection of phenols. The plasmonic enhancement of the 1O2 generation by Pcs was clearly elucidated by complementary experimental and computational classical electromagnetic models. The dependence of plasmonic enhancement on the spectral position of the excitation laser wavelength and the absorbance of the Pc molecules with respect to the wavelength specific near-field enhancement is clearly demonstrated. A high similar to 8 times enhancement is obtained with green laser (532 nm) at the LSPR due to the maximum near-field enhancement at the resonance wavelength. Zinc phthalocyanine is covalently linked to plasmonic AuNPs via click chemistry to investigate the synergistic effect that boosts the overall activity toward the detection of HQ under visible light illumination. The 1O2 quantum yield of ZnPc improved significantly after conjugating with AuNPs, resulting in enhanced photoelectrochemical activity. image | ||||
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Publisher | Place of Publication | Editor | |||
Language | Wos | 001214481000001 | Publication Date ![]() |
2024-05-02 | |
Series Editor | Series Title | Abbreviated Series Title | |||
Series Volume | Series Issue | Edition | |||
ISSN | 2196-0216 | ISBN | Additional Links | UA library record; WoS full record | |
Impact Factor | 4 | Times cited | Open Access | ||
Notes | Approved | Most recent IF: 4; 2024 IF: 4.136 | |||
Call Number | UA @ admin @ c:irua:205962 | Serial | 9142 | ||
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Author | Maerivoet, S.; Tsonev, I.; Slaets, J.; Reniers, F.; Bogaerts, A. | ||||
Title | Coupled multi-dimensional modelling of warm plasmas: Application and validation for an atmospheric pressure glow discharge in CO2/CH4/O2 | Type | A1 Journal Article | ||
Year | 2024 | Publication | Chemical Engineering Journal | Abbreviated Journal | Chemical Engineering Journal |
Volume | 492 | Issue | Pages | 152006 | |
Keywords | A1 Journal Article; Plasma, laser ablation and surface modeling Antwerp (PLASMANT) ; | ||||
Abstract | To support experimental research into gas conversion by warm plasmas, models should be developed to explain the experimental observations. These models need to describe all physical and chemical plasma properties in a coupled way. In this paper, we present a modelling approach to solve the complete set of assumed relevant equations, including gas flow, heat balance and species transport, coupled with a rather extensive chemistry set, consisting of 21 species, obtained by reduction of a more detailed chemistry set, consisting of 41 species. We apply this model to study the combined CO2 and CH4 conversion in the presence of O2, in a direct current atmospheric pressure glow discharge. Our model can predict the experimental trends, and can explain why higher O2 fractions result in higher CH4 conversion, namely due to the higher gas temperature, rather than just by additional chemical reactions. Indeed, our model predicts that when more O2 is added, the energy required to reach any set temperature (i.e., the enthalpy) drops, allowing the system to reach higher temperatures with similar amounts of energy. This is in turn related to the higher H2O fraction and lower H2 fraction formed in the plasma, as demonstrated by our model. Altogether, our new self-consistent model can capture the main physics and chemistry occurring in this warm plasma, which is an important step towards predictive modelling for plasma-based gas conversion. | ||||
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Publisher | Place of Publication | Editor | |||
Language | Wos | Publication Date ![]() |
2024-05-09 | ||
Series Editor | Series Title | Abbreviated Series Title | |||
Series Volume | Series Issue | Edition | |||
ISSN | 1385-8947 | ISBN | Additional Links | ||
Impact Factor | 15.1 | Times cited | Open Access | ||
Notes | This research was supported by the Excellence of Science FWO-FNRS project (FWO grant ID G0I1822N; EOS ID 40007511) and the European Research Council (ERC) under the European Union’s Horizon 2020 research and innovation programme (grant agreement No. 810182–SCOPE ERC Synergy project, and grant agreement No. 101081162–PREPARE ERC Proof of Concept project). computational resources and services used in this work were provided by the HPC core facility CalcUA of the Universiteit Antwerpen, and VSC (Flemish Supercomputer Center), funded by the Research Foundation – Flanders (FWO) and the Flemish Government. | Approved | Most recent IF: 15.1; 2024 IF: 6.216 | ||
Call Number | PLASMANT @ plasmant @ | Serial | 9132 | ||
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Author | Van Gordon, K.; Ni, B.; Girod, R.; Mychinko, M.; Bevilacqua, F.; Bals, S.; Liz‐Marzán, L.M. | ||||
Title | Single Crystal and Pentatwinned Gold Nanorods Result in Chiral Nanocrystals with Reverse Handedness | Type | A1 Journal Article | ||
Year | 2024 | Publication | Angewandte Chemie International Edition | Abbreviated Journal | Angew Chem Int Ed |
Volume | Issue | Pages | |||
Keywords | A1 Journal Article; Electron Microscopy for Materials Science (EMAT) ; | ||||
Abstract | Handedness is an essential attribute of chiral nanocrystals, having a major influence on their properties. During chemical growth, the handedness of nanocrystals is usually tuned by selecting the corresponding enantiomer of chiral molecules involved in asymmetric growth, often known as chiral inducers. We report that, even using the same chiral inducer enantiomer, the handedness of chiral gold nanocrystals can be reversed by using Au nanorod seeds with either single crystalline or pentatwinned structure. This effect holds for chiral growth induced both by amino acids and by chiral micelles. Although it was challenging to discern the morphological handedness for<italic>L</italic>‐cystine‐directed particles, even using electron tomography, both cases showed circular dichroism bands of opposite sign, with nearly mirrored chiroptical signatures for chiral micelle‐directed growth, along with quasi‐helical wrinkles of inverted handedness. These results expand the chiral growth toolbox with an effect that might be exploited to yield a host of interesting morphologies with tunable optical properties. | ||||
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Publisher | Place of Publication | Editor | |||
Language | Wos | Publication Date ![]() |
2024-05-24 | ||
Series Editor | Series Title | Abbreviated Series Title | |||
Series Volume | Series Issue | Edition | |||
ISSN | 1433-7851 | ISBN | Additional Links | ||
Impact Factor | 16.6 | Times cited | Open Access | ||
Notes | Ana Sánchez-Iglesias is acknowledged for support in the synthesis of pentatwinned gold nanorods. The authors acknowledge financial support by the European Research Council (ERC CoG No. 815128 REALNANO to S.B.), from MCIN/AEI/10.13039/501100011033 (Grant PID2020- 117779RB-I00 to L.M.L.-M and FPI Fellowship PRE2021- 097588 to K.V.G.), and by KU Leuven (C14/22/085). This work has been funded by the European Union under Project 101131111—DELIGHT. Funding for open access charge: Universidade de Vigo/ CRUE-CISUG. | Approved | Most recent IF: 16.6; 2024 IF: 11.994 | ||
Call Number | EMAT @ emat @ | Serial | 9129 | ||
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Author | Cai, Y.; Michiels, R.; De Luca, F.; Neyts, E.; Tu, X.; Bogaerts, A.; Gerrits, N. | ||||
Title | Improving Molecule–Metal Surface Reaction Networks Using the Meta-Generalized Gradient Approximation: CO2Hydrogenation | Type | A1 Journal Article | ||
Year | 2024 | Publication | The Journal of Physical Chemistry C | Abbreviated Journal | J. Phys. Chem. C |
Volume | 128 | Issue | 21 | Pages | 8611-8620 |
Keywords | A1 Journal Article; Plasma, laser ablation and surface modeling Antwerp (PLASMANT) ; | ||||
Abstract | Density functional theory is widely used to gain insights into molecule−metal surface reaction networks, which is important for a better understanding of catalysis. However, it is well-known that generalized gradient approximation (GGA) density functionals (DFs), most often used for the study of reaction networks, struggle to correctly describe both gas-phase molecules and metal surfaces. Also, GGA DFs typically underestimate reaction barriers due to an underestimation of the selfinteraction energy. Screened hybrid GGA DFs have been shown to reduce this problem but are currently intractable for wide usage. In this work, we use a more affordable meta-GGA (mGGA) DF in combination with a nonlocal correlation DF for the first time to study and gain new insights into a catalytically important surface reaction network, namely, CO2 hydrogenation on Cu. We show that the mGGA DF used, namely, rMS-RPBEl-rVV10, outperforms typical GGA DFs by providing similar or better predictions for metals and molecules, as well as molecule−metal surface adsorption and activation energies. Hence, it is a better choice for constructing molecule−metal surface reaction networks. |
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Publisher | Place of Publication | Editor | |||
Language | Wos | Publication Date ![]() |
2024-05-30 | ||
Series Editor | Series Title | Abbreviated Series Title | |||
Series Volume | Series Issue | Edition | |||
ISSN | 1932-7447 | ISBN | Additional Links | ||
Impact Factor | 3.7 | Times cited | Open Access | ||
Notes | H2020 Marie Sklodowska-Curie Actions, 813393 ; Fonds Wetenschappelijk Onderzoek, 1114921N ; H2020 European Research Council, 810182 ; Nederlandse Organisatie voor Wetenschappelijk Onderzoek, 019.202EN.012 ; | Approved | Most recent IF: 3.7; 2024 IF: 4.536 | ||
Call Number | PLASMANT @ plasmant @ | Serial | 9248 | ||
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