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  1. Article ; Online: Direct CO

    Lombardo, Loris / Ko, Youngdon / Zhao, Kun / Yang, Heena / Züttel, Andreas

    Angewandte Chemie (International ed. in English)

    2021  Volume 60, Issue 17, Page(s) 9580–9589

    Abstract: We demonstrate the ability of tetraalkylammonium borohydrides to capture large amounts of ... ...

    Abstract We demonstrate the ability of tetraalkylammonium borohydrides to capture large amounts of CO
    Language English
    Publishing date 2021-03-11
    Publishing country Germany
    Document type Journal Article
    ZDB-ID 2011836-3
    ISSN 1521-3773 ; 1433-7851
    ISSN (online) 1521-3773
    ISSN 1433-7851
    DOI 10.1002/anie.202100447
    Database MEDical Literature Analysis and Retrieval System OnLINE

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  2. Article ; Online: Elucidating the Mechanism of Fe Incorporation in In Situ Synthesized Co-Fe Oxygen-Evolving Nanocatalysts.

    Pham, Thi Ha My / Shen, Tzu-Hsien / Ko, Youngdon / Zhong, Liping / Lombardo, Loris / Luo, Wen / Horike, Satoshi / Tileli, Vasiliki / Züttel, Andreas

    Journal of the American Chemical Society

    2023  Volume 145, Issue 43, Page(s) 23691–23701

    Abstract: Ni- and Co-based catalysts with added Fe demonstrate promising activity in the oxygen evolution reaction (OER) during alkaline water electrolysis, with the presence of Fe in a certain quantity being crucial for their enhanced performance. The mode of ... ...

    Abstract Ni- and Co-based catalysts with added Fe demonstrate promising activity in the oxygen evolution reaction (OER) during alkaline water electrolysis, with the presence of Fe in a certain quantity being crucial for their enhanced performance. The mode of incorporation, local placement, and structure of Fe ions in the host catalyst, as well as their direct/indirect contribution to enhancing the OER activity, remain under active investigation. Herein, the mechanism of Fe incorporation into a Co-based host was investigated using an in situ synthesized Co-Fe catalyst in an alkaline electrolyte containing Co
    Language English
    Publishing date 2023-10-20
    Publishing country United States
    Document type Journal Article
    ZDB-ID 3155-0
    ISSN 1520-5126 ; 0002-7863
    ISSN (online) 1520-5126
    ISSN 0002-7863
    DOI 10.1021/jacs.3c08099
    Database MEDical Literature Analysis and Retrieval System OnLINE

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    In stock of ZB MED Bonn / Germany

    Z 4' 55/32: Show issues
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  3. Article: Support-Dependent Cu–In Bimetallic Catalysts for Tailoring the Activity of Reverse Water Gas Shift Reaction

    Li, Mo / My Pham, Thi Ha / Ko, Youngdon / Zhao, Kun / Zhong, Liping / Luo, Wen / Züttel, Andreas

    ACS sustainable chemistry & engineering. 2022 Jan. 18, v. 10, no. 4

    2022  

    Abstract: Cu-based bimetallic catalysts have attracted great attention for the reverse water gas shift (RWGS) reaction due to their high activity and selectivity. This work reports the application of Cu–In bimetallic catalysts for the RWGS reaction and ... ...

    Abstract Cu-based bimetallic catalysts have attracted great attention for the reverse water gas shift (RWGS) reaction due to their high activity and selectivity. This work reports the application of Cu–In bimetallic catalysts for the RWGS reaction and demonstrates that the promotion effect of In on Cu is support sensitive. The Cu–In/ZrO₂ catalyst exhibited significantly higher CO₂ conversion than the Cu/ZrO₂ catalyst, whereas the CO₂ conversion over Cu–In/CeO₂ was much lower than that of Cu/CeO₂. The reasons of the support-dependent RWGS activity was revealed by systematic characterizations. On the ZrO₂ support, Cu and In formed Cu–In alloys and promoted the activation of CO₂ by the oxygen vacancies from partially reduced In₂O₃. On the CeO₂ support, Cu and In were in the form of metallic Cu and In₂O₃, respectively. The dispersion of Cu and the formation of oxygen vacancies on CeO₂ were obstructed by the introduction of In, leading to decreased RWGS activity. Among these catalysts, Cu/CeO₂ showed the best RWGS activity because of the strong CO₂ activation ability of the partially reduced CeO₂ support and the highly active Cu/CeO₂–ₓ interfaces. These results provide new insights into the design and understanding of supported bimetallic catalysts for CO₂ hydrogenation.
    Keywords carbon dioxide ; catalysts ; green chemistry ; hydrogenation ; oxygen
    Language English
    Dates of publication 2022-0118
    Size p. 1524-1535.
    Publishing place American Chemical Society
    Document type Article
    ISSN 2168-0485
    DOI 10.1021/acssuschemeng.1c06935
    Database NAL-Catalogue (AGRICOLA)

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  4. Article: Time delay neural network modeling for particle size in SAG mills

    Ko, Young-Don / Shang, Helen

    Powder technology. 2011 Jan. 10, v. 205, no. 1-3

    2011  

    Abstract: Particle size is a very important variable in semi-autogenous grinding processes. It is desirable to measure the variable efficiently or even predict its variations in advance. In this paper, the time delay neural network model is developed to predict ... ...

    Abstract Particle size is a very important variable in semi-autogenous grinding processes. It is desirable to measure the variable efficiently or even predict its variations in advance. In this paper, the time delay neural network model is developed to predict the feed particle size of a semi-autogenous grinding mill, and the Levenberg–Marquardt algorithm is used to train the network. Results show that the model predicted values fit well with the industrial operating data. The proposed model can predict the particle size in advance and allow adequate time to take corrective actions during abnormal operations, and therefore provide a great advantage in monitoring and control of the industrial processes.
    Keywords algorithms ; grinding ; monitoring ; neural networks ; particle size
    Language English
    Dates of publication 2011-0110
    Size p. 250-262.
    Publishing place Elsevier B.V.
    Document type Article
    ISSN 0032-5910
    DOI 10.1016/j.powtec.2010.09.023
    Database NAL-Catalogue (AGRICOLA)

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  5. Article: A neural network-based soft sensor for particle size distribution using image analysis

    Ko, Young-Don / Shang, Helen

    Powder technology. 2011 Oct. 10, v. 212, no. 2

    2011  

    Abstract: Many industrial processes require on-line measurement of particle size and particle size distribution for process monitoring and control. The available techniques for reliable on-line measurement are, however, limited. In this paper, based on the ... ...

    Abstract Many industrial processes require on-line measurement of particle size and particle size distribution for process monitoring and control. The available techniques for reliable on-line measurement are, however, limited. In this paper, based on the captured surface images of randomly disarranged ore particles, the image uniformity was characterized. Particle size distribution was then investigated by applying a neural network-based modeling with the obtained image uniformity. The proposed soft sensor provides an improved prediction model and can be used for real time measurement of particle size distribution in the industrial operations.
    Keywords image analysis ; models ; particle size ; particle size distribution ; prediction ; process monitoring
    Language English
    Dates of publication 2011-1010
    Size p. 359-366.
    Publishing place Elsevier B.V.
    Document type Article
    ISSN 0032-5910
    DOI 10.1016/j.powtec.2011.06.013
    Database NAL-Catalogue (AGRICOLA)

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  6. Article: Time delay neural network modeling for particle size in SAG mills

    Ko, Young-Don / Shang, Helen

    Powder technology

    Volume v. 205,, Issue no. 1

    Abstract: Particle size is a very important variable in semi-autogenous grinding processes. It is desirable to measure the variable efficiently or even predict its variations in advance. In this paper, the time delay neural network model is developed to predict ... ...

    Abstract Particle size is a very important variable in semi-autogenous grinding processes. It is desirable to measure the variable efficiently or even predict its variations in advance. In this paper, the time delay neural network model is developed to predict the feed particle size of a semi-autogenous grinding mill, and the Levenberg–Marquardt algorithm is used to train the network. Results show that the model predicted values fit well with the industrial operating data. The proposed model can predict the particle size in advance and allow adequate time to take corrective actions during abnormal operations, and therefore provide a great advantage in monitoring and control of the industrial processes.
    Keywords particle size ; monitoring ; neural networks ; algorithms ; grinding
    Language English
    Document type Article
    ISSN 0032-5910
    Database AGRIS - International Information System for the Agricultural Sciences and Technology

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    Order via subito

    This service is chargeable due to the Delivery terms set by subito. Orders including an article and supplementary material will be classified as separate orders. In these cases, fees will be demanded for each order.

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  7. Article: neural network-based soft sensor for particle size distribution using image analysis

    Ko, Young-Don / Shang, Helen

    Powder technology

    Volume v. 212,, Issue no. 2

    Abstract: Many industrial processes require on-line measurement of particle size and particle size distribution for process monitoring and control. The available techniques for reliable on-line measurement are, however, limited. In this paper, based on the ... ...

    Abstract Many industrial processes require on-line measurement of particle size and particle size distribution for process monitoring and control. The available techniques for reliable on-line measurement are, however, limited. In this paper, based on the captured surface images of randomly disarranged ore particles, the image uniformity was characterized. Particle size distribution was then investigated by applying a neural network-based modeling with the obtained image uniformity. The proposed soft sensor provides an improved prediction model and can be used for real time measurement of particle size distribution in the industrial operations.
    Keywords models ; particle size ; prediction ; process monitoring ; particle size distribution ; image analysis
    Language English
    Document type Article
    ISSN 0032-5910
    Database AGRIS - International Information System for the Agricultural Sciences and Technology

    More links

    Kategorien

    Order via subito

    This service is chargeable due to the Delivery terms set by subito. Orders including an article and supplementary material will be classified as separate orders. In these cases, fees will be demanded for each order.

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