| 1. |
- Wang, Shule, et al.
(författare)
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Van Krevelen diagrams based on machine learning visualize feedstock-product relationships in thermal conversion processes
- 2023
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Ingår i: Communications Chemistry. - : Springer Nature. - 2399-3669. ; 6:1
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Tidskriftsartikel (refereegranskat)abstract
- Feedstock properties play a crucial role in thermal conversion processes, where understanding the influence of these properties on treatment performance is essential for optimizing both feedstock selection and the overall process. In this study, a series of van Krevelen diagrams were generated to illustrate the impact of H/C and O/C ratios of feedstock on the products obtained from six commonly used thermal conversion techniques: torrefaction, hydrothermal carbonization, hydrothermal liquefaction, hydrothermal gasification, pyrolysis, and gasification. Machine learning methods were employed, utilizing data, methods, and results from corresponding studies in this field. Furthermore, the reliability of the constructed van Krevelen diagrams was analyzed to assess their dependability. The van Krevelen diagrams developed in this work systematically provide visual representations of the relationships between feedstock and products in thermal conversion processes, thereby aiding in optimizing the selection of feedstock and the choice of thermal conversion technique.
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| 2. |
- Ma, Shuaiyin, et al.
(författare)
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Big data-driven correlation analysis based on clustering for energy-intensive manufacturing industries
- 2023
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Ingår i: Applied Energy. - : ELSEVIER SCI LTD. - 0306-2619 .- 1872-9118. ; 349
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Tidskriftsartikel (refereegranskat)abstract
- In Industry 4.0, the production data obtained from the Internet of Things has reached the magnitude of big data with the emergence of advanced information and communication technologies. The massive and low-value density of big data challenges traditional clustering and correlation analysis. To solve this problem, a big data-driven correlation analysis based on clustering is proposed to improve energy and resource utilisation efficiency in this paper. In detail, the production units with abnormal and energy-intensive consumption can be classified by using clustering analysis. Additionally, feature extraction is carried out based on clustering analysis and the same cluster data is migrated to the training data set to improve correlation analysis accuracy. Then, correlation analysis can balance the relationship between energy supply and demand, which can reduce carbon emission and enhance sustainable competitiveness. The sensitivity analysis results show that the feature extraction method can improve the correlation analysis accuracy compared to the original analysis model. In conclusion, the big data-driven correlation analysis based on clustering can uncover the potential relationship between energy consumption and product yield, thus improving the efficiency of energy and resources.
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| 3. |
- Wang, Yuming, et al.
(författare)
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Mechanisms for improved open-circuit voltage in ternary organic solar cells
- 2023
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Ingår i: Nature Energy. - : NATURE PORTFOLIO. - 2058-7546.
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Tidskriftsartikel (övrigt vetenskapligt/konstnärligt)abstract
- The addition of a guest component can improve the open-circuit voltage in ternary organic solar cells. Spectroscopic experiments, combined with quantum chemistry simulations, conducted on a series of ternary organic solar cells provide a guide to further improving the open-circuit voltage, and hence the power conversion efficiency, of these solar cells.
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| 4. |
- Wang, Yuming, et al.
(författare)
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Origins of the open-circuit voltage in ternary organic solar cells and design rules for minimized voltage losses
- 2023
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Ingår i: Nature Energy. - : NATURE PORTFOLIO. - 2058-7546. ; 8:9, s. 978-988
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Tidskriftsartikel (refereegranskat)abstract
- The power conversion efficiency of ternary organic solar cells (TOSCs), consisting of one host binary blend and one guest component, remains limited by large voltage losses. The fundamental understanding of the open-circuit voltage (V-OC) in TOSCs is controversial, limiting rational design of the guest component. In this study, we systematically investigate how the guest component affects the radiative and non-radiative related parts of V-OC of a series of TOSCs using the detailed balanced principle. We highlight that the thermal population of charge-transfer and local exciton states provided by the guest binary blend (that is, the guest-component-based binary blend) has a significant influence on the non-radiative voltage losses. Ultimately, we provide two design rules for enhancing the V-OC in TOSCs: high emission yield for the guest binary blend and similar charge-transfer-state energies for host/guest binary blends; high miscibility of the guest component with the low gap component in the host binary blend. The performance of ternary organic solar cells is limited by voltage losses. Using the detailed balance principle, Wang et al. show how the third component of the blend affects the open-circuit voltage and delineate molecular design rules.
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| 5. |
- Xiong, Binyu, et al.
(författare)
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Numerical analysis of vanadium redox flow batteries considering electrode deformation under various flow fields
- 2023
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Ingår i: Journal of Power Sources. - : Elsevier BV. - 0378-7753. ; 564
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Tidskriftsartikel (refereegranskat)abstract
- The porous electrode of vanadium redox flow batteries (VRBs) is subject to deformation due to mechanical stress during stack assembling. The forces compress the electrode fiber into the flow channel and thus alter the electrode porosity ratio. Due to the complex mechanisms, the effects of resulting electrode morphological changes on VRB performance were usually ignored in existing studies. This paper proposes a three-dimensional VRB model considering the uneven electrode deformation to investigate the cell performance under different electrode compression ratios with three flow-field designs. Compression ratio (CR) and the intrusive part of the electrode are obtained under various mechanical stress by adjusting gasket thickness in the experiment. The proposed electrochemical model is established based on the comprehensive description of conservation laws and analyzed using the COMSOL platform. Three indices, namely the concentration overpotential, pressure drop, and distribution uniformity, are selected for the analysis under the three flow field designs and different CRs. The numerical study reveal that the pressure drop and the concentration overpotential are sensitive to the CR but less affected by the concentration uniformity. The minimum overpotential can be reached when the CR is around 40%–50%, depending on flow field designs, while a higher CR can cause a drastically increased pressure drop. It is also found that the interdigitated flow field with a CR of 45% is considered optimal. The insights from the proposed method demonstrate the significance of considering the effects of electrode deformation in the stack design under various flow fields.
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| 6. |
- Zhang, Han, et al.
(författare)
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Atopic dermatitis and chronic kidney disease : a bidirectional Mendelian randomization study
- 2023
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Ingår i: Frontiers in Medicine. - : Frontiers Media SA. - 2296-858X. ; 10
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Tidskriftsartikel (refereegranskat)abstract
- Background: A bidirectional association between atopic dermatitis and chronic kidney disease (CKD) has been revealed in observational studies, whereas the causality of this association was unclear. We conducted a Mendelian randomization study to determine the bidirectional causal association between atopic dermatitis and CKD.Methods: Independent genetic instruments associated with atopic dermatitis and CKD at the genome-wide significance level were chosen from corresponding meta-analyses of genome-wide association studies. Summary-level data for atopic dermatitis were obtained from the EAGLE Eczema consortium (30,047 cases and 40,835 controls) and FinnGen consortium (7,024 cases and 198,740 controls). Summary-level data for CKD were derived from CKDGen consortium (64,164 cases and 625,219 controls) and FinnGen consortium (3,902 cases and 212,841 controls). The inverse-variance weighted method was used in the main analysis and supplemented with three sensitivity analyses.Results: Genetic predisposition to atopic dermatitis was associated with an increased risk of CKD. For a one-unit increase in the prevalence of atopic dermatitis, the odds ratio of CKD was 1.07 (95% confidence interval: 1.01-1.12). In the reverse Mendelian randomization analysis, the odds ratio of atopic dermatitis was 1.14 (95% confidence interval: 1.03-1.26) for a one-unit increase in the prevalence of CKD. The associations persisted in sensitivity analyses and no pleiotropy was detected.Conclusion: This Mendelian randomization study suggests a bidirectional positive association between atopic dermatitis and CKD.
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