Parameter Optimization in the Drying Process of Catalyst Ink for PEFC Electrode Films with Few Cracks

Nagai, Kohei; Nagato, Keisuke; Osa, Takayuki; Araki, Takuto; Inoue, Gen; Tsujiguchi, Takuya; Kuroda, Yoshiyuki; Tomizawa, Morio; Kurosu, Masato

doi:10.1149/10409.0017ecst

Cited by 2 publications

(5 citation statements)

References 9 publications

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“…6 d). The effect of heating on the formation of the skin and the subsequent defect reduction was confirmed in our previous study 48 . In the samples that continued to be heated at high temperatures even after the skin was formed, radial cracks were observed.…”

Section: Resultssupporting

confidence: 78%

“…Moreover, the detailed mechanism of the drying phenomenon could be determined. In our previous study 48 , we confirmed that the parameters determined by BO were partially applicable for this process. However, the effectiveness of the parameter exploration system was not evaluated.…”

Section: Introductionsupporting

confidence: 80%

“…In ( b ) and ( c ), the raw images are shown on the left side, and the images with the defect areas detected by binarization are shown on the right side (adapted with permission from ref. 48 Copyright (2021) the Electrochemical Society). …”

Section: Resultsmentioning

confidence: 99%

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Sample-efficient parameter exploration of the powder film drying process using experiment-based Bayesian optimization

Nagai

Osa

Inoue

et al. 2022

Sci Rep

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Parameter optimization is a long-standing challenge in various production processes. Particularly, powder film forming processes entail multiscale and multiphysical phenomena, each of which is usually controlled by a combination of several parameters. Therefore, it is difficult to optimize the parameters either by numerical-model-based analysis or by “brute force” experiment-based exploration. In this study, we focus on a Bayesian optimization method that has led to breakthroughs in materials informatics. Specifically, we apply this method to exploration of production-process-parameter for the powder film forming process. To this end, a slurry containing a powder, polymer, and solvent was dropped, the drying temperature and time were controlled as parameters to be explored, and the uniformity of the fabricated film was evaluated. Using this experiment-based Bayesian optimization system, we searched for the optimal parameters among 32,768 (85) parameter sets to minimize defects. This optimization converged at 40 experiments, which is a substantially smaller number than that observed in brute-force exploration and traditional design-of-experiments methods. Furthermore, we inferred the mechanism corresponding to the unknown drying conditions discovered in the parameter exploration that resulted in uniform film formation. This demonstrates that a data-driven approach leads to high-throughput exploration and the discovery of novel parameters, which inspire further research.

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Section: Resultssupporting

confidence: 78%

Section: Introductionsupporting

confidence: 80%

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Sample-efficient parameter exploration of the powder film drying process using experiment-based Bayesian optimization

Nagai

Osa

Inoue

et al. 2022

Sci Rep

Self Cite

View full text Add to dashboard Cite

show abstract

“…. , 0] [12,13]. Using the mode shape decomposition method of the structural equation of motion, the vertical displacement y(x, t) of a simply supported beam at a time x and position t can be expressed as a linear combination of beam mode shapes, that is shown in the following formula:…”

Section: Frequency Domain Response Of Beam-tmdi System Undermentioning

confidence: 99%

“…where ϕ j (x) is the first mode shape of the beam, and for a simply supported beam of equal section, the mode shape function is ϕ j (x) � sin(jπx/L); u j (t) is the generalized coordinate corresponding to the j-th mode of the simply supported beam [13]. e virtual acceleration excitation is constructed using the known self-spectrum as follows:…”

Section: Frequency Domain Response Of Beam-tmdi System Undermentioning

confidence: 99%

Application of the Lagrange Equation for Intelligent Sensor Vibration Control for Power Network Monitoring

Cheng

2022

International Transactions on Electrical Energy Systems

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Objective. In order to control the vibration of the beam structure more effectively and improve the safety and availability of the beam structure, an application study of the Lagrange equation for vibration control of smart sensors for power grid monitoring is proposed. The vibration of the beam structure, the displacement of the beam structure under the excitation of seismic acceleration, the response analytical electrical formula, and the displacement response formula of the beam structure under the action of the kinematic force are deduced. The optimal parameters of the beam-TMDI system are given, and the parameter sensitivity analysis is carried out. Then, the control effect of the TMDI system is studied by numerical analysis, and the vibration reduction effect of the TMDI system and the tuned mass damper (TMD) system is compared. Experimental results show that when the mass ratio μ of the TMDI system and the TMD system are both set to a fixed value of 0.005, and the parameter β of the TMDI system is set to 0, namely β = b = 0 , at this time, the TMDI system degenerates into a TMD system. The TMD natural frequency is 14.179 rad/s and the damping ratio is 0.0432 by the DH optimization method, while the TMD natural frequency is 14.1812 rad/s, and the damping ratio is 0.0436 by the augmented Lagrangian optimization algorithm. Conclusion. The vibration displacement response spectrum of a beam structure obtained by the frequency domain method can effectively reflect electricity in the displacement response of a beam structure. The parameters that minimize the vibration response of the beam structure can be accurately obtained by using the augmented Lagrangian parameter optimization method. The sensitivity of the TMDI system is controlled by the inertial device, and the inertial device has a significant impact on its robustness. The vibration reduction performance of the TMDI system is obviously better than in the conventional TMD systems.

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Parameter Optimization in the Drying Process of Catalyst Ink for PEFC Electrode Films with Few Cracks

Cited by 2 publications

References 9 publications

Sample-efficient parameter exploration of the powder film drying process using experiment-based Bayesian optimization

Sample-efficient parameter exploration of the powder film drying process using experiment-based Bayesian optimization

Application of the Lagrange Equation for Intelligent Sensor Vibration Control for Power Network Monitoring

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