In-line monitoring and modelling of particle size reduction of hexagonal boron nitride (hBN) suspension in femtosecond laser processing

H. Muneoka, Takeru Koike, Tsuyohito Ito, Kazuo Terashima, Eisuke Miura
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Abstract

This study investigates the particle-size reduction of hexagonal boron nitride (hBN) suspensions under femtosecond-laser irradiation. We propose an in-line monitoring method that uses transmission spectroscopy (TS) in the visible wavelength region to evaluate the changes in particle-size distribution. The Ångström exponent (α), derived from the wavelength dependence of optical thickness, is employed as an indicator of particle-size reduction. The effectiveness of α is validated through comparison with particle-size distributions obtained by the particle tracking method. We demonstrate real-time monitoring of particle-size variation in a flow system using in-line TS measurements. The dependence of α on laser energy and hBN concentration is also investigated. Furthermore, we introduce an indicator, the average number of size-reduction events per particle (NSR), and a model for estimating it under various experimental conditions. The NSR indicator and the model for its derivation provide a unified understanding of the experimental results obtained under various conditions, such as treatment volume, laser energy, and hBN concentration, suggesting that they capture the essential aspects of laser propagation in the suspension and the particle-size reduction process. This study highlights the potential of α as an in-line process monitoring tool and the significance of the NSR indicator and its model in understanding the underlying mechanisms of laser processing for particle-size reduction in suspensions.
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飞秒激光加工过程中六方氮化硼(hBN)悬浮液粒度降低的在线监测和建模
本研究探讨了六方氮化硼(hBN)悬浮液在飞秒激光辐照下的粒度减小问题。我们提出了一种在线监测方法,利用可见光波长区域的透射光谱(TS)来评估粒度分布的变化。根据光学厚度的波长依赖性推导出的Ångström 指数 (α),被用作粒度减少的指标。通过与颗粒跟踪法获得的颗粒大小分布进行比较,验证了 α 的有效性。我们展示了利用在线 TS 测量实时监测流动系统中颗粒大小变化的方法。我们还研究了 α 与激光能量和 hBN 浓度的关系。此外,我们还介绍了一种指标,即每个颗粒的平均粒度还原事件数(NSR),以及在各种实验条件下估算该指标的模型。NSR 指标及其推导模型统一了在处理量、激光能量和 hBN 浓度等不同条件下获得的实验结果,表明它们捕捉到了激光在悬浮液中传播和粒度还原过程的重要方面。本研究强调了 α 作为在线过程监控工具的潜力,以及 NSR 指标及其模型在理解悬浮液中粒度还原激光处理的基本机制方面的重要意义。
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