用超短脉冲抽运高非线性硫系玻璃光波导是产生宽带中红外超连续谱的重要途径,超连续谱的输出平均功率主要受材料激光损伤阈值(LDT)的限制。为了阐明硫系玻璃的LDT与玻璃化学组成的关系,以及不同重复频率超短脉冲辐照下对应的损伤机理,以脉冲宽度为216 fs、中心波长为1030 nm、重复频率为1~1000 kHz的激光为辐照源,对Ge-Sb-S硫系玻璃进行激光辐照,研究了玻璃的激光损伤特性。结果表明:玻璃的LDT随辐照源重复频率的增大而减小;具有较高平均键能的玻璃表现出了较高的LDT,化学计量配比的玻璃具有最优的抗激光损伤性能;当辐照脉冲的重复频率在10 kHz以下时,损伤主要由雪崩电离引起;相比之下,当辐照脉冲的重复频率超过10 kHz时,热积累变得显著,会促进玻璃的损伤。

为了解决铝材表面激光处理无法形成高色差、高对比度的黑色图形问题,以阳极氧化5052铝合金为研究对象,选用脉冲宽度为4 ns的光纤激光器,设定扫描速度为130 mm/s,频率为300 kHz,扫描间距为0.005 mm,设定功率为27%P₀~33%P₀(P₀为激光器的额定功率),以得到高色差、高对比度的黑色图形,研究激光功率对图形对比度及微观形貌的影响,分析阳极氧化铝表面激光处理形成图形的机理。结果表明:当激光功率超过1.64 W时,激光能量达到铝材熔化阈值,材料表面开始形成图形,随着功率的增大,对比度逐渐上升;当激光功率增大到2.13~2.76 W时,铝材表面熔化与蒸发形成细裂纹的微观形貌,宏观显示为黑色,对比度达到最大;激光功率增大至3.32 W后,铝材表面完全熔化,细裂纹形貌消失,宏观显示为灰白色,对比度下降。该技术有助于激光与铝材作用机理的进一步研究,对推动物联网技术的发展具有重要意义。

Near infrared (NIR) spectroscopy has been developed into one of the most important process analytical techniques (PAT) in a wide field of applications. The feasibility of NIR spectroscopy with partial least square regression (PLSR) to monitor the concentration of paeoniflorin, albiflorin, gallic acid, and benzoyl paeoniflorin during the water extraction process of Radix Paeoniae Alba was demonstrated and verified in this work. NIR spectra were collected in transmission mode and pretreated with smoothing and/or derivative, and then quantitative models were built up using PLSR. Interval partial least squares (iPLS) method was used for the selection of spectral variables. Determination coe±cients (R2 cal and R2 pred), root mean squares error of prediction (RMSEP), root mean squares error of calibration (RMSEC), and residual predictive deviation (RPD) were applied to verify the performance of the models, and the corresponding values were 0.9873 and 0.9855, 0.0487 mg/mL, 0.0545 mg/mL and 8.4 for paeoniflorin; 0.9879, 0.9888, 0.0303 mg/mL, 0.0321 mg/mL and 9.1 for albiflorin; 0.9696, 0.9644, 0.0140 mg/mL, 0.0145 mg/mL and 5.1 for gallic acid; 0.9794, 0.9781, 0.00169 mg/mL, 0.00171 mg/mL and 6.9 for benzoyl paeoniflorin, respectively. The results turned out that this approach was very e±cient and environmentally friendly for the quantitative monitoring of the water extraction process of Radix Paeoniae Alba.