中国激光, 2024, 51 (7): 0701016, 网络出版: 2024-04-02  

基于遗传算法的快轴流CO2激光放大器的参数优化

Optimization of Fast Axial Flow CO2 Laser Amplifier Parameters Based on Genetic Algorithm
作者单位
1 华中科技大学光学与电子信息学院,湖北 武汉 430074
2 湖北大学微电子学院,湖北 武汉 430062
3 江苏科技大学理学院,江苏 镇江 212003
摘要
获得13.5 nm极紫外光刻光源的主流方案为激光激发等离子体,即利用高功率、高重复频率、高光束质量的短脉冲CO2激光与液滴锡靶作用产生极紫外光。高功率CO2激光由振荡器产生的高重复频率CO2种子经多级放大产生,所以功率放大器是驱动光源系统的核心器件之一。建立了射频激励快轴流CO2激光放大器的六温度模型,可以模拟计算放大过程中稳态与瞬态的能量分布情况、光强变化情况、增益系数等。以此模型为适应度函数,采用遗传算法对自研射频激励快轴流CO2激光放大器的腔压和CO2、N2、He气体体积比进行全局优化,优化结果为80 mbar(1 bar=100 kPa)和V(CO2)∶V(N2)∶V(He)=12.2%∶15.3%∶72.5%。在波长10.6 μm种子光注入功率110 W的情况下,放大器的激光输出功率从2504 W 提高到3422 W,验证了该方法的可行性和有效性。
Abstract
Objective

The mainstream approach for obtaining a 13.5 nm extreme ultraviolet (EUV) lithography light source involves laser-excited plasma. This requires the use of a high-power, high-frequency, and high-beam-quality short-pulse CO2 laser, as well as a droplet Sn target, to generate extreme ultraviolet light. To satisfy the power requirements of EUV lithography, a high-frequency CO2 oscillator must be used to generate high-frequency CO2 seeds. These seeds undergo multi-stage amplification to produce a high-power CO2 laser that serves as the driving laser. Consequently, a power amplifier is the core device for driving a light source system. Therefore, this study aims to optimize the operating parameters of a radio frequency (RF)-excited fast axial-flow CO2 laser power amplifier to achieve better gain performance and higher amplified output power. This optimization has significant practical significance for efficiently obtaining EUV light sources.

Methods

Generally, the output power of an RF-excited fast axial laser amplifier is intricately linked to several factors such as the seed optical power, gas composition ratio, RF injection power, discharge tube diameter, gas pressure, and flow rate. In this paper, we establish a six-temperature model for an RF-excited fast axial CO2 laser amplifier. This model encompasses the most abundant energy levels for simulating and calculating steady-state and transient energy distributions, light intensity changes, gain coefficients, etc. in the amplification process. As optimizing a single parameter with a six-temperature model may result in local optimization and a considerable workload, we employ a global optimization approach for the amplifier. Multiple parameters of the amplifier are optimized simultaneously. Thus, a six-temperature model serves as the fitness function, and a genetic algorithm is applied to globally optimize the cavity pressure and gas pressure ratio of CO2∶N2∶He in a self-developed RF-excited fast axial CO2 laser amplifier. Furthermore, by continuously adjusting the relevant parameters of the genetic algorithm, we obtain optimized results. Finally, the feasibility of this approach is confirmed through amplification experiments performed on an experimental platform.

Results and Discussions

In this study, a six-temperature model is employed to identify the optimal operating conditions for the amplifier. Initially, a fixed V(CO2)∶V(N2)∶V(He)=5%∶25%∶70% is used to simulate the changes in the small-signal gain coefficients with the excitation electron number density under varying cavity pressures. The results indicate that the small-signal gain coefficients exhibit a pattern of increasing, stabilizing, and then gradually decreasing with increasing excitation electron number density. Different electron number densities (corresponding to the RF injection power) result in distinct optimal cavity pressures, with optima of 80 mbar (1 bar=100 kPa) and 100 mbar for a lower and higher excitation electron number density, respectively (Fig.7). Based on the simulation results, an optimal gas ratio and gas pressure are determined, considering the impact of the amplifier gas pressure and ratio on the small-signal gain and incorporating experimental data. Subsequently, the steady-state solution is used as the initial boundary condition, and a seed pulse with a pulse width of 150 ns and an average power of 110 W is injected to obtain the transient solution. This involves capturing the time-domain pulse evolution waveforms of both the seed and amplified output lasers (Fig.8). Based on the preliminary optimization results from the six-temperature model, a relatively optimal solution is obtained, resulting in an output power measurement of 2504 W under the operating conditions. As the experiment primarily considers the scenario of a 100% duty cycle for the seed, the small-signal gain coefficients derived from the steady-state solution serve as the objective function. After optimization using a genetic algorithm, the output power increases to 3422 W. The sum of the three gas pressures is 80 mbar, and the gas V(CO2)∶V(N2)∶V(He)=12.2%∶15.3%∶72.5%. Notably, the optimized He gas pressure corresponds closely with the initial value, whereas the optimized CO2 and N2 gas pressures differ from the initial values. This validates the feasibility and effectiveness of the proposed method (Table 4).

Conclusions

In this study, we optimize the gas pressure ratio and barometric pressure in an RF-excited fast axial CO2 laser amplifier by integrating a genetic algorithm with a six-temperature model. This optimization aims to achieve a higher small-signal gain, as indicated by the laser-amplified output power. In experiments injecting a 10.6 μm seed with 110 W using the gas pressure ratio optimized through the genetic algorithm, the laser amplified output power significantly increases from 2504 W in the unoptimized laser system to 3422 W. This model is valuable for enhancing the amplifier performance and offers practical guidance for designing and optimizing internally developed amplifiers. Owing to equipment constraints, the current optimization has focused on continuous seed amplification parameters, with further exploration planned for the optimal parameters in pulse amplification.

游聪, 黄维, 林高洁, 李波, 赵江, 胡友友. 基于遗传算法的快轴流CO2激光放大器的参数优化[J]. 中国激光, 2024, 51(7): 0701016. Cong You, Wei Huang, Gaojie Lin, Bo Li, Jiang Zhao, Youyou Hu. Optimization of Fast Axial Flow CO2 Laser Amplifier Parameters Based on Genetic Algorithm[J]. Chinese Journal of Lasers, 2024, 51(7): 0701016.

引用该论文: TXT   |   EndNote

相关论文

加载中...

关于本站 Cookie 的使用提示

中国光学期刊网使用基于 cookie 的技术来更好地为您提供各项服务,点击此处了解我们的隐私策略。 如您需继续使用本网站,请您授权我们使用本地 cookie 来保存部分信息。
全站搜索
您最值得信赖的光电行业旗舰网络服务平台!