贝尔格莱德碰撞和辐射数据库/对分子动力学重要数据集的当前阶段和未来发展
Veljko Vujčić1, Bratislav P Marinković2, Vladimir A Srećković2
1Astronomical Observatory Belgrade, Volgina 7, 11000 Belgrade, Serbia. veljko@aob.rs.
Physical chemistry chemical physics : PCCP
|October 4, 2023
概括
准确的原子和分子 (A&M) 数据库对于科学建模至关重要. 这项研究介绍了精选的A&M数据集,并探索了用于预测光学属性的机器学习,从而提高数据可靠性.
科学领域:
- 原子和分子物理 原子和分子物理
- 计算化学计算化学
- 等离子体物理学的物理学
背景情况:
- 原子和分子 (A&M) 数据库是物理学,化学和化学/物理信息学的重要工具.
- 在A&M数据库中的数据不准确可能导致预测和建模中的重大错误.
- 严格的数据策划对于保持A&M数据集的完整性至关重要.
研究的目的:
- 介绍研究活动的重点是精选的贝尔格莱德"节点"数据集用于光谱分析.
- 解释创建和使用这些A&M数据集的方法.
- 探索扩展这些数据集用于使用机器学习进行Judd-Ofelt参数预测.
主要方法:
- 开发和管理A&M数据集,包括碰撞/辐射截面和速率.
- 这些数据集在各种物理领域的光谱分析中的应用.
- 研究用于预测Judd-Ofelt参数和光学属性的机器学习技术.
主要成果:
- 建立并策划的贝尔格莱德"节点"数据集用于A&M光谱.
- 证明了数据应用和分析的方法.
- 探索机器学习在扩展数据库功能以预测光学属性的潜力.
结论:
- 策划的贝尔格莱德"节点"数据集是光谱学和A&M研究的宝贵资源.
- 机器学习为扩展A&M数据库和预测材料光学特性提供了一个有前途的途径.
- 这些数据集和可视化的公共可用性旨在鼓励进一步的研究和数据利用.
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