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End Point Prediction: Gran Plot01:07

End Point Prediction: Gran Plot

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A Gran plot is used to predict the equivalence volume or endpoint of a potentiometric or acid-base titration without reaching the endpoint. Typically, titration data is collected as a function of the titrant's volume up to a point less than the equivalence volume and then transformed into a linear format. The straight line is extended to the x-axis, indicating the necessary titrant volume to achieve the equivalence point.
For potentiometric titration, the Gran plot is created by plotting...
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MXgap:用于带隙预测的MXene学习工具

Diego Ontiveros1, Sergi Vela2, Francesc Viñes1

  • 1Departament de Ciència de Materials i Química Física & Institut de Química Teòrica i Computacional (IQTCUB), Universitat de Barcelona, c/Martí i Franquès 1-11, 08028 Barcelona, Spain.

ACS catalysis
|August 21, 2025
PubMed
概括

机器学习加速了MXenes的发现, 一个新的Python包,MXgap,有效地预测了MXene带隙,用于增强光催化和水分裂应用.

科学领域:

  • 材料科学
  • 可再生能源
  • 计算化学

背景情况:

  • 越来越多的清洁能源需求推动了对先进的光催化材料的研究.
  • MXenes (二维过渡金属碳化物/化物) 在水分解方面具有前景.
  • 预测MXene带隙对于光催化非常重要,

研究的目的:

  • 开发一个机器学习 (ML) 框架,用于高效的MXene带隙预测.
  • 加速发现和优化MXenes用于光催化应用.
  • 为了选基于La的MXenes的水分合适性.

主要方法:

  • 在4356个MXene结构的数据集上训练了多个ML模型.
  • 开发了一个强大的分类器-回归管道用于带隙预测.
  • 在一个开源的Python包 (MXgap) 中实现框架.

主要成果:

  • 实现了92%的分类准确度和0.17 eV的MAE频段间隙预测.
  • 选了396种基于La的MXenes,确定了6种有前途的候选物.
  • 对选定的候选物质进行评估的光学性能和太阳能效率.
关键词:
其他类型密度函数理论机器学习光催化水分离

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结论:

  • ML显著加速了MXene材料的能源应用.
  • MXgap套件为MXenes的高通量选提供了一个有价值的工具.
  • 确定了有前途的MXene候选物,用于高效的光催化水分解.