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机器学习辅助的高通量选用于电催化进化反应

Guohao Yin1, Haiyan Zhu1,2, Shanlin Chen1,2

  • 1Shaanxi Key Laboratory for Theoretical Physics Frontiers, Institute of Modern Physics, Northwest University, Xi'an 710069, China.

Molecules (Basel, Switzerland)
|February 26, 2025
PubMed
概括

机器学习和高通量计算加速了高效演变反应 (HER) 电催化剂的发现. 这种方法有助于通过优化催化剂性能来开发可持续的能解决方案.

关键词:
密度函数理论密度函数理论高吞吐量选的高吞吐量选气演化反应反应的反应机器学习是机器学习.

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Bioreactor Controls-II01:18

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In aerobic fermentations, oxygen is vital for microbial growth and metabolite production. Since air comprises only about 20% oxygen and the gas is poorly soluble in water—just 9 ppm at 20°C—supplying sufficient oxygen becomes a critical challenge, especially in high-demand processes like yeast growth or citric acid production. Even a fully saturated broth may offer only a few seconds of oxygen availability.To address this, sterile or scrubbed air is introduced into the fermentor via a sparger...