Data-Driven Catalyst Design: A Machine Learning Approach to Predicting Electrocatalytic Performance in Hydrogen Evolution and Oxygen Evolution Reactions

Documenti analoghi

• Unlocking Thermoelectric Potential: A Machine Learning Stacking Approach for Half Heusler Alloys
  di: E, Vipin K., et al.
  Pubblicazione: (2024)
• Advancements in Tuning Thermoelectric Properties: Insights from Hybrid Functional Studies, Strain Engineering, and Machine Learning Models
  di: E, Vipin K, et al.
  Pubblicazione: (2024)
• Assessment of Thermoelectric Properties of Bi2Se3: Insights from Hybrid Functional Studies, Strain Engineering, and Machine Learning Methodology
  di: Vipin Kurian Elavunkel, et al.
  Pubblicazione: (2024)
• Anomalous Enhancement of the Electrocatalytic Hydrogen Evolution Reaction in AuPt Nanoclusters
  di: Kang, Jiahui, et al.
  Pubblicazione: (2024)
• Evaluating ChatGPT's Performance in Classifying Pneumonia from Chest X-Ray Images
  di: Prahallad, Pragna, et al.
  Pubblicazione: (2025)