Robotics & Machine Learning Daily News2024,Issue(Nov.13) :42-43.

Hebei Normal University Reports Findings in Machine Learning (Screening of Silve r-Based Single-Atom Alloy Catalysts for NO Electroreduction to NH3 by DFT Calcul ations and Machine Learning)

河北师范大学报道机器学习的发现(DFT计算和机器学习筛选无电还原NH3的银r基单原子合金催化剂)

Robotics & Machine Learning Daily News2024,Issue(Nov.13) :42-43.

Hebei Normal University Reports Findings in Machine Learning (Screening of Silve r-Based Single-Atom Alloy Catalysts for NO Electroreduction to NH3 by DFT Calcul ations and Machine Learning)

河北师范大学报道机器学习的发现(DFT计算和机器学习筛选无电还原NH3的银r基单原子合金催化剂)

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摘要

由一名新闻记者-机器人与机器学习日报的工作人员新闻编辑每日新闻-机器学习的新研究是一篇报道的主题。据新闻报道来自中华人民共和国石家庄,由NewsRx记者报道,研究称,高活性高选择性的(NORR)无红色还原电催化剂对NO去除和NH合成都是必不可少的。由于其优异的电催化活性,单原子合金(SAA)催化剂已引起广泛关注。

Abstract

By a News Reporter-Staff News Editor at Robotics & Machine Learning DailyNews Daily News – New research on Machine Learning is th e subject of a report. According to newsoriginating from Shijiazhuang, People’s Republic of China, by NewsRx correspondents, research stated,“Exploring NO red uction reaction (NORR) electrocatalysts with high activity and selectivity towar d NHis essential for both NO removal and NH synthesis. Due to their superior el ectrocatalytic activities,single-atom alloy (SAA) catalysts have attracted cons iderable attention.”

Key words

Shijiazhuang/People’s Republic of China/Asia/Cyborgs/Emerging Technologies/Machine Learning

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出版年

2024
Robotics & Machine Learning Daily News

Robotics & Machine Learning Daily News

ISSN:
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