Robotics & Machine Learning Daily News2024,Issue(Dec.2) :28-29.

Report Summarizes Machine Learning Study Findings from Beijing Jiaotong Universi ty (Machine Learning-driven Precise Design of Stable Oled Materials: Predicting and Enhancing Multi-state C-n Bond Dissociation Energies)

报告总结了北京交通大学的机器学习研究结果(机器学习驱动的稳定Oled材料精确设计:预测和增强多态c-n键离解能)

Robotics & Machine Learning Daily News2024,Issue(Dec.2) :28-29.

Report Summarizes Machine Learning Study Findings from Beijing Jiaotong Universi ty (Machine Learning-driven Precise Design of Stable Oled Materials: Predicting and Enhancing Multi-state C-n Bond Dissociation Energies)

报告总结了北京交通大学的机器学习研究结果(机器学习驱动的稳定Oled材料精确设计:预测和增强多态c-n键离解能)

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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-机器学习的研究结果在一份新的报告中讨论。根据NewsRx记者的新闻报道,研究“有机发光二极管(OLED)材料的本征稳定性关键取决于键离解能(BDEs)脆弱键,特别是c-n键。尽管有必要考虑有机材料复杂工作条件下多重电子状态下的BDEs在OLED器件中,全面的探索仍然具有挑战性。

Abstract

By a News Reporter-Staff News Editor at Robotics & Machine Learning DailyNews Daily News - Research findings on Machine Learning are discussed in a new report. According tonews reporting originating from Beij ing, People’s Republic of China, by NewsRx correspondents, researchstated, “The intrinsic stability of organic light-emitting diode (OLED) materials critically hinges on thebond dissociation energies (BDEs) of fragile bonds, particularly C-N bonds. Despite the necessity ofconsidering BDEs in multiple electronic stat es due to the complex working conditions of organic materialsin OLED devices, c omprehensive exploration remains challenging.”

Key words

Beijing/People’s Republic of China/Asi a/Cyborgs/Emerging Technologies/Machine Learning/Beijing Jiaotong University

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出版年

2024
Robotics & Machine Learning Daily News

Robotics & Machine Learning Daily News

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