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[Example] Add TADF材料分子的光电性质预测 #974

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@YfB1125 YfB1125 commented Aug 17, 2024

TADF材料分子的光电性质预测

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有机发光二极管(OLED)具有高效率、结构灵活和低成本的优势,在先进显示和照明技术中受到广泛关注。在有机发光二极管器件中,电注入载流子以1:3的比例形成单线态和三线态激子。以纯荧光材料为发光材料构建的OLED发光效率IQE理论极限为25%。另一方面,有机金属复合物发光材料通过引入稀有金属(Ir,Pt等)带来强自旋轨道耦合(SOC),可以将单线态激子通过系间窜越过程转化成三线态激子,从而利用三线态激子发出磷光,其IQE可达100%,但是稀有金属价格昂贵,为推广使用带来了阻碍。热活化延迟荧光材料(TADF)为解决这些问题提供了新思路,并引起了广泛关注。在TADF中,三线态通过逆系间窜越过程(RISC)转化成单重态并发出荧光,从而实现100%的IQE,而RISC过程很大程度上取决于最低单线态(S1)和最低三线态(T1) 之间的能隙(ΔEST)。根据量子力学理论,ΔEST相当于HOMO和LUMO之间的交换积分的两倍。因此TADF分子的常见设计策略是将电子供体(D)和电子受体(A)以明显扭曲的二面角结合以实现HOMO和LUMO在空间上明显的分离。然而,与ΔEST相反,振子强度(f)需要较大的HOMO和LUMO之间的重叠积分,这二者之间的矛盾需要进一步平衡。

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paddle-bot bot commented Aug 17, 2024

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@luotao1 luotao1 self-assigned this Aug 19, 2024
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HydrogenSulfate commented Aug 21, 2024

请起一个合适的标题 @YfB1125 ,并补充一下PR的简单描述
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HydrogenSulfate commented Aug 21, 2024

commit代码之前请安装pre-commit,并且使用pre-commit格式化代码,否则code-style-check CI无法通过

  1. https://paddlescience-docs.readthedocs.io/zh-cn/latest/zh/development/#1
  2. https://paddlescience-docs.readthedocs.io/zh-cn/latest/zh/development/#4

@HydrogenSulfate HydrogenSulfate changed the title Dev model [Example] Add TADF材料分子的光电性质预测 Aug 26, 2024
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leeleolay commented Aug 26, 2024

辛苦按照paddlescience代码规范提交代码@YfB1125 可参考其他PR:#964 , #962
建议写一个文档说明该项目

@YfB1125 YfB1125 closed this Aug 26, 2024
@YfB1125 YfB1125 deleted the dev_model branch August 26, 2024 09:21
@YfB1125 YfB1125 reopened this Aug 26, 2024
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YfB1125 commented Jun 10, 2025

image

已经修改,辛苦您再看看

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请参考建议修改代码细节


``` sh
#Est 预测:
cd TADF_angle
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这里写错文件名了

cd TADF_angle
python angle.py
cd ../
```
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评估命令应指明预训练模型权重路径,可参考其他案例格式

eval_during_train: False #
batch_size: 8 #
learning_rate: 0.0001
save_model_path: './est_model.pth'
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pth是torch的模型名,建议修改为paddle格式

!!! note

1. 开始训练、评估前,请先确保性质数据文件(.dat)和SMILES(smis.txt)数据文件的存在,并对应修改 yaml 配置文件中的 `data_dir` 为性质数据文件路径,`sim_dir` 为SMILES数据文件路径。
2. 如果需要使用预训练模型进行评估,请先下载预训练模型[Est.pdparams](https://paddle-org.bj.bcebos.com/paddlescience/models/TADF/Est/Est_pretrained.pdparams), [f.pdparams](https://paddle-org.bj.bcebos.com/paddlescience/models/TADF/f/f_pretrained.pdparams), 并对应修改 yaml 配置文件中的 `load_model_path` 为模型参数路径。
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这里少了angle

eval_during_train: False #
batch_size: 8 #
learning_rate: 0.01
save_model_path: './angle_model.pdparams'
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默认的路径和train默认的模型名不一致

# evaluation settings
EVAL:
test_size: 0.1
load_model_path: './f_pretrained.pdparams'
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建议和train保存的模型名一致

#Est 评估:
cd TADF_angle
python Est.py
cd ../
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cd 这个命令可能没必要 有点冗余

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YfB1125 commented Jun 30, 2025

已对文档和配置文件进行修改。请协助修改预训练模型参数的文件名,以保持训练和评估的模型参数文件名一致。我希望下载修改后模型文件的文件名为
https://paddle-org.bj.bcebos.com/paddlescience/models/TADF/Est/Est_model.pdparams
https://paddle-org.bj.bcebos.com/paddlescience/models/TADF/f/f_model.pdparams
https://paddle-org.bj.bcebos.com/paddlescience/models/TADF/angle/angle_model.pdparams

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预训练模型权重路径已修改,其他请参考review意见

test_size: 0.1
load_model_path: './angle_model.pdparams'
seed: 20
pretrained_model_path: null
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请检查三个yaml文件的运行脚本命令和该行字段,包括”EVAL“

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三个yaml文件中与读取、保存模型参数的字段均已修改

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文档(.md)也已经修改

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image 修改完的代码辛苦运行测试下

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