化工学报 ›› 2020, Vol. 71 ›› Issue (S1): 282-292.doi: 10.11949/0438-1157.20190795
毛海涛1(),王璐1,许志颖2,解万翠2,都健1,张磊1(
)
Haitao MAO1(),Lu WANG1,Zhiying XU2,Wancui XIE2,Jian DU1,Lei ZHANG1(
)
摘要:
由于混合物性能的可调控性,当前市场对其关注与日俱增。对于这类产品,基于模型的设计方法由于具有高效性以及普适性,相较于其他产品设计方法得到了更快的发展。但是对于很多性质,如气味、颜色等,准确且普适的模型尚不可得。因此,本文提出了一种基于分子表面电荷密度分布描述符(S描述符)和机器学习模型的混合物设计方法,采用描述符表征产品、再通过机器学习模型将其与性质关联,直接用于混合物产品设计。具体地,根据给定的产品性质需求,机器学习模型直接预测/设计混合物产品的S描述符;然后以欧几里德距离为指标,在给定的数据库中筛选出S描述符满足要求的候选混合物组成。最后,对候选混合物及其组分性质进行实验验证,完成设计。本文以香精的混合替代物设计作为算例,设计得到丙酸叶醇酯的两种混合香精替代物,通过实验对混合物进行了验证。结果表明,混合替代物的气味及其组分的各理化性质均与丙酸叶醇酯相近,证实本文所提出方法的有效性。
中图分类号:
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