二元硫属中远红外非线性光学材料构效关系研究与高通量计算设计
批准号:
22075282
项目类别:
面上项目
资助金额:
63.0 万元
负责人:
程曦月
依托单位:
学科分类:
无机功能材料化学
结题年份:
2024
批准年份:
2020
项目状态:
已结题
项目参与者:
程曦月
中文摘要
中远红外NLO晶体材料是一类不可或缺的先进激光材料,在激光通讯、光电对抗等高新领域有重要应用。相比于目前广泛研究的多元NLO材料,二元硫属化合物有着合成及晶体生长方面的独特优势,应是寻找新一代中远红外NLO材料的重要体系。该体系存在大量非心化合物,但其NLO性质缺乏系统研究,已知实用NLO材料还非常有限,迫切需要高通量计算方法的介入,加速这类复杂而特殊材料的研发。本项目拟采用第一原理计算耦合的高通量结构预测及数据挖掘方法,围绕NLO材料定量构效关系等科学问题,研究二元硫属NLO化合物原子尺度结构拓扑规律,积累非心化合物结构性能数据。补充完善NLO原子响应理论,探索NLO材料设计半经验筛选判据,揭示NLO材料物理新机制。在此基础上,发展适合二元硫属NLO材料的全链条高通量计算方法,高效设计新型高性能中远红外NLO材料,解决该类材料在结构设计中的关键问题,并为后续研究提供数据支撑和理论依据。
英文摘要
As indispensable advanced laser materials, middle and far-infrared (MFIR) nonlinear optical (NLO) materials have important applications in the high-tech fields of laser communication, photoelectric countermeasure, etc. Compared with the currently widely studied multicomponent NLO materials, the binary chalcogenides should be an important system in searching for the new generation of high performance NLO materials because of their unique advantages in the synthesis and crystal growth. There have been a large number of known noncentrosymetric phases and compounds in this system. However, the systematic researches on their NLO properties are lacking and the practically applicable NLO materials are very limited. Therefore, it is necessary to make use of the high-throughput computational methods to accelerate the research and development of such complex and important materials. By using the state-of-the-art first-principles calculations coupled with the high-throughput crystal structure prediction and data mining methods, this project focuses on the important scientific problem: the quantitative relationship between the structure and property of NLO materials, and aims to study the structural topology rules at the atomic length scale of the binary chalcogenides, and to accumulate the structure-property data of noncentrosymetric compounds. This project plans to further develop the NLO atomic response theory, to find some semi-empirical screening criteria for the design of NLO materials, and to reveal new physical mechanism of NLO materials. On the basis of theoretical research, this project intends to develop a systematic high-throughput computational method suitable for binary chalcogenide NLO materials, and to design new high performance binary chalcogenide NLO materials effectively. The goal of this project is to solve the key problems on the structural design of NLO materials, and to supply reliable data and theoretical basis for the further researches on NLO materials.
非线性光学(NLO)材料是重要的无机光电信息功能材料之一,是激光技术和现代军事技术中不可或缺的关键材料。由于当前高性能中远红外NLO材料的种类和数目还非常有限,亟需材料高通量计算方法的介入,加速这类复杂而特殊材料的研发。本项目采用第一原理计算耦合的高通量结构预测及机器学习方法,开展了二元硫属化合物体系的机器学习特征衍生工程,提取了局域结构信息和原子间的相互作用的机器学习特征集,建立了具有较好预测性能的二元硫属化合物NLO性质机器学习模型;开发完成了2套普适的NLO材料计算软件,即ARTATOP光学性质及原子响应分析软件以及HTOP非线性光学材料高通量数值计算软件包;并用于4类NLO材料体系的理论预测计算,设计出系列高性能NLO材料,包括硫属化合物(二元SnS2,四元Li2HgGeSe4和Li2HgSnSe4),金属卤化硼酸盐(Sn2B5O9I)与有机无机杂化材料(CuMoO3(p2c))。在此基础上,设计并搭建了基于MySQL的非线性光学材料基因数据库,目前该数据库包含经典或新型非线性光学材料理论计算及实验数据,化合物数量640个,存储的数据条目约55000条,为非线性光学材料机器学习+高通量计算设计提供了丰富的数据基础。相关成果发表在Angew. Chem. Int. Ed.(IF= 16.6),Research(IF= 8.5),Chem. Mater.(IF= 7.2),J. Phys. Chem. Lett.(IF= 5.3),等化学、材料领域著名SCI期刊12篇,获得软件著作权2项,申请专利2项,参加7次国际国内学术会议(特邀报告5次,分会报告2次),培养博士研究生1名,硕士生3名。
基于机器学习的红外非线性光学材料设计
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批准号:2023J01212
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项目类别:省市级项目
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资助金额:6.0万元
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批准年份:2023
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负责人:程曦月
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依托单位:
新型磷酸盐深紫外非线性光学材料的高通量计算设计
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批准号:21703251
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项目类别:青年科学基金项目
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资助金额:24.0万元
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批准年份:2017
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负责人:程曦月
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依托单位:
国内基金
海外基金