Knowledge graph representation of zeolitic crystalline materials†

IF 6.2 Q1 CHEMISTRY, MULTIDISCIPLINARY
Aleksandar Kondinski, Pavlo Rutkevych, Laura Pascazio, Dan N. Tran, Feroz Farazi, Srishti Ganguly and Markus Kraft
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引用次数: 0

Abstract

Zeolites are complex and porous crystalline inorganic materials that serve as hosts for a variety of molecular, ionic and cluster species. Formal, machine-actionable representation of this chemistry presents a challenge as a variety of concepts need to be semantically interlinked. This work demonstrates the potential of knowledge engineering in overcoming this challenge. We develop ontologies OntoCrystal and OntoZeolite, enabling the representation and instantiation of crystalline zeolite information into a dynamic, interoperable knowledge graph called The World Avatar (TWA). In TWA, crystalline zeolite instances are semantically interconnected with chemical species that act as guests in these materials. Information can be obtained via custom or templated SPARQL queries administered through a user-friendly web interface. Unstructured exploration is facilitated through natural language processing using the Marie System, showcasing promise for the blended large language model – knowledge graph approach in providing accurate responses on zeolite chemistry in natural language.

Abstract Image

沸石晶体材料的知识图谱表示法
沸石是一种复杂多孔的结晶无机材料,可作为各种分子、离子和团簇物种的宿主。由于各种概念需要在语义上相互关联,因此对这种化学性质进行正式的、机器可操作的表述是一项挑战。这项工作展示了知识工程在克服这一挑战方面的潜力。我们开发了本体论 OntoCrystal 和 OntoZeolite,使结晶沸石信息的表示和实例化成为一个动态、可互操作的知识图谱,称为 "世界阿凡达"(TWA)。在 TWA 中,结晶沸石实例与作为这些材料客体的化学物种在语义上相互关联。可通过用户友好的网络界面管理自定义或模板 SPARQL 查询来获取信息。通过使用玛丽系统进行自然语言处理,可以方便地进行非结构化探索,从而展示了混合大型语言模型-知识图谱方法在用自然语言提供沸石化学准确回复方面的前景。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
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来源期刊
CiteScore
2.80
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0.00%
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