Abstract
Using generative Artificial Intelligence (AI), we transformed a set of 1,000 scientific papers in the area of biological materials into detailed ontological knowledge graphs, revealing their inherently scale-free nature. Using graph traversal path detection between dissimilar concepts based on combinatorial ranking of node similarity and betweenness centrality, we reveal deep insights into unprecedented interdisciplinary relationships that can be used to answer queries, identify gaps in knowledge, and propose never-before-seen material designs and their behaviors. One comparison revealed detailed structural parallels between biological materials and Beethoven's 9th Symphony, highlighting shared patterns of complexity through isomorphic mapping. The algorithm further created an innovative hierarchical mycelium-based composite that incorporates joint synthesis of graph sampling with principles extracted from Kandinsky's Composition VII painting, where the resulting composite reflects a balance of chaos and order, with features like adjustable porosity, mechanical strength, and complex patterned chemical functionalization. We uncover other isomorphisms across physical, biological, and artistic spheres, revealing a nuanced ontology of immanence and material flux that resonates with postmodern philosophy, and positions these interconnections within a heterarchical framework. Our findings reveal the dynamic, context-dependent interplay of entities beyond traditional hierarchical paradigms, emphasizing the significant role of individual components and their fluctuative relationships within the system. Our predictions achieve a far higher degree of novelty, technical detail and explorative capacity than conventional generative AI methods. The approach establishes a widely useful framework for innovation by revealing hidden connections that facilitate discovery.
Abstract (translated)
使用生成人工智能 (AI)，我们将1,000篇生物材料领域的科学论文转换为详细的概念知识图，揭示了它们固有的无尺度特性。通过基于节点相似度和连通性排名的组合排名在相似概念之间进行图遍历路径检测，我们揭示了前所未有的跨学科关系，这些关系可以用于回答问题、发现知识空白和提出新颖的物质设计和它们的特性。一个比较揭示了生物材料与贝多芬第九交响曲之间的详细结构相似性，通过同构映射揭示了共享的复杂性模式。该算法还创新性地制备了一种基于菌丝的复合材料，将图采样与Kandinsky的《构图 VII》中提取的原则相结合，形成了一个平衡熵和秩序的复合物，具有可调节的孔隙率、机械强度和复杂图案化学功能性。我们在物理、生物和艺术领域发现了其他同构体，揭示了物质存在的隐含维度和物质流动的细微差别，与后现代哲学产生共鸣，并将其置于分层框架中。我们的研究结果揭示了超越传统等级范式的实体之间的动态、上下文相关的相互作用，强调了个体组件及其在系统中的波动关系的重要性。我们的预测实现了与传统生成人工智能方法远更高的新颖性、技术细节和探索能力。该方法为创新建立了广泛的有用框架，通过揭示隐藏的连接促进了发现。
URL
https://arxiv.org/abs/2403.11996
