arXiv:2605.13618cond-mat.mtrl-scics.AI2026-05被引 1

构建分布式材料智能研究框架,让多机构协作不泄露数据。

OpenAaaS: An Open Agent-as-a-Service Framework for Distributed Materials-Informatics Research

论文配图:OpenAaaS: An Open Agent-as-a-Service Framework for Distributed Materials-Informatics Research
图 1 · 摘自论文原文
  • 以代码流动、数据不动为原则,实现跨机构安全协作。
  • 实测文献分析任务准确率达4.66/5.0,远超传统RAG方法。
  • 适合需数据主权的高价值材料研发团队使用。

材料基因计划推动了SaaS、PaaS和IaaS等中心化平台的发展,整合计算与实验资源以加速材料发现。与此同时,大语言模型和自主代理在科学推理方面取得突破。然而,仍存在关键的“最后一公里”问题:尽管拥有顶尖模型和海量材料数据,却缺乏跨机构安全集成的组织基础设施。针对严苛服役环境下的结构与功能材料(如高温合金、抗辐射钢、耐腐蚀涂层)研发,其长期迭代、机制复杂、领域专家依赖性强,远超单一代理系统与传统中心化平台能力。为此,本文提出OpenAaaS——一个开源的分层分布式代理即服务框架,支持智能材料设计中的多代理协同。核心理念为“代码流动,数据不动”:主代理规划任务但无需访问子代理的数据与资源;子代理作为近数据执行节点,保有本地数据、专有算法与硬件的完全主权。该架构确保原始数据不离开所属域,同时实现跨尺度、跨领域的安全融合。通过两个案例验证:(i) AlphaAgent 文献分析器在深度问答上达到4.66/5.0,优于单次检索增强生成基线;(ii) 超大规模六元高熵合金描述符数据库服务,在严格数据主权约束下完成近数据执行与领域特定科学工作流。OpenAaaS为代理集体实现“有序科研”提供可扩展路径,是下一代材料智能设计平台的基础。源码见 https://github.com/Wolido/OpenAaaS。

原文摘要 · Abstract (English)

The Materials Genome Initiative catalyzed the proliferation of centralized platforms--SaaS, PaaS, and IaaS--that aggregate computational and experimental resources for accelerated materials discovery. In parallel, breakthroughs in large language models (LLMs) and autonomous agents have created powerful new reasoning capabilities for scientific research. Yet a critical "last mile" problem remains: while we possess world-class models and vast repositories of materials data, we lack the organizational infrastructure to compose these capabilities securely across institutional boundaries. The development of structural and functional materials for harsh service environments--high-temperature alloys, radiation resistant steels, corrosion-resistant coatings--remains characterized by long-term iteration, mechanistic complexity, and high domain expertise--demands that exceed both monolithic agent systems and traditional centralized platforms. To address this gap we propose OpenAaaS, an open-source hierarchical and distributed Agent-as-a-Service framework that enables organized multi-agent collaboration for intelligent materials design. OpenAaaS is built on a single foundational principle: code flows, data stays still. A Master Agent plans and decomposes complex research tasks without requiring direct access to subordinate agents' managed data and computational resources. Sub-agents, deployed as near-data execution nodes, retain full sovereignty over local datasets, proprietary algorithms, and specialized hardware. This architecture guarantees that raw data never leaves its domain of origin while enabling cross-scale, cross-domain secure integration of previously isolated materials intelligence silos. We validate the framework through two representative case studies: (i) AlphaAgent, an evidence-grounded materials literature analysis executor that achieves 4.66/5.0 on deep analytical questions against single-pass RAG baselines; and (ii) an ultra-large-scale hexa-high-entropy alloy descriptor database service that demonstrates secure near-data execution and domain-specific scientific workflows under strict data-sovereignty constraints. OpenAaaS establishes a principled pathway toward "organized research" via agent collectives, offering a scalable foundation for next-generation materials intelligent design platforms. All source code is available at https://github.com/Wolido/OpenAaaS.

材料智能多代理系统数据主权联邦学习

Thank you to arXiv for use of its open access interoperability. PaperDance 不是 arXiv 官方产品;中文卡片由大模型生成,请以原文为准。