mlsanityData to 7 Oct 2026

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

arXiv 2605.13618 ↗First posted 13 May 2026cond-mat.mtrl-sci cs.AIcited by 0

On the map: LLM agents and tool use → Medical and scientific domain agents

Abstract (arXiv)

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.

Key facts. No citing papers in the map yet (data through 7 Oct 2026). Placed in Medical and scientific domain agents, one of 16 directions in LLM agents and tool use. Builds on 16 of its 47 references that are in the map. First posted on arXiv 13 May 2026.

Builds on

16 of 47 references.

Closest ancestors · 2

Same direction, newest first

  1. 2026MatClaw: An Autonomous Code-First LLM Agent for End-to-End Materials Exploration3 Apr
  2. 2025DREAMS: Density Functional Theory Based Research Engine for Agentic Materials Simulation18 Jul

Other references · 14

  1. 2020Language Models are Few-Shot Learnerscited by 32,199
  2. 2023GPT-4 Technical Reportcited by 18,132
  3. 2022Training language models to follow instructions with human feedbackcited by 15,712
  4. 2020Retrieval-Augmented Generation for Knowledge-Intensive NLP Taskscited by 9,160
  5. 2022Emergent Abilities of Large Language Modelscited by 2,483
  6. 2023AutoGen: Enabling Next-Gen LLM Applications via Multi-Agent Conversationcited by 1,906
  7. 2023MetaGPT: Meta Programming for A Multi-Agent Collaborative Frameworkcited by 1,761
  8. 2023CAMEL: Communicative Agents for "Mind" Exploration of Large Language Model Societycited by 1,348
  9. 2020Leveraging Passage Retrieval with Generative Models for Open Domain Question Answeringcited by 1,203
  10. 2024The AI Scientist: Towards Fully Automated Open-Ended Scientific Discoverycited by 1,002
  11. 2025Towards Scientific Intelligence: A Survey of LLM-based Scientific Agentscited by 96
  12. 2024SciAgents: Automating scientific discovery through multi-agent intelligent graph reasoningcited by 90
2 more
  1. 2026InternAgent-1.5: A Unified Agentic Framework for Long-Horizon Autonomous Scientific Discoverycited by 24
  2. 2025Agent-as-a-Service based on Agent Networkcited by 3

Built on by

Not cited yet.

Similar, not cited

Close in wording, no citation either way

  1. 2026Towards Agentic Intelligence for Materials Science
  2. 2025Large language models in materials science and the need for open-source approaches
  3. 2025AGAPI-Agents: An Open-Access Agentic AI Platform for Accelerated Materials Design on AtomGPT.org
  4. 2024HoneyComb: A Flexible LLM-Based Agent System for Materials Science
  5. 2026ALKEMIE Agent: an autonomous platform for computational materials design
  6. 2025PriM: Principle-Inspired Material Discovery through Multi-Agent Collaboration
  7. 2025Hierarchical Multi-agent Large Language Model Reasoning for Autonomous Functional Materials Discovery
  8. 2026A collaborative agent with two lightweight synergistic models for autonomous crystal materials research