The plant phenotyping workflow of the Orchestrated Platform for Autonomous Laboratories is explored, which couples Oak Ridge National Laboratory's Advanced Plant Phenotyping Laboratory with the Frontier supercomputer and replaces roughly twelve hours of manual analysis with interactive queries returning in seconds to minutes.
Abstract
Autonomous, cross-facility science requires capabilities that no individual project should have to build for itself: managed execution for long-lived services, versioned distribution of models to remote compute systems, governed access to large language models, a shared substrate for experimental data, and end-to-end provenance. The U.S. Department of Energy Genesis Mission platform, delivered through the American Science Cloud, provides these as reusable services. This paper reports how the Genesis platform enables cross-facility experiments and accelerates scientific discovery. We explore the plant phenotyping workflow of the Orchestrated Platform for Autonomous Laboratories as the exemplar: it couples Oak Ridge National Laboratory's Advanced Plant Phenotyping Laboratory with the Frontier supercomputer. In a 40-day nickel-treatment campaign, the resulting workflow replaced roughly twelve hours of manual analysis with interactive queries returning in seconds to minutes.
AI co-scientists could accelerate computational research, but over a long-running study the workflow also has to stay inspectable, resumable and reproducible, which requires persistent computational state and provenance. Here we present OpenAI4S, an open-source scientific research agent built around the principle of \e...
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HPC-AutoResearch is presented, a proof-of-concept system for the autonomous execution of compiled-code research workflows in HPC-like environments that divides this sub-pipeline into five phases—planning, environment setup, coding, compilation, and execution—localizing failures within each phase and enabling iterative...
T. Kotama, Shun-ichiro Hayashi, Daichi Mukunoki et al.· 0 citations
HEPToolBench is introduced, a benchmark of 28 collider-simulation tasks scored by deterministic, task-specific scorers, plus a three-task structured-debugging extension, and moving syntax generation into deterministic software can substantially improve reliability for both small local and frontier models.
High-throughput and autonomous experimentation generate complex, heterogeneous datasets whose reuse, large-scale analysis, and linking to data from first-principles calculations remain challenging. Here, we report on an operational deployment of the open-source NOMAD Oasis data infrastructure as a digital backbone for...
Lena A. Mittmann, Hampus Nässtrom, Eugène Bertin et al.· Faraday discussions· 0 citations
We present an extension and comprehensive real-world validation of Co-Scientist, a Gemini-based multi-agent system designed to accelerate end-to-end scientific research across hypothesis generation, experimentation, and manuscript generation. Moving beyond in silico hypothesis generation, this specialized configuration...
S. Schmidgall, Xiao-Kai Zhu, Marian Shaw et al.· 1 citation
The integration combines DAGonStar’s orchestration capabilities with CAPIO’s efficient data handling to better support workflows operating on continuous or large-scale datasets and improves the responsiveness and flexibility of scientific workflows.
Simone Perrotta, G. de Vita, Gennaro Mellone et al.· 0 citations