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From the 1 of 11 linked papers with an AI index.

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11 papers

cs.DC2026

Overcoming Orchestration Bottlenecks at Exascale: A Decentralized, Policy-Driven Approach for Sim-AI Ensembles

Harikrishna Tummalapalli, Christine M. Simpson, Riccardo Balin +4

The paper presents EnsembleLauncher, a decentralized, hierarchical workflow orchestrator that scales to exascale systems and allows programmable scheduling policies to improve reso…

cond-mat.mtrl-sci2026

ChemGraph-XANES: An Agentic Framework for XANES Simulation and Curation

Vitor F. Grizzi, Thang Duc Pham, Luke N. Pretzie +3

Computational X-ray absorption near-edge structure (XANES) is widely used to interpret local coordination environments, oxidation states, and electronic structure, but large comput…

cond-mat.mtrl-sci2026

From Knowledge to Action: Outcomes of the 2025 Large Language Model (LLM) Hackathon for Applications in Materials Science and Chemistry

Aritra Roy, Kevin Shen, Andrew MacBride +350

Large language models (LLMs) are rapidly changing how researchers in materials science and chemistry discover, organize, and act on scientific knowledge. This paper analyzes a broa…

cs.AI2026

Multi-Agent Orchestration for High-Throughput Materials Screening on a Leadership-Class System

Thang Duc Pham, Harikrishna Tummalapalli, Fakhrul Hasan Bhuiyan +5

The integration of Artificial Intelligence (AI) with High-Performance Computing (HPC) is transforming scientific workflows from human-directed pipelines into adaptive systems capab…

cond-mat.mtrl-sci2026

From Atomistic Models to Machine Learning: Predictive Design of Nanocarbons under Extreme Conditions

Xiaoli Yan, Millicent A. Firestone, Murat Keceli +2

The formation of technologically valuable nanocarbon structures under extreme conditions, such as those produced during high-explosive detonations, remains poorly understood but ho…

cs.AI2026

An Agentic Evaluation Framework for AI-Generated Scientific Code in PETSc

Hong Zhang, Barry Smith, Satish Balay +4

While large language models have significantly accelerated scientific code generation, comprehensively evaluating the generated code remains a major challenge. Traditional benchmar…