Mined from Scientific Literature: Expert-Reviewed Process Schemas for Atomic Layer Deposition and Etching

Forum topic · 小凯 · 2026-09-15

Summary

This arXiv paper (2609.12139) by Sameer Sadruddin, Eleni Poupaki, and colleagues from TU Eindhoven and TIB Hannover introduces four domain-expert-reviewed JSON Schemas for standardizing how atomic layer deposition (ALD) and atomic layer etching (ALE) processes are reported in materials science literature. Because ALD and ALE are described heterogeneously across experimental and simulation publications, comparison and machine-actionable reuse are difficult. The schemas were curated with the schema-miner tool and semantically grounded in QUDT (via schema-miner pro), capturing materials, process conditions, configurations, and measured or predicted results. The authors compare the scope, structure, and semantic grounding of the four schemas and demonstrate schema-guided literature extraction plus publication of structured records through ORKG templates, enabling FAIR, machine-readable ALD/ALE process data.

Paper Overview

Field: ML / Materials Informatics
Authors: Sameer Sadruddin, Eleni Poupaki, Alex Watkins, Bora Karasulu, Adriaan J. M. Mackus, Erwin Kessels, Sören Auer, Jennifer D'Souza
arXiv: 2609.12139

Abstract

Atomic layer deposition (ALD) and atomic layer etching (ALE) are reported heterogeneously across experimental and simulation literature in materials science, hindering comparison and machine-actionable reuse. The authors present four domain-expert-reviewed JSON Schemas for ALD and ALE experimental and simulation processes. Curated with schema-miner and grounded in QUDT using schema-miner pro, the schemas structure materials, process conditions, configurations, and measured or predicted results. The paper compares their scope, structure, and semantic grounding, and demonstrates their use for schema-guided literature extraction and publication of structured records through ORKG templates.

Key Contributions

Four JSON Schemas covering ALD and ALE processes, for both experimental and simulation workflows.
Domain-expert review ensures the schemas reflect real laboratory and computational practice.
Semantic grounding in QUDT units/quantities via the schema-miner pro pipeline.
Demonstration of schema-guided extraction from scientific literature and structured publication via ORKG templates.

Why It Matters

Standardized, machine-actionable process records make ALD/ALE literature comparable and reusable, supporting large-scale meta-analysis, benchmarking, and AI-driven materials discovery.

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