abstract
- This data repository contains the extracted JSON schemas for Atomic Layer Deposition (ALD) and Atomic Layer Etching (ALE) processes, extracted using the Schema-Miner tool. The schemas are categorized under two distinct use cases: experimental and simulation, to reflect the differing perspectives in ALD/E process modeling. Each schema captures essential process properties, along with their respective constraints, data types, and other structural details necessary for standardized representation and interoperability. The schema extraction was conducted from a curated set of scientific publications related to ALD/E, leveraging large language models (LLMs) in combination with domain-expert insights to ensure both accuracy and relevance. The complete methodology is described in our paper “LLMs4SchemaDiscovery: A Human-in-the-Loop Workflow for Scientific Schema Mining with Large Language Models,” presented at ESWC Conference 2025. Read the paper here. The Schema-Miner tool is publicly available on GitHub: Access the repository. The extracted schemas have also been uploaded as templates to the Open Research Knowledge Graph (ORKG), and can be accessed via the following links: Atomic Layer Deposition: Experimental Schema: https://orkg.org/templates/R1434174 Simulation Schema: https://orkg.org/templates/R1368294 Atomic Layer Etching Experimental Schema: https://orkg.org/templates/R1379646 Simulation Schema: https://orkg.org/templates/R1434008 What is New in Version 3? This version introduces significant improvements only to the ALD Experimental schema, while other schemas remain unchanged from Version 2. The following updates have been made: The schema now models ALD processes involving binary, ternary, or quaternary compounds, enhancing its applicability to complex material systems. Processes utilizing supercycle-based ALD, such as those for IGZO (Indium Gallium Zinc Oxide), are now explicitly supported through extended schema structures. The growthPerCycle property now includes growth values for each constituent compound within a super cycle, number of cycles per compound, total film thickness. Flow rates of individual reactants are now captured as explicit process parameters. Each property under material properties is now annotated with its corresponding characterization method, which shows the technique used to compute the corresponding property value. A new device properties section has been added to capture Thin-Film Transistor (TFT) performance metrics, including field effect mobility, threshold voltage, subthreshold swing and onOffRatio.