Year: 2025
Type: article
Abstract: Accelerating materials discovery and optimization is crucial for transitioning to sustainable energy conversion and storage.In this regard, materials acceleration platforms (MAPs) can significantly shorten the discovery process, cutting material and labor costs (Aspuru-Guzik & Persson, 2018).Combinatorial and high-throughput methods are instrumental in developing said MAPs, enabling autonomous operation and the generation of large datasets (Maier et al., 2007).Therefore, in a previous work, we developed combinatorial deposition and analysis techniques for the discovery of new semiconductor materials (Wolf et al., 2023).To drive further innovation in the field, COHESIVM was created, which facilitates combinatorial analysis of material and device properties through the following key features:• A generalized workflow reduces redundancy and ensures consistency across different experimental setups.• The modular design abstracts devices, contact interfaces, and measurement routines into interchangeable units.• Efficient data handling is achieved through robust metadata collection and well-structured storage.
DOI: 10.21105/joss.07291
Institutions: AIT Austrian Institute of Technology GmbH, TU Wien
Language: English
Subfield: Materials Chemistry
Field: Materials Science
Domain: Physical Sciences
Open Access status: diamond
OpenAlex ID: W4407162939