Automated Data Analysis
NREL has developed both local and network-based analysis capabilities to more efficiently turn data from high-throughput experiments into useful materials knowledge.
Data generated during combinatorial depositions and subsequent spatially resolved characterization of combinatorial libraries is of tremendous value.
Significant investments have been made to support the navigation of this data stream by researchers, they include:
- Local computer analysis – custom software package COMBIgor installed on user computers implemented in Igor-PRO, which offers project level management and analysis of data from combinatorial experiments.
- Network accessible database – interactive visualization of deposition and characterization data from combinatorial experiments in High-Throughput Experimental Materials Database (HTEM-DB)
- Research data Infrastructure – automated data harvesting, processing and alignment of deposition and characterization data from combinatorial experiments.
COMBIgor
COMBIgor is an open-source software package written in the Igor-PRO environment and designed to offer a systematic approach to loading, storing, processing, and visualizing combinatorial data. Some features include:
- Methods for loading and storing data sets from combinatorial libraries
- Data-analysis routines for simplified processing across libraries of data
- Advanced visualization routines to construct informative figures
- Extensive documentation and example code for easy user customization.
COMBIgor is designed to be easily customized for integration with additional instruments and data processing algorithms.
For more information, read COMBIgor: Data Analysis Package for Combinatorial Materials Science, ACS Comb. Sci. (2019).
High-Throughput Experimental Materials Database
The HTEM-DB contains the materials data obtained from high-throughput experiments.
HTEM-DB was designed with the purpose of releasing large amounts of high-quality experimental data to the public through an interactively searchable and programmatically accessible long-term repository. Some features include:
- Web-based interactive search and filter tools for finding entries of interest
- Data visualization tools for inspection and comparison of data sets
- Application programming interface with machine learning algorithms
- More than 100,000 unique compositions at unique processing conditions.
For more information, read An Open Experimental Database for Exploring Inorganic Materials, Scientific Data (2018).
Research Data Infrastructure
The HTEM-DB is built from an extensive research data infrastructure for high-throughput experimental materials science. It features a data warehouse, which is a raw file repository automatically harvested from laboratory computers and stored in a central location, and a custom web form-based application for capturing synthesis conditions associated with the characterized sample libraries known as the Lab Metadata Collector. Some features include:
- Digital data collection by a data warehouse
- Metadata collection by the Laboratory Metadata Collector
- Data extraction, transformation, and loading
- Direct links to HTEM-DB and COMBIgor.
For more information, read Research Data Infrastructure for High-Throughput Experimental Materials, Patterns (2021).
Publications
An Open Experimental Database for Exploring Inorganic Materials, Scientific Data (2018)
COMBIgor: Data Analysis Package for Combinatorial Materials Science, ACS Combinatorial Science (2019)
Research Data Infrastructure for High-Throughput Experimental Materials, Patterns (2021)
Contacts
Share
