# Large Language Model-Informed X-ray Photoelectron Spectroscopy Data Analysis
## 7 Integrating LLM-Informed Strategy with TANGO Control System at CELLS ALBA Synchrotron  
The CELLS ALBA Synchrotron employs the TANGO (7.2.x/8.1.x/9.2.x/9.3.3) control system, a software framework for controlling and monitoring scientific and industrial hardware. Integrating the LLM-informed XPS data analysis strategy within this framework can significantly enhance the capabilities of the system, enabling more sophisticated and efficient processing and interpretation of XPS data. This section outlines the proposed integration approach. TANGO Control System is an object-oriented distributed control system using CORBA (Common Object Request Broker Architecture). It provides a framework for device interfacing and management, offering tools for configuring and operating a wide range of devices and instruments. At CELLS ALBA Synchrotron, TANGO plays a critical role in managing beamline operations, including data acquisition systems. The integration of the LLM-informed XPS analysis strategy into the TANGO system involves several key components and steps:  
1. Data Acquisition and Preprocessing: The XPS data acquired from experiments at the beamline are first pre-processed to align with the input requirements of the LLM. This involves noise reduction, normalization, and any other relevant data conditioning. 2. Enhancing TANGO Device Servers: TANGO device servers, which control various hardware components, will be enhanced to include an interface to the LLM analysis module. This interface will handle the sending of processed XPS data to the LLM and receiving the interpreted results. 3. LLM Integration: A new device server or an extension to an existing server will be developed to incorporate the LLM. This server will manage the communication with the LLM API, sending the pre-processed XPS data and receiving the analysis results. Automated Analysis Workflow: The TANGO system will automate the workflow where the XPS data, once acquired and pre-processed, are automatically sent to the LLM server for analysis. The interpreted results are then fed back into the TANGO system for user review or further automated processing. * User Interface and Visualization: The existing user interface of the TANGO system will be updated to include features for visualizing and interacting with the results provided by the LLM. This may include graphical representations of the XPS spectra with annotated peaks and interpretations, as well as tools for manual review or modification of the analysis. * Data Storage and Retrieval: Integration with TANGO's database system for storing both the raw XPS data and the interpreted results. This ensures that all information is readily available for future reference, comparison, or further analysis. The integration of the LLM-informed strategy into the TANGO control system at CELLS ALBA Synchrotron offers several benefits:  
* Enhanced Data Interpretation: Leveraging LLM for XPS data interpretation brings a higher level of accuracy and depth in analysis, aiding researchers in understanding complex chemical states and materials properties. * Increased Efficiency: Automating the data interpretation process reduces the time and effort required by researchers, allowing them to focus on more critical aspects of their experiments. * Scalability: As the volume of data generated at the synchrotron grows, the LLM-informed system can scale accordingly, providing consistent and reliable analysis. * User Accessibility: The integration makes advanced data analysis accessible to a broader range of users, including those who may not have deep expertise in XPS data interpretation. The integration of an LLM-informed strategy within the TANGO control system at CELLS ALBA Synchrotron represents a significant advancement in the field of synchrotron data analysis. It exemplifies the potential of AI and ML in enhancing scientific research capabilities, paving the way for more accurate, efficient, and accessible scientific experimentation and data analysis.