Harnessing STA-IR-MS for the experimental teaching of energy materials: A case study on the thermal stability of lithium-based polymer electrolyte materials

The growing prominence of advanced analytical techniques in materials science has underscored the need to integrate coupled instrumentation systems into graduate education. Introducing synchronous thermal analysis (STA) combined with infrared spectroscopy (IR) and mass spectrometry (MS) into experimental teaching is an important initiative for cultivating interdisciplinary talent capable of addressing complex research challenges in energy materials development.

This study systematically examines the architectural principles and operational mechanisms of STA-FTIR-MS and STA-FTIR-GC-MS (gas chromatography-MS) coupled technologies, demonstrating their distinctive advantages in energy materials education through an integrated teaching experiment focused on the Thermal Stability of Lithium-based Polymer Electrolyte Materials.” The experiment was designed to cultivate comprehensive skills in multimodal data acquisition and interpretation and was structured around four fundamental components. These include establishing learning objectives to familiarize students with the working principles of STA, FTIR, MS, and GC-MS systems while demonstrating correlations among mass loss, thermal events, and gas evolution to develop capabilities in analyzing complex multidimensional datasets; implementing experimental procedures in which students prepare lithium-based polymer electrolyte samples and subject them to programmed heating under an inert atmosphere, with the STA module recording real-time mass changes and enthalpy variations and evolved gases simultaneously transferred via a heated transfer line to FTIR and MS/GC-MS systems for compositional identification and quantification; facilitating integrated data analysis in which trainees learn to synchronize thermogravimetric data with FTIR spectral profiles and MS/GC–MS to establish causal relationships between thermal decomposition stages and specific gas release events, while enabling direct comparison of the analytical capabilities of MS and GC-MS detection systems in characterizing thermal decomposition processes; and conducting teaching assessments through evaluation rubrics that examine laboratory performance, data interpretation accuracy, and final report quality, with particular emphasis on critical reasoning skills and scientific communication abilities.

The integrated experiment enabled students to quantitatively correlate mass loss events with specific gas evolution profiles through synchronized data analysis. During programmed heating, participants identified characteristic decomposition stages—such as solvent evaporation, polymer chain degradation, and inorganic salt decomposition—by cross-referencing STA curves with IR absorption bands (e.g., C=O stretching at 1740 cm^-1 for carbonate decomposition) and MS ion fragments or GC–MS chromatographic peaks. This approach revealed clear structure-property relationships between material composition and thermal behavior while demonstrating the complementary strengths of MS (rapid detection) and GC-MS (superior resolution for complex mixtures). Assessment based on operational proficiency, data interpretation accuracy, and scientific reporting demonstrated considerable improvement in students' ability to extract meaningful insights from multidimensional datasets, propose mechanistic explanations for observed phenomena, and communicate findings effectively. The experiment has established a new pedagogical model for advanced instrumental training within the New Engineering Education framework, emphasizing critical thinking and technical problem-solving.

The integration of STA-IR-MS/GC-MS coupled technologies into energy materials laboratory teaching represents a successful reform that goes beyond traditional single-technique experiments. Through this thoughtfully designed project, students gained hands-on experience with state-of-the-art instrumentation and developed a researcher's mindset. They learned to navigate analytical complexity, reconcile complementary datasets, and construct evidence-based scientific narratives. This pedagogical approach effectively bridges the gap between theoretical knowledge and practical research skills, fostering the interdisciplinary competencies required for innovation in advanced materials science. Moreover, this model offers a scalable framework for future curriculum development and can be adapted to other emerging fields where coupled characterization techniques are essential.