## 2 Materials and Method
### Map Programming  
Depending on the exact nature of the experiment one or several hyperspectral Raman images were recorded before having fired the sample to the next temperature step. At each temperature step, a spectrum of the black body radiation was first recorded. Thereby, the acquisition parameters were identical, except that the sample was not excited by the laser. Depth profiles were acquired using the auto-focus function (depth profiling) before recording the first image at each temperature step to monitor reaction- and temperature-related shrinking or expansion effects and to obtain an optimal signal-to-noise ratio. The \"tilt at limits\" mode acquires depth profiles of the image center and the four corners and determines the best focus regarding the Raman signal from which the focus at each position (pixel) in the image is interpolated. Thereby an inclined sample surface can be compensated. The quality of the Raman spectra and therefore also of the Raman images depends on a number of instrumental (e.g., laser power, acquisition time, quality of the lenses, grating, sensitivity of the detector, the size of confocal hole, the microscope objective) and sample parameters (e.g., surface roughness, color, heterogeneity, the refractive index of the sample) [29]. Raman spectra were collected during continuous x-y stage movement with a speed of 1.6 \(\upmu\)m/s (SWIFT(r) mode). During movement, Raman intensities were recorded for 0.6 s in the wavenumber range from 100 to 1750 cm\({}^{-1}\). All recorded images comprised an area of 100 \(\times\) 100 \(\upmu\)m\({}^{2}\) in size. The step size was 1 \(\upmu\)m, yielding 10,000 spectra per image. Despite the short acquisition time per spectrum, the total exposure time was still about 2 h for a single image. Hence, an image is not always an accurate snapshot, because processes may still run while recording the image. This has to be taken into account when interpreting the hyperspectral Raman images. However, reactions that are faster than image acquisition can easily be detected by line-by-line shifts in the image (Figure 2), so that the total acquisition time can be adjusted, e.g., by imaging a smaller area or by using shorter single point acquisition times. Figure 2: Hyperspectral Raman images of (**a**) fused silica-calcite and (**b**) quartz-time green bodies recorded at 833 and 704 \({}^{\circ}\)C with a total exposure time of about 2 h, showing line-by-line image shifts. The sudden phase changes (white arrows) indicate that the respective reactions in (a), i.e., CaCO\({}_{3}\)\(\rightarrow\) CaO + CO\({}_{2}\)\(\uparrow\), and (b), i.e., \(\gamma\)-Ca\({}_{2}\)SiO\({}_{4}\)\(\rightarrow\)\(\beta\)-Ca\({}_{2}\)SiO\({}_{4}\), were faster than the total imaging time. In general, superior spectral quality can be obtained using a point-by-point mapping approach, as data sets can benefit from longer acquisition times. However, in this work, the hyperspectral Raman images were recorded with a continuous moving table to save imaging time and maximizing the imaged area. It is noted that even poor-quality spectra usually provide sufficient detail for phase identification. The situation will be different, however, when other band parameters than the amplitude are needed, for instance, to visualize structural or chemical variations reflected by the width and frequency of a Raman band. For Raman phase images, the quality of the reference spectra is more crucial for their quality than the signal-to-noise ratio obtained from the sample [30]. A comparison of a map recorded in the fast scanning mode (SWIFT(r) mode, 0.6 s per spectrum, recording time of 50 min) and in the point-by-point mode with an acquisition time of 10 s per spectrum (10 times 1 s for, recording time of 8 h 43 min) shows that the large increase in acquisition time has only a minor influence on the quality of a hyperspectral Raman image (Figure 3). A semi-quantitative estimate of the increase or decrease of a mineral fraction within the analyzed volume as a function of temperature and time is still reliable.