## 2 Methods and Materials
### Data Processing  
#### 2.4.1 Tensile Data Processing  
The flowchart of data processing involved in the routine tensile test is shown in Figure 3, where data acquired from all four sensors are colour-marked, and the interactions between different data sub-sets and different processing steps are shown by arrows. Sampled load data were interpolated to be aligned precisely with optical images in time. We have chosen the open-source DIC software Ncorr [91] ([[http://www.ncorr.com](http://www.ncorr.com)]([http://www.ncorr.com](http://www.ncorr.com)) (accessed on 24 June 2021)), which allows for creating and building-in the user-made scripts to facilitate the automation of the data analysis process without compromising the quality of the obtained displacements and strain fields [92]. Numerous studies have demonstrated that with the appropriate settings, DIC can capture the strain on the surface of tested with the accuracy comparable to that of high precision extensometers or strain gauges attached to the same specimen [93; 94; 95]. Specifically, the Ncorr efficiency benefits from the state-of-the art inverse-compositional Gauss-Newton (IC-GN) optimisation algorithm proposed by [PERSON] et al. [96] for fast, robust and accurate full-field displacement tracking with sub-pixel resolution. Leaving the correlation algorithm unchanged, the cross-system data handling and integration software was developed in the present work in MATLAB [97]. Digital Image Correlation  
The first step in the processing of images captured by the visible light camera was the DIC analysis. The reference image corresponded to the undeformed specimen. The subset radius was selected between 20 and 25 pixels, and, since the subset spacing reduces the data size, it was chosen to roughly match the size of the images from IRT. For the high strain analysis, the reference image was updated once the correlation became poor. In a later step, the displacements were formatted to be expressed with respect to the initial reference image. With the automatic seed propagation, a seed which is the initial location used for correlation, seeds are updated too. More information can be found in the Ncorr manual [98]. Once the point-wise displacements were calculated, further processing was divided into two distinct parts. In the first part, a virtual extensometer was applied to measure the global engineering and true strain concurrently with the corresponding engineering and true stress calculated using the load signal and the dimensions of the specimen cross-section. In the second part, local deformations and deformation rates were calculated. Ncorr provides displacement fields in the reference and deformed configurations, from which the deformation gradient can be calculated using Equation (1). The property of primary interests, besides the stress and strain, is the mechanical power, which requires the rate of deformation tensor \(\mathbf{D}\). This tensor is based on the velocity gradient given in the deformed configuration \(\mathbf{L}\), as described by Equation (2), so to express it in the reference configuration, the relation between the deformation gradient in reference configuration and velocity gradient in deformed configuration in Equation (4) was used. After this step, the displacements, deformation, and deformation rate are known. Calculation of engineering stresses is performed from the load signal and samples geometry. To quantify the overall true stress \(\sigma_{T}\), the scalar engineering strain \(\epsilon\) obtained from the virtual extensometer is used, and \(\sigma_{T}\) calculated conventionally as  
Figure 3: Flow-chart of data processing for the tensile test. \[\sigma_{T}=\frac{P}{A_{0}}(1+\epsilon) \tag{14}\]  
where \(P\) denotes the applied load, \(A_{0}\) is the initial cross-section. The last expression gives an average value for the region covered by the virtual extensometer in the loading direction. The \(\sigma_{T}\) value provides a good representation of the flow stress as long as the deformation is homogeneous.