This work explored an electrochemical approach for synthesizing lanthanum-modified nickel oxide (NiO_x:La) as a hole transport layer (HTL) in inverted perovskite solar cells (IPSCs). By varying the La³⁺ concentration, the chemical, charge transport, structural, and morphological properties of the NiO_x:La film and the HTL/PVK interface were evaluated to enhance photovoltaic performance. X-ray photoelectron spectroscopy (XPS) confirmed La³⁺ incorporation, a higher Ni³⁺/Ni³⁺ ratio, and a valence band shift, improving p-type conductivity. Electrochemical impedance spectroscopy and Mott–Schottky analyses indicated that NiO_x:La 0.5% exhibited the lowest resistance and the highest carrier density, correlating with higher recombination resistance. The NiO_x:La 0.5% based cell achieved a PCE of 20.08%. XRD and SEM confirmed no significant changes in PVK structure, while photoluminescence extinction demonstrated improved charge extraction. After 50 days, this cell retained 80% of its initial PCE, whereas a pristine NiO_x device retained 75%. Hyperspectral imaging revealed lower optical absorption loss and better homogeneity. These results highlight NiO_x:La as a promising HTL for efficient and stable IPSCs.

Accurate color property measurements are critical for advancing artificial vision in real-time industrial applications. RGB imaging remains highly applicable and widely used due to its practicality, accessibility, and high spatial resolution. However, significant uncertainties in extracting chromatic information highlight the need to define when conventional digital images can reliably provide accurate color data. This work simultaneously compares six chromatic properties across 700 Pantone^® TCX fabric samples, using optical data acquired simultaneously from both hyperspectral (HSI) and digital (RGB) cameras. The results indicate that the accurate interpretation of optical information from RGB (sRGB and REC2020) images is significantly influenced by lightness ($L^{*}$) values. Samples with bright and unsaturated colors ($L^{*}>$ 50) reach ratio-to-performance-deviation (RPD) values above 2.5 for four properties ($L^{*}, a^{*}, b^{*}$ $h_{ab}$), indicating a good correlation between HSI and RGB information. Absolute color difference comparisons (${∆E}_a$) between HSI and RGB images yield values exceeding 5.5 units for red-yellow-green samples and up to 9.0 units for blue and purple tones. In contrast, relative color differences (${∆E}_r$) comparisons show a significant decrease, with values falling below 3.0 for all lightness values, indicating the practical equivalence of both methodologies according to the Two One-Sided Test (TOST) statistical analysis. These results confirm that RGB imagery achieves reliable color consistency when evaluated against a practical reference.

Accurate color property measurements are critical for advancing artificial vision in re-al-time industrial applications. RGB imaging remains highly applicable and widely used due to its practicality, accessibility, and high spatial resolution. However, significant un-certainties in extracting chromatic information highlight the need to define when conven-tional digital images can reliably provide accurate color data. This work simultaneously compares six chromatic properties across 700 Pantone® TCX fabric samples, using opti-cal data acquired simultaneously from both hyperspectral (HSI) and digital (RGB) camer-as. The results indicate that the accurate interpretation of optical information from RGB (sRGB and REC2020) images is significantly influenced by lightness (L*) values. Samples with bright and unsaturated colors (L* > 50) reach ratio-to-performance-deviation (RPD) values above 2.5 for four properties (L*, a*, b* H), indicating a high correlation between HSI and RGB information. Direct color difference comparisons (∆E) between HSI and RGB images yield values exceeding 5.5 for red-yellow-green samples and up to 9.0 for blue and purple tones. However, when relative color differences (∆E′) are calculated using a specific reference, the values drop significantly falling below 2.0 for light-colored samples (L* > 50). These results confirm that RGB imagery achieves reliable color consistency when evalu-ated against a practical reference.