Boriding is a widely used thermochemical treatment to improve surface hardness and wear resistance in steels used in demanding mechanical applications. However, boronizing processes using new boron paste increase costs and generate waste, creating a need for more sustainable alternatives. In this context, the reuse of dehydrated boron paste has proven effective in the formation of Fe₂B layers on AISI 9254 steel. In this study, AISI 9254 steel was boronized using reused dehydrated boron paste at 1173 K, 1223 K, and 1273 K for 3600, 7200, 10,800, and 14,400 s. Optical microscopy revealed layer thicknesses ranging from 16.07 $\mathsf{\mu }\mathrm{m}$ to 69.35 $\mathsf{\mu }\mathrm{m}$ X-ray diffraction confirmed the formation of single-phase Fe₂B, while EDS indicated elemental redistribution within the layer. The Vickers microhardness profile characterized the mechanical behavior, and the adhesion force showed HF1-HF2 ratings. The activation energy for boron diffusion in Fe₂B was calculated at 106.567 kJ ${\mathrm{mol}}^{-1}$. Auto-affine analysis verified the fractal nature of interface growth, with a scale $\omega \left(d\right)$ according to $\omega \left(\delta \right)\sim {\delta }^H$. These results confirm that reused paste allows the formation of Fe₂B layers, supporting sustainable boronization strategies with controlled interfacial evolution.

This study focuses on a hydrocarbon reservoir located in southeastern Mexico. The analysis uses well log data derived from petrophysical evaluations of storage capacity. The structural complexity of the reservoir and observed heterogeneity in Cretaceous units motivate a fractal-based characterization of spatial fluctuations. The objective is to assess the fractal scaling of storage capacity fluctuations using the Family–Vicsek dynamic framework. Critical exponents α (roughness), β (growth), and z (dynamic) are obtained through structure function metrics. Data collapse techniques and local Hurst exponent distributions are used to explore long-range memory and spatial heterogeneity across wells. This study aims to classify storage capacity fluctuation records based on Euclidean or fractal geometries. This analysis allows a novel characterization of storage trends in the reservoir. The analysis reveals persistent scaling behavior, indicating long-range correlations in the storage capacity fluctuations. Multiscale patterns and variations in local Hurst exponents highlight the presence of multifractality and regional heterogeneity. Specifically, the spatial distribution of local Hurst exponents obtained in this study enables the inference of statistical properties in synthetic wells, providing key input for the structural and functional characterization of the reservoir’s geological model. This approach aims to identify preferential subsurface flow pathways for hydrocarbons, gas.

The air pollution due to tropospheric ozone (O₃) is one of the most serious problems of large industrialized cities in the world. The excessive increase in O₃ has a negative impact on the population health. Consequently, researchers have focused their efforts establishing measures to characterize the statistical analysis of spatio-temporal data. This work shows a study based on seasonal analysis of spatio-temporal data through second order structure function to and the scale behavior in power law by using the Hurst exponent (H) and analyzing the trend of fluctuations associated with O₃ pollution concentration records at four monitoring stations in the Metropolitan Area of Mexico City (MAMC) considering the four season of the year. The records were consulted from the database of the Automatic Atmospheric Monitoring Network (AAMN) in Mexico City from 2010 to 2018. The results show the differences in behavior of ozone according to the seasons of the year in this megacity. The behavior of statistical persistence predominates in spring, with 63.89% of occurrence over the total of the samples analyzed. In winter, the observed regime is antipersistent, with 80.56%. The three regimes: persistence, randomness and antipersistence were observed in summer and autumn, with a similar proportion of occurrence of 33% ± 3%. Given the above, the climatological characteristics of each season could be associated with the regimes of persistent, random and antipersistent behavior of the fluctuation of the concentration of the pollutant O₃

This study evaluates flow capacity fluctuations in well cores from a southeastern Mexico formation using pdpk records. Petrophysical measurements provide wellbore wall flow capacity data, used to identify trends. Applying a dynamic scaling approach akin to the Family-Vicsek method, we analyze discrete kh* records. In particular, the order parameter structure function q was applied to the flow capacity records, and the exponents characterizing dynamic scaling α, β, z were identified, revealing self-affine scalings for fluctuations. Data collapse of flow capacities occurs in the northern zone with higher fractures and oil production, contrasting with the poorly collapsed flow capacity in the southern zone. This suggests superior flow capacity in fractal reservoir media compared to Euclidean counterparts.

This study investigates the seasonal influence on the nitrogen oxide NO _x pollution records at four monitoring sites in Mexico City from 2010 to 2018. The analysis employs the second-order structure function to examine the trends in NO _x concentration fluctuations. The findings reveal that the fluctuations follow a power law pattern characterized by Hurst exponents, predominantly in the statistical persistence regime, with a scaling range spanning three orders of magnitude. Specifically, the autumn period exhibits fluctuations with an exponent of $$\overline{H}=0.72$$ H ¯ = 0.72 , indicating relatively smaller fluctuations compared to other seasons, but with the potential for NO _x concentrations to surpass those in other periods. In contrast, for spring, summer, and winter, the fluctuations are characterized by exponents of $$\overline{H}=0.59$$ H ¯ = 0.59 , $$\overline{H}=0.61$$ H ¯ = 0.61 , and $$\overline{H}=0.62$$ H ¯ = 0.62 , respectively, demonstrating greater fluctuations with lower NO _x concentrations compared to autumn. These results are consistent with various studies conducted worldwide. Additionally, a negative correlation between NO _x and ozone (O ₃ ) has been established during the winter season, as NO _x and O ₃ fluctuations display persistent and anti-persistent behavior, respectively.

This study focuses on a hydrocarbon reservoir located in southeastern Mexico. The analysis uses well log data derived from petrophysical evaluations of storage capacity. The structural complexity of the reservoir and observed heterogeneity in Cretaceous units motivate a fractal-based characterization of spatial fluctuations. The objective is to assess the fractal scaling of storage capacity fluctuations using the dynamic Family–Vicsek framework. Critical exponents $\alpha$ (roughness), $\beta$ (growth), and z (dynamic) are obtained through structure function metrics. Data collapse techniques and local Hurst exponent distributions are used to explore long-range memory and spatial heterogeneity across wells. This study aims to classify storage capacity fluctuation records based on Euclidean or fractal geometries. This analysis allows a novel characterization of storage trends in the reservoir. The analysis reveals persistent scaling behavior, indicating long-range correlations in the storage capacity fluctuations. Multiscale patterns and variations in local Hurst exponents highlight the presence of multifractality and regional heterogeneity. Specifically, the spatial distribution of local Hurst exponents obtained in this study enables the inference of statistical properties in synthetic wells, providing key input for the structural and functional characterization of the reservoir’s geological model. This approach aims to identify preferential subsurface flow pathways for hydrocarbons and gas.