Characterization Methods Research Articles

Fe(OH)3/Ti3C2Tx nanocomposites for enhanced ammonia gas sensor at room temperature

Two-dimensional material (2D material) MXene has great application potential in gas sensors because of its excellent controllable performance and vast specific surface area. In this study, we used a straightforward in-situ electrostatic self-assembly technique to create Fe(OH)3/Ti3C2Tx nanocomposites, which were then used to fabricate gas sensors for ammonia detection at room temperature (25 ℃). Several characterization methods were performed aimed at determining the surface appearance and construction of the nanocomposites, and the sensing characteristics and mechanism were also systematically examined. The findings demonstrate the effective incorporation of amorphous Fe(OH)3 nanoparticles on the surface of Ti3C2Tx. Additionally the nanocomposites of Fe(OH)3/Ti3C2Tx have considerably higher specific surface area than pure Ti3C2Tx, hence offering more active NH3 adsorption sites. The response of the sensor to 100 ppm NH3 was 48.6% at room temperature, which was 9.3 times more higher than that of pure Ti3C2Tx. The sensors also have the advantages of long-term stability (33 days), low NH3 detection limit (500 ppb), and rapid recovery time (85 s) and response times (78 s). It is anticipated that this work will be helpful for developing the new generation of wearable ammonia sensors at room temperature.

Evolution and Characterization of Uniaxial Compression Damage of Coal Measure Rock

In order to study the evolution law of uniaxial compression damage and its characterization method, three kinds of rocks with different lithology that commonly exist in coal measure rock were taken as the research objects to explore the relationship between their mineral composition, microstructure and mechanical properties, and the feasibility of acoustic emission (AE) characteristic parameters and AE spatial location to characterize the evolution process of uniaxial compression damage of rocks was compared and analyzed. A damage constitutive model based on AE cumulative ringing count was established and verified by numerical simulation. The results show that the differences in the micromorphology and mineral composition of coal measures with different lithology directly affect their physical and mechanical properties and load damage characteristics. AE characteristic ringing count can effectively represent the damage evolution process of rock during loading. Based on rock porosity characteristics and AE cumulative ringing count during loading, a constitutive model considering initial damage and cumulative damage was established. The theoretical analysis results of the damage constitutive model are in good agreement with the results of laboratory experiments and numerical simulation, which can be used to analyze the damage process of coal measure rock under load.

Imaging Locally Inhomogeneous Properties of Metal Halide Perovskites.

Metal halide perovskites (MHPs) are a perfect example of state-of-the-art photovoltaic materials whose compositional and structural diversity,coupled with utilization of low-temperature processing, can undesirably result in spatially inhomogeneous properties that locally vary within the material. This complexity of MHPs requires sensitive imaging characterization methods at the microscopic level to gauge the impact of such inhomogeneities on device performance and to formulate mitigation strategies. This review consolidates properties of MHPs that are susceptible to local variations and highlights appropriate imaging techniques that can be employed to map them. Inhomogeneities in morphology, emission, electrical response, and chemical composition of MHP thin films are specifically considered, and possible microscopic techniques for their visualization are reviewed. For each type of microscopy, a short discussion about spatial resolution, sample requirements, advantages, and limitations is provided, thus leaving the reader with a guide of available imaging characterization tools to evaluate inhomogeneities of their MHPs.

Electrodeposition and optimisation of amorphous NixSy catalyst for hydrogen evolution reaction in alkaline environment.

Anion exchange membrane (AEM) water electrolyser has shown its potential in green hydrogen production. One of the crucial tasks is discover novel cost-effective and sustainable electrocatalyst materials. In this study, a low-cost Ni-S-based catalyst for hydrogen evolution reaction was prepared via a simple electrodeposition process from a modified Watts bath recipe. Physical characterisation methods suggest this deposit film to be amorphous. Optimisation of the electrodeposition parameters of the NixSy catalyst was carried out using a rotating disk electrode setup. The optimised catalyst exhibited excellent catalytical performance in 1 M KOH on a microelectrode, with overpotentials of 41 mV, 111 mV and 202 mV at 10, 100 and 1000 mA cm-2 with Tafel slope of 67.9 mV dec-1 recorded at 333 K. Long-term testing of the catalyst demonstrated steady performance over a 24 h period on microelectrode at 100 mA cm-2 with only 71 mV and 37 mV overpotential increase at 293 K and 333 K respectively. Full cell testing with the optimised NixSy as cathode and NiFe(OH-)2 as anode showed 1.88 V after 1 h electrolysis at 500 mA cm-2 in 1 M KOH under 333 K with FAA-3-30 membrane.

Novel pervaporation separation of PVA/CS blend membranes for the removal of DMF from industrial wastewater

AbstractAchieving satisfactory separation of N, N‐Dimethylformamide (DMF)/water is still challenging in industrial wastewater treatment. To address this issue, a novel method involving pervaporation (PV) separation using polyvinyl alcohol/chitosan (PVA/CS) blend films is proposed. Various characterization methods confirmed the strong compatibility between PVA and CS, and the blending improved their mechanical properties and thermal stability. Heat treatment significantly reduced the swelling degree of the membranes. In a binary aqueous system with low concentrations of DMF, controlled separation can be achieved by adjusting the blending ratio of PVA to CS. The membranes exhibited preferential selectivity for DMF when the CS content is 40–75 wt%, which allowed for the concentration and recovery of DMF. At 20 °C with a feed of 10 wt% DMF solution, 2 h heat‐treated PVA/CS‐50 membrane exhibited the best performance, which could be attributed to its strong hydrogen bonding force, with a total flux of 484.09 g m−2 h−1 and a separation factor of 5.41 for DMF. The PVA/CS blend membranes exhibit excellent acid and alkali resistant and are promising candidates for the separation and recovery of DMF from industrial wastewater by membrane technology.

Use of Computerised X-ray Tomography in the Study of the Fabrication Methods and Conservation of Ceramics, Glass and Stone Building Materials

This work will review and discuss the use of computerised X-ray tomography (CXT) for analysing ancient, manufactured items, like stone building materials, glass and ceramics. It will consider particular techniques required, and/or of benefit, for CXT of heritage materials, such as special precautions during the experimentation to ensure there is no damage to the materials, special imaging methods such as elemental-specific imaging, and sample-specific image analysis requirements. This study shows how the knowledge of internal features, particularly pores, discerned from CXT can be used to reverse engineer the artefact fabrication process. CXT can be used to obtain information on both the raw materials (such as types and impurities) and fabrication techniques used. These abilities can then be used to establish technological evolution and the incidence of ancient behaviours like recycling and allow the linking of particular items to specific production sites. It will also be seen how CXT can aid the development of effective conservation techniques. This work will also consider how conclusions drawn from CXT data can be amended or augmented by the use of complementary non-destructive characterisation methods, such as gas overcondensation.

Synthesis of β-Ga2O3:Mg Thin Films by Electron Beam Evaporation and Postannealing

Doping divalent metal cations into Ga2O3 films plays a key role in adjusting the conductive behavior of the film. N-type high-resistivity β-Ga2O3:Mg films were prepared using electron beam evaporation and subsequent postannealing processing. Various characterization methods (X-ray diffraction, X-ray photoelectron spectroscopy, photoluminescence, etc.) revealed that the Mg content plays an important role in affecting the film quality. Specifically, when the Mg content in the film is 3.6%, the S2 film’s resistivity, carrier content, and carrier mobility are 59655.5 Ω·cm, 1.95 × 1014 cm3/C, and 0.53682 cm2/Vs. Also, the film exhibits a smoother surface, more refined grains, and higher self-trapped exciton emission efficiency. The Mg cation mainly substitutes the Ga+ cation at a tetrahedral site, acting as a trap for self-trapped holes.

AutoGater: a weakly supervised neural network model to gate cells in flow cytometric analyses

Flow cytometry is a useful and efficient method for the rapid characterization of a cell population based on the optical and fluorescence properties of individual cells. Ideally, the cell population would consist of only healthy viable cells as dead cells can confound the analysis. Thus, separating out healthy cells from dying and dead cells, and any potential debris, is an important first step in analysis of flow cytometry data. While gating of debris can be conducted using measured optical properties, identifying dead and dying cells often requires utilizing fluorescent stains (e.g. Sytox, a nucleic acid stain that stains cells with compromised cell membranes) to identify cells that should be excluded from downstream analyses. These stains prolong the experimental preparation process and use a flow cytometer’s fluorescence channels that could otherwise be used to measure additional fluorescent markers within the cells (e.g. reporter proteins). Here we outline a stain-free method for identifying viable cells for downstream processing by gating cells that are dying or dead. AutoGater is a weakly supervised deep learning model that can separate healthy populations from unhealthy and dead populations using only light-scatter channels. In addition, AutoGater harmonizes different measurements of dead cells such as Sytox and CFUs.

Formal Methods for Characterization and Analysis of Quality Specifications in Component-based Systems

Formal Methods for Characterization and Analysis of Quality Specifications in Component-based Systems

Chemical synthesis of NiO nanoparticles from Solanum trilobatum leaf extract for antibacterial and cytotoxic properties

The chemical precipitation approach was employed to synthesize Nickel oxide nanoparticles (NiONPs) using Solanum trilobatum leaf extract as the stimulant and Nickel nitrate as the precursor. The Nickel oxide is examined using a range of characterization methods including X-ray diffraction, Fourier Transform Infrared spectroscopy, High-Resolution Transmission Electron Microscopy, High-Resolution Scanning Electron Microscopy, X-ray photoelectron spectroscopy, Thermo gravimetric Analysis/Derivative Thermo gravimetric Analysis, Diffuse Reflectance Spectroscopy, cytotoxicity and antimicrobial investigations The X-ray diffraction examination determined that the average size of the crystals increases as the quantities of leaf extract in the NiO2 composites rise. The decrease in line broadening (β) value and the increase in leaf extract concentrations may be the cause of this phenomenon. The FTIR spectrum confirms that the as-synthesized NiO-NPs are of great purity and match well with the XRD pattern. The thermal stability of the synthesized samples was determined using TGA/DTG analysis. The analysis was conducted in an air atmosphere, with the temperature increasing at a rate of 10°C per minute. The temperature range for the analysis was from room temperature to 750°C. The optical properties are determined by the use of Diffuse Reflectance Spectroscopy, which examines the coordinated movement of electrons in the conduction band when exposed to electromagnetic waves. Rat skeletal muscle cell line and SKMEL cancer cells were cultured on 96-well plates and incubated at 37°C and 5 % CO2 for 24 hours to allow them to adapt to the culture conditions. An investigation was conducted to assess the antibacterial properties of synthesized nanocomposites against two types of bacteria: gram-positive Staphylococcus aureus (MTCC No: 87) and gram-negative Escherichia coli (MTCC No: 443), in order to explore their potential for biological applications.

Numerical Simulation of Gas–Water Two-Phase Flow Patterns in Fracture: Implication for Enhancing Natural Gas Production

The main objective of this paper is to investigate the evolution of rock fracture slug structures and decongestion strategies for natural gas extraction processes. For this purpose, the level set method was used to simulate the evolution of the slug structure under the effect of different flow ratios, fracture surface wettability, and fracture tortuosity. The results show that an increase in the water-to-gas flow ratio and fracture tortuosity leads to a significant increase in the proportion of slug structures in the fracture, while an increase in the surface contact angle leads to a decrease in the proportion of slug structures in the fracture. Based on the above slug structure evolution law, a quantitative characterization method for the slug structure of two-phase fluids considering the combined effects of the water–gas flow ratio, average wall contact angle, and flow channel tortuosity was developed. Subsequently, we engage in further discussion on the optimization of the extraction and decongestion process in natural gas extraction.

A Remote-Sensing-Based Method Using Rockfall Inventories for Hazard Mapping at the Community Scale in the Arequipa Region of Peru

Small communities in the Arequipa region of Peru are susceptible to rockfall hazards, which impact their lives and livelihoods. To mitigate rockfall hazards, it is first necessary to understand their locations and characteristics, which can be compiled into an inventory used in the creation of rockfall hazard rating maps. However, the only rockfall inventory available for Arequipa contains limited data of large, discrete events, which is insufficient for characterizing rockfall hazards at the community scale. A more comprehensive inventory would result in a more accurate rockfall hazard rating map—a significant resource for hazard mitigation and development planning. This study addresses this need through a remote method for rockfall hazard characterization at a community scale. Three communities located in geographically diverse areas of Arequipa were chosen for hazard inventory and characterization, with a fourth being used for validation of the method. Rockfall inventories of source zones and rockfall locations were developed using high-resolution aerial imagery, followed by field confirmation, and then predictions of runout distances using empirical models. These models closely matched the actual runout distance distribution, with all three sites having an R2 value of 0.98 or above. A semi-automated method using a GIS-based model was developed that characterizes the generation and transport of rockfall. The generation component criteria consisted of source zone height, slope angle, and rockmass structural condition. Transport was characterized by rockfall runout distance, estimated rockfall trajectory paths, and hazard ratings of corresponding source zones. The representative runout distance inventory model of the validation site matched that of a nearby site with an R2 of 0.98, despite inventorying less than a third of the number of rockfalls. This methodology improves upon current approaches and could be tested in other regions with similar climatic and geomorphic settings. These maps and methodology could be used by local and regional government agencies to warn residents of rockfall hazards, inform zoning regulations, and prioritize mitigation efforts.

A rapid and reliable method for early Legionella pneumophila identification and characterization in support of the epidemiology study

IntroductionLegionnaires’ disease is a severe pneumonia predominantly caused by Legionella pneumophila (Lp), whose major reservoirs are artificial water systems. As most human infections are caused by L. pneumophila serogroup 1 (Lp1), a reliable method for Lp distinction can be crucial for bacterial spread prevention. As the ability to withstand in environments and to cause the waterborne disease is strongly related to specific genes, the identification of virulent strains can be of great relevance to implement water environmental monitoring and to contain harmful outbreaks to public health. We aimed to test an assay for Lp identification among different Legionella species, and to determine the serogroups. Additionally, we investigated the carriage of virulence and antimicrobial resistance genes.MethodsA total of 90 Legionella spp. isolates identified by phenotypic tests were subjected to the designed quantitative PCR assay targeting specific mip for Lp, wzm for Lp1, pvcA and ahpD for biofilm production. Eleven serogroups were investigated in all our isolates tested positive for mip gene, subsequently analyzed for 12 virulence and 8 antimicrobial resistance genes.ResultsOnly the 70 Lp isolates were positive for mip. Out of 27 Lp isolates belonging to serogroup 1 based on agglutination test, 23 (85.2%) carried wzm. The presence of ahpD and pvcA was found in 94.3 and 98.6% of Lp isolates, respectively. By multiplex PCR, all 23 wzm-positive strains were confirmed as serogroup 1 that was the most predominant (33%). At least one virulence gene was detected in all Lp isolates. The most frequent gene was ispE (100%), followed by issD (96%), icmK and enhC (93%), cpxA (91%), rtxA2 (74%), lvhB8-B9 (61%), and prpA (54%). The other genes were less diffused in Lp strains (rtxA1, 44%; lvhB3-B4, 47%; pvcB, 27%; lvrE, 24%). Of the macrolide resistance genes, the ereA was found in 84% of Lp strains, while only 14 (20%) harbored the lpeAB among the efflux pump genes.ConclusionThe assays validated in this study enable the simultaneous Lp and Lp1 detection. The differentiation of Lp strains according to their virulence properties could be useful to predict the bacterial ability to survive and to cause the disease.

Investigating Exposure and Hazards of Micro- and Nanoplastics During Pregnancy and Early Life (AURORA Project): Protocol for an Interdisciplinary Study.

Micro- and nanoplastics (MNPs) are emerging pollutants of concern with ubiquitous presence in global ecosystems. MNPs pose potential implications for human health; however, the health impacts of MNP exposures are not yet understood. Recent evidence suggests that MNPs can cross the placental barrier, underlying the urgent need to understand their impact on reproductive health and development. The Actionable eUropean ROadmap for early-life health Risk Assessment of micro- and nanoplastics (AURORA) project will investigate MNP exposures and their biological and health effects during pregnancy and early life, which are critical periods due to heightened vulnerability to environmental stressors. The AURORA project will enhance exposure assessment capabilities for measuring MNPs, MNP-associated chemicals, and plastic additives in human tissues, including placenta and blood. In this interdisciplinary project, we will advance methods for in-depth characterization and scalable chemical analytical strategies, enabling high-resolution and large-scale toxicological, exposure assessment, and epidemiological studies. The AURORA project performs observational studies to investigate determinants and health impacts of MNPs by including 800 mother-child pairs from 2 existing birth cohorts and 110 women of reproductive age from a newly established cohort. This will be complemented by toxicological studies using a tiered-testing approach and epidemiological investigations to evaluate associations between maternal and prenatal MNP exposures and health perturbations, such as placental function, immune-inflammatory responses, oxidative stress, accelerated aging, endocrine disruption, and child growth and development. The ultimate goal of the AURORA project is to create an MNP risk assessment framework and identify the remaining knowledge gaps and priorities needed to comprehensively assess the impact of MNPs on early-life health. In the first 3 years of this 5-year project (2021-2026), progress was made toward all objectives. This includes completion of recruitment and data collection for new and existing cohorts, development of analytical methodological protocols, and initiation of the toxicological tiered assessments. As of September 2024, data analysis is ongoing and results are expected to be published starting in 2025. As plastic pollution increases globally, it is imperative to understand the impact of MNPs on human health, particularly during vulnerable developmental stages such as early life. The contributions of the AURORA project will inform future risk assessment. DERR1-10.2196/63176.

Micro-Nanoparticle Characterization: Establishing Underpinnings for Proper Identification and Nanotechnology-Enabled Remediation

Microplastics (MPLs) and nanoplastics (NPLs) are smaller particles derived from larger plastic material, polymerization, or refuse. In context to environmental health, they are separated into the industrially-created “primary” category or the degradation derivative “secondary” category where the particles exhibit different physiochemical characteristics that attenuate their toxicities. However, some particle types are more well documented in terms of their fate in the environment and potential toxicological effects (secondary) versus their industrial fabrication and chemical characterization (primary). Fourier Transform Infrared Spectroscopy (FTIR/µ-FTIR), Raman/µ-Raman, Proton Nuclear Magnetic Resonance (H-NMR), Curie Point-Gas Chromatography-Mass Spectrometry (CP-gc-MS), Induced Coupled Plasma-Mass Spectrometry (ICP-MS), Nanoparticle Tracking Analysis (NTA), Field Flow Fractionation-Multiple Angle Light Scattering (FFF-MALS), Differential Scanning Calorimetry (DSC), Thermogravimetry (TGA), Differential Mobility Particle [Sizing] (DMPS), Scanning Electron Microscopy (SEM), Transmission Electron Microscopy (TEM), and Scanning Transmission X-ray Microspectroscopy (STXM) are reviewed as part of a suite of characterization methods for physiochemical ascertainment and distinguishment. In addition, Optical-Photothermal Infrared Microspectroscopy (O-PTIR), Z-Stack Confocal Microscopy, Mueller Matrix Polarimetry, and Digital Holography (DH) are touched upon as a suite of cutting-edge modes of characterization. Organizations, like the water treatment or waste management industry, and those in groups that bring awareness to this issue, which are in direct contact with the hydrosphere, can utilize these techniques in order to sense and remediate this plastic polymer pollution. The primary goal of this review paper is to highlight the extent of plastic pollution in the environment as well as introduce its effect on the biodiversity of the planet while underscoring current characterization techniques in this field of research. The secondary goal involves illustrating current and theoretical avenues in which future research needs to address and optimize MPL/NPL remediation, utilizing nanotechnology, before this sleeping giant of a problem awakens.

Method for enhancing fault feature signals of rolling bearings in gas turbine engines

Aiming at the problem that the weak fault signal of rolling bearings in gas turbine engines (GTEs) is affected by environmental noise, which leads to the difficulty of effective information extraction and easy to ignore, the characterization method for cyclic extraction of main bearing fault feature components in GTEs is proposed. The proposed method begins by subjecting raw vibration signals to wavelet packet decomposition and correlating correlation coefficient and kurtosis values for each node component. These values are then normalized and amalgamated into a comprehensive parameter denoted as P. Subsequently, a confidence interval is established to categorize node components into three groups: high signal-to-noise ratio signals, low signal-to-noise ratio signals, and high-noise signals. Then, the high signal-to-noise ratio signals are continuously filtered according to the feature component cyclic extraction criterion until the termination condition is reached. Finally, all high signal-to-noise ratio signals are reconstructed, followed by envelope demodulation to extract subtle bearing fault characteristics. The findings underscore the efficacy of this approach in extracting fault features within the intricate transmission path of rolling bearings, offering a robust solution for the intricate signal processing and diagnosis of complex rolling bearing faults in GTEs.

Experimental investigation of mechanical properties of structural interlayers for rock masses during drilling process

With the continuous development of underground engineering construction in China, it is particularly important to study the identification of structural plane characteristics of rock masses. In this study, three types of pseudo-rock specimens with structural plane interlayers were fabricated to analyze the patterns of drilling parameter changes in rock bodies with structural planes during the drilling process and to explore the characterization and identification methods of rock body structural planes. Gneiss, granite, and sandstone were used as rock materials, with gypsum mortar as the interlayer material for the structural planes in these three types of specimens. The indoor digital drilling equipment was utilized for conducting indoor digital drilling experiments. The variation patterns of drilling parameters in rock bodies with structural surfaces under different interlayer inclinations and thicknesses were analyzed. The relationship between the ratio of the change in rotational speed and drilling speed during the stable phase of the upper rock mass and the peak torque and peak drilling pressure has been established. The relationship between the structural plane inclination angle and the ratio of change in rotational speed and drilling speed has been determined. By utilizing the variation in these ratios, the impacts of the structural plane inclination angle and the thickness of the structural plane on the peak torque and peak drilling pressure have been elucidated. The research results provide a theoretical basis for the stability evaluation of rock masses with structural planes under drilling action.

A new method for the characterization of perforated facings using a wide frequency range Impedance Sensor

Perforated facings (like fabrics, micro-perforated screens, ...) are widely employed in noise reduction solutions. Following previous works, it has been shown that they can be described as a porous media with identical cylindrical perforations. Then, a classical five parameters JCA model can be employed to predict the acoustical behaviour of perforated facings and, due to their small thicknesses, these five parameters can be obtained from only two independent quantities: the perforation average radius and the perforation rate. The CTTM and LAUM have recently developed a new approach for the measurement of JCA porous model parameters. This approach relies on the properties of two innovative apparatuses: an Impedance Sensor which allows for accurate impedance measurements over a wide frequency range combined with a patented compact anechoic termination. These devices are used to propose an improvement of an existing method for perforated facings characterisation. By using a non-resonant acoustic load and the Impedance Sensor, an accurate estimation of facing bulk magnitude can be done over a wide frequency range. Then the possible impact of the facing vibrational mode and of the acoustic load resonances is reduced, allowing for a more accurate estimation of facing parameter. Results are presented and discussed for different samples.

Capacitive deionization and electrochemical performance of a hierarchical porous electrodes enabled by nitrogen and phosphorus doped CNTs and removable NaCl template

Capacitive Deionization (CDI) is an electrochemical desalination technique based on the electrical double layer, which accumulate salts from the water stream; however, achieving higher salt adsorption for low-concentration salt is hindered due to several obstacles, such as low adsorption capacity and slow kinetics on the electrode surface. In this study, we reported a novel electrode fabrication method designed to enhance the hydrophilicity of the electrode material and activate hierarchical porosity, making a more accessible adsorption surface area. This modification enables more than 210 % improvement in salt adsorption capacity, achieving 17.5 mg g-1 in a single pass process with good stability in an 850 mg/L NaCl solution at 1.2 V, surpassing most reported carbon-based electrodes under similar operating conditions. Electrode formulation consists of Nitrogen (N) and Phosphorus (P) doped hierarchical carbon nanotubes (CNTs) network blended with additional NaCl as a green and removable template to reach higher levels of porosity. The electrochemical sorption behavior of the sample was characterized over a voltage range of –0.5 to 0.7 V. Furthermore, the electrode materials were characterized utilizing various characterization methods, including Scanning Electron Microscopy (SEM), Transmission Electron Microscopy (TEM), X-ray Diffraction (XRD), Raman Spectroscopy, Fourier Transformed Infrared (FTIR), X-ray Photoelectron Spectroscopy (XPS), and Brunauer-Emmett-Teller (BET) to explore the correlation between microstructure, morphology, and properties. Our finding reveals that not only N and P can affect adsorption, but also the novel cathode preparation method, which employs a removable NaCl templated hierarchical porous electrode, has a profound effect on the electrochemical and CDI results. This finding will open a new perspective in designing electrodes for all electrochemical systems.

Porous material characterization with Bayesian and machine learning method

Two main classes of characterization methods are usually employed for acoustic parameters of porous media, namely the analytical inversion method or the numerical fitting procedure. While analytical inverse methods suffer from a high sensivity to the operator, the numerical fitting methods can lead to non physical sets of parameters. The fitting procedure can be bounded by the analytical inversion. The Bayesian method, which is presented in this work, is the appropriate tool to couple these methods. It enables to carry out a numerical fitting procedure using the analytical inversion as prior estimation while increasing the confidence in the resulting uncertainties. In a second part, machine learning method and data mining are used as an alternative characterization method which could be a good prior estimation for the Bayesian method. Results and performances will be shown for various porous media.