Physical adsorption test analysis - Database & Sql Blog Articles

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◆Hysteresis Loop 1. The hysteresis loop occurs due to capillary condensation, where nitrogen molecules condense in mesopores under pressure lower than the normal saturation pressure. This process happens at the liquid surface of an annular adsorption membrane on the pore walls. During desorption, the process starts from the spherical meniscus at the pore opening, leading to a mismatch between the adsorption and desorption isotherms, forming a hysteresis loop. Another explanation involves the contact angle: during adsorption, the advancing angle is observed, while during desorption, the receding angle is measured. These differences affect the Kelvin equation. Although both mechanisms may coexist, many prefer the first explanation as it provides a more intuitive understanding (e.g., Xuan Ji). 2. Types of Hysteresis Loops Each type of hysteresis loop corresponds to different pore structures. For example: - **H1** represents a uniform pore model, often visualized as straight channels. However, it’s important to note that H1 does not necessarily indicate a hexagonal structure. While S1-15 might show hexagonal ordering via small-angle XRD, H1 itself only suggests ordered mesopores without specifying the exact geometry. - **H2** is more complex and is typically associated with "ink-bottle" pores or irregular pore networks. During desorption, liquid nitrogen trapped in narrow necks can suddenly escape, creating a distinct hysteresis pattern. - **H3** shows higher adsorption at high pressures, suggesting slit-shaped pores formed by stacked flaky particles. - **H4** also refers to slit-like pores but is typically associated with layered structures rather than particle stacking. 3. In some cases, the medium-pressure region shows significant adsorption without forming a hysteresis loop. At relative pressures around 0.2–0.3, the pore radius is very small, and capillary condensation leads to overlapping adsorption and desorption curves. For example, MCM-41 with pore sizes of 2–3 nm may exhibit no hysteresis, indicating a highly ordered mesoporous structure. ◆Mesoporous Analysis The BJH model (Barrett-Joiner-Halenda) is widely used for mesoporous analysis, based on the Kelvin equation applied to cylindrical pores. It works well within the mesoporous range but tends to underestimate pore sizes. A more accurate method, KJS (Kruk-Jaroniec-Sayari), was developed for analyzing materials like MCM-41 and SBA-15. It offers better precision, especially for pore sizes between 2 and 6.5 nm, and has since been extended to cover larger ranges, up to 30 nm for SBA-15. ◆t-Plot and αs Methods These are techniques used to analyze entire adsorption or desorption curves. The t-plot method involves plotting the monolayer adsorption amount against the thickness of the adsorbed layer, which is calculated by multiplying the number of layers by the monolayer thickness (0.354 nm). Specific surface area can be estimated using this data. For non-porous samples, the t-plot forms a straight line through the origin. When micropores or mesopores are present, the curve becomes nonlinear and requires separate analysis. The αs method, proposed by Sing, uses the adsorption amount at a relative pressure of 0.4 instead of the monolayer value. It's commonly used in instrument-based analyses and shares similarities with the t-plot. The two methods are related, with the conversion formula: t = 0.538αs. ◆Microporous Analysis Analyzing micropores requires precise vacuum control, temperature regulation, and longer testing times—often ten to twenty times longer than for mesoporous materials. Due to the similarity between micropore size and probe molecule size, some molecules may not penetrate, making it challenging to obtain accurate results. Different analytical methods must be selected based on the sample type. If necessary, referring to literature or conducting a batch of tests is recommended. While the overall trend of the results is usually reliable, it remains difficult to fully characterize all pore sizes with a single model. The NLDFT (Nonlinear Density Functional Theory) approach is effective but less commonly used in published studies.

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