Keywords

cryogenic, adsorption, aerogel, predictive model

Abstract

Commodities that are gaseous at standard temperature and pressure are generally stored in thick-walled pressure vessels, or as cryogenic liquids in vacuum-jacketed tanks. An advantage of cryogenic storage is that more mass can be stored per unit volume. However, cryogenic tanks are often bulky and cannot be made into conformal geometries. Adsorption storage in porous and flexible materials, such as aerogel blankets, is a promising method for storing these commodities. Previous studies have shown that when the commodity is adsorbed from the liquid cryogen, instead of from a gaseous state, the mass adsorbed per unit volume of aerogel blanket is higher than the mass for the same volume of cryogen at normal boiling point. However, while gaseous adsorption is well studied, studies on liquid cryogen adsorption have been limited, and therefore the mechanism is not as well understood. Currently, there are no models for predicting liquid cryogen adsorption, and those adapted from gaseous adsorption models have two main shortcomings. First, models such as the Brunauer-Emmett-Teller or deep-learning require extensive experimental data for validation, which are not currently available. Second, alternative solutions are based on computationally intensive methods, such as Monte-Carlo simulation.

This thesis presents a new closed-form predictive model for liquid cryogen adsorption that does not require computationally expensive techniques. Based on the principle that physisorption involves the adhesion of molecules to a surface through van der Waals forces, the model uses the van der Waals diameters of the cryogens and iteratively calculates the mass of each layer of adsorbed molecules on the aerogel surface.

Using existing datasets, the proposed predictive model is demonstrated to be versatile, and capable of predicting adsorption of cryogens in various porous materials, including pure silica aerogel and aerogel-based materials (e.g., aerogel blanket). The model achieves an accuracy between 96% to over 99%, depending on the type of adsorbent and cryogen. An important finding of this thesis is that, while the commodity inside the nanopores of the aerogel exists solely as adsorbed molecules, the density of the commodity inside the pores is equivalent to a solid close-packed crystal of that cryogen.

Completion Date

2025

Semester

Fall

Committee Chair

Raj Vaidyanathan

Degree

Master of Science in Materials Science and Engineering (M.S.M.S.E.)

College

College of Engineering and Computer Science

Department

Materials Science and Engineering

Format

PDF

Identifier

DP0029716

Document Type

Thesis

Campus Location

Orlando (Main) Campus

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