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شبیه سازی هسته سازی الکترولیت ها با حلال های صریح از طریق دو روش
Simulate the Nucleation of Electrolytes with Explicit Solvents Via Two Approaches
Nucleation is a key step in the synthesis of crystalline materials, whether from the melt or from solution. Despite the importance of these early-stage nucleation processes, a detailed atomic-level understanding is often lacking due to the difficulties in probing the nuclei at the associated length- and time-scales. In this thesis, we propose two approaches to model the nucleation in atomic-level. We first introduce a hybrid grand canonical Monte Carlo/molecular dynamics (GCMC/MD) method for simulating the nucleation of weak electrolytes in explicit solvent. The approach is capable of efficiently simulating the nucleation of dilute solutions while including the atomistic influence of the surrounding solvent, and provides access to the full nucleation free energy surface and associated nucleation free energy barrier. After validating the method against a simple model system, we applied the approach to the nucleation of a low-solubility rock-salt structure in liquid water. We find that the calculated nucleation barriers, in conjunction with analytic rate theories, yields predicted nucleation rates that are in excellent agreement with brute-force MD simulations of the supersaturated solution. To further improve the efficiency and parallelism, we have developed a second simulation approach based on the graph structure of the nucleus. This approach models the nucleation for each individual cluster structure and averages the results according to their Boltzmann distribution, thus avoids complete structural sampling in one single simulation. The graph-based method was validated against lattice model and later tested for the low-solubility rock-salt system, which yields similar results with our hybrid GCMC/MD approach. We anticipate possible applications of above approaches to a wide variety of related weak electrolytes, including CaCO3, zeolites, and metal-organic frameworks.
تشخیص زودهنگام خوردگی از طریق حسگرهای طیف الکتروشیمیایی مبتنی بر هیدروژل
Early Detection of Corrosion via Hydrogel-Based Spectroelectrochemical Sensors
The backbone of the industrialized world is comprised of refined, zerovalent metal, a material which thermodynamically favors an oxidative return to more chemically stable states. There are many methods used to slow or delay this process, such as protective coatings, sacrificial anodes, and alloys, but no method can entirely prevent corrosion. This body of work instead proposes detecting the earliest chemical markers of corrosion: that is, metal ions as they solubilize from a metal surface. Such information would allow maintenance personnel to make informed decisions about the necessity or lack thereof of preventive maintenance, and intervene before advanced damage has a chance to occur.
This dissertation finds that hydrogel-based sensors are capable of such detection and offer a multisensory response, with colorimetric, electrical, volumetric and vibrational changes. Both the colorimetric and electrical trends were calibrated and used for quantification of metal ions both in solution and directly from metal substrate surfaces. Observing how the hydrogels responded to various metal ions contributed to a greater understanding of how ion-headgroup associations can affect the sensory responses of a hydrogel, something that can be exploited in future sensor work. The ability of the sensors to detect ions directly from metal surfaces allowed for an investigation of the protective quality of fatty acids as corrosion inhibitors. A range of chain lengths were tested using the hydrogels, and the comparison to current characterization techniques showed good correlation. This accessible technique, beyond contributing to the current meager literature of fatty acids as corrosion inhibitors, can also allow for the determination of acceptable benchmarks of corrosion, information that is sorely needed to efficiently steward global infrastructure.