In recent years, metal-organic frameworks (MOFs) have been identified as promising adsorbents in a number of industrially relevant, yet challenging, separations, including the removal of propane from propane/propylene mixtures and the separation of mixtures of xylene isomers. The highly tuneable nature of MOFs - wherein structures may be constructed from a variety of diverse building blocks – has resulted in the publication of a staggering number of frameworks incorporating a wide range of network topologies, pore shapes and pore diameters. As a result, there are a huge number of candidate adsorbents to consider for a given separation. Molecular simulation techniques allow the identification of those structural features and characteristics of a MOF which exert the greatest influence on the adsorption and separation of the compounds of interest, providing insights which can both guide the selection and accelerate the development of adsorbents for a specific application. The separation of propane/propylene mixtures via adsorption has typically focused on selective adsorption of the olefin, propylene, via specific olefin-adsorbent interactions. These propylene-selective MOFs result in processes which selectively remove the most abundant species in the process stream and are typically characterised by high heats of adsorption, resulting in large adsorption units and adsorbents which are difficult to regenerate. In this work, the capability of MOFs to selectively adsorb propane over propylene is explored, potentially allowing for the design of smaller and more energy-efficient adsorption units. By studying a range of different MOFs as well as carbon-based model pores, it was found that the low-pressure selectivity of the structure is determined by the strength of the electrostatic interaction between propylene and the framework, while the adsorptive preference at industrially-relevant pressures is dominated by the enhanced packing efficiency of propylene over propane. The confinement of C3 molecules, however, may be employed to negate this entropic advantage and guide the development of materials which selectively adsorb propane over propylene. It has recently been reported that the adsorptive preference of a MOF for one xylene isomer over another may be predicted based solely on the pore size distribution of the structure. In this work, the impact of pore size on selectivity was studied systematically in both one-dimensional model pore systems of varying geometries and analogous published MOF structures. The ability of the framework to discriminate between xylene molecules in these systems was found to be determined primarily by the different packing arrangements available to the different isomers – while small pores were found to favour the slimmest of the isomers, larger pores were found to favour the more compact ortho- isomer. Finally, the adsorption and diffusion of xylene isomers in a more complex MOF, UiO-66(Zr), was studied in depth. Simulations were able to correctly predict the previously-reported preference of the MOF for ortho-xylene (oX). The smaller volume of the oX molecule compared to the other isomers was found to be responsible both for an enhanced entropic contribution and higher guest-host interaction energies. The importance of framework flexibility in the diffusion of xylene isomers in UiO-66(Zr) was also explored, with distortion of the structure in response to interaction with adsorbed molecules found to be essential in allowing xylenes to diffuse through the pore space.

Metal--organic frameworks (MOFs) are porous crystalline materials that are synthesized from rigid organic ligands and metal-containing clusters. They are highly tunable as a number of different structures can be made by simply changing the organic ligand and/or metal ion. MOFs are a promising class of materials for many energy-related applications, including H2 storage and CO2 capture and sequestration. Computational studies can provide insights into MOFs and the mechanism of gas sorption and separation. Theoretical studies on existing MOFs are performed to determine what structural characteristics leads to favorable gas sorption mechanisms. The results from these studies can provide insights into designing new MOFs that are tailored for specific applications. In this work, grand canonical Monte Carlo (GCMC) simulations were performed in various MOFs to understand the gas sorption mechanisms and identify the favorable sorption sites in the respective materials. Experimental observables such as sorption isotherms and associated isosteric heat of adsorption, Qst, values can be generated using this method. Outstanding agreement with experimental measurements engenders confidence in a variety of molecular level predictions. Explicit many-body polarization effects were shown to be important for the modeling of gas sorption in highly charged/polar MOFs that contain open-metal sites. Indeed, this was demonstrated through a series of simulation studies in various MOFs with rht topology that contain such sites. Specifically, the inclusion of many-body polarization interactions was essential to reproduce the experimentally observed sorption isotherms and Qst values and capture the binding of sorbate molecules onto the open-metal sites in these MOFs. This work also presents computational studies on a family of pillared square grid that are water-stable and display high CO2 sorption and selectivity. These MOFs are deemed promising for industrial applications and CO2 separations. Simulations in these materials revealed favorable interactions between the CO2 molecules and the SiF62- pillars. Further, the compound with the smallest pore size exhibits the highest selectivity for CO2 as demonstrated through both experimental and theoretical studies. Many other MOFs with intriguing sorption properties are investigated in this work and their sorption mechanisms have been discerned through molecular simulation.

Carbonaceous engine deposits tend to accumulate on most of the inner surfaces of the car engine. The presence of these deposits leads to a deteriorated efficiency of the engine and a number of adverse effects, such as higher propensity of the engine to knock. It has been proposed that selective adsorption of some of the fuel components in the porous deposits (and changing composition of the pre-combustion fuel) could be a contributing mechanism of the diminished efficiency of the engine. This, as well as other mechanisms of the deposits action, crucially depend on the porous structure of the material. Therefore, the aim of this investigation is to develop a method, which is able to accurately characterize the internal porous structure of the engine deposits and predict their adsorption properties at different conditions. This should allow us to assess whether the selective adsorption of fuel components is indeed a plausible contributing mechanism to the diminished performance of the engine. Accurate characterization of the engine deposits faces several difficulties due to their complex porous structure and chemical composition. A widely adopted approach in the characterization of activated carbons, which combines molecular simulation, specifically grand canonical Monte Carlo (GCMC) in slit pores, and experimental adsorption isotherms, is the starting point for the method suggested in this work. In this thesis, we will demonstrate that, by systematic modification of the solid-fluid interaction in the molecular simulation, we are able to correctly account for the chemical structural heterogeneity of the samples used. The new parameters of solid-fluid interaction allow us to extract representative pore size distributions and investigate the adsorption properties under different conditions of temperature and pressure, based on the obtained pore size distribution. Specifically, using the experimental data from a single ethane isotherm at 278K we accurately predict ethane adsorption at other temperatures and in different samples. Additionally, the proposed method is able to predict the adsorption of more complex hydrocarbons, i.e. n-butane and isobutane. The performance of the method is assessed by comparing the simulations results with the experimental adsorption measurements data on the engine deposits samples. Another important capability of the method is that it enables us to generate adsorption predictions of two key components commonly used to represent the combustion properties of the fuel, n-heptane and isooctane. We explore the equilibrium adsorption properties of these components based on the determined pore size distributions of the deposit samples. The results presented in the thesis highlight the importance of the adsorption in the internal porous structure of the engine deposits. The present study reinforces the value of molecular simulation combined with a limited number of experimental measurements, to accurately characterize heterogeneous carbonaceous materials and to make predictions at different conditions with sufficient precision.

Molecular dynamics (MD) simulations find their applications in fundamental understanding of molecular level mechanisms of physical processes. This assists in tuning the key features affecting the development of the novel hybrid materials. A certain application demanding the need for a desired function can be cherished through the hybrids with a blend of new properties by a combination of pure materials. However, to run MD simulations, an accurate representation of the interatomic potentials i.e. force-fields (FF) models remain a crucial aspect. This thesis intricately explores the fusion of MD simulations, uncertainty quantification, and data-driven methodologies to accelerate the computational design of innovative materials and models across the following interconnected chapters. Beginning with the development of force fields for atomic-level systems and coarse-grained models for FCC metals, the study progresses into exploring the intricate interfacial interactions between 2D materials like graphene, MoS2, and water. Current state-of-the-art model development faces the challenge of high dimensional input parameters' model and unknown robustness of developed model. The utilization of advanced optimization techniques such as particle swarm optimization (PSO) integrated with MD enhances the accuracy and precision of FF models. Moreover, the bayesian uncertainty quantification (BUQ) assists FF model development researchers in estimating the robustness of the model. Furthermore, the complex structure and dynamics of water confined between and around sheets was unraveled using 3D Convolutional Neural Networks (3D-CNN). Specifically, through classification and regression models, water molecule ordering/disordering and atomic density profiles were accurately predicted, thereby elucidating nuanced interplays between sheet compositions and confined water molecules. To further the computational design of hybrid materials, this thesis delves into designing and investigating polymer composites with functionalized MOFs shedding light on crucial factors governing their compatibility and performance. Therefore, this report includes the study of structure and dynamics of functionalized MOF in the polymer matrix. Additionally, it investigates the biomedical potential of porous MOFs as drug delivery vehicles (DDVs). Often overlooked is the pivotal role of solvents (used in MOF synthesis or found in relevant body fluids) in the drug adsorption and release process. This report underscores the solvent's impact on drug adsorption within MOFs by comparing results in its presence and absence. Building on these findings, the study delves into the effects of MOF functionalization on tuning the drug adsorption and release process. It further explores how different physical and chemical properties influence drug adsorption within MOFs. Furthermore, the research explores the potential of functionalized MOFs for improved carbon capture, considering their application in energy-related contexts. By harnessing machine learning and deep learning, the thesis introduces innovative pathways for material property prediction and design, emphasizing the pivotal fusion of computational methodologies with data-driven approaches to advance molecular-level understanding and propel future material design endeavors. / Doctor of Philosophy / Envision a world where scientific exploration reaches the microscopic scale, powered by advanced computational tools. In this frontier of materials science, researchers employ sophisticated computer simulations to delve into the intricate properties of materials, particularly focusing on Metal-Organic Frameworks (MOFs). These MOFs, equivalent to microscopic molecular sponges, exhibit remarkable abilities to capture gases or hold medicinal drug compounds. This thesis meticulously studies MOFs alongside materials like graphene, Boron Nitride and Molybdenum disulfide, investigating their interactions with water with unprecedented precision. Through these detailed explorations and the fusion of cutting-edge technologies, we aim to unlock a future featuring enhanced drug delivery systems, improved energy storage solutions, and innovative energy applications.

Orientadores: Munir Salomão Skaf, Vitor Rafael Coluci / Tese (doutorado) - Universidade Estadual de Campinas, Instituto de Química / Made available in DSpace on 2018-08-26T20:42:42Z (GMT). No. of bitstreams: 1 Faro_TatianaMellodaCosta_D.pdf: 8054394 bytes, checksum: ce0d79df42ce453ffc39b51bf0ad1094 (MD5) Previous issue date: 2015 / Resumo: Atualmente, a economia mundial depende do uso de combustíveis fósseis para a geração de energia. Esse modelo apresenta problemas ambientais graves, uma vez que o petróleo é um material não-renovável e muito poluente. O gás hidrogênio apresenta-se como uma alternativa promissora para substituir os combustíveis utilizados atualmente devido a um conjunto de características positivas: ele é atóxico, tem uma alta densidade energética gravimétrica e gera apenas água como produto de sua combustão. Apesar de tais vantagens, ele ainda não é utilizado comercialmente em larga escala. O maior empecilho tecnológico para que o hidrogênio possa substituir os combustíveis fósseis está no seu armazenamento. Existem diversas propostas para armazenar o hidrogênio, como tanques contendo o hidrogênio nas formas de gás pressurizado ou de líquido, além de sistemas sólidos que permitam a sua adsorção. Todavia, nenhum sistema construído até então foi capaz de armazenar o hidrogênio de forma tão barata, segura e eficaz quanto seria necessário. Nanoestruturas de carbono são vistas como uma boa alternativa para construir dispositivos de armazenamento de hidrogênio baseados na fisissorção. Os nanopapiros de carbono, formados por folhas de grafeno enroladas no formato de um papiro, são considerados particularmente promissores para armazenar o hidrogênio, uma vez que possuem uma alta área superficial, extremidades abertas e distâncias intercamadas facilmente controláveis. Na primeira etapa deste trabalho, realizamos simulações de Dinâmica Molecular (MD) para estudar a dinâmica e a estabilidade de diversos nanopapiros em função de alguns dos seus parâmetros estruturais. Posteriormente, aplicamos o método de Monte Carlo Grand-Canônico (GCMC) para estudar o processo de adsorção de hidrogênio em nanopapiros selecionados, de forma a caracterizar quantitativamente e qualitativamente as fases adsorvidas / Abstract: Presently, the world economy depends on the use of fossil fuels to generate energy. This model presents serious environmental problems, since petroleum is a non-renewable and very pollutant material. Hydrogen gas presents itself as a promising alternative to substitute the fuels currently used due to a few positive characteristics: it is non-toxic, possesses a high gravimetric energetic density and only generates water as a combustion byproduct. In spite of all these advantages, hydrogen still isn't used commercially in a large scale. The biggest technological drawback for hydrogen to substitute fossil fuels is in its storage. There are many proposed ways to store hydrogen, such as tanks containing highly pressurized or liquid hydrogen, or solid systems that allow its adsorption. However, no system built up to the date had been able to store hydrogen as cheap, safe and efficiently as necessary. Carbon nanostructures are seen as a good alternative to build hydrogen storage devices based on physisorption. Carbon nanoscrolls, formed by graphene sheets scrolled in a papirus-like shape, are considered as particularly promising adsorption materials, since they possess a high surface area, open edges and easily controllable interlayer distances. In the first step of this work, we made Molecular Dynamics (MD) simulations to study the dynamics and the stability of several nanoscrolls as a function of their structural parameters. Subsequently, we used the Grand-Canonical Monte Carlo (GCMC) method to study the hydrogen adsorption process in selected nanoscrolls, as to characterize the adsorbed phases quantitatively and qualitatively / Doutorado / Físico-Química / Doutora em Ciências

<p>Co and Ni are two major elements in high temperature structural alloys that include superalloys for turbine engines and hard metals for cutting tools. The recent development of complex concentrated alloys (CCAs), loosely defined as alloys without a single principal element (e.g. CoNiFeMn), offers additional opportunities in designing new alloys through extensive composition and structure modifications. Within CCAs and Co- and Ni-based superalloys, solid-solution strengthening and stacking fault energy engineering are two of the most important strengthening mechanisms. While studied for decades, the potency and quantitative materials properties of these mechanisms remain elusive. </p> <p><br></p> <p>Solid-solution strengthening originates from stress field interactions between dislocations and solute of various species in the alloy. These stress fields can be engineered by composition modification in CCAs, and therefore a wide range of alloys with promising mechanical strength may be designed. This thesis initially reports on experimental and computational validation of newly developed theories for solid-solution strengthening in 3d transition metal (MnFeCoNi) alloys. The strengthening effects of Al, Ti, V, Cr, Cu and Mo as alloying elements are quantified by coupling the Labusch-type strengthening model and experimental measurements. With large atomic misfits with the base alloy, Al, Ti, Mo, and Cr present strong strengthening effects comparable to other Cantor alloys. </p> <p> </p> <p>Stacking fault energy engineering can enable novel deformation mechanisms and exceptional strength in face-centered cubic (FCC) materials such as austenitic TRIP/TWIP steels and CoNi-based superalloys exhibiting local phase transformation strengthening via Suzuki segregation. We employed first-principles calculations to investigate the Suzuki segregation and stacking fault energy of the FCC Co-Ni binary alloys at finite temperatures and concentrations. We quantitatively predicted the Co segregation in the innermost plane of the intrinsic stacking fault (ISF). We further quantified the decrease of stacking fault energy due to segregation.  </p> <p><br></p> <p>We further investigated the driving force of segregation and the origin of the segregation behaviors of 3d, 4d and 5d elements in the Co- and Ni-alloys. Using first-principles calculations, we calculated the ground-state solute-ISF interaction energies and revealed the trends across the periodic table. We discussed the relationships between the interaction energies and the local lattice distortions, charge density redistribution, density of states and local magnetization of the solutes. </p> <p><br></p> <p>Finally, this thesis reports on new methodologies to accelerate first-principles calculations utilizing active learning techniques, such as Bayesian optimization, to efficiently search for the ground-state energy line of the system with limited computational resources. Based on the expected improvement method, new acquisition strategies were developed and will be compared and presented. </p>