A. James Clark School of Engineering
Permanent URI for this communityhttp://hdl.handle.net/1903/1654
The collections in this community comprise faculty research works, as well as graduate theses and dissertations.
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Item WATER, ION, AND GRAPHENE: AN ODYSSEY THROUGH THE MOLECULAR SIMULATIONS(2019) Wang, Yanbin; Das, Siddhartha; Mechanical Engineering; Digital Repository at the University of Maryland; University of Maryland (College Park, Md.)Water is known as the most common and complicated liquid on earth. Meanwhile, graphene, defined as single/few layer graphite, is the first member in the 2-dimensional materials family and has emerged as a magic material. Interactions between water and graphene generate many interesting phenomena and applications. This thesis focuses on applying molecular dynamics (MD), a powerful computational tool, for investigating the graphene-water interactions associated with various energetic and environmental applications, ranging from the wettability modification, species adsorption, and nanofluidic transport to seawater desalination. A key component of one domain of applications involves a third component, namely salt ions. This thesis attempts that and discovers a fundamentally new way in which the behavior of ions with the air-water interfaces should be probed. In Chapter 1, we introduce the motivation and methods and the overall structure of this thesis. Chapter 2 focuses on how MD simulations connect the statistical mechanics theory with the experimental observations. Chapter 3 discusses the simulation results revealing that the spreading of a droplet on a nanopillared graphene surface is driven by a pinned contact line and bending liquid-surface dynamics. Chapter 4 probes the interactions between a water drop and a holey graphene membrane, which is prepared by removing carbon atoms in a circular shape and which can serve as catalyst carriers. Accordingly, chapter 5 studies the effects of various terminations on water-holey graphene interactions, showing that water flows faster and more thoroughly through the membrane with hydrophobic terminations, compared to that with hydrophilic terminations. In chapter 6, simulations describe the generation of enhanced water-graphene surface area during the water-holey-graphene interactions in presence of an applied time-varying force on the water drop. In chapter 7, we focus on the ion-water interaction at the water-air interface to fully understand the fluidic dynamics during any seawater desalination. Our research revisits the energetic change while ion approaches water-air interface and shows that the presence of ion at the interface enhances capillary-wave fluctuation. Finally, in chapter 8 we summarize the main findings of the thesis and provide the scope of future research.Item Modeling and Experimental Techniques to Demonstrate Nanomanipulation With Optical Tweezers(2011) Balijepalli, Arvind K.; Gupta, Satyandra K; LeBrun, Thomas W; Mechanical Engineering; Digital Repository at the University of Maryland; University of Maryland (College Park, Md.)The development of truly three-dimensional nanodevices is currently impeded by the absence of effective prototyping tools at the nanoscale. Optical trapping is well established for flexible three-dimensional manipulation of components at the microscale. However, it has so far not been demonstrated to confine nanoparticles, for long enough time to be useful in nanoassembly applications. Therefore, as part of this work we demonstrate new techniques that successfully extend optical trapping to nanoscale manipulation. In order to extend optical trapping to the nanoscale, we must overcome certain challenges. For the same incident beam power, the optical binding forces acting on a nanoparticle within an optical trap are very weak, in comparison with forces acting on microscale particles. Consequently, due to Brownian motion, the nanoparticle often exits the trap in a very short period of time. We improve the performance of optical traps at the nanoscale by using closed-loop control. Furthermore, we show through laboratory experiments that we are able to localize nanoparticles to the trap using control systems, for sufficient time to be useful in nanoassembly applications, conditions under which a static trap set to the same power as the controller is unable to confine a same-sized particle. Before controlled optical trapping can be demonstrated in the laboratory, key tools must first be developed. We implement Langevin dynamics simulations to model the interaction of nanoparticles with an optical trap. Physically accurate simulations provide a robust platform to test new methods to characterize and improve the performance of optical tweezers at the nanoscale, but depend on accurate trapping force models. Therefore, we have also developed two new laboratory-based force measurement techniques that overcome the drawbacks of conventional force measurements, which do not accurately account for the weak interaction of nanoparticles in an optical trap. Finally, we use numerical simulations to develop new control algorithms that demonstrate significantly enhanced trapping of nanoparticles and implement these techniques in the laboratory. The algorithms and characterization tools developed as part of this work will allow the development of optical trapping instruments that can confine nanoparticles for longer periods of time than is currently possible, for a given beam power. Furthermore, the low average power achieved by the controller makes this technique especially suitable to manipulate biological specimens, but is also generally beneficial to nanoscale prototyping applications. Therefore, capabilities developed as part of this work, and the technology that results from it may enable the prototyping of three-dimensional nanodevices, critically required in many applications.Item SEQUENCE MODELING OF RAFT POLYMERIZATIONS WITH THE METHOD OF MOMENTS(2008-10-13) Zargar, Amin; Schork, Joseph; Chemical Engineering; Digital Repository at the University of Maryland; University of Maryland (College Park, Md.)Attempts to model the sequence structure of copolymers consisted of probabilistic functions that were incomplete and inaccurate. A novel technique to track sequence parameters is developed that determines not only copolymer composition, but sequence distribution as well. RAFT polymerizations are simulated with two independent and concurrent models to track MWD, conversion, copolymer composition, and sequence characteristics. Batch polymerizations are simulated with varying reactor conditions as a proof-of-concept to illustrate the power of the sequence model to track the composition of the polymer. Series of CSTR and PFR reactors with varying reactor conditions are then presented as applications to iteratively fine-tune copolymers with predetermined sequence and compositional structure.