Structural motifs for the BC2N superlattices were identified from a systematic search based on a greedy algorithm. Using a tree data structure, we have retrieved seven structural models for c-BC2N 1x1x lattice which were identified previously by Sun et al. [Phys. Rev. B 64, 094108 (2001)]. Furthermore, the atomic structures with the maximum number of C-C bonds for c-BC2N 2x2x2, 3x3x3, and 4x4x4 superlattices were found by imposing the greedy algorithm in the tree data structure. This new structural motif has not been previously proposed in the literature. A total of up to 512 atoms in the c-BC2N superlattice are taken into consideration. The atoms in these superlattices are in diamond-like structural form. Furthermore, the C atoms, as well as B and N atoms, form the octahedral motif separately. The octahedral structure consisting of C is bounded with {111} facets, and each facet is interfaced to a neighboring octahedral structure consisting of B and N atoms. The electronic and mechanical properties of newly identified low energy structures were analyzed.

Research into efficient thermoelectric materials has gained traction recently be cause of their applications in converting waste heat into electricity. Chalcogenide and transition metals are among emerging classes of materials for potentials thermoelectric applications. In this work, we employ first-principle calculations and the Boltzmann transport equation along with self-consistent phonon theory to evaluate the thermoelectric performance of barium chalocgenide perovskites BaBX3 (B= Zr, Hf and X= S, Se) in the orthorhombic perovskite phase, as well as BaZreS3 in the needle-like phase. Vibrational properties were investigated through the phonon dispersion, mode Gruneisen parameters and lattice thermal conductivity to understand and measure the anharmonicity in the systems. The carrier transport properties including the Seebeck coefficient, electric conductivity and the electron contribution to thermal conductivity were evaluated. We report ultra low lattice thermal conductivity of κl = 1.23W/mK for BaHSe3 at T=300K by including high order phonon scattering events. A maximum power factor of 1.16 mW/mK2 was achieved at high n-doping concentration, resulting in a thermoelectric figure of merit zT = 0.2 for BaHSe3.

A new multiresolution scheme based on interpolating scaling function(ISF) on adaptive gridding(AG) shows promising in the first principle calculation. We also use ISFs on solving Poisson equation(PE), and find good approximations on the expansions of the second derivatives of ISFs. It is simpler than the wavelet scheme and fully implements the fast wavelet transformation so that the method is very suitable to problems with frequently updating charge density such as the first-principle calculation in electronic structures in atoms, molecules, and solids. Although the scheme is similar to the AG scheme on real space, the ISFs can represent fields more effectively and it needs less grids than the scheme of real space does. This simple and effective method provides an alternative to both the real space and the wavelet methods in the first principle calculation. Also, The method can be easily parallelized due to the block structure of the grid layout.

Abstract The search for nanoscale active electronic devices has been an important objective in nanoscience and nanotechnology. In this study, the electronic and transport properties of the benzene-1,4-dithiol-molecule (BDT) and Au-atom-S-benzene-ring-O-(SBO)-Au-atom junctions and the Au-AlN(0001)-Au polar semiconductor junction have been calculated using the first-principles calculation method and a new integrated piecewise thermal equilibrium approach for the current. The current-voltage (I-V) and conductance-voltage (C-V) characteristic curves obtained for the Au-BDT-Au molecular junction agreed reasonably well with experimental ones. The study of Au-BDT-Au identifies that treating Au 5d electrons as core electrons and letting the S end of BDT be bonded to the Au surface directly overestimated the current. Calculated I-V characteristic curve revealed that the asymmetric Au-SBO-Au molecular junction has a pulse-like I-V characteristic curve with dual differential conductance, which resembled well the one observed experimentally. The analysis of the electronic structures showed that this dual differential conductance transport property was due to a subtle charge transfer at the electrode-molecule contacts. The calculated J-V characteristic curve of the Au-Al(0001)-Au junction shows coexistence of ohmic, switching effect and negative differential conductance. The electronic structure calculations show the existence of an intrinsic band tilt due to the polar nature of the AlN(0001) film, which gives rise to an asymmetric transport property of the junction and the presence of hole states at the N-surface side and interface states at the Al-surface side of the AlN film. The bias induced changes of the hole states, interface states and the states of the Al and N ions in central layers in the vicinity of the local chemical potential give rise to the interesting transport property of the Au-AlN(0001)-Au junction.

The first-principles calculation method has been used to obtain electronic and structural properties of few-layer-graphenes (FLG) with and without an external electric potential Vext. For Vext=0, the AB stacked two-layer FLG has a band overlapping of 9meV. However, an energy gap (Eg) emerges when Vext is greater than about 0.04Volts. Beyond this threshold, Eg increases monotonically with the increase of Vext. The Eg vs. Vext result suggests a semi-metal-semiconductor transition in the AB stacked two-layer FLG, which can be utilized as a nanoscale electronic switch. Three- and four-layer AB stacked FLG¡¦s don¡¦t have a similar dependence of Eg on Vext

The U.S. Food and Drug Administration has accepted the guidelines put forth by the International Conference on Harmonization (ICH-Q8) that allow for operational flexibility within a validated design space. These Quality by Design initiatives have allowed drug manufacturers to incorporate more rigorous scientific controls into their production streams. <br>Fully automated control systems can incorporate information about a process back into the system to adjust process variables to consistently hit product quality targets (feedback control), or monitor variability in raw materials or intermediate products to adjust downstream manufacturing operations (feedforward control). These controls enable increased process understanding, continuous process and product improvement, assurance of product quality, and the possibility of real-time release. Control systems require significant planning and an initial investment, but the improved product quality and manufacturing efficiency provide ample incentive for the expense. <br>The fluid bed granulation and drying unit operation was an excellent case study for control systems implementation because it is a complex unit operation with dynamic powder movement, high energy input, solid-liquid-gas interactions, and difficulty with scale-up development. Traditionally, fluid bed control systems have either used first principle calculations to control the internal process environment or purely empirical methods that incorporate online process measurements with process models. This dissertation was predicated on the development of a novel hybrid control system that combines the two traditional approaches. <br>The hybrid controls reduced the number of input factors for the creation of efficient experimental designs, reduced the variability between batches, enabled control of the drying process for a sensitive active pharmaceutical ingredient, rendered preconditioned air systems unnecessary, and facilitated the collection of data for the development of process models and the rigorous calculation of design spaces. Significant variably in the inlet airstream was able to be mitigated using feedforward controls, while process analytical technology provided immediate feedback about the process for strict control of process inputs. Tolerance surfaces provided the ideal tool for determining design spaces that assured the reduction of manufacturing risk among all future batches, and the information gained using small scale experimentation was leveraged to provide efficient scale-up, making these control systems feasible for consistent use. / Mylan School of Pharmacy and the Graduate School of Pharmaceutical Sciences / Pharmaceutics / PhD / Dissertation

First-principle modelling of chemical processes and their unit operations has been of great interest in the chemical process, as well as the control and allied industries over the past decades. This is because it offers the opportunity to develop virtual representations (models) of real process systems, which can be used to describe and predict the dynamic behaviour of those systems. These models are based on the fundamentals of the transport phenomena of fluid dynamics (involving momentum transfer), mass transfer, and energy transfer of the systems they describe. A first-principle model of a semi-batch rhodium dissolution chemical process has been developed. It describes the dynamic behaviour of two exothermic reactions, occurring simultaneously in a semi-batch process. The dissolution of 29 kg of solid crude rhodium sponge (Rh) into 546 L of a solution of hydrochloric acid (HCl(aq)), to produce a solution of aqueous rhodium(III) chloride (RhCl3.H2O), as well as the reaction of chlorine (Cl2(aq)) with water (H2O(l)) to produce some more HCl(aq) in the reactor. The model was formulated as a system of explicit ordinary differential equations (ODEs), which demonstrated some good and stable qualitative tracking of the temperature and pressure data of the real reactor. The molar responses of all chemical species, as well as the heats of reactions, showed to be consistent with the description of the process, and no negative values of those variables were generated. Estimates of the key parameters of heat and mass transfer coefficients, arrhenius constants, and activation energies of reactions were assumed and tuned to satisfaction by trial-and-error, but not optimised. This is because during simulations, the numerical solver would often fail to integrate the equations, due to the appearance of large derivatives in some model equations whenever those parameters varied, thereby stopping simulations. Finally, the model was validated with a set of data from 45 batches. For all simulations done, the simulated temperature responses showed better prediction of data than the simulated pressure responses did, with an average percentage accuracy of 80% against 60 percent, respectively. / Dissertation (MSc)--University of Pretoria, 2017. / Anglo American Platinum / BluESP (Pty) Ltd / Chemical Engineering / MSc / Unrestricted

京都大学 / 新制・課程博士 / 博士(工学) / 甲第24616号 / 工博第5122号 / 新制||工||1979(附属図書館) / 京都大学大学院工学研究科材料工学専攻 / (主査)教授 田中 功, 教授 奥田 浩司, 教授 中村 裕之 / 学位規則第4条第1項該当 / Doctor of Philosophy (Engineering) / Kyoto University / DGAM

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Third submission of my master thesis, first one didn't finish for some reason, the second I think I forgot to include my name. / This thesis focuses on the creation of new parallel hybrid model designs for prediction and control in batch and fed-batch reactors within Model Predictive Control (MPC) frameworks. In the hybrid model, the first principle (FP) explains the dynamics and the residual Subspace Identification (SID) model explains the error between the FP and the process. Modifications to the structure of the hybrid model are motivated by limitations of MPC frameworks. MPCs need accurate models to explain the system dynamics to make informed control decisions, and mechanistic models can be difficult to implement due to challenges of solving the optimization problem in real time. Two tools are demonstrated to help solve these problems. The first tool, Residual First Principle 0 Hybrid (RFP0H) model, helps to deal with the intractability of a mechanistic model in a hybrid modelling framework. The input for the FP model is kept constant and the SID predicts the error between the first principle and the process. Allowing for the desired output to be subtracted by the predicted FP to create a desired error value. Thus, MPC control only needs to be solved using the linear SID model in a linear or quadratic framework. Making a potentially intractable problem, tractable in MPC. This is demonstrated using a simulated fed-batch crystallization process. The second tool, Scaling Factor First Principle 0 Hybrid (SFFP0H) model, modifies the hybrid model structure to multiple the sub-models’ outputs together. The SID data driven model predicts a factor to scale the FP output for the process prediction. The results demonstrate that the SFFP0H model has increased predictive ability and has smaller variability in control compared to the RFP0H model. Helping to solve the problem of needing accurate models within an MPC formulation. This is demonstrated by using a laboratory scale batch polymerization process. / Thesis / Master of Applied Science (MASc)