The magnetic properties of axially confined, hydrogenated single-walled carbon nanotubes (SWCNTs) of the (n,0)-type with n=5-24 are systematically explored by density functional theory. Emphasis is placed on the relation between the ground-state magnetic moments of SWCNTs and zigzag graphene nanoribbons (ZGNRs). Comparison between the SWCNTs considered here and ZGNRs of equal length gives rise to two basic questions: 1) how does the nanotube curvature affect the antiferromagnetic order known to prevail for ZGNRs, and 2) to what extent do the magnetic moments localized at the SWCNT edges deviate from the zero-curvature limit of n/3 μB? In response to these questions, it is found that systems with n≥7 display preference for antiferromagnetic order at any length investigated, whereas for n=5, 6 the magnetic phase varies with tube length. Furthermore, elementary patterns are identified that describe the progression of the magnitude of the magnetic moment with n for the longest tubes explored in this work. The spin densities of the considered SWCNTs are analyzed as a function of the tube length L, with L ranging from 3 to 11 transpolyene rings for n≥7 and from 3 to 30 rings for n=5 and 6. Magnetic carbon nanostructures are explored by density functional theory calculations on axially confined, single-walled carbon nanotubes (SWCNTs) of the (n,0)-type with n=5-24. For SWCNTs with n≥7, antiferromagnetic (AFM) order is favored energetically over ferromagnetic (FM) order for all lengths L investigated, whereas for n=5, 6 the magnetic phase varies with tube length (see picture).

The magnetic properties of axially confined, hydrogenated single-walled carbon nanotubes (SWCNTs) of the (n,0)-type with n=5-24 are systematically explored by density functional theory. Emphasis is placed on the relation between the ground-state magnetic moments of SWCNTs and zigzag graphene nanoribbons (ZGNRs). Comparison between the SWCNTs considered here and ZGNRs of equal length gives rise to two basic questions: 1) how does the nanotube curvature affect the antiferromagnetic order known to prevail for ZGNRs, and 2) to what extent do the magnetic moments localized at the SWCNT edges deviate from the zero-curvature limit of n/3 μB? In response to these questions, it is found that systems with n≥7 display preference for antiferromagnetic order at any length investigated, whereas for n=5, 6 the magnetic phase varies with tube length. Furthermore, elementary patterns are identified that describe the progression of the magnitude of the magnetic moment with n for the longest tubes explored in this work. The spin densities of the considered SWCNTs are analyzed as a function of the tube length L, with L ranging from 3 to 11 transpolyene rings for n≥7 and from 3 to 30 rings for n=5 and 6. Magnetic carbon nanostructures are explored by density functional theory calculations on axially confined, single-walled carbon nanotubes (SWCNTs) of the (n,0)-type with n=5-24. For SWCNTs with n≥7, antiferromagnetic (AFM) order is favored energetically over ferromagnetic (FM) order for all lengths L investigated, whereas for n=5, 6 the magnetic phase varies with tube length (see picture).

Submitted to the faculty of the School of Informatics in partial fulfillment of the requirements for the degree Master of Science in Chemical Informatics (Laboratory Informatics Specialization)Indiana University May 2006 / The Zymark™ System is a lab automation workstation that uses the Caliper Life Sciences (Hopkinton, MA) Zymate XP robot. At Indiana University-Purdue University Indianapolis, a Zymate is used in a course, INFO I510 Data Acquisition and Laboratory Automation, to demonstrate the fundamentals of laboratory robotics. This robot has been re-engineered to function with National Instruments™ graphical software program LabVIEW™. LabVIEW is an excellent tool for robotic control. Based on changing conditions, it is able to dynamically use data from any source to modify the operating parameters of a robot. For dynamically changing information, storage of that information must be readily accessible. For example, there is a need to continuously store and update the calibration data of the robot, populate the setting of each axis and positioning inside the workplace, and also store robot positioning information. This can be achieved by using a database which allows for robotic control data to be easily searched and accessed. To address this need, an interface was developed which would allow full, dynamic communication between any LabVIEW program (called “virtual instruments,” or VIs) and the database. This has been accomplished by developing a set of subVIs that can be dropped into the calling robotic control VIs. With these subVIs, a user has the ability to create table and column information, delete a table, retrieve table information by clicking a particular table name on the user interface, or query using any SQL-specific combination of columns or tables within the database. For robot functionality, subVIs were created to store and retrieve data such as calibration data points and regression calculations. / Chemical Informatics

京都大学 / 0048 / 新制・課程博士 / 博士(工学) / 甲第20699号 / 工博第4396号 / 新制||工||1683(附属図書館) / 京都大学大学院工学研究科機械理工学専攻 / (主査)教授 北村 隆行, 教授 西脇 眞二, 教授 鈴木 基史 / 学位規則第4条第1項該当 / Doctor of Philosophy (Engineering) / Kyoto University / DFAM

The vibrational entropy calculated by applying the harmonic oscillator approximation to all vibrational degrees of freedom is inherently inaccurate. One major reason is because low frequency modes such as internal rotations are not properly described by this approximation. Various techniques were developed in the past to overcome this problem. The hindered rotor potential can be approximated by a series of cosine functions, and the relevant coe cients can be determined by tting to a calculated potential energy surface. However, such a method is di cult and time consuming. Therefore, in this dissertation we propose and describe two less tedious approaches to determine entropy of internal rotational modes. The rst approximation is to express the barrier height in terms of the harmonic oscillator frequency, the local periodicity, and the reduced moment of inertia of the rotation and to approximate the torsional potential by a single cosine function. Thus, the 1D Schr odinger equation for internal rotations can be solved without nding the torsional potential, transition states, or barrier heights. We propose a further simpli cation to this approach, achieved through a simple mathematical formula, that interpolates the hindered rotor entropy between the free rotor and harmonic oscillator limits. We also propose a procedure to automatically determine the axis of rotation for any hindered rotor. The proposed methods were applied to determine the torsional entropy of n- alkanes from ethane to hexane. The entropies calculated from the proposed methods give good agreement with the experimental and accurately calculated values and have a signi cantly better accuracy than the harmonic oscillator approximation. Furthermore, we performed approximate and full hindered rotor treatments to nd the corrected vibrational entropy of bis(chromiumtricarbonyl) dibenzo[a,e]cyclooctatetraene (DBCOT). The eighth chapter of this dissertation is an independent molecular dynamics (MD) project to study how ethanol interacts with human and mouse Toll-Like- Receptor3 (TLR3) monomers and a TLR3-dsRNA complex. No major structural changes were observed during the ethanol docking and subsequent MD simulations, but the MD simulations revealed a reduction in the proportion of alpha helix present during a 1000 ns MD simulation on the h-TLR3 monomer in 0.5 percent ethanol.

Randek is a company that develops machines. The machines are used to build prefabricated houses. They have developed a CNC machine called Nailing Bridge that creates house walls. One of their issues is that they must predict the time it takes to build a wall because their customers need to know how long it takes to deliver their house. Our project solves this problem by making a program that calculates the time it takes to build a wall on the Nailing Bridge with help from NC files (Numerical Control files) consisting of G-code. One NC file contains the machine's operations, such as sawing, nailing, and routing. The goal was to develop a program with a maximum margin of error of 3% from reality. The machine was tested to measure the time of different operations to develop the program, and the NC files were analysed. Calculations for the jerk, acceleration, deceleration, and velocity of the CNC machine were considered to predict the time of the movements with high enough precision. The calculations and implementation are written in C#. A GUI is created for the user to use the program easily. The end product is a program that can take in one NC file and gives output on the time it should take for the Nailing Bridge to go through the file. The margin of error was between 5% to 31% for one operation of sawing or nailing, which is significantly higher than the goal of 3%. The program was therefore debugged with unit testing and new tests of the Nailing Bridge to find the sources for this margin of error. The conclusion is that the program works but not exactly to the company's standards.

<p>With increasing global renewable energy demands, there is a need for new materials with improved performance, lower cost, and less toxicity. One such application is photovoltaics, where halide perovskites (HaPs) represent the fastest growing market of absorbers owing to their impressive optoelectronic properties and excellent tunability from composition engineering and structural manipulation. However, the practically infinite composition-structure space of HaPs when considering cation and/or anion site mixing, octahedral distortion and rotation, and other forms of polymorphism, raise considerable challenges when comprehensively exploring their stability and optoelectronic properties. First principles calculations are powerful tools that can investigate large numbers of compounds and structures in a high-throughput fashion. </p><p>In my thesis, I performed high-throughput density functional theory (DFT) computations to generate a HaP dataset within a wide chemical space covering ~500 unique chemical compositions in the (pseudo-)cubic phase, across a 14-dimensional ionic space. This work explored both pure and alloyed compositions, with the latter simulated using the special quasi-random structures approach. Many critical properties were computed using the semi-local GGA-PBE and hybrid non-local HSE06 functionals, including decomposition and mixing energies, electronic band gap, and spectroscopic limited maximum efficiency (SLME), which is a theoretical surrogate for the likely absorption efficiency of the compound when used in a single-junction solar cell. Property screening over this dataset yielded 32 stable perovskite candidates with attractive optoelectronic properties.</p><p>Polymorphism in HaPs is investigated by simulating larger supercell alloys with different ionic ordering, generating compounds with random octahedral distortions and rotations, and optimizing various compositions in non-cubic phases such as tetragonal and orthorhombic. Linear correlation analysis is performed to gain a critical understanding of how properties are influenced by specific cations and anions, their mixing fractions, the perovskite phase, ionic clustering, and amount of strain or distortion in the lattice. Finally, trends, design rules, and predictive insights achieved from the DFT datasets are applied over a much larger set of thousands of hypothetical compounds, resulting in identification of more promising materials and understanding of the most important A-B-X combinations that yield multiple desired objectives.</p><p>Furthermore, a similar DFT workflow is applied for designing transition metal electrocatalysts. DFT simulations are performed to model Hydrogen adsorption, OH adsorption, and the water splitting reaction on Ni3N/Ni and Co2N/Co hybrid structures, to explore their likelihood in being used for Hydrogen Evolution Reaction (HER). The results reveal the excellent catalytic performance of transition metal and transition metal nitride hybrid structures.</p><p><br></p>

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