Computational Study Of Transition Metal Complexes For Solar Energy Conversion And Molecular Interaction With Strong Laser Fields

There are two topics in this dissertation: ground state and excited state modeling of a few series of transition metal complexes that facilitate solar energy conversion, and Born-Oppenheimer Molecular Dynamics (BOMD) simulations of molecular cations interacting with intense mid-infrared laser light. In Chapter 2 and 3, a few series of transition metal complexes that facilitate solar energy conversion are studied computationally. Metal-to-ligand charge-transfer (MLCT) excited states of several (ruthenium) (monodentate aromatic ligand, MDA) chromophore complexes are modeled by using time-dependent density function theory (TD-DFT). The calculated MLCT states correlate closely with the heretofore unknown emission properties that were observed experimentally. The hydrogen evolution mechanisms of three new series of cobalt based water splitting catalysts are modeled by Density Functional Theory (DFT). The three series include: 1) a family of cobalt complexes with pentadentate pyridine-rich ligands, 2) a family of three heteroaxial cobalt oxime catalysts, namely [CoIII(prdioxH)(4tBupy)(Cl)]PF6, [CoIII(prdioxH)(4Pyrpy)(Cl)]PF6, and [CoIII(prdioxH)(4Bzpy)(Cl)]PF6, 3) a pentadentate oxime that has ligand incorporated water upon metal coordination and is water soluble. These calculations provide reasonable interpretations of the experimental observations. In Chapter 4, 5 and 6, mode selective fragmentation of ClCHO+ and circular migration of hydrogen in protonated acetylene with intense mid-IR laser pulses are simulated by BOMD trajectory calculations. The ionization rate of ClCHO in the molecular plane has been calculated by time-dependent configuration interaction with a complex absorbing potential (TDCI-CAP), and is nearly twice as large as perpendicular to the plane, suggesting a degree of planar alignment can be obtained experimentally for ClCHO+, starting from neutral molecules. The BOMD simulations demonstrate circularly polarized light with the electric field in the plane of the molecule deposits more energy and yields larger branching ratios for higher energy fragmentation channels than linearly polarized light with the same maximum field strength. The trajectories with different pairs of the dual laser pulses give very different branching ratios. The difference in branching ratios is even more pronounced when one of the two pulses started one quarter of the total duration earlier than the other vs. the other way around for the same pulse pair. In protonated acetylene, hydrogen migration around the C2 core occurs by interchange between the Y shaped classical structure and the bridged, T-shaped non-classical structure of the cation, which is 4 kcal/mol lower in energy. The linearly and circularly polarized pulses transfer similar amounts of energy and total angular momentum to C2H3+. There is an appreciable amount of angular displacement of the three hydrogens relative to the C2 core for circularly polarized light, but only an insignificant amount for linearly polarized light. This suggests a propeller-like motion of the three hydrogens is induced only by the circularly polarized light. In Chapter 7, an inherent problem in BOMD is explained and mostly circumvented by using ADMP method. Since BOMD is based on the Born-Oppenheimer approximation, the wavefunction of the system is converged at each time step to calculate the force for integrating the classical equations of motion. This resulted in an artifact manifested for a few trajectories as anomalously large charge oscillations on an H atom (H+/H/H–) when it was well-separated (beyond ca. 3 Å) from the rest of the molecule, thus absorbing an anomalously large amount of energy. ADMP method, an alternative to BOMD method, propagates the density matrix using extended Lagrangian dynamics. Our ADMP calculations in intense laser fields show that the accuracy is similar to BOMD while the charge oscillation problem is eliminated naturally because the electronic wavefunction is propagated rather than converged at each step. In Chapter 8, in order to interpret the experimental results of two-electron angular streaking for methane molecule, TDCI calculations and BOMD trajectory calculations are carried out with the additional help from a logistic regression machine learning algorithm to analyze geometric changes. The ionization angular dependence of various stable and meta-stable structures of methane cation, as well as neutral methane, is calculated by our TDCI-CAP approach. The ionization is mostly along the C–H bond direction for the neutral methane and monocation in the tetrahedral geometry, while the directions of ionization for other geometries are less straightforward. The relaxation time needed for neutral methane geometry (tetrahedron shape) to collapse into D2d and C2v structures on the cation potential energy surface is estimated to be 3 fs (half of the initial population converted) by classifying geometries along BOMD trajectories with a machine learning algorithm

Filler Toughening of Plastics: Study of the Deformation Mechanism

Precipitated calcium carbonate nanoparticles (PCC), surface treated with stearin in aqueous medium, were investigated in this thesis as rigid fillers for polymer toughening. The surface characterization of a series of PCC coated with different stearin amount indicated the presence of two different types of calcium alkanoate layers on the surface. One is the chemisorbed monolayer (CSM) bonded to the active sites of PCC surface with a maximum coverage degree of around 72%. The other one is constituted by the physisorbed calcium alkanoate multilayers linked to the CSM by weak intermolecular forces. The micelle adsorption mechanism has been proposed to be the dominating process due to the limited solubility of stearin in water, compared to the coating process in solvent where a full monolayer can be achieved. The calcium alkanoate molecules, present on the PCC surface as physisorbed multilayers, have been shown to have a complicated thermal behavior. The drying process for PCC particles resulted in molecular rearrangement from the monohydrate phase to the anhydrous phase. Molecular polymorphism and orientation of calcium alkanoate on the PCC surface are strongly connected with the surface free energy of the coated particles. The coated PCC particles showed a continuously decreasing surface free energy, both for the dispersion and specific components, with an increase in the amount of surface coating. Based on the investigation of the thermal transition and the determination of surface layer thickness, a molecular arrangement model has been proposed suggesting that the CSM is vertical to the PCC surface linked tail-to-tail with the physisorbed multilayers with alkyl chains oriented outwards. This series of coated PCC nanoparticles were then applied to high-density polyethylene (HDPE) and polylactic acid (PLA) as toughening fillers. The HDPE/PCC nanocomposites achieved the expected balance between the stiffness and toughness. In fact, the yield stress showed a slightly decreasing trend while the impact strength showed a tendency of increase when the surface coating amount on the PCC surface increased. Those mechanical properties were related to the micromorphology and also to the interfacial adhesion between PCC particles and HDPE polymer matrix, which on the other hand connected to the dependence of the surface free energy from the surface coating amount of PCC fillers. PLA/PCC nanocomposites showed a notable improvement of the elongation-at-break and toughness compared to that of pure PLA. This result can be attributed to both the weaker interfacial adhesion facilitating the debonding process and the plasticizing effect of calcium alkanoate which enhance the deformability of PLA nanocomposites. In fact, the thermal behavior study elucidated that PCC particles acted as nucleating agents for PLA, decreasing the crystallization half-time and the cold crystallization temperature of PLA composites. Also the plasticizing effect of the calcium alkanoate coated PCC nanoparticles was confirmed by the decreased glass transition temperature for PLA/PCC nanocomposites

Synergistic effects of nucleating agents and plasticizers on the crystallization behavior of Poly(lactic acid)

The synergistic effect of nucleating agents and plasticizers on the thermal and mechanical performance of PLA nanocomposites was investigated with the objective of increasing the crystallinity and balancing the stiffness and toughness of PLA mechanical properties. Calcium carbonate, halloysite nanotubes, talc and LAK (sulfates) were compared with each other as heterogeneous nucleating agents. Both the DSC isothermal and non-isothermal studies indicated that talc and LAK were the more effective nucleating agents among the selected fillers. Poly(D-lactic acid) (PDLA) acted also as a nucleating agent due to the formation of the PLA stereocomplex. The half crystallization time was reduced by the addition of talc to about 2 min from 37.5 min of pure PLA by the isothermal crystallization study. The dynamic mechanical thermal study (DMTA) indicated that nanofillers acted as both reinforcement fillers and nucleating agents in relation to the higher storage modulus. The plasticized PLA studied by DMTA indicated a decreasing glass transition temperature with the increasing of the PEG content. The addition of nanofiller increased the Young's modulus. PEG had the plasticization effect of increasing the break deformation, while sharply decreasing the stiffness and strength of PLA. The synergistic effect of nanofillers and plasticizer achieved the balance between stiffness and toughness with well-controlled crystallization

Exploratory Study on the Methodology of Fast Imaging of Unilateral Stroke Lesions by Electrical Impedance Asymmetry in Human Heads

Stroke has a high mortality and disability rate and should be rapidly diagnosed to improve prognosis. Diagnosing stroke is not a problem for hospitals with CT, MRI, and other imaging devices but is difficult for community hospitals without these devices. Based on the mechanism that the electrical impedance of the two hemispheres of a normal human head is basically symmetrical and a stroke can alter this symmetry, a fast electrical impedance imaging method called symmetrical electrical impedance tomography (SEIT) is proposed. In this technique, electrical impedance tomography (EIT) data measured from the undamaged craniocerebral hemisphere (CCH) is regarded as reference data for the remaining EIT data measured from the other CCH for difference imaging to identify the differences in resistivity distribution between the two CCHs. The results of SEIT imaging based on simulation data from the 2D human head finite element model and that from the physical phantom of human head verified this method in detection of unilateral stroke

Bioprinting and biomaterials for dental alveolar tissue regeneration

Three dimensional (3D) bioprinting is a powerful tool, that was recently applied to tissue engineering. This technique allows the precise deposition of cells encapsulated in supportive bioinks to fabricate complex scaffolds, which are used to repair targeted tissues. Here, we review the recent developments in the application of 3D bioprinting to dental tissue engineering. These tissues, including teeth, periodontal ligament, alveolar bones, and dental pulp, present cell types and mechanical properties with great heterogeneity, which is challenging to reproduce in vitro. After highlighting the different bioprinting methods used in regenerative dentistry, we reviewed the great variety of bioink formulations and their effects on cells, which have been established to support the development of these tissues. We discussed the different advances achieved in the fabrication of each dental tissue to provide an overview of the current state of the methods. We conclude with the remaining challenges and future needsThis work was supported by the Japan Society for the Promotion of Science (JSPS) KAKENHI (Grant Numbers 22K18936 and 21K04852); AMED (Grant Number JP21gm1310001); The JST Adaptable and Seamless Technology Transfer Program through Target-driven R&D (Grant Number JPMJTM22BD), CASIO SCIENCE PROMOTION FOUNDATION, and by the Research Center for Biomedical Engineering at Tokyo Medical and Dental University, Japan

Optimized sample preparation for two-dimensional gel electrophoresis of soluble proteins from chicken bursa of Fabricius

<p>Abstract</p> <p>Background</p> <p>Two-dimensional gel electrophoresis (2-DE) is a powerful method to study protein expression and function in living organisms and diseases. This technique, however, has not been applied to avian bursa of Fabricius (BF), a central immune organ. Here, optimized 2-DE sample preparation methodologies were constructed for the chicken BF tissue. Using the optimized protocol, we performed further 2-DE analysis on a soluble protein extract from the BF of chickens infected with virulent avibirnavirus. To demonstrate the quality of the extracted proteins, several differentially expressed protein spots selected were cut from 2-DE gels and identified by matrix-assisted laser desorption ionization time-of-flight mass spectrometry (MALDI-TOF MS).</p> <p>Results</p> <p>An extraction buffer containing 7 M urea, 2 M thiourea, 2% (w/v) 3-[(3-cholamidopropyl)-dimethylammonio]-1-propanesulfonate (CHAPS), 50 mM dithiothreitol (DTT), 0.2% Bio-Lyte 3/10, 1 mM phenylmethylsulfonyl fluoride (PMSF), 20 U/ml Deoxyribonuclease I (DNase I), and 0.25 mg/ml Ribonuclease A (RNase A), combined with sonication and vortex, yielded the best 2-DE data. Relative to non-frozen immobilized pH gradient (IPG) strips, frozen IPG strips did not result in significant changes in the 2-DE patterns after isoelectric focusing (IEF). When the optimized protocol was used to analyze the spleen and thymus, as well as avibirnavirus-infected bursa, high quality 2-DE protein expression profiles were obtained. 2-DE maps of BF of chickens infected with virulent avibirnavirus were visibly different and many differentially expressed proteins were found.</p> <p>Conclusion</p> <p>These results showed that method C, in concert extraction buffer IV, was the most favorable for preparing samples for IEF and subsequent protein separation and yielded the best quality 2-DE patterns. The optimized protocol is a useful sample preparation method for comparative proteomics analysis of chicken BF tissues.</p

Legume Lectin FRIL Preserves Neural Progenitor Cells in Suspension Culture In Vitro

In vitro maintenance of stem cells is crucial for many clinical applications. Stem cell preservation factor FRIL (Flt3 receptor-interacting lectin) is a plant lectin extracted from Dolichos Lablab and has been found preserve hematopoietic stem cells in vitro for a month in our previous studies. To investigate whether FRIL can preserve neural progenitor cells (NPCs), it was supplemented into serum-free suspension culture media. FRIL made NPC grow slowly, induced cell adhesion, and delayed neurospheres formation. However, FRIL did not initiate NPC differentiation according to immunofluorescence and semiquantitive RT-PCR results. In conclusion, FRIL could also preserve neural progenitor cells in vitro by inhibiting both cell proliferation and differentiation

Advances of deep learning in electrical impedance tomography image reconstruction

Electrical impedance tomography (EIT) has been widely used in biomedical research because of its advantages of real-time imaging and nature of being non-invasive and radiation-free. Additionally, it can reconstruct the distribution or changes in electrical properties in the sensing area. Recently, with the significant advancements in the use of deep learning in intelligent medical imaging, EIT image reconstruction based on deep learning has received considerable attention. This study introduces the basic principles of EIT and summarizes the application progress of deep learning in EIT image reconstruction with regards to three aspects: a single network reconstruction, deep learning combined with traditional algorithm reconstruction, and multiple network hybrid reconstruction. In future, optimizing the datasets may be the main challenge in applying deep learning for EIT image reconstruction. Adopting a better network structure, focusing on the joint reconstruction of EIT and traditional algorithms, and using multimodal deep learning-based EIT may be the solution to existing problems. In general, deep learning offers a fresh approach for improving the performance of EIT image reconstruction and could be the foundation for building an intelligent integrated EIT diagnostic system in the future