Deposition of multi-layer coatings on sawtooth substrate will allow a new kind of x-ray gratings, Multilayer-coated Blazed gratings which will be a basis for a new generation of high resolution and high throughput x-ray instrumentation. The flow of energy and electric charge in molecules are central to both natural and synthetic molecular systems that convert sunlight into fuels and evolve over a multitude of timescales.We address this challenge by probing chemically complex systems in the gas phase by combining the precise time information of ultrafast spectroscopy techniques with the chemical sensitivity characteristic of synchrotron radiation. An ultrafast pulse pair with VUV or soft x-ray photons from the synchrotron are used to make measurements with atomic-site specificity. With access to photons spanning the range of terahertz to hard X-rays that is provided by a synchrotron, coupled with the rich spectroscopy available in the UV-VIS-IR region provided by table top ultrafast lasers, a multi-dimensional tool to probe dynamics is enabled.We have developed a portable transient absorption experimental apparatus to perform time resolved analysis of two color laser excitation schemes applicable to a variety of gaseous systems. This setup is currently deployed at the soft x-ray Beamline 6.0.2 at the Advanced Light Source,ebb flow tray where we are interrogating the excited state spectroscopy and dynamics of nitrophenols: Here one ultrafast pulse excites onitrophenol while a second ultrafast infrared pulse promotes the system to nearby vibronic state after a suitable time delay. The transmitted IR light is detected by a photodiode and a high-sensitivity photon spectrometer to determine the absorption as a function of IR wavelength and time delay.
These experiments will be performed in parallel with laser-synchrotron experiments as a complementary diagnostic tool, allowing for the precise control of the electronic states in model chromophores that is crucial towards developing ultrafast laser-synchrotron multicolor spectroscopy. We have measured ion momentum images of o-nitrophenol following photoexcitation and photoionization from its electronic ground state by soft x-rays tuned near the core-level resonances of oxygen and nitrogen, at Beamline 6.0.2 at the Advanced Light Source. Ultraviolet pulses, produced from the 3rd harmonic of a Ti:sapphire laser system that is synchronized to the ALS storage ring and the 4kHz repetition rate of the soft x-ray Beamline, were also employed in these experiments in an effort to measure the products of laser photo dissociation by core-level ion momentum spectroscopy. Our subsequent improvements to the reliability of the laser systems have increased the laser pulse energies from a few hundreds of nanojoules to above 10 microjoules for each of the UV and IR laser beams that will be used for the 3 color experiments. With all the hardware and staff in place experiments are underway to probe the dynamics of evolving excited states in gas phase systems.In parallel, we have developed a dual catalyst system to homologate alpha-olefins to tertiary amines by sequential hydroformylation and reductive amination . Hydroformylation occurs in the organic phase of the reaction medium and is catalyzed by the combination of Rh2 and BISBI, a ligand developed by Eastman Kodak for hydroformylation with high selectivity for linear aldehydes. The aldehyde intermediate condenses with secondary amine reagents to form an iminium ion, which reacts with a metal hydride to afford the tertiary amine product. Reductive amination occurs in the aqueous phase of the reaction medium and is catalyzed by the combination of Cp*Ir3 and a water-soluble diphosphine ligand. Finally, we have prepared artificial enzymes by two methods, In the first, we prepared noble metal-porphyrin active sites in myoglobin. Based on prior reconstitution of myoglobin with both abiotic protoporphyrins and [M]-salen complexes, we incorporated new Ir, Rh, Co, and Ru-based cofactors into myoglobin mutants in which the axial ligand and secondary coordination sphere are varied.
In the past year, we developed a new, highly efficient method for the generation of artificially metallated myoglobins based on the direct expression and purification of apo-myoglobins. Using these new myoglobin-based catalysts, we have shown for the first time that an artificially-metallated PPIX-binding protein can catalyze organic reactions that cannot be catalyzed by the same protein binding its native Fe-PPIX cofactor. In particular, Ir-PPIX-myo catalyzes cyclopropanation of internal olefins and carbene insertion into C-H bonds, while Co-salen-myo catalyzes intramolecular hydroamination of unbiased substrates. In the second approach, we developed artificial metalloenzymes for transformations for which there are no known metal catalysts. We are doing so by a bottom-up approach in which we identify by high throughput screening of unrestricted metal-ligand combinations a model reaction using reagents and conditions compatible with proteins. We then conjugate this catalytic site into a protein hosts, using covalent or non-covalent interactions; the catalytic properties of the conjuagates are then be evaluated, and the activity of the enzyme fined-tuned by modification of the ligand used. Following this proposed methodology, identified a metalloenzyme for regioselective halogenation of aromatic substrates. A Cobalt cofactor covalently bound to nitrobindin catalyzes the halogenation of a simple, water-soluble arene. There are two synergistic purposes to this project. The first objective is to improve our ability to understand the physical factors that are responsible for intermolecular interactions. Electronic structure calculations are nowadays capable of calculating intermolecular interactions nearly as accurately as they can be measured. However such calculations by themselves do not provide any understanding of why the interactions have the magnitudes that they do. Methods for this purpose are called energy decomposition analyses . It is an important open challenge to design improved EDA’s, a problem that is best attacked by deepening our understanding of the factors controlling intermolecular interactions. The second objective of the project is to develop new, more efficient numerical methods for solving the equations of electronic structure theory for molecular clusters .
There should be natural connections between new EDA tools, and the problem of computing those interactions more efficiently than has been hitherto possible. We believe the combination of improved EDA’s for analysis together with lower scaling algorithms for calculating the interactions will be a potentially significant step forwards in quantum chemistry. The electron-electron correlation energy is negative, and attractive dispersion interactions are entirely a correlation effect, so the contribution of correlation to intermolecular binding is commonly assumed to be negative, or binding in nature. However, we have discovered that there are many cases where the long-range correlation binding energy is positive, and therefore anti binding, with certain geometries of the water dimer as a prominent example. We have also undercover the origin of this effect, which is the systematic overestimation of dipole moments by mean-field theory, leading to reduced electrostatic attraction upon inclusion of correlation. Thus, EDA’s that include correlation but do not correct mean field electrostatics are sub-optimal, especially those that describe all of the correlation energy as dispersion. This result has major implications for the correct design of new EDA’s, which we look forward to taking up in future post-LDRD work. Our second major activity has been exploring new ways of using the natural separation of energy scales between intra-molecular and intermolecular interactions to improve the efficiency of electronic structure theory calculations. Specifically,flood and drain tray we have explored whether coupled cluster calculations can be accurate approximated by a starting point where the CC calculation is performed on only the intra-molecular excitations or intra-molecular + dispersive intermolecular excitations . The remaining contributions are then evaluated approximately by perturbation theory . The question is whether this approach can improve the often-questionable accuracy of PT, without the prohibitive computational cost of a full CC calculation on a molecular cluster. Our results indicate that PT based on the linear model does not significantly improve upon direct use of PT, while the quadratic model does yield significant gains in accuracy. Work is presently underway to explore whether this result can be improved by using orbitals relaxed in the cluster environment, and how to obtain such orbitals more efficiently than brute force solution as if the cluster is a supermolecule.The purpose of this project is to develop a powerful theoretical framework capable of discovering general design rules based on nanoscale properties of molecule shape and size, charge distributions, ionic strength, and concentration to influence the mechanism, percolation, morphology, and rates of assembly over mesoscale time and lengthscales. The ability to control for structure and dynamics of the assembly process is a fundamental problem that, if solved, will broadly impact basic energy science efforts in nanoscale patterning over mesoscale assemblies of block copolymer materials, polyelectrolyte organization at solid or liquid interfaces, forces governing multi-phasic soft colloids, and growth of quantum dots in polydisperse colloidal medium. Fundamental design rules applied to complex and heterogeneous materials are important to DOE mission science that will enable next generation fuel cells, photovoltaics, and light emitting device technologies. At present our ability to design and control complex catalytic activity by coupling simpler modular systems into a network that executes novel reactive outcomes is an unsolved problem. And yet, highly complex catalytic processes in nature are organized as networks of proteins or nucleic acids that optimize spatial proximity, feedback loops, and dynamical congruence of reaction events to optimize and fine tune targeted biochemical functions.
The primary intellectual activity of bio-mimetic scaffolding – the design of spatial organizations of modular bio-catalysts – is to restore their catalytic power in these new chemical organizations after they have lost their catalytic functions optimized in a separate biological context. That is our goal. Some inspiration for our approach to catalytic network design is derived from another highly successful bio-mimetic approach- laboratory directed evolution – an experimental strategy based on the principle of natural selection. The goal is to alter the protein through multiple rounds of mutagenesis and selection to isolate the few new sequences that exhibit enhanced catalytic performance, selectivity, or protein stability, or to develop new functional properties not found in nature in the creation of new bio-catalysts. Given the limitations of our understanding of the structure-function relationship, LDE provides an attractive alternative to rational design approaches and is highly flexible in application to different bio-catalysis reactions. However, there are still outstanding problems when transferring LDE into new optimization strategies for new bio-catalysts. First the finite size and composition of the LDE libraries may be limiting for the optimization of enzymes that act on, for example, solid substrates, and there has been little effort devoted to developing LDE libraries for optimizing bio-catalytic activity in the context of chemical networks. Furthermore, although often highly successful, LDE is an opaque process because it offers no rationale as to why the mutations were successful, and therefore stands outside our ability to systematically reach novel catalysis outcomes. This proposal is a theoretical study to offer new rational design strategies for building an artificial chemical network of bio-catalytic reactions that execute complex but now non-biological catalytic functions using computational directed evolution . Traditionally enzyme optimization is often focused on the energetics of active site organization but there is correspondingly little effort directed toward optimizing entropic or dynamical effects that are also equally relevant for improvements in catalytic activity. Therefore we propose a new CDE design strategy that considers not only energetics but novel physical and theoretical concepts Recent studies report evidence that some organic aerosols might exist in the atmosphere not as well mixed liquids – the traditional description, and their general state when they are formed – but rather as highly viscous, glassy materials with extremely slow internal reaction-diffusion times and low evaporation rates. These observations suggest that the characteristics of organic aerosols currently used in regional and global climate models are fundamentally incorrect: viscosity affects reactivity and indeed, the models consistently under-predict the quantity of aerosol in the atmosphere by factors of 5 to 10. We are addressing this gap by developing a quantitative and predictive description of how initially liquid aerosols are transformed into glassy ones, in particular by gas phase oxidizers. Reaction-diffusion models that are chemically accurate and fully validated by experimental data have not been previously used in this field, and hold promise for improving parameters for atmospheric models. Model simulations are performed using stochastic methods, which are well-suited to large dynamic ranges of conditions, and capture fluctuations and rare events key to liquid-solid transitions.